To find out whether the oil spill target can be better identified by polarization remote sensing and which spectrum and observing angles are suitable for detection, it is necessary to acquire data of the oil slick spectral polarization properties. In this paper, different oil slicks are made with different thicknesses by a kind of oil on water basis, and a series of experiments are set up in laboratory with ellipsometry to measure the mirror reflective polarization parameters: auxiliary angle Ψ and phase difference Δ from UV to near infrared (270~900 nm). We have changed different viewing angles and compared the result with those of oil and water under the same conditions. The result shows that except for Brewster angle, there exist significant distinctions between oil slick and water at different observation angles. Besides, the spectral refractive indexand extinction coefficient of the pure water/oil samples are obtained by Ψ and Δ at 45°. The water refractive index by the experiment meets the water model by Schiebener with standard deviation 3×10-5 after offset correction. The oil spill is modeled with ideal thin oil film on water basis according to those refractive index and extinction coefficient. The Fresnel theory is used to simulate and calculate the reflective light. The simulation shows the reflective light from oil has distinct degree of polarization (DOP) or polarization angle (AOP) vs. spectral with that from water background. Compared with the experiment results, the model shows the same results at 300~350 nm, which has weak interference effect and the properties are close to the oil’s, whileat 350~550 nm, the amplitude of the interference simulation results is weaker than the experiment result, and until wavelength greater than 550 nm, the clear interference is detected. The fact indicates the more absorption or scattering phenomenon in oil slick than in oil. According to parameter identification, it is true that the extinction coefficient of oil slickhas a first smaller then bigger property with wavelength. To sum up, we found that spectral ellipsometry can be used to measure and analyze the spectral polarization properties and reflection index of liquid samples through multi band and multi angle measurements. Suitable observing angles for polarization to oil spill is related to the Brewster angle of oil/water. At incident angles except for Brewster observation angle, oil film can be distinguished from water. Visible and infrared spectrum are suitable for the interior optical properties of the oil film, while ultraviolet spectrum has good stability and is more suitable for observation of surface optical properties of very thin oil film. The method involved in the experiment can be applied to the polarization spectrum measurement of other oil slicks. The experimental data provide theoretical support and technical reference for the selection of appropriate spectral band and observation angle of water surface oil spill polarization remote sensing.

Bilirubin (BR) is one of the final products of heme catabolism, which has functions of anti-oxidation and anti-inflammatory. Normal content of bilirubin in human body plays an indispensable role in human health, which has been confirmed to be protective against diseases such as cancer, stroke, diabetes and cardiovascular diseases etc.［1-2］. However, excess bilirubin has been long recognized as a sign of liver dysfunction as well as a potential toxic factor causing severe brain damage in newborns. Thus, the analysis of bilirubin in body fluids is very important, speeding up the development of a cheap and accurate analytical method. Generally a lot of techniques have been used to detect bilirubin in serum samples, include diazo methods, peroxidase methods, fiber optic sensors, fluorometric methods etc.. Fluorometric methods have the advantages of quick response and simple operation, attracting more and more researchers’ attention. However, the fluorescence quantum yield of bilirubin itself is quite low, which is on the order of 10-4, resulting in the difficulty in direct measurement of its content, so it is usually measured indirectly. Wabaidur et al. measured the content of bilirubin by using bilirubin to quench the fluorescence of Ru(bipy)2+３; Aparna et al. measured that by using bilirubin to quench the fluorescence of copper nanocluster; Iwatani et al. measured that by using protein UnaG to conjugate bilirubin for its fluorescence enhancement. UnaG has a high affinity with bilirubin and UnaG itself is almost non-fluorescent. When combined with UnaG, the fluorescence of bilirubin would be increased by three orders of magnitude and thus it can be used as a fluorescent sensor in human body. However, the cost of protein production and preservation is pretty high, and researchers prefer to use organic small molecules or inorganic molecules to increase the fluorescence of bilirubin. For example, Yanget al. found that the zinc ions were helpful to significantly enhance the fluorescence of bilirubin. Kotal et al. proposed the use of zinc ions for the measurement of bilirubin metabolite (urobilinogen) content. Basing on using zinc ions to enhance the fluorescence of bilirubin for its content measurement, we applied the steady-state fluorescence and UV-visible absorption spectroscopy to characterize bilirubin with different concentration of zinc ions, and the fluorescence quantum yield was measured by using the relative method. By analyzing the excitation spectra of zinc-bilirubin complex at different emission wavelengths, we proposed a hypothesis that the complex has two fluorescence subunits. Besides, the femtosecond transient absorption spectroscopy was used to explore the photodynamic process of the complex and the hypothesis was confirmed. The experimental data was in a good agreement with previous studies of bilirubin and zinc ions complex. Moreover, combining together with the transient absorption spectra, steady-state spectra and the proposed hypothesis, we calculated the average excited-state lifetime of bilirubin with/without zinc ions, and obtained its theoretical value of radiative and non-radiative decay rate. Compared with bilirubin itself, the complex has a larger value of extinction coefficient, which caused a greater radiative decay rate. We believe the coordination of zinc ions and bilirubin has increased its deactivation efficiency byinternal conversion.

In recent years, with the rapid development of world economy, a large number of harmful substances are discharged into the environment, and the global environmental problems are becoming increasingly serious. Spectroscopic methods have been widely used in the detection and analysis of water quality, atmosphere and soil environment due to their speed, simplicity for real-time, in-situ field analysis. However, the environment system is an open and complex system, which is easily affected by many factors, so it is difficult to extract the characteristic information of the interesting components from the complex environment system based on the conventional one-dimensional spectroscopy. Two-dimensional (2D) correlation spectroscopy, which presents characteristic spectral information changes in response to the special external, can not only extract the weak and covered spectral information in the complex environment, but also provide the relationship between these peaks. On the basis of a review of the new development of 2D correlation spectroscopy in recent years, the application of the technology in the analysis of water, soil and atmosphere environment was introduced in detail, including pesticide residues in water, qualitative and quantitative analysis of organic pollutants in water, the formation mechanism of marine mucus and foam. the quantitative analysis of organic pollutants in soil, the mechanism of repairing and adsorption for soil pollutants; the formation mechanism of aerosol in atmosphere, and the qualitative and quantitative analysis of polluted gases. Finally, it was introduced in detail that the application of 2D correlation spectroscopy to the study of the molecular characteristics of organic matter and the interaction mechanism with other metal ions in the environment. It was pointed out that 2D correlation spectroscopy has broad application prospects in the field of environmental science.

Double-peaked emission lines may reflect some rare scenes, such as binary active nucleus (AGNs), double supermassive black holes (SMBHs), interaction between jet and narrow line regions, or be low-quality spectra. Generally, at least 2 peaks are included in double-peaked emission lines, which are useful in searching rare objects such as AGNs, SMBHs, galaxypairs. It is meaningful in researching double-peaked emission lines for further studying formation and revolution of galaxies and even the universe. In this paper, a new method based on relevant subspace for extracting and analyzing of double-peaked emission line spectra is proposed. There are 3 parts in this paper: (1) Sparse difference factor δ is defined to measure attribute difference degree in spectra with double-peaked emission lines. And KNN algorithm is employed to restrain the involved spectral data. Then, characteristics extraction method for low solution spectra is proposed based on relevant subspace. (2) To test the efficient of parameters of sparse difference factor δ and k of KNN algorithm, 664 spectra are selected from LAMOST as training set, including 332 positive samples and 332 negative ones. To ensure 8 lines (Hα, Hβ, ［OⅢ］λλ4 959, 5 007, ［NⅡ］λλ6 548, 6 584, ［SⅡ］λλ6 717, 6 731) are in wavelength coverage of LAMOST, the redshift region is z<0.3. And then influence of experiment result about two parameters k and α of δ threshold is analyzed. The result indicates that distribution of relevant attributes is dense with less sparse points when k=18 and α=0.6. (3) Wavelength coverage, red/blue shift interval and line strength ratio of double-peaked emission lines in subspace are analyzed and measured theoretically. Then characteristic description of double peaks based on relevant subspace is given. Finally profiles of double peaks are analyzed according to emission excitation mechanism and line strength relationship.

The terrestrial solar spectrums record the imprints and information of sunlight passing through the atmosphere, it provides practical information for the study of atmospheric environment and ecological protection. Tibet is one of the world’s best-known areas with strongest solar radiation. Observation of solar radiation on the ground in Tibet can provide field data for solar energy utilization and research on atmospheric environment etc.. A systematic field observation was conducted to observe the surface solar spectrums, solar global irradiance and solar UV irradiance in Tibet by using the German RAMSES hyperspectral Irradiance Sensors, the Dutch CMP6 Pyranometers and the Norwegian NILU-UV Multi-filter Radiometers. The monthly spectral characteristics of Lhasa, Tibet, for 2017 were observed. The results of solar spectral observations at the local noons (13:55BJ) of Lhasa for the two equinoxes and the two solstices were reported. The ground spectra of Tibet were compared with the standard spectra of AM1.5 and AM0. The characteristics of global solar irradiance and solar ultraviolet intensity in Lhasa and Naqu of Tibet were observed and studied. It is found that the spectral intensities for visible and infrared lights in summer even exceed the corresponding wavelength spectral intensities of the AM0 spectra in Lhasa. In other words, the spectral intensities for visible and infrared lights on the surface of Lhasa occasionally exceed the spectral intensities of the corresponding radiation at the top of the atmosphere. The maximum spectral value of Lhasa usually occurs at wavelengths of about 476.6 nm, and the maximum observed in summer solstice in 2017 is about 2.331 W·m-2·nm-1. However, the observation of solar UV radiation (280～400 nm) spectrum shows that the spectral intensity of the ground solar UV region is always significantly lower than that of the corresponding intensity of the AM0 spectrum. Although Lhasa is located at about 3 680 meters above sea level, the ground measurements of the local noon solar UV spectrums indicate that the wavelengths less than 300 nanometers of UV irradiances are almost zeroes in Lhasa, which means that the solar UV irradiance with wavelengths less than 300 nm is absorbed by the atmosphere and does not reach the ground. It indicates that the short-wave solar UV radiations are absorbed effectively by atmospheric ozone. At the same time, the characteristics of the solar spectra at the high altitude of Tibet and lower places in Beijing and Chengdu are observed and studied, and the information on atmospheric composition and content in various places are revealed. The results of the solar global irradiance in Tibet during July of 2010—December of 2013 are reported. The results show that about 18% of the global irradiances in Lhasa exceed the solar constant (1 367 W·m-2). It is found that the instantaneous maximum value of the global irradiance in Lhasa reaches 1 756.09 W·m-2 (June 24, 2011). The observation results of solar UV radiation in Tibet during July of 2008—December of 2013 are also reported. The results show that the averaged daily maximum value of UVA for both Lhasa and Naqu is about 67 W·m-2, and the maximum value of UVB for the same places is about 5.1 W·m-2. The daily maximum values of UVA and UVB for both Lhasa and Naqu are maintained a good consistency. During the observation period of more than 5 years, there was no obvious enhancement or weakening trend for the UV intensities.

Due to the transparency to the terahertz waves, many polymeric materials have been demonstrated various important applications as optical components as well as dilution matrix for terahertz research. Certain dielectric responses are usually preferred considering different application circumstances. The adjustment of dielectric property could be achieved by proper selection of polymer as well as design of polymer blend by physically mixing. Methodology is well described in this study for the terahertz dielectric analysis of polymeric materials and their mixtures in a quantitative manner, as exemplified by experiments with polyethylene (PE) and polytetrafluoroethylene (PTFE) for their widespread applications in terahertz research. Following the regular procedure of measuring the THz dielectric property of single component pellets with the phase delay information provided by the coherent detection of terahertz time domain spectroscopy, the intrinsic dielectric constants of PE and PTFE were determined as 2.315±0.003 (±0.13%) and 2.109±0.003 (±0.14%) by removing the influence of trapped air utilizing effective medium theory (EMT). These measured values were then used to simulate the THz dielectric constants of mixture pellets consisting of PE and PTFE at several mass ratios combing with EMT. The comparison between simulated values and experimental values of mixture samples presents a well linear correlation with R2=0.964 3 while the overall relative difference is 1.08%.

Terahertz time-domain spectroscopy has been gradually used in the study of ores. Usually, the rock should be ground and mixed with a binder to prepare samples. Thecontent and particle size of rock will affect the test result. Therefore, in this paper, the quartz sand (different particle size) was mixed with polyethylene(PE) particles in different proportions, and made into suitablesamples for terahertz system by means of tableting. The purpose was to explore the effect of quartz sand content and its particle size on the experimental results. Firstly, the effect of scattering particles content on the experimental results was studied. Particle size of quartz sand remain unchanged. It can be found that the time delay and peak values of time-domain signals show a non-monotonic trend. To explore this phenomenon, the refractive indexs and absorption coefficients of samples were further analyzed. The results showed that the refractive indexs of samples will gradually increase with the increase of the content of quartz sand in samples. Because the refractive index of quartz sand was larger than that of PE, which can be explained by the effective medium theory applicable to this experiment phenomenon. However, the absorption coefficients of samples increased first and then decreased with the increase of quartz sand content, and reached the maximum value when the mass fraction of quartz sand was about 60%. In order to explainthis phenomenon, the microstructure of the sample was observed by scanning electron microscope(SEM). It can be found that with the increase of quartz sand content, the breakage of PE particles during the pressing caused the particle size of PE to become smaller. According to the principle of Mie scattering and Rayleigh scattering, with decreasing particle size of PE, the scattering intensitydecreased, resulting in the phenomenon that absorption coefficients first increased and then decreased. In this paper, the influence of particle size of quartz sand on experimental results was studied. Samples with different particle sizes of quartz sand were tested. It can be found that refractive indexs of samples remained constant with the change of particle size of quartz sand. However, with the gradual decrease of particle size of quartz sand, the absorption coefficients of samples under the same ratio showed gradual decrease. According to Mie scattering principle, it could be inferred that the scattering intensities of samples gradually decrease with the decrease of the silica sand particle, so that the absorption coefficients of samples decrease with the decrease of the quartz sand particle. The research in this paper showed that the volume fractionand the particle size of quartz sand affect the experimental results. Under the condition of the same particle size, the absorption coefficient of quartz sand increased first and then decreased with the increase of the quartz sand content. With the same quartz sand content, the absorption coefficients of the samples gradually decreased with the decrease of the particle size of quartz sand. While the refractive index of samples increased with the increase of content of quartz sand, but the refractive index was broadly stableto the particlesize of quartz sand. Through the analysis of the refractive index and the absorption coefficient of the quartz sand and the mixture of PE particles in this paper, it has a certain degree of significance to the preparation of the mineral sample and the experimental results of the mixture.

Nearly every small gas-phase molecule (e. g., H2O, CO2) has a unique near-infrared absorption spectrum. At sub-atmospheric pressure, each tiny gas-phase molecule has a one-to-one characteristic spectral line. Based on this principle, it can use the Isotope Ratio Infrared Spectroscopy (IRIS) to accurately analyze the isotopic composition of gas samples, which overcomes the limitations of the conventional Isotope Ratio Mass Spectrometry (IRMS) and has become a recognized high-precision, high-sensitivity and high-accuracy method for trace-gas detection. In recent years, commercial laser spectroscopy gas composition analysis technology has gradually developed, and more and more scholars have made significant progresses in their respective fields using laser spectroscopy instruments. Among them, especially the study of atmospheric water vapor stable isotope has important significance to the study of hydrological cycle process. Laser spectroscopy makes it possible to conduct continuous and in-situ high-resolution measurement of atmospheric water vapor stable isotope (δ18O and δD). However, its observational precision and accuracy are affected by factors such as the operating characteristics, the sensitivity of different concentrations of atmospheric water vapor to specific spectral absorbance and so on, usually leading to the observations with obvious nonlinear response problems. Therefore, it is necessary to calibrate various deviations during the process of instrument observation. But at this stage, many users are not yet clear about the international calibration methods for the new observational technology. Therefore, based on Wavelength-Scanned Cavity Ring-Down Spectroscopy (WS-CRDS) technology, the atmospheric water vapor isotope observation system (Picarro L2120-i)measures the ring-down time at different wavelengths by Tunable Diode Laser (TDL) emitting laser of different wavelengths that can be absorbed by the target gas and that cannot be absorbed by the gas. And then by analyzing the ring-down time difference of the sample absorption and without any gas absorption, it can calculate molecular concentration of the target gas with high precision, and then determine the water vapor stable isotope composition. This paper establishes a set of accurate and reliable observation procedures and calibration methods in respect to memory effect, drift effect, concentration effect and so on, which provides a reference for researchers who are using or will use such equipment to obtain high-precision and high-reliability atmospheric water vapor stable isotope observation data.

Perovskite quantum dots have been widely studied in the fields of illumination, display, and laser because of excellent luminescence properties, such as high luminous efficiency, narrow-band light emission, and adjustable optical wavelengths. However, the problem of stability of perovskite materials has prevented the application of perovskite photoelectric device. Among them, the perovskite material in the air is easy to decompose and the instability is particularly prominent, seriously affecting its luminescence properties. Therefore, the researchers have tried a variety of methods to improve the stability of perovskite materials. At present, the common way is to introduce some hydrophobic polymer materials (such as POSS, PMMA etc.) into the perovskite nanocrystals or embedded perovskite nanocrystals in mesoporous silica spheres to avoid the exposure of the perovskite nanocrystals to the air and the stability of perovskite material was enhanced effectively. Moreover, the surface of perovskite nanocrystals was passivated, and it was also a common method to improve the optical stability of perovskite. Although these methods can improve the optical stability of the perovskite nanocrystals, their preparation methods are complicated and will introduce other organic functional groups in the perovskite, and surface passivation treatment of perovskite nanocrystals can destroy the original structure of perovskite nanocrystals, which affects the optical properties of the perovskite nanocrystals, which is not conducive to their use in photovoltaic devices. For optical devices silicon (Si), it is a dominant material in today’s photoelectric device industry because of the low cost, large size, and good electrical conductivity. However, The Si has been exposed to the air for a long time, the surface layer is easily to form a hydrophilic silanol group (Si—OH), which will be detrimental to silicon-based perovskite devices stability. So, passivate the Si surface in order to destroy the surface hydrophilic groups (Si—OH) and make the surface from hydrophilic to hydrophobic, to improve the stability of perovskite material in the device. In this study, Use the hydrofluoric acid (HF) treatment for Si surface passivation. It was found that the contact angle of the Si substrate with water after passivation was changed from 50.4° to 87.7°, indicating that the surface of the silicon substrate was changed from hydrophilic to hydrophobic after HF passivation treatment. Field emission scanning electron microscope (FE-SEM) test showed that after the passivation of Si substrate surface is rough, CsPbBr3 QDs film are uniformly dispersed, which is different from the cluster of CsPbBr3 QDs film on the Si substrate surface which is not passivated. The optical properties of CsPbBr3 QDs film at different time were studied by photoluminescence (PL) spectroscopy, and the fitting results of the power-dependent PL measurement confirming the excitonic characteristics is exciton emission because β is 1.12 and 1.203. Through the temperature-dependent PL measurements, it was found that as the temperature rises, the peak energy will gradually have a blueshift because the thermal expansion of the lattice leads to the forbidden gap increases. When the temperature increased from 10 to 300 K, the thermal stability of CsPbBr3 QDs film increased gradually with the increase of passivation time to the Si substrate surface. And the time-dependent PL measurements showed, after HF passivation treatment Si substrate surface, the stability of the CsPbBr3 QDs film gradually increased and the luminescence stability was up to 15 days. Therefore, by simply and effectively passivating the bottom surface of the Si substrate, the hydrophilic groups on the surface can be effectively reduced, improving the Optica stability of the CsPbBr3 QDs film. This provides a new way to enhance the stability of CsPbBr3 QDs film in the application of optoelectronic devices.

In the research of atmospheric remote sensing based on the hyper-spectral infrared radiance, it is an important step to accurately simulate the hyper-spectral infrared radiance. In this paper, the measurement principle of hyper-spectral infrared radiometer is analyzed, and a forward model is established based on ARTS by concerning about the process of interferograms-truncated and discretization. In the forward model, an ideal discretization spectrum was simulated by ARTS firstly, and then the spectrum was transformed into an interference figure through the inverse Fourier transform. After the interference figure was truncated by a specific window function, the Fourier transform was further applied to obtain the simulated spectrum (called “target spectrum” in this paper). During this process, the window function type is dependent on the method of truncation of interference figure in the instrument measurement, (for example, a rectangular function corresponds to an interference figure without a truncation process by apodization function), and both the inverse Fourier transform and the Fourier transform must satisfy the Nyquist sampling law. Based on the forward model, 108 groups of clear sky radiation data in SGP site have been simulated, and the simulation results were compared with the actual measurement results of AERI. The results showed that there was notable difference between ideal spectrum and the spectrum measured by AERI on the gases absorption line, and the maximum residual reached around 35 RU. When a truncation process was added to the simulated spectrum, the maximum residual was constrained within 10 RU, indicating that the truncation process can improve accuracy of the simulated spectrum, especially in the gases absorption lines. Furthermore, the simulated spectrum obtained from six commonly used window function was compared with the spectrum measured by AERI. The results showed that the spectrum processed with rectangular window was most close to AERI measured spectrum, which meant that the window function used in AERI can be seen as a rectangle function. Because the ideal spectral resolution determines the sample rate of the interference figure and computation efficiency of ARTS in transformation of the ideal spectrum to interference figure, it is necessary to find an appropriate ideal spectral resolution to guarantee both the modeling accuracy and efficiency. For this purpose, instrument measurement spectrum were simulated with different ideal spectral resolution, and the residuals between simulated radiations and AERI measured radiations were analyzed. Meanwhile, the influence of spectral resolution on the computational time was discussed. The results showed that when the ideal spectral resolution is set as 0.241 1 cm-1 in the forward mode, the model calculation efficiency can be maximized on the premise of modeling accuracy.

Because the visible and near-infrared reflectance spectrum is easily to be acquired using cheap instrument and suitable for online analysis, the features and generation principle of spectral reflectance curve of coal in the visible and near-infrared range were studied and analyzed in this paper. 12 typical types in the three major coal types of anthracite, bituminous and lignite were collected from coal mines in Shanxi, Shandong, Ningxia and Jilin. With decreasing coal rank, these coals included No. 1 anthracite, No.2 anthracite, meager coal, meager lean coal, lean coal, coking coal, fat coal, 1/3 coking coal, gas fat coal, gas coal, No.1 lignite and No.2 lignite. Spectral reflectance curves of these lump coals were acquired in the visible and near-infrared range by a field spectrometer in the laboratory. By analyzing features of these spectral curves, it was found that reflectance curves of anthracites tend to be horizontal in the whole wavelength range and the absorption valleys are not obvious. With decreasing coal rank, spectral reflectance, spectral slope in the near-infrared range, the numbers of obvious absorption valleys and the absorption intensities all increased. Bands of 13 obvious absorption valleys were selected. Carbon structures and mineral compositions of these coal samples were measured through X-ray diffraction (XRD) analyses. With increasing coal rank, the aromatization tendency of amorphous molecular structures of coal plays a major role in reducing the spectral reflectance and flatting the reflectance curve. With decreasing coal rank, overtones and combinations in the near-infrared range generated by the fundamental frequencies of absorption groups mainly including aliphatic side chains in the mid-infrared range generate a lot of absorption superposition. And most of the absorption valleys are not obvious due to the absorption superposition and the relatively more pronounced absorption valleys appear near 1 700 and 2 300 nm. At the same time, transition metals mainly Fe-contained minerals, H2O, clay minerals and other inorganic components are also the factors that increase the number of absorption valleys of reflectance curve of coal. Through X-ray fluorescence (XRF) and proximate analyses of these coal samples, the contents of major mineral elements such as Fe and Al and the contents of moisture, ash, volatile, and fixed carbon based on air-dried basis were acquired. It was shown that the spectral slope of reflectance curve of coal in the near-infrared range is positively and negatively correlated with volatile yield and fixed carbon content respectively. The sum of absorption depths of H2O bands is well linearly correlated with intrinsic moisture content. There is a basically linear relationship between Fe or Al content and the sum of absorption depths of the relevant bands. However, there is a poorly linear relationship between volatile yield and the sum of depths of 1 700 and 2 300 nm absorption valleys which are mainly caused by overtones and combinations of the organic fundamental absorption bands. The acquisition of reflectance spectrum features of typical lump coals in the visible and near-infrared range provides the basis for hyperspectral remote sensing of coal mine areas and establishment of spectral library of coals, and also the reference for the rapid, low cost and qualitative identification of coal categories by shapes of spectral reflectance curves directly. At the same time, it is of great significance to the development of spectral sensor for coal detection in coal mine.

The current testing of concrete chemical etching mainly includes scanning electron microscope, energy spectrum, X-ray diffraction,which has many disadvantages for the concrete in service such as easy to damage, longertest time, poorer continuity. It was proposed that a novel non-destructive testing of concrete corrosion products based on hyper-spectral technology could be used to overcome this shortage. Hyper-spectral test of concrete has many merits such as non-contact, convenient, and continuous lossless, but there are problems in practical application for the unmixed process and analysis of concrete measured spectrum. It was assumed that the spectrum of the concrete under sodium sulfate was a linear mixture of the two component spectra: one component was the spectral reflectivity of the cement hydration product, and another component was the spectral reflectivity of gypsum and ettringite, according toits features of hydration product in concrete, which was proposed the spectral unmixing model of corrosion products of concrete based on the derivative model of the ratio spectroscopy. The hyper-spectral test of concrete was carried out, and the test objects were two concrete sample groups, which were soaked in water and 10%Na2SO4 solution and measured the reflection spectrume very 15 days for 30 to 120 day age of concrete. Themeasured data was smoothed and continuum removed, and then was processedby spectral unmixing model of the corrosion product of the concrete in order to know the features of unmixingspectrum, which was fitted with the standard spectral curve of the mixture of gypsum and ettringite by SFF matching, and observed ettringite and gypsumcorrosion products by SEMand X-ray diffraction in theconcretesamples. the secondary unmixing of the measured spectrum was used the ratio spectrum curve of concrete divided by the gypsumto study ettringiteformation during the 30 to 120 dayscorrosion processing.The result shows that: (1) With the increase of corrosion time, there is obvious difference in the reflectance spectrum curve of two concrete sample groups at different ages in clean water and 10% Na2SO4 solution. Both of them have strong absorption near 1 445 and 1 945 nm, but the absorption depth and absorption area of the spectral curve of 10% Na2SO4 solution concrete are significantly larger than that of clear water. (2) After the once-processed about concrete spectral unmixing model, there are clear absorption valley at around 1 450 and 1 945 nm in the ratio spectrum curve, which is consistent with the standard spectrum of the mixture of gypsum and ettringite, and matching fitting value of the SFF reached 0.96; (3) The spectral characteristics of the corrosion product ettringite are well highlighted by the curve after the ratio spectrum divided by the gypsum, which indicate that the abundance of ettringite produced show down first and then upfor 30 to 120 day age of concrete.(4) The results ofhyper-spectral, SEM, and X-ray diffraction ofconcrete corrosion product undersodium sulfate attackare identical, which indicates that the type and abundance of corrosion products of the concrete can be calculated correctly with the spectral unmixing modelin the non-destructive test, and provides a theoretical basis for the research of hyper-spectral nondestructive testing of concrete.

Reed canary grass (Phalaris arundinacea L.) is a perennial cool-season gramineae grass with a high yield. Crude protein (CP) is a key indicator in the evaluation of forage quality, but the use of chemical analytical methods to determine the CP content is disadvantageous. Therefore, a fast, efficient, accurate, and safe determination method is required in the development of modern grassland agriculture, animal husbandry and grassland ecological restoration. The purpose of this study is to use near-infrared spectroscopy (NIRS) techniques to develop a quantitative model for the analysis of CP in reed canary grass and provide an effective method for a rapid determination. We collected 454 samples of reed canary grass from various resources, including different cultivars (or strains), different growth stages, different cultivation conditions, different drying methods, different growth years, different parts and different harvest times. The original spectra of all of the samples were obtained using a near-infrared spectrometer (NIRFlex N-500) and Operator software of the Swiss Buchi company. A total of 210 samples were selected for the development and evaluation of models after deleting samples with similar spectra by a K-S algorithm, and were assayed using the Kjeldahl nitrogen method to obtain the chemical values of CP; we then assigned them to spectra in a Management console software. The samples were randomly divided into a calibration set and a validation set according to the proportion of 6∶3, using the NIRcal 5.4 software; the outliers were then eliminated. We established 8 quantitative analysis models for the CP content of reed canary grass by applying different spectral data pretreatments, primary/secondary principal components, spectral regions, and regression algorithms. We revealed that all of the 8 models can be used in the determination of CP by performing an external validation. The best model was chosen by comparing statistic parameters. The results showed that the best calibration model was developed by the spectral data pretreatment of sa3+ncl+db1 (smoothing average 3 points+ normalization by closure+first derivative BCAP), choosing the primary/secondary principal component of 8/1-4 and spectral region of 4 000~10 000 cm-1 in combination with the partial least square (PLS) regression algorithm. Its calibration coefficient of determination (R2cal) and external validation coefficient of determination (R2val) were 0.982 1 and 0.980 2, respectively; both were larger than 0.98, suggesting an excellent predictive ability. The standard errors of calibration (SEC) and prediction (SEP) were 0.780 2 and 0.783 2, respectively; both were very small and similar, which demonstrated the high analytical accuracy and robust fitting. The bias value of -0.000 5, close to 0, demonstrated the model’s stability and robustness, i. e., its insensitivity to the external factors. The correlation coefficient of validation (r) of 0.99 indicated a very high correlation between the predicted and chemical values. The residual predictive deviation (RPD) was 7.37 (above 4.0), further confirming that the CP model can be used for a high-quality quantitative analysis. Therefore, in this study, a quantitative model for a CP analysis of Phalaris arundinacea L. was developed using NIRS for the first time in China with a large data collection from different sources and high accuracy, which guaranteed the reliability and practicability. The model provides an effective method to quantify CP of reed canary grass for a rapid screening of germplasm in breeding programs, optimization of the allocation of livestock diets, and classification of forage products in the supply chain.

The technology of near infrared spectroscopy that has unique advantage in fault detection in industrial processes is an accurateand effective method. Combining the mutual information entropy and the traditional principal component analysis, a new method for extracting the near infrared spectral feature information was first developed. The operating states of the industrial process was described by the constructed process pattern.Near infrared spectroscopy data were used to obtain the process pattern of industrial systems from the vibration information of hydrogen groups in organic molecules in this paper. An effective method to improve accuracy of fault detection in industrial processes was explored from the microscopic molecular level. Combined with Bayesian statistical learning method, an industrial processes fault detection technique based on near infrared spectroscopy data was proposed. Firstly, for the characteristics of rich information, wide spectrum band and weak characteristic, first-order derivative preprocessing of near infrared spectroscopic absorbance data under different operating states of industrial process was applied. Principal component analysis(PCA) was used to compress the amount of spectral data, expand the differences in spectral feature information under different operating states, and extract the internal feature information of the spectrum. Then, mutual information entropy(MIE) was used as correlation measure function of spectral feature information, and the minimum redundancy maximum relevance algorithm was used to further reduce the redundancy between the spectral feature information and maximize the relevance between the spectral and class.It made up for the deficiency of unsupervised feature wavelength selection of PCA. Therefore, a process pattern construction method based on PCA-MIE was proposed. The obtained process pattern subset was more compact and more expressive. Furthermore, Bayesian statistical learning method was applied to make decisions based on posterior probability of the constructed process pattern subset to identify the normal and accident state of the production process. Because the process pattern subset combines the advantages of PCA in density variance reduction and the feature information selection method of mutual information entropy correlation measure, it contains more essential information and inherent laws of near infrared spectroscopy, which can better describe the operating states of the industrial process. Next, The test accuracy (TA) was set as the evaluation criteria to evaluate the performance of the fault detection method. Finally, the data of crude oil desalination and dehydration process provided by the chemical plant was used to verify the effectiveness of the proposed method. Compared with the performance of traditional near infrared spectral feature information selection methods PCA and MIE, the results showed that the process pattern fault detection based on PCA-MIE outperforms the other two methods on almost all dimensions subsets. The highest accuracy rate is 94.6% when the feature dimensions is 18, which proves the superiority of the proposed method.

The diversity of components and interferences of spectral overlapping highly and background reduce the features of the mid-infrared of the complex mixtures. Furthermore, the mid-infrared spectrum of a multi-component complex sample is generally not a simple sum of spectra of the components. Chemometrics techniques are needed for quantitative interpretation of the mid-infrared spectra. The problems of serious overlap and nonlinearity in infrared spectra were solved by data accumulation, feature extraction and correction modeling from chemometrics methods such as PLS and ANN, etc. And bi-measurement quantitative analysis was applied preliminarily based on Lambert Bill’s law and the popularization of the sampling technology of ATR. Then how to reduce these disturbances and ensure the accuracy of the results effectively was the main direction of research. Based on evaluating the spectral intensity of optical channel and background, this study proposed a new approximate linear quantitation method combined with vector angle transformation. Through the preliminary theoretical calculation, it was found that there was a certain relationship between the multi-component mixture and the vector angle value of the relative content in the mixture, and the relationship was not influenced by the batch sampling. Further, the Gauss curve was used to simulate the mixed signal, which fully illustrated a linear correlation within a certain range if suitable wavelength range was selected, and the correlation was not affected by the change of the measurement conditions. The KBr compression method was used to get the mixed samples, into which the components were added step by step, and the spectral and mixed-sample spectral signals were obtained. The first order derivation was carried out to eliminate the additive error signals which were converted into the space vector angle to the elimination of light path difference in batch sampling, and then they converted the content into a percentage. The angle values of the mixed samples have simple linear relationships with the contents of the reference materials. Then the quantitative analysis was made by using the standard curve of the calculated result angle values and the contents. This method was utilized to determine the contents in samples of the mixing of TGS and TGS-6-A (two-component systems), and the deacylated products of TGS-6-A (multi-component systems) with satisfactory results. The established correlation coefficients (r) of the standard curves were all above 0.995 0 and the relative errors were less than 8%. The result shows the established analytical method could meet the content analysis of multi-component samples. It has great reference value for the study of multi-component samples by mid-infrared transmission spectroscopy.

Crop disease is a major biological hazard in agriculture of China and causes serious interference to farming process, so a fast, accurate and efficient diagnosis method for crop disease is in pressing need. Compared to some common crop disease detection technologies (such as polymerase chain reaction technique, artificial sensory evaluation technique, and statistical method), which are time-consuming or can only be used to detect obvious disease spots, spectral technology has potential in rapid detection of crop diseases and has been studied extensively. This passage mainly focuses on the application of visible/near infrared spectroscopy technology in disease detection, discusses instruments involved in this technology, and analyzes research status of visible/near infrared spectroscopy in disease detection from cell, plant tissue, canopy and larger scale aspects. At present, most of researches on visible/near infrared spectroscopy related to plant diseases are based on plant leaves. Few researches are on smaller scale (from cell to microscale) or larger scale (from canopy to aeronautical/spaceflight remote sensing scale), especially when it comes to disease researches on single cell scale, which are only done in the field of animal cells and have no successful application of visible/near infrared technology. However, visible/near infrared technology has many successful application in researches which are on organ scale of plant leaves. Most of common crops and major diseases of common crops, and diseases caused by fungal and bacterial pathogens are involved in current researches of disease detection. These researches are studied usually in three ways: (1) automatic and rapid diagnosis of disease information based on computer image processing and pattern recognition technology, (2) judgement model spectral analysis for Region of Interest (ROI) extracted from hyperspectral images was established based on stoichiometric method, (3) spectral model of some physical and chemical parameters of leaves related to crop diseases was established to quantify the extent of disease. The main problem related to this scale is that the research is so fragmented, which means only one or a few kinds of diseases are studied, that models can only be used in very specific conditions and can’t be used directly to make a full automatic judgment on field samples. What’s more, there are few studies on direct monitoring of crop diseases or multi-spectral imaging of near ground whole plants and the classification methods adopted are similar with those of leaf scale data processing. In near ground canopy scale, three dimensional forms of plants become a new source of interference in the spectral model, and some passage showed that 2D image was used as disease detection data with a percentage deviation of 13%. Finally, according to the present situation of all aspects of researches, it is believed that visible /near infrared spectroscopy technology has a good application prospect in crop disease detection, but it is in the bottleneck period now. There exist some problems, including that unbalanced research content of plant disease detection, lack of systematisms caused by overabundance of disease species and insufficient cooperation of different subjects. According to those problems, this passage points out that visible/near infrared spectroscopy technology should pay more attention to the in-depth cooperation of multidisciplinary in the field of disease detection, and it is urgent to make breakthroughs in the related equipment and method model.

The study of the interaction between drugs and biomembrane is of great significance to the understanding of the drug efficacy and the improvment of their biological properties. However, the composition of biomembrane is complex, which makes it difficult to study the interaction between active components of drugs and biomembrane directly. We used liposome as mimetic biomembrane, investigated the interaction of evodiamine with liposome, analyzed the entrapment position of evodiamine among liposome, and the possible mechanism of the anti-inflammatory effect of evodiamine was also discussed. 1,2-Dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) has been used as membrane material in this study and liposomes containing different molar percentage of evodiamine (x) were prepared by thin-film dispersion method. Fourier transform infrared spectroscopy (FTIR) and Differential scanning calorimetry (DSC) were used to analyze the frequency and shape of infrared absorption peaks and the changes of the calorimetric parameters of DPPC molecules with the increasing of the molar percentage of drugs. The entrapment position of the evodiamine in liposome and the effect of this drug on the fluidity of liposome membrane were discussed. Data showed that the frequency of the asymmetric stretching vibration of the phosphate group in the DPPC head region hardly changed in the concentration range of 0＜x＜10 mol%, but the phase transition temperature and enthalpy of the liposome decreased with increasing x in this concentration range. In the concentration range of 0＜x＜5 mol%, the absorption wave number of hydrated carbonyl in the DPPC interface region increased from 1 726.0 to 1 731.8 cm-1, however, this wave number decreased to 1 728.0 cm-1 at x=10 mol%. In the concentration range of 10 mol%≤x＜20 mol%, the wave number of asymmetric stretching vibration of phosphate group decreased from 1 242.0 to 1 236.3 cm-1, but the absorption frequency of hydrated carbonyl hardly changed, and the phase transition temperature and enthalpy of liposome increased with increasing x. The wave number of the symmetrical stretching vibration of methylene in pure DPPC liposomes was 2 848.4 cm-1, which increased to 2 850.3 cm-1 after drug loading. These results indicated that the entrapment location of evodiamine in liposomes is concentration-dependent: in the concentration range of 0＜x＜10 mol%, evodiamine molecules mainly incorporate into the hydrophobic region of DPPC molecules and a few locate at the interfacial region of DPPC molecules. In the range of 10 mol%≤x＜20 mol%, evodiamine molecules mainly incorporate into the hydrophilic head region of the DPPC molecules and a few locate at the hydrophobic tail chain of DPPC molecules. The phase transition temperatures of all drug containing liposomes are lower than those of pure DPPC liposomes. That is to say, the membrane fluidity of the liposomes could be increased by different concentrations of evodiamine. Moreover, at x=10 mol%, the membrane fluidity of liposomes is the largest. This study will play an important role in the further investigation of the interaction mechanism of evodiamine with biomembrane.

Caffeic acid (CA) is a medicinal component with high medical value. It is widely applied in antibacterial and antiviral applications. In particular, caffeic acid and its derivatives have a enormous function in antitumor. Nowadays, there are many researches about caffeic acid. However, most of them are about the medicinal properties of caffeic acid, as a result the investigation of the microstructure of caffeic acid molecules is necessary. So far, there are no theoretical and experimental studies about the surface-enhanced Raman scattering spectroscopy (SERS) of CA on Ag surface. It is worth noting that the research on the vibrational spectrum and surface enhancement mechanism of caffeic acid can be a variety of pharmaceutical mechanisms of caffeic acid. Therefore, a combine surface-enhanced Raman scattering (SERS) and density functional theory (DFT) techniques are applied to conduct a comprehensive study of the adsorption properties and surface enhancement mechanism of caffeic acid on Ag nanoparticles, which can provide a scientific explanation to the medicinal properties of caffeic acid. This has important reference for advancing their related research in medicine and other fields. In this paper, surface-enhanced Raman spectroscopy of CA molecules on the surface of Ag nanoparticles was studied using combined SERS and DFT techniques. Ag nanoparticles were prepared using trisodium citrate and silver nitrate under heating and stirring using the principle of thermal reduction reaction and conventional Raman scattering (NRS) spectra and SERS spectra of CA molecules were measured usingthe laser confocal micro-Raman spectrometer. In terms of theoretical calculations, we applied B3LYP method to optimize the molecular configuration of caffeic acid, the adsorption configuration of Ag4, the adsorption configuration of carboxyl group and Ag4, and the configuration of adsorption of Ag4 by both hydroxyl and carboxyl groups, using 6-31+G** and LANL2DZ as the basis set for C, H, O, and Ag, respectively. Then, the NRS spectra of CA molecules and the SERS spectra of three possible adsorption models were calculated and compared with experimental results. At the same time, the vibration mode of CA molecules was confirmed. According to the experimental data and theoretical results, the peak at 452 cm-1 was attributed to the coupling of the torsional bending vibration and the —OH out-of-plane bending vibration, which indicated that the phenolic hydroxyl group on the CA molecule have a weak interaction with the Ag nanoparticle. We speculated that the CA molecular plane may not be perpendicular to the surface of the Ag substrate. The peak appearing at 1 338 cm-1 was attributed to COO— stretching vibration, which indicated that the carboxyl group on the CA molecular is vertically adsorbed with the Ag nanoparticle. The results showed that CA molecules adsorbed on the surface of Ag nanoparticles with carboxyl groups and phenolic hydroxyl groups as adsorption sites. At the same time, we have identified the vibrational modes of CA molecules in detail. This work has an important effect on the further applications of caffeic acid in biomedicine and other fields.

The accurate detection of the content of chlorophyll in citrus leaves is of great significance to the nutritional status and the growth trend of citrus. A rapid and non-destructive method for diagnosing chlorophyll content in citrus leaves was studied in order to provide a reference for the detection of chlorophyll content in citrus leaves by Raman spectroscopy. A hundred and twenty slices of citrus leaves with different canopy heights and different geographical distributions were collected. The dust on the surface of the leaves was wiped off. The deionized water was used in the laboratory to clean it, dried in a sealed bag, and labeled with a label. The Raman spectra of citrus leaves were then collected. The parameters were set as follows: resolution 3 cm-1, integration time 15 s; laser power 50 mW. Three methods were used, such as baseline wavelet, iterative restricted least squares （IRLS）and asymmetric least squares (ALS), for background correction of Raman spectroscopy. After that, Partial least squares (PLS) method was used to establish the quantitative model. Subsequently, four methods of spectral pretreatment, like Savitzky-Golay convolution smoothing (SG smoothing), normalization, multiplicative scatter correction (MSC) and the Savitzky-Golay 1st derivative, were used to further optimize the spectra which had been treated by the background correction. The research process showed that the PLS model was established by the spectra of the original spectrum, Baseline Wavelet, IRLS, and ALS preprocessing. The correlation coefficients of the models were 0.858, 0.828, 0.885, and 0.862, respectively. The root mean square error cross validation, RMSECV were 5.392, 5.870, 4.934, and 5.336, respectively. The best principal component factors were 8, 3, 8 and 8 respectively. The RMSECV of the pre-processed PLS model deducted from the IRLS background was the smallest, the correlation coefficient was the highest, and the modeling effect was the best. SG smoothing, normalization, MSC and SG 1st Der preprocessing methods were used to preprocess IRLS background correction spectrum and establish PLS model. The results showed that: IRLS spectrum and its combination of SG smoothing, normalization, MSC and SG 1st Der The PLS of the four pretreatment methods of r were 0.885, 0.897, 0.852, 0.863, and 0.888, respectively. The RMSECV were 4.934, 4.715, 5.595, 5.182, and 4.962, respectively. The best principal component factors were 8, 8, 8, 8 and 5, respectively; the RMSECV of the PLS model after IRLS-SG smoothing was the smallest, and the model had the best effect. After verifying the PLLS model preprocessed by IRLS-SG, the predictive correlation coefficient r of the prediction set was 0.844, the root mean square error of prediction (RMSEP) was 5.29, and the prediction accuracy was high. Three kinds of background correction methods combined with four kinds of spectral pretreatment methods were used to quantitatively model the Raman spectra of citrus leaves. It can be concluded that the experimental results after IRLS background correction combined with the SG smoothing are optimal. The modeling set r is 0.897, the RMSECV is 4.715, the prediction set r is 0.844, and the RMSEP is 5.29, and the prediction accuracy is high. Studies have shown that Raman spectroscopy combined with background correction methods can provide a quick and easy analytical method for quantitative analysis of chlorophyll content in citrus leaves.

Milk fat is the main raw constituent of dairy cream. The source of the milk has a significant influence on its physicochemical properties and the presence of the dispersed phase in the emulsion, which, in turn, influences the quality of cream products. In this paper, Raman spectroscopy combined with dynamic light scattering, near infrared spectrum-stability analysis, and other spectroscopy techniques were used to study the physiochemical characteristics of milk fat from three different sources, namely MF-A, MF-B and MF-C, and to compare the corresponding stability of dairy cream. The Raman spectra results indicatedthat 1 303 and 1 446 cm-1 were —CH2 vibrations, 2 800～3 000 cm-1was a C—H vibration, and 1 131 cm-1 was a C—C vibration, ith a peak intensity of MF-A>MF-B>MF-C (pMF-B>MF-A (pMF-B>MF-C (pXMF-B>XMF-C (p<0.05). The results of this research, which examines the physicochemical properties of milk fats in their continuous/dispersive phase and the mechanism of milk fat composition and crystallization behavior on dairy cream quality, thus provide a theoretical basis for the selection of raw materials in the preparation of a variety of dairy products.

The fluorescence spectroscopic characteristics of DhaA immobilized by amino-modified-mesocellular foam (MCF-NH2) were investigated during denaturation procedures with urea and DMSO as denaturant by using F-4600 fluorescence spectrometer. The unfolding process of DhaA in denaturants was analyzed by phase diagram of fluorescence, and thermodynamic parameters were calculated with residual activity ratio of DhaA. The difference between the non-immobilized and immobilized DhaA in aspect of unfolding process and thermodynamic parameters were compared. The results showed that the catalytic activity of DhaA declined with the increasing concentration of denaturants, and the catalytic activity of immobilized DhaA could be maintained better than that of free DhaA at the same concentration of denaturant. The stabilization effect of MCF-NH2 to DhaA was obvious before the denaturants concentration reached a critical concentration (5.5 mol·L-1 for urea, 7 mol·L-1 for DMSO). The unfolding procedure of DhaA induced by urea conformed to typical “two-state” model. The unfolding procedure of DhaA induced by DMSO conformed to “three-state” model, and the intermediate state of DhaA appeared at the DMSO concentration of 5.6 mol·L-1. Immobilization by MCF-NH2 didn’t change the degeneration process of DhaA, but could raise the thermodynamic parameters during the unfolding process of DhaA. When induced by urea, the ΔG(H2O) was 8.51 kcal·mol-1 for free DhaA and was increased to 9.55 kcal·mol-1 for the immobilized one. However, the solvent-accessible surface area (m) increased from 3.69 to 4.00 kcal·(mol·mol·L-1)-1 after immobilization, which might be caused by the convenient moving of urea molecules into MCF-NH2 with electrostatic attraction. The amino and hydroxyl groups in the channel of MCF-NH2 could enhance DhaA rigidity through hydrogen bonding effectively reduced the effect of increasing of urea-accessible surface area, and improved the urea tolerance of DhaA. When DhaA was induced by DMSO, the ΔG(H2O) values of process from fold state to intermediate state were always 12.12 kcal·mol-1 in the before and after immobilization. The solvent-accessible surface area of DhaA dropped from 3.39 to 2.30 kcal·(mol·mol·L-1)-1 after immobilization, which might be caused by the block effect of amino and hydroxyl groups in MCF-NH2 which effectively inhibiting the entry of non-polar DMSO molecules. From intermediate state to unfold state, the exposure of hydrophobic amino acids in DhaA leaded to an increase of m value, but the m value of immobilized DhaA ［4.40 kcal·(mol·mol·L-1)-1］ was still lower than the free DhaA ［4.94 kcal·(mol·mol·L-1)-1］ due to the polar microenvironment in the channel. Studying the unfolding process and thermodynamic parameters by fluorescence spectrometer is an effective technological mean for the research on DhaA stability, which can also offer a methodological guidance for stabilization mechanism study for other enzymes.

The traditional fluorescence detection method of PAEs is mainly the indirect fluorescence detection with bovine serum albumin (BSA). The 6 environmental priority control pollutants PAEs were taken as an example, and the 4th position on the benzene ring were introduced by substituent groups for molecular design to obtain PAEs derivatives with high fluorescence spectral intensity, which is advantageous for direct fluorescence detection. Simultaneously, the molecular docking method was used to simulate the binding of PAEs and BSA. The fluorescence intensities of PAEs after binding with BSA were calculated and compared with the fluorescence intensities of PAEs derivatives. The PAEs derivatives with significantly enhanced fluorescence spectra intensity were screened, which can provide theoretical support for the detection of PAEs derivatives. The results showed that 30 PAEs derivatives have been designed, and the fluorescence intensities of 18 PAEs derivatives were significantly increased by 100%～1850%, indicating that the intensities of the direct fluorescence detection of the PAEs derivatives are significantly stronger than those of the traditional fluorescence detection of the PAEs; the functional properties of the 18 PAEs derivatives (represented by stability and insulation) were less affected, and the environmental persistence values of the PAEs derivatives were reduced, and the bioconcentration values did not change significantly, and the mobility values and the toxicity values had different degrees of reduction. In addition, there is no interference between PAEs derivatives and other fluorescent substances (PAHs) (the minimum wave number difference is greater than the fluorescence detection resolution 0.30 nm), and the occupied orbital energies and the mulliken charge numbers are the main controlling factors that lead to the spectral characteristics of PAEs derivatives.

In order to explore the three-dimensional fluorescence characteristics of DOM during the preoxidation process of high algae-laden water with ClO2, the three-dimensional fluorescence spectroscopy technique was used to qualitatively investigate the changes of the composition of intracellular and extracellular organic matters in algae, and the quantitative analysis of changes in DOM composition was performed by fluorescence regional integral method. The results showed that the IOM fluorescence spectrum of the raw water containing high concentration of Microcystis aeruginosa had four distinct fluorescence peaks, which were protein fluorescence peaks, humic acid fluorescence peaks, fulvic acid fluorescence peaks, and soluble microbial metabolites peaks that were represented mainly by tyrosine-like substances and tryptophan-like proteins with 14.52%, 48.27%, 16.22% and 20.99%, respectively. While the EOM fluorescence spectrum had only one significant fluorescence peak with 63.14% that was mainly behalf of soluble microbial metabolites, and algae organics were mainly contained in IOM. The removal rate of chlorophyll a reached to 73.58% within 3 minafter preoxidation process with 0.5 mg·L-1 ClO2. During this process, substances in the regions Ⅰ, Ⅱ, and Ⅲ represented by amino acids, proteins, and fulvic acid respectively were released to outside of the algal cell membrane, and then were oxidized to non-biological humus by ClO2. Owing to algal cells burst constantly, IOM was released into the water during the ClO2 preoxidation process, leading to the results that the total response value of EOM increased by 54.89% within 3 min and the total response value of IOM decreased by 51.50%. Therefore, the drinking water treatment of high algae-laden water should pay close attention to the release of IOM from the algae cells. The appropriate preoxidation time and dosage should be properly selected, and the release of IOM should be reduced as much as possible under the premise of effective algae removal.This study will provide further theoretical and scientific basis for the removal of algae by pre-oxidation in drinking water and the control of algae disinfection by-products.

Polycyclic aromatic hydrocarbons (PAHs) have strong carcinogenicity and threaten human health. In the complex water quality detection environment, when the concentrations of PAHs are detected by fluorescence spectrum, the spectral signal may contain obvious non-stationary noise due to the influence of Rayleigh scattering in the measured spectrum. The common multiple sampling and averaging method tend to generate obvious measurement error in the PAHs spectrum, thereby leading to low detection accuracy of PAHs. In this paper, an optimal detection method for PAHs concentration based on three-dimensional (3D) fluorescence spectral analysis and N-way partial least square (N-PLS) is proposed. First, the spectral features of the four PAHs solutions of phenanthrene, fluorene, acenaphthene and fluoranthene were analyzed. The Rayleigh scattering noise in the spectrum was eliminated by fitting the scattering band data point values while the original spectrum information was preserved as much as possible. The features such as the mean, variance, and one-dimensional marginal distribution of the four PAHs spectrum were extracted,and the similar spectral data samples were merged according to samples classification of four spectral data by feature clustering analysis. Secondly, the N-PLS model was established based on the relationship between the spectral signal of the correction set and the different PAHs concentration. Subsequently the N-PLS model was used to predict and analyze the concentration of various PAHs, and verify the relationship between the PAHs concentration and the fluorescence intensity of the spectral data. Finally, the concentration residuals were modified by bilinear decomposition, the concentration residuals between aqueous solutions containing various PAHs and real water samples were verified, and the prediction errors of PAHs under different parameters were also analyzed. The experimental results showed that the phenanthrene solvent exists two obvious fluorescence peaks, and their excitation and emission wavelengths are 285/245 and 315/345 nm respectively. Both fluorene and fluoranthene have six obvious fluorescence feature peaks. Their excitation and emission wavelengths are 265/255, 325/345, 335/325, 365/355 nm, 385/395 and 405/415 nm respectively. Moreover, the fluorescence peaks are far away from the other PAHs. There appear continuous peaks in the acenaphthene solution where the emission wavelength is in the range of 300~485 nm, and the corresponding excitation wavelength is 255~360 nm. The PAHs prediction error of N-PLS method for different water quality is small, where the RMS error of phenanthrene and fluorene are less than 0.4 μg·L-1, the relative error is less than 6%, and the RMS error of acenaphthene and fluoranthene are less than 1.0 μg·L-1, their relative error are less than 9%. The diffusion degree of PAHs is determined by the simulation and analysis of the diffusion tendency of four different kinds of PAHs in river, where the diffusion rate of fluorene and phenanthrene is about 51 mg·L-1, and acenaphthene and fluoranthene is 21 mg·L-1. Their diffusion rate is linear in a certain range and there is a linear relationship between PAHs and its concentration in accordance with Lambert-Beer law. The iteration times with the highest RMS error accuracy are obtained through the RMS error analysis of N-PLS method with different iteration times. The fit and correlation coefficient of the N-PLS method for PAHs prediction with different main factor numbers are compared The results showed that when the number of main factors is 3, the fitness could be up to 96.5, and the effect of N-PLS prediction model is optimal. Overall, the proposed method has higher detection accuracy, better recovery rate and stronger robustness compared with other detection methods.

Phenol, thymol and other phenolic compounds seriously harm the human body, animals and plants. They often exist in water at the same time. Because the excitation emission spectra of phenol and thymol are overlapped severely, and the conventional fluorescence method cannot achieve direct and rapid determination. Identification and quantification of two phenolic compounds (phenol and thymol) in lake water with unknown interferences using the three-dimensional fluorescence spectroscopy combined with four- dimensional parallel factor (4-PARAFAC) algorithm. The spectral data were analyzed and processed by the three-way parallel factor and the four-way parallel factor algorithm to explore the “high-order advantage” of the third-order correction algorithm. In this paper, the method of introducing an extra solvent mode to construct four-way data set was firstly used. The four-dimensional data array was obtained by superimposing the excitation emission matrixs obtained by scanning at different temperatures along the temperature dimension. Identification and quantification of two analytes using third-order calibration method based on four-way PARAFAC coupled with four-dimensional data. In order to avoid the influence of the instrument and scattering of solvent, firstly, the data obtained by scanning was preprocessed. The scattering signal in the excitation emission matrixs was removed by subtracting the blank sample and Delaunay trigonometric interpolation, and further excitation emission correction was performed to obtain true spectra. Then the data were analyzed using the second-order calibration algorithm based on the parallel factor and the third-order calibration algorithm based on the four-dimensional parallel factor, and the analysis results of two algorithms were compared. The results showed that the four-dimensional data array does not stimulate the simple superposition of emission matrices, and the four-dimensional data have rich high-dimensional information, which helps to improve the measurement results of the analytes. The average recoveries were obtained by the four-way parallel factor analysis algorithm, being the results: 97.7%±9.2% for phenol and 96.5%±8.8% for thymol. And the root-mean-square error of prediction values, for phenol and thymol, were 0.047 and 0.057 μg·mL-1, and the values of prediction relative error were less than 10%. Which were better than the results of three-way parallel factor analysis (105.7%±15.3% for phenol and 111.0%±3.6% for thymol, and the root-mean-square error of prediction values, for phenol and thymol, were 0.090 and 0.056 μg·mL-1, and the values of prediction relative error were larger than 10%). In short, the third-order calibration algorithm was superior to the second-order calibration algorithm in the sample with high background interference and severe collinearity. It provides a reliable method for the determination of phenol and thymol in the complex system.

Ultraviolet absorption spectrophotometry was applied to the determination of sodium lauryl diphenyl ether disulfonate (SLDED) in SLDED and sodium dodecyl sulfonate (SDS) complex systems. The results indicated that the existence of SDS not only can improve the ultraviolet absorption intensity of SLDED but also can greatly decrease the apparent critical micelle concentration values of SLDED in aqueous solution. With the addition of 0.500 mmol·L-1 SDS, the ultraviolet absorption intensity of SLDED increased from 0.631 to 0.682, with an increase of 8.1%. In addition, the apparent critical micelle concentration values of SLDED reduced from 1.12 to 0.702 mmol·L-1 when the concentrations of SDS respectively increased from 0 to 0.500 mmol·L-1. The results also showed that the interference of SDS on the ultraviolet absorption intensity of SLDED could be greatly reduced by HP-β-CD. With the addition of 1.000 mmol·L-1 HP-β-CD, the ultraviolet absorption intensity of 0.500 mmol·L-1 SLDED increased from 0.796 to 0.798, with an increase of only 0.3%, much lower than the increase without HP-β-CD. SLDED molecules were more likely to form inclusion complexes with HP-β-CD rather than micelles. Thus, the standard molar Gibbs free energy for SLDED from aqueous SDS/SLDED binary blend solution to the micelle, ΔγGθm, was respectively increased from -41.098 to -39.833 kJ·mol-1, -39.488 and -38.184 kJ·mol-1 while the concentrations of HP-β-CD increased from 0 to 0.400, 0.800 and 1.200 mmol·L-1. The results of Job’s plot for inclusion complexation of SLDED with HP-β-CD indicated that “HP-β-CD/SLDED” inclusion might be formed with the molar ratio of 2∶1. The concentration of SLDED in aqueous SDS/SLDED binary blend solution, could be accurately calculated by adding HP-β-CD with the molar ratio of 2∶1, and the recovery rate of SLDED was 100.8%~101.4%. The results of 1H-NMR and FT-IR exhibited that the interference of SDS on determination of SLDED could be greatly reduced because of the formation of SLDED/HP-β-CD inclusion with SLDED molecule locating within the HP-β-CD molecule.

The proliferation of algae has had a major impact on drinking water sources, aquaculture, tourism and human health. As a kind of biological control, algae-lysing bacteria, have shown great potential in controlling algal blooms. The research group isolated a strain of Chrysosporium sp. S7 in the early stage and found that, by secreting algae-dissolving substances, the strain had obvious algae-dissolving effect on algae in an indirect way. In order to reveal its algae-dissolving characteristics and mechanism, this study, with the Microcystis aeruginosa as the target algae species, employed S7 UV-Vis, EEMs, FTIR and FCM techniques to analyze the spectral characteristics of the algae-dissolving process of Chryseobaterium sp. S7. By co-culturing the fermentation broth of the strain with the solution of algae for 7 days and by analyzing the change trend of Chla content and PC fluorescence value of algae cells through UV-Vis and EEMs techniques, the research group got the following results: the content of Chla in algae cells began to decrease on the 1st day, which indicated that the extracellular algae-dissolving substances of bacteria could quickly act on algae cells in short time, and the removal rate of Chla was 59.37% on the 7th day. In addition, the fluorescence value of PC cells in algae cells also showed a similar downward trend with the trend of Chla, indicating a decrease in Chla and PC during the algae-dissolving process. The research group found that the absorption peaks of CO, C—H and O—H bonds in the algal cell structure showed a significant downtrend at 1 647, 2 927 and 3 475~3 437 cm-1 respectively, which suggested that the polysaccharide content in algae cells and the protein structure might be destroyed, while several small absorption peaks in the range of 2 500~1 700 cm-1 further indicated the phenomenon of disintegration of algae cells. The research group also carried out PI-specific staining of algae liquid on the 3rd and 7th day, and analyzed the PI-specific fluorescence of algae cells and the auto fluorescence characteristics of Chla and PC by FCM technique. The results showed that, the PI-specific fluorescence of cells increased gradually in the algae-dissolving process of bacteria S7, and the autofluorescence of Chla and PC showed a downward trend, indicating that the damage degree of algal cell membrane, Chla and PC had a close internal relationship with each other and high consistency in the algae-dissolving process. During the algae-dissolving process, the algae cells showed various forms of damage, and the damage was in the process of dynamic change, with the Q1 (Q5) quadrant cells gradually moving to the Q4 (Q8) quadrant cells in sequence. Therefore, the possible algae-dissolving process of Chryseobaterium sp. S7 could be speculated as follows: The bacteria release the algae-dissolving active substance to the outside of the cell, and the algae-removing active substance changes the structure and permeability of the algal cell membrane by destroying the structure of the polysaccharide and protein in the cell membrane of Microcystis aeruginosa, which will further destroy Chla in the cell body, PC, DNA/RNA and other substances. All these will cause the algae to lyse and die, eventually forming cell debris. This study, by analyzing the crystallization characteristics of algae cells in the algae process of Chryseobaterium sp. S7, reveals the algae-dissolving mechanism of algae-lysing bacteria, and thus provides a theoretical basis for microbial algae control and restoration technology.

In order to improve visible multispectral image (MSI) compression efficiency and further facilitate their storage and transmission for the applications of generic fields, in which both high colorimetric and spectral accuracy are desired, a nonlinear spectral reflectance model is proposed. Then based on this, LabW2P codec is presented, which has the advantages of moderate complexity, good illuminant stability and support for consistent color reproduction across devices. First, according to spectral characteristics of MSIs, a nonlinear spectral reflectance model is proposed for the decomposition and representation of spectral data to different transformation spaces. In the model, spectra are expressed as linear component and difference spectra. The linear component consists of six transformation basis and spectral projection coefficients. And the difference spectra are non-linear represented components. The model provides the theoretical basis for the construction of the coding algorithm and the improvement of spectral and chrominance reconstruction performance. Then, according to the characteristics of human visual system, illumination conditions, and CIE standard chromaticity space transform function, the three-dimensional (3D) colorimetric information Lab of spectral reflectance is extracted to ensure the colorimetric accuracy of the reconstructed image. Meanwhile, based on the nonlinear spectral model, visual-curve-like trigonometric function basis are used to obtain the first 2D projection coefficients of linear component as the latter 2D coding values that are W1 and W2, which can be utilized to approximate R and G channels, and also improve the colorimetric and spectral reconstruction accuracy. Combined with error compensation mechanism, predicted difference spectral is generated. The Principal Component Analysis (PCA) method is used to extract the first principal component P which compensates for the linear spectral reconstruction error and further improves the spectral accuracy. Finally, the extracted three components are combined to form LabW2P coding. LabW2P decoding scheme is the inverse of the coding. First, according to Lab, W1 and W2, combined with CIELAB to CIEXYZ conversion function, illumination conditions, CIE standard observer color matching function, and trigonometric function basis, the reconstructed projection coefficients on transform space are obtained by using least square regression, and then linear spectral data is rebuilt. Next, based on the value of P, inverse PCA is utilized to gain the reconstructed prediction difference data. Finally, two parts of reconstruction data are combined to get the reconstructed MSI. Experimental results show that the average colorimetric precision of LabW2P algorithm is 0.207 6, which is increased by 81.54%, 55.48% and 32.29% respectively in comparison with that of the classical PCA, LabPQR and LabRGB methods. The maximum average color difference is 0.507 0, and in addition, it is between 0 and 0.5, reaching the color reconstructed level of being visually neglected. Meanwhile, the average spectral precision is 0.012 7, which is slightly weaker than that of PCA, but 13.01% and 6.62% higher than that of LabPQR and LabRGB respectively. The results indicate that LabW2P has obvious advantages of both colorimetric and spectral reconstruction performance. Besides, our coding values can be used directly for object color estimation. And compared with PCA and LabPQR, LabW2P transmits less side information and has higher compression ratio.

Astronomical spectrum is an important research object in astrophysics. Many physical and chemical properties such as effective temperature, metal abundance, surface gravity and radial velocity can be inferred according to the spectra. The white dwarf main sequence binary star (WDMS) is a kind of binary star system, which is of great significance to the study of the evolution of binary stars, especially the evolution of post-common envelope. Domestic and foreign survey telescopes such as SDSS and LAMOST generate massive spectral data every day and such a large amount of spectral data cannot be analyzed manually. Therefore, it is very practical to use the machine learning method to automatically search for the WDMS spectra from the massive survey spectra. Current automatic spectral identification methods mainly depends on the existing labeled samples. Nevertheless, the number of WDMS spectra is limited. To accurately study the spectral features of WDMS spectra through a limited sample set, it is necessary to increase the number of samples and improve the accuracy of the feature extraction algorithm simultaneously. In the previous work, a batch of WDMS spectra was identified through machine learning methods in the sky survey data, providing data source for the experiment. In this paper, the generative adversarial network (GAN) is used to generate new WDMS spectra and expand the training data volume to about twice the original data set, which enhances the generalization ability of the classification model. By modifying the loss function by Anti-Bayesian learning method, the value of the loss function is correlated with the variance of the sample, which suppresses the influence of abnormally large data on the model. It improves the robustness of the model and solves the problems like vanishing gradient and getting stuck in a local optimal solution caused by the deviation of the training sample. The experiments in this paper are based on the Tensorflow deep learning library. The GAN built by Tensorflow is robust and encapsulates the internal implementation details, making the algorithm itself better represented. In addition, the Convolutional Neural Network (CNN) built by Tensor flow was used in this experiment for classification accuracy testing. The experimental results show that the two-dimensional convolutional neural network can use the convolution kernel to effectively extract the convolution characteristics of WDMS spectra and classify them. The convolutional neural network classifier based on the anti-Bayesian learning strategy achieves an accuracy of about 98.3% in the identification task of original WDMS spectra and GAN generated data. The method can also be used to search for other specific targets such as cataclysmic variable stars or supernova in the massive spectra of the telescope.

The spectral emissivity is an important parameter of the radiant capacity of the radiator. Through the spectral emissivity, the relationship between the radiator and the blackbody can be setup. Therefore, the theory of the blackbody radiation can be applied to the general radiator. By using the planck formula, each spectral channel of a spectral pyrometer can constitute an equation, which includes the true temperature, the brightness temperature and the spectral emissivity. There are Nmeasurement channels, but N+1 are unknowns (Nunknown emissivities εi and a temperature T). Because the equations are under determined, there are many solutions in theory. In order to solve this equation group, the assumption of mathematical model between the spectral emissivity and wavelength or temperature is required and the number of unknown numbers of the equation group is reduced to N, and then the true temperature can be solved. When the law of the spectral emissivity and wavelength or temperature is correctly obtained, the true temperature can be calculated by multispectral radiation thermometry. Through the analysis of the two commonly the spectral emissivity models, the basic idea of the two methods is to try to find the relationship between the spectral emissivity and the wavelength or the temperature and establish the mathematical model between the spectral emissivity and the wavelength or temperature. Because the spectral emissivity has certain uncertainty, the assumed spectral emissivity model is inconsistent with the variation rule of the actual the spectral emissivity, which will cause larger inversion error. The mathematical model between the spectral emissivity and the wavelength or temperature is needed a lot of experiments and experiences, and the mathematical model is poor in generality. Especially when the measured radiator is changed, the mathematical model is also meaningless. In order to solve the problem of multispectral pyrometer in actual measurement, it is an urgent need to find a multispectral true temperature inversion method which does not have to assume the mathematical model between the spectral emissivity and the wavelength or temperature. Therefore, the idea of optimization is introduced into the multispectral true temperature solution for the first time, and the problem of multispectral true temperature is transformed into a multi objective minimization optimization problem(MMP). The mathematical model between the spectral emissivity and wavelength or temperature is no longer needed, and the complexity and the difficulty of the system is reduced. Based on the planck formula and equality constrained conditions among spectral emissivities, the method constructs six objective functions and the solution of true temperature is realized. The inversion accuracy of new method is greatly improved, and the error of simulation data is less than 1%. With the aid of the actual measurement data in the past, the multi objective planck minimization optimization method is used to realize the inversion of the true temperature.

Large grained synthetic diamond single crystals have been synthesized by international advanced six-sided top hydraulic press by Ji’nan Zhongwu New Material Co. Ltd. To characterize the quality of these synthetic diamonds and establish the identification principles, 225 large colorless, yellow, and blue HPHT synthetic diamonds produced by the company were studied by stereoscopic microscope, multi-spectral induced luminescence imaging system (GV5000), infrared absorption spectrometer (FTIR), diamond photoluminescence spectrometer (PL5000), laser induced breakdown spectrometer (LIBS) and X-ray energy dispersive spectrometer (EDS) and compared to natural diamonds. The crystal morphology of HPHT synthetic diamonds is mainly composed of octahedral (111) plane and cubic (100) plane. The yield rate of the round bright cut diamonds is between 20% and 67%. The clarity grades of colorless HPHT synthetic diamonds range from VVS to P, and color grades are between D to H. GV5000 is employed to perform a study of both growth structure and luminescence characteristics of the samples. The cubic-octahedral luminescence patterns related to crystal growth structure can be observed in all samples of three colors. The colorless samples show strong blue fluorescence and phosphorescence. The luminescence peak is at 495 nm, which is related to the paramagnetic nitrogen in the lattice. The blue samples show blue to greenish blue fluorescence and blue phosphorescence, with the luminescence peak at 501 nm, related to the paramagnetic nitrogen and boron in the lattice. The yellow samples show weak green fluorescence and phosphorescence and the luminescence peaks related to Ni+ are at 556 and 883 nm. Synthetic diamonds with those features above can be distinguished from natural ones. Infrared absorption spectra show that the colorless HPHT synthetic diamonds having no significant nitrogen-related absorption at 1 332~1 100 cm-1, with boron (B0) related absorption at 2 802 cm-1, are classified as type Ⅱa containing a small amount of boron. The blue HPHT synthetic diamonds are type Ⅱb with strong boron-related absorption at 1 294 cm-1. The yellow HPHT synthetic diamond samples are type Ⅰb with obvious absorption peaks at 1 130 and 1 344 cm-1 which are caused by single nitrogen. Luminescence peaks related to Ni defects at 659, 694, 708, 714 and 883 nm are observed in colorless, blue and yellow samples under photoluminescence spectra (PL5000). In contrast, natural colorless and yellow diamonds are usually type Ⅰa, with infrared absorption peaks at 1 282 and 1 175 cm-1 caused by aggregate nitrogen. Zero phonon lines at 415 nm (N3) can be detected by photoluminescence spectra. Spectral features caused by isolated nitrogen, boron and nickel are extremely rare in natural colorless and yellow diamonds. Therefore, infrared absorption spectra and photoluminescence spectra features can be used as the significant evidence for identification. The main composition of the extrusive inclusions in colorless HPHT synthetic diamonds turns out to be Fe by LIBS. EDS analysis displays that among samples with a relatively large number of inclusions, Fe is detected in blue and colorless samples, and Fe and Ni are tested in yellow samples. Both Fe and Ni are compositions of inclusions, which can be used as one of the identifiable characteristics of HPHT synthetic diamonds. In conclusion, the large grained HPHT synthetic diamonds can be distinguished from natural diamonds based on the fluorescence and phosphorescence characteristics under ultra-short ultraviolet light irradiation (GV5000), accompanied by infrared absorption spectra, photoluminescence spectra (PL5000) and X-ray energy dispersive analysis features.

Tea polyphenol is one of the main biochemical active components in green tea. Being a higher content of components and more active and effective ingredient in tea polyphenols, the epigallocatechin-3-gallate (EGCG) molecule and its stereoisomer GCG are selected to calculate and study the infrared spectrum and ultraviolet spectrum in this paper. In Gaussian software 09, the B3LYP density functional theory (DFT) was used to optimize the molecular geometric configuration at the base ground level of 6-311G (d,p). After frequency calculation, the infrared spectrum was obtained, and then the vibration characteristics were analyzed. It can be seen that the weight of all groups’ vibration in each vibration mode in the infrared spectrum of EGCG and GCG, and the corresponding vibration attribution and comparative analysis were made. It is found that the infrared spectra of molecule EGCG and GCG are similar. The absorption peaks for carbonyl stretching vibration are at 1 711 and 1 717 cm-1, respectively. The absorption peak of stretching vibration of phenolic hydroxyl groups on the benzene ring is mainly concentrated in 3 500~3 800 cm-1. Multiple absorption peaks in 1 000～1 600 cm-1 are in-plane bending vibration of benzene. The absorption peaks near 1 350 and 1 280 cm-1 are caused by methylene and methine in-plane bending vibration. The absorption peaks of out-plane bending vibrations are all below 500 cm-1. The infrared spectrum of EGCG molecule (400～4 000 cm-1) was measured through solid powder tableting method by using the IRPRESTIGE-21 infrared spectrometer manufactured by Shimadzu Corporation of Japan. The experimental infrared spectrum of EGCG is compared with the theoretical infrared spectrum. The result shows that the IR spectrum measured in the solid phase is almost consistent with the values calculated in gas phase. The theoretical infrared spectrum has slightly red-shift. The reason may be that the potential function used in theoretical calculation under the gas phase exist error. Compared with the gas phase without molecular interaction, the actual bond strength in the solid phase is slightly higher than that under the gas phase condition. In Gaussian software 09, the time-dependent density functional theory (TD-DFT) was used to calculate 15 excited states of EGCG molecules in ethanol solvent. The composition and energy level transition of the excited state were analyzed. The two absorption peaks by theoretical calculation were 229.3 and 276.4 nm, respectively. They were main corresponding the transition of p-π conjugated electron of p-electron and benzene ring π bond and the π-π* transition on benzene ring and heterocyclic ring. According to the analysis of the intensity of the oscillator, the transition from the ground state to S4, S5, S6 and S12 excited states is the main reason for the ultraviolet spectrum. The other excited state may be the forbidden transition, because the intensity of the oscillators are all less than 0.01. The above calculated value is almost consistent with the maximum absorption peak of the experimental values of EGCG. The absorption peak of experiment is at 235.1 and 278.7 nm in ethanol solvent. The calculated value is slightly blue-shift, which may be caused by the weak alkaline of the tea polyphenols or the weak alkaline of the molecules themselves. This study can provide theoretical reference for studying the properties and biological activities of EGCG and GCG molecules and the antioxidant properties of tea polyphenols.

Sleep Apnea Syndrome (SAS) is known as the “sleep killer”. The diagnostic rate is low due to the limitations of the Polysomnography (PSG) diagnostic criteria. Studies have shown that heart rate rhythm changes when apnea occurs, so automatic screening of SAS can be achieved by measuring Electrocardiograph (ECG) signals based on Heart Rate Variability (HRV) analysis. However, the electrodes used in the ECG-SAS method are cumbersome, can easily cause skin allergy, and affect sleeping comfort. Due to Pulse Rate Variability (PRV) analysis being highly correlated with HRV analysis and photoplethysmography (PPG) signals being simpler to acquire than ECG signals, this study proposes using synchronously acquired PPG and ECG signals and applying the same modeling method to compare the recognition ability of the two methods. The benefits for acquiring PPG instead of ECG are that the electrode does not cause skin allergyand is easier to wear so that it has little interference with sleeping comfort. The Back-Propagation (BP) neural network is applied to establish the automatic screening models of PPG-SAS and ECG-SAS, respectively. The 10-fold cross validation method and the Receiver Operating Characteristic (ROC) curves are used to compare and to evaluate the models. The experimental data are from MIT-BIH Polysomnographic Data base that contains 8 248 samples, including 6 227 normal samples. First of all, we established PPG-SAS and ECG-SAS models using a three-layer BP neural network with the default parameters, and compare their classification performances through the 10-fold cross validation method and the ROC curves. And then, we successively adjusted the number of hidden layer nodes, training functions and transfer functions to establish corresponding PPG-SAS and ECG-SAS models, and compare the respective optimal models obtained by using the 10-fold cross validation method. Through the comparisons of the recognition and prediction accuracies and the area of the ROC curves, the results illustrate that the PPG-SAS model is better than the ECG-SAS model when default parameters were applied. By comparing the average classification performances, we obtained the optimal model of PPG-SAS with 50 hidden layer nodes, trained function based on one-step secant method, and transferred function based on hyperbolic tangent sigmoid. The optimal PPG-SAS model has the highest recognition accuracy of 80.30% and prediction accuracy of 80.13%. Similarly but with a different transfer function of radial basis, the optimalECG-SAS model has the highest recognition accuracy of 77.60% and prediction accuracy of 77.67%. The results showed that the optimal PPG-SAS model is better than the optimal ECG-SAS model. The above experimental results demonstrated that the SAS classification ability by using PPG signals is superior to that by using ECG signals, which proved the feasibility and reliability of the PPG-SAS screening method. Therefore, the PPG-SAS screening method will lay a theoretical foundation on early detection of SAS and improvement of its diagnostic rate.

The land reclamation and its monitoring in coal mining area is of great significance to land use and ecological environment governance in China. The Microbial Reclamation Technology can promote the plant’s absorption and utilization for mineral nutrient and water, and strengthen the soil fertility, having a significant effect on ecological restoration of mining area. The traditional method for monitoring the land reclamation on plant growth is usually collecting plant and soil samples in the field for indoor analysis. But this method not only destroys rhizosphere soil, causing damages to plants, but also consumes large quantity of manpower, material resources, and time. The hyperspectral remote sensing technology has the advantages of fast data acquisition, large information, high precision and nondestructive for plants, having great potential for land reclamation monitoring. At present, the research on the monitoring of land reclamation through remote sensing still stays at the laboratory level of observing the leaf spectra of potted soybean, corn and other crops. In fact, the observation of satellite remote sensing data is the canopy spectra, not the leaf spectra, but now there is no research result on the monitoring of land reclamation in the mining area based on vegetation canopy spectra. The vegetation canopy spectrum is not only affected by the leaf spectrum, but also influenced by other factors such as plant growth condition and underlying surface, and the spectral change is more complicated. Analysis on susceptibility of vegetation canopy spectra in coal mining area to land reclamation is the basis of the quantitative inversion for the physical and chemical parameters of vegetation, and the main bottlenecks of the hyperspectral technology to be applied in large area reclamation monitoring.This research performs field experiment on vegetation canopy spectral observation in the land reclamation basement of coal mining area, obtains the wild plant canopy spectral data of reclamation group and the control group, and comprehensively analyses the spectral susceptibility of vegetation canopy spectra to land reclamation, from the aspects of spectral waveform and spectral feature parameters. In terms of the spectral waveform of canopy, standard deviation and spectral sensitivity are used as effective indicators for the difference of spectral waveform within each group and between two groups. As for the canopy spectral feature parameters, we selected the red edge, yellow edge, blue edge, red valley and green mountain as typical spectral features, calculated their parameters (such as wavelength position, slope and area), and performed descriptive statistical analysis and one-way ANOVA to investigate the canopy spectral feature parameters’ sensitivity to the effect of land reclamation. Results showed that the canopy spectral waveform trend of the reclamation group is similar with that of the control group, but the plants in the reclamation group have smaller spectral difference, and their vegetation typical features, such as green peak and red valley, are more prominent. This indicated that land reclamation can reduce the canopy spectral difference between plants and strengthen the typical vegetation spectral features, while green peak and red valley are the most sensible spectral features to land reclamation effect. In terms of the specific canopy spectral feature parameters, the wavelengths of green peak, red valley and red edge tend to shift to longer wavelength significantly under the function of land reclamation, but the slope of red edge and blue edge, which are sensitive to land reclamation changes in previous studies on leaf spectra, are not significant any more in this research. This showed that the analysis results based on vegetation canopy spectra in the field are not in consistent with previous laboratory analysis results of leaf spectra, which may be caused by vegetation types, growth cycle, the interference of soil background, etc. When monitoring the vegetation environment in mining area based on satellite or aerial remote sensing, the data obtained are canopy spectra, not leaf spectra. Therefore, the conclusions of this research have strong reference value for future practical applications.

Powdery mildew is one of the common diseases of cucumber, which has a rapid propagation speed and can cause a large reduction of cucumber. Quick and accurate recognition of cucumber powdery mildew has great significance for the diagnosis and control of cucumber diseases. Utilize visible spectrum technology combined with principal component analysis and support vector machine algorithm can realize the quick recognition of cucumber powdery mildew. Sphaerotheca fuliginea was used to make spore suspension and inoculated it into the cucumber leaves in a scientific research solar greenhouse to induce powdery mildew. When the powdery mildew occurred, the spectral information of cucumber leaves was collected by the Ocean Optics USB2000+ portable spectrometer. Five point sampling method was used to collect samples, two cucumber plants were inspected at each point and four leaves were checked on each plant, and five areas were chosen randomly on each leaf to use to spectral information acquisition. Then 200 samples of cucumber powdery mildew leaves were got , and 200 healthy leaf samples were collected as contrast by the same method. the standard white plate and dark current was Utilized to calibrate the spectrometer. The integral time and the scanning times were adjusted and the smoothness parameters of Ocean Optics Spectra-Suite software was used to smooth spectral curves and suppress noise. Through classification and recognition of spectral features, the spectral bands with big noise was removed and the 450~780 nm visible light band was chosen as the research range. The principal component analysis (PCA) was used to reduce the dimension of high-dimensional spectral data (947 dimension). According to the cumulative contribution rate of principal components, the former 5 principal components were chosen as input variables and the discriminant results as the output to build the classification model. We utilized support vector machine (SVM) algorithm and randomly took 120 samples as the training set to build the classification model, and the rest 80 samples as testing set for model checking, and the optimal model was obtained by selecting different kernel functions. The confusion matrix was used to evaluate the accuracy of the classification model, when the radial basis kernel function was selected, the recognition accuracy of the classification model for cucumber healthy leaves and powdery mildew leaves were respectively 100% and 96.25%, and the total accuracy was 98.125%. The results showed that the visible light spectrum analysis combined with PCA and SVM algorithm could be used to identify cucumber powdery mildew quickly and accurately, which provides a method and reference for the diagnosis of cucumber diseases.

In order to satisfy the field management requirement, the research was conducted to indicate the optimizing parameters and identify the growth stage based on the canopy spectral response of potato plants. Aiming to the four growth stages of potato, tillering stage (M1), tuber formation stage (M2), tuber expansion stage (M3) and starch accumulation stage (M4), 80 sample plots were divided in the potato field. The 314 groups data of canopy spectral reflectance were collected by ASD Handheld2 portable spectrometer. The potato leaves were collected synchronously in per sample plot to determine the chlorophyll content. After spectral pretreatment, the spectral reflectance changes of potato crop at different growth stages were analyzed. The spectral response parameters of potato growth stages were selected according to the “peak-valley” reflectance characteristics. A new algorithm was proposed to select sensitive spectral response parameters based on the variance analysis combined with variable reduction (VACVR) method. The Kennard-Stone (K-S) algorithm was used to divide the all samples into training sets and test sets. The identification model of potato growth stages was established by the support vector machine (SVM) method. For spectral reflectance, the standard normalized variable (SNV) was used for spectral pretreatment. Based on the qualitative analysis of the canopy reflection characteristics change trend as potato growth stage progress, the 14 spectral response parameters, including the 8 position parameters, the 2 area parameters and the 4 vegetation index parameters, were selected combining with spectral “peak-valley” characteristics and the dynamicspectral response of potato growth stages. The K-S algorithm was used to divide the overall sample according to 3∶1 into a training set (240 samples) and a test set (74 samples). In general, the canopy spectral reflectance varied with the growth stages progress. In the range of 400~500 and 740~880 nm, the spectral reflectance decreased. In the range of 530~640 and 910~960 nm, the spectral reflectance increased. In the range of 530~640 nm, the canopy average spectral reflectance of the M2 and M3 growth stage were very close. The canopy average spectral reflectance of the M4 growth stage was significantly different from that of the other three growth stages. The average chlorophyll content increased from M1 (28.12 mg·L-1) to M2 (31.04 mg·L-1), reaching a maximum in the M2 growth stage. And the average chlorophyll content of M3 (22.00 mg·L-1) and M4 (15.36 mg·L-1) reduced successively. With the progress of the growth stage, the green peak position and the red valley position gradually red-shifted, the red edge position gradually blue-shifted, the blue edge area gradually increased, the red edge area decreased gradually, and the ratio and normalized ratio of red edge area to blue edge decreased in turn. According to the VACVR algorithm, 10 sensitive spectral response parameters were selected to establish the SVM identification model. The identification rate of the training set was 100%, and the identification rate of the test set was 94.59% (70/74). Therefore, the model can identify the potato growth stage to support the water and fertilizer management in the potato field.

Hyperspectral remote sensing image contains abundant spectral information, which has strong ability to distinguish ground objects, thus promoting the development of hyperspectral anomaly detection technology without any prior information. Kernel-RX algorithm uses the kernel function to ably RX algorithm mapped to high-dimensional feature space, which has a strong ability to solve the spectrum inseparable problem in the low dimensional space. However, it also reveals the disadvantages such as large inverse error in ill-conditioned matrix and low efficiency. In order to realize the strong detection performance of KRX algorithm in theory, this paper proposes an improved KRX detection technology based on new clustering algorithm. (1) Due to the strong spectral similarity of spatial neighborhood pixels, the Gram matrix is ill-conditioned, which seriously affects the detection performance of anomalies, so the phenomenon of background error detection is serious. In order to solve the problem of the inverse error of ill-conditioned Gram matrix, the algorithm improves the KRX operator. By decomposing the singular value of Gram matrix and selecting the principal component with larger eigenvalue, the algorithm ensures the inverse accuracy of Gram matrix. In the end, the detection result of the pixel to be measured is expressed by l-2 norm. The experiment shows that the detection effect is improved obviously. (2) Based on the improved KRX, a spatial clustering KRX algorithm is proposed. There is strong a correlation between spatial pixels, which not only leads to the ill-condition of Gram matrix, but also affects the detection efficiency. The experimental results show that combining pixels in the clustercenters can reduce the spatial dimension and improve the computational efficiency. At the same time, the clustering center is given different weight factors according to the size of the cluster, which ensures the detection accuracy. (3) On the other hand, it is difficult to select an appropriate clustering algorithm. Clustering KRX algorithm requires high accuracy and real-time performance. It is found that a new clustering algorithm based on the peak density fast search algorithm has better clustering performance. The Euclidean distance is used to calculate the similarity of any two pixels, and the Local Density and Neighborhood Distance are used to calculate the clustering center. The clustering center is obtained by sorting the results of the Joint Judgement Criterion. The clustering results show that this clustering algorithm is fast and can cluster arbitrary shape distribution, which is very suitable for hyperspectral images with high dimension and complex components, and can be used for repeated clustering with high frequency of anomaly detection. In conclusion, DC-KRX algorithm provides a new idea of hyperspectral anomaly detection based on spatial clustering preprocessing. Finally, the algorithm is compared with the advanced method. The results show our method has a strong detection performance. And, it is found that the detection efficiency of clustering algorithm is improved by more than 30%, which greatly improves the real-time performance of KRX algorithm.

The rapid development of small and low-cost unmanned aerial imaging spectrometer has provided new means for water quality monitoring and precision agriculture. The ZK-VNIR-FPG480 airborne hyperspectral imager is a domestic development instrument with independent property right. The image has a total of 270 bands, the spectral range is 400～1 000 nm, the spectral resolution is 3 nm, and the spatial resolution is 0.9 m@1 km. The imaging method is motion push broom imaging, which is characterized by no overlap between the images and only overlapping. While providing high spectral and high spatial resolution images, it also has a series of problems: ①the narrow field of unmanned aerial vehicle (UAV) restricts the coverage of the ground surface of each airstrip, and requires the splicing of flights; ②the positioning accuracy of its POS system is low; ③In order to improve operational efficiency, the overlap ratio between navigation bands is relatively low, which is generally set at about 30%, making it difficult to image splicing; ④Due to the influence of wind, light, and the instrument itself during flight, there is a difference in brightness between each band, and stitching occurs when stitching occurs. This paper proposes a method for splicing UAV hyperspectral images based on surface spline function and phase correlation, aiming at solving the above problems. The aim is to splice a single hyperspectral band taken by UAV into a complete panorama with geographic coordinates, and to achieve image geometry and spectral matching. The method includes the following steps: First, the hyperspectral flight is georeferenced using the surface spline function method with the orthophoto image as the reference, and the real geographic coordinates of each flight are assigned; second, the local variance method is used to calculate the signal-to-noise ratio of each band, and the highest value band is taken as the optimal band; and then the phase correlation algorithm based on the 2 power image is used to correct the existing geographic spatial mapping relations between flights and eliminate the dislocation of the flight. Finally, the weighted average fusion method is used to fuse the adjacent flights and eliminate the problem of the mosaic line caused by the illumination and the instrument itself. Through the above steps, we can get a hyperspectral panorama with absolute geographic coordinates. The experiment uses ZK-VNIR-FPG480 airborne hyperspectral imager to get the hyperspectral data of a region of Dali to splice. The results show that the splicing method has no dislocations in the panorama stitching, and the geometric position is accurate. The curve directions of the 4 typical objects before and after splicing are basically the same. The average value of the spectral cosine of the left and right images before and after the stitching image was calculated to be 0.965 2, the average value of the spectral correlation coefficient was 0.863 2, the average value of the spectral information divergence was 0.424 0, and the average value of the Euclidean distance was 0.494 1. The four kinds of spectral curve similarity measure indicators objectively showed the high similarity of the curves, indicating that the spectral matching degree of the same name point before and after splicing is high, which is suitable for the splicing of UAV hyperspectral data. The method not only improves the accuracy of the geographical coordinates of the spliced image, but also ensures the maximum spectrum fidelity on the basis of the elimination of the joint joint. The 2 power image is introduced to solve the problem of the registration algorithm failure under the low overlap of the image. However, there is a spectral difference between the same name points in adjacent bands before splicing, and the amount of hyperspectral data is large and the splicing takes more time. It is still a problem to figure out how to use the pixels of the overlapped region to correct the system error, to unify the measurement space of the image, to improve the spectral accuracy and stability and to improve the stitching speed.

Metal aluminum foil surface with micro-nano composite structure using femtosecond laser plasma filament (femtosecond filament) under different femtosecond filament scanning speed (5, 15, 25, 35, 45 mm·s-1)was prepared. In addition, the reflectivity measurements were carried out in the spectrum of sunlight energy mainly covered within the range (330~890 nm), and the result indicated that surface with micro-nano structure induced by femtosecond filament has significant high spectral absorption characteristic The slower the femtosecond filament scanning speed, the stronger the absorptivity/ Micro-nano structure surface absorption is even more than 97% under the condition of 5 mm·s-1. The prepared micro-nano structure surfaces with high spectral absorption are used as light absorbers of thermoelectric generator(TEG), on this basis, the simulation environment was established considering sunlight irradiation and heat dissipation of thermoelectric generator module (TEG module: combination of micro-nano structure metal surface with the TEG), and conducting power generation measurement. The results show that the photoelectric conversion efficiency (power generation efficiency) of aluminum surface with micro-nano structure (5 mm·s-1 preparation condition) can be increased by 43.3 times and 10.7 times respectively compared with polished aluminum foil or bare TEG. The generation process and mechanism of TEG module are further studied, the thermoelectric power generation process of TEG module is divided into two transformation processes to analyze: photothermal transformation process (optical energy converted into heat energy) and thermoelectric transformation process (heat energy converted into electricity): First in the photothermal conversion process, the presence of the micro-nano structure surface enhances the efficiency of sunlight absorption, to provide more photonic energy for photothermal conversion, implements the more heat deposition at the surface, and then in the subsequent thermoelectric transformation process, the carrier mobility of TEG module has been greatly improved by more heat deposition. Thus the micro-nano structure surface compared with the general surface can gain higher thermoelectric conversion efficiency under the condition of the same temperature difference (Temperature difference between hot and cold junctions of TEG module). Therefore, micro-nano structure on the surface of high spectral absorption performance makes TEG module to obtain high heat deposition after the photothermal conversion, bringing about promotion of the carrier mobility, and then increasing the TEG module power performance significantly, which is the main reason to significantly improve the power generation performance of TEG module. The discovery of this mechanism provides theoretical basis for further optimization and improvement of TEG module’s power generation performance, which is of great significance to the practical application of TEG module with micro-nano structural surface.

Hyperspectral imaging combined with chemometrics was successfully proposed to identify the rice sheath blight disease. First, infected rice plants with rice sheath blight in the seedling period to get the infected rice plants, then used the hyperspectral imaging system to acquire the hyperspectral imagines in the spectral range of 358~1 021 nm, finally selected 240 samples of all hyperspectral imagines to analyze, including 120 healthy samples and 120 infected samples. According to the spectral dimension of hyperspectral image, extracted the region of interest(ROI) of healthy and infected rice leaves, pretreated the spectral data of the region of interest with pretreatments including SG smoothing, SG-1D, SG-2D, SNV and MSC, then established the linear discriminant analysis (LDA) and support vector machine (SVM) classification models. The result showed that the linear discriminant analysis (LDA) model with SG-2D pretreatment achieved the better performance, with the correct recognition rate of the modeling set being 98.3% and the correct recognition rate of the prediction set being 95%. After five kinds of pretreatments, extracted the feature wavelengths with the method of x-loading weights, then established the linear discriminant analysis (LDA) and support vector machine (SVM) classification models based on feature wavelengths. The result showed that the linear discriminant analysis (LDA) model with SG-2D pretreatment achieved the better performance, with the correct recognition rate being 97.8% in the modeling set and 95% in the prediction set. Moreover, the model performance based on x-loading weights was equivalent to that of the whole band. So, it can be used to identify the rice sheath blight disease with x-loading weights. According to the image dimension of hyperspectral image, the principal component analysis, probabilistic filtering and second-order probabilistic filtering were proposed in this paper, then established the back propagation neural network (BPNN) and support vector machine (SVM) classification models. The result showed that the BPNN based on image principal component analysis achieved the better performance, with the correct recognition rate being 90.6% in the modeling set and 93.3% in the prediction set. According to the spectral and image dimension of hyperspectral image, the chlorophyll content was proposed to be another feature of disease recognition, which was combined with spectral characteristics and image features to build models to compare the performance of each model. Then established the back propagation neural network (BPNN) and linear discriminant analysis (LDA) classification models. The spectral features combining with chlorophyll content, image features combining with chlorophyll content and spectral, image features combining with chlorophyll content were proposed. The performance of spectral, image features combining with chlorophyll respectively were both better than that using the spectral and image features alone. BPNN based on spectral features combining with chlorophyll content achieved the better performance, with the correct recognition rate being 100% in the modeling set and 96.7% in the prediction set, also, this model achieved the best performance compared with all models in this paper. The overall results indicated that hyperspectral imaging technology with chlorophyll content can accurately identify the early rice sheath blight disease and provide a new method for early detection of rice disease.

Ramie（Boehmeiria nivea L）is a special and traditional fiber crop in China, having higher economic status. Determining the hyperspectral reflectance of ramie leaves with the spectrometer and developing a hyperspectrum-based method of ramie variety identification of high efficiency will be beneficial for the cultivation of ramie, the development and utilization of germplasm resources as well as the provision of critical technological supports to realize the top quality and high production of ramie and the accurate management of ramie croplands, which are significant for improving ramie yield and quality. In order to apply the hyperspectral technology for identifying ramie varieties, total 1458 hyperspectral data on the ramie leaves coming from nine ramie varieties of different genotypes were collected. According to these data, we explored the using of the Principal Components Analysis(PCA) to reduce dimensions of the hyperspectral data and how to determine the best appropriate number of principal factors in the PCA. Further, we compared different combinations constituted by different principal factors and different Discriminant Analysis approaches, and the results of the ramie variety identifying models based on the hyperspectrum of ramie leaves were established. After the principal component analysis of the full-band data sample, with 2~20 principal components as the feature variables, we applied three discriminant models, namely the Linear Discriminant analysis(LDA), the Quadratic Discriminant Analysis(QDA), and the Mahalanobis Distance Discriminant Analysis, (MD-DA), to create variety discriminant models and used them to predict, and with the accuracy of the prediction set as the evaluation criteria, the effects of various combinations were compared. The results showed that when we used the cumulative contribution rate(≥85%) as the criteria and selected two principal components, the accuracies for the LDA, the QDA and the MD-DA prediction sets were respectively 32.92%, 38.48% and 33.54%; but, when we used the feature value(≥1) as the criteria, and selected eleven principal components, the accuracies for the prediction sets of above discriminant models were respectively 68.72%, 87.04% and 83.54%; and further, when we considered the accuracy of the prediction set as the preferential criteria and selected twenty principal components, the accuracies for above discriminant models were all significantly improved and were respectively 84.98%, 95.68% and 95.27%. Therefore, we can draw the following conclusions: (1) it is feasible to establish the ramie leaf-based hyperspectral variety identification model by combining the PCA and the DA, but there are big differences between results due to different numbers of factors, different DA criterias and different combination approaches; （2）The impact of the number of principal factors on the identification results are significant, and the appropriate adding of the principal components can notably improve the accuracies of corresponding models, thus it is not confined to how to select the feature values of the PCA and the accumulative variance contribution rate ; (3) When the numbers of principal factors are the same, among above three discriminant criteria, the effect of the QDA is the best while that of the LDA is the worst; (4) Twenty principal components and the QDA approach constitute the best combination, which makes data dimensions be hugely reduced, from 2031 dimensions of the full-band down to 20 dimensions, and the accuracy of the prediction set is 95.68%.

The freshness of Tan mutton is an important index of its quality and safety, and it is also a key link in the quality control of meat products. Total Volatile Basic Nitrogen (TVB-N) is the main chemical information which can effectively reflect the loss of freshness of Tan mutton. However, the traditional detection method of TVB-N must destroy the samples, the detection process is tedious, the man-made influencing factors are large, and the test result is lack of objectivity and consistency. Hyperspectral imaging technology which is a non-destructive method meets the needs of modern detection technologies for multi-source information fusion that has been widely used in the field of food safety. This paper used visible/near-infrared spectroscopic imaging technology (400~1 000 nm) combined with dynamics and chemometrics methods and computer programming to achieve the rapid detection of TVB-N concentration and prediction of safe storage period during the storage period of Tan mutton（15 ℃）. The research contents were as follows: The average spectral data for each sample area of interest were extracted and the monte carlo algorithm was selected to eliminate the abnormal samples. The X-Y symbiotic distance (Sample set partitioning based on joint X-Y distances, SPXY) was used to divide the mutton set into the correction set and the prediction set. Multiplicative Scatter Correction (MSC), Savitzky-Golay (SG), Standard Normalized Variate(SNV), normalization (Normalization) and baseline calibration (Baseline) were used to preprocess the original spectral data. 21 and 6 feature wavelengths were extracted by the Campetitive Adaptive Reweighted Sampling (CARS) and Successive Projections Algorithm (SPA). In order to simplify the model and improve the accuracy of prediction of the model, the SPA algorithm was used to perform secondary extraction of selected feature wavelengths of CARS and 14 feature wavelengths were selected. A PLSR model with TVB-N concentration was established based on the extracted characteristic wavelengths, and the SNV-CARS-SPA-PLSR model was preferred to have a higher prediction ability (R2c=0.88, RMSEC=2.51, R2p=0.65, RMSEP=2.11) Meanwhile, a dynamic model of mutton TVB-N change and storage time could be established. Finally, the dynamic model of spectral absorbance value and storage time of mutton were established by combining the optimized spectral model with the dynamic first order reaction model, and predicte the storage time, and the PLS-DA model was realized to discriminate the storage time of mutton (the correction set discriminant accuracy rate was 100%, and the prediction set is 97%). The result showed that visible/near-infrared hyperspectral imaging technology in combination with dynamics and chemometrics methods and computer programming could effectively detect TVB-N index of mutton rapidly and non-destructively, and be realized to monitor the quality and safety of mutton and provide a theoretical reference for developing on line defection equipment.

Based on the concept of organic-inorganic hybrid materials, take advantage of the fact that rare earth terbium nitrate ［Tb(NO3)3］, organic ligands BINDI (BINDI=N,N′-bis (5-isophthalic acid)-1,4,5,8-naphthalenediimide and the Keggin-type polyoxometallate H4SiW12O40·26H2O will react under solvothermal conditions to successfully synthesize a polyacid rare earth coordination polymer Tb4［SiW12O40］·［BINDI)］2·［DMA］16. The structure, composition, thermal stability, luminescence properties and photochromic properties of the rare earth polymer are characterized by X-ray single crystal diffractometer, X-ray powder diffractometer, infrared spectrometer, thermal gravimetric analyzer, ultraviolet-visible absorption spectrometer, elemental analyzer, fluorescence spectrometer and electron paramagnetic resonance spectrometer. X-ray single crystal diffraction analysis revealed that the rare-earth coordination polymer is crystallized in the tetragonal crystal system, and the space group is P42/n, exhibiting the 3D chiral double helix network structural characteristics. Among them, the polyacid anion SiW12O40 (abbreviated as {SiW12}) is embedded in the pores formed by rare earth organic groups; Through infrared and ultraviolet absorption spectroscopy analysis we found that rare earth Tb3+ and ligand (BINDI) have been coordinated to form a bond; Fluorescence spectroscopy indicated that at the excitation wavelength of 380 nm, the ligand shows the strongest fluorescence emission peak at 441 nm, while the strongest emission peak of the compound is at 471 nm. Since the trivalent europium ion is not easily oxidized and is difficult to be reduced, the fluorescence emission of the compound cannot be attributed to the electron radiation transition between the metal and the ligand, and the emission peak of the compound is similar with the emission peak of the ligand. Therefore, the fluorescence is mainly the luminescence of the ligand BINDI. In addition, the special transitional emission band of Tb(Ⅲ) ions does not appear, because the color of the sample has break due to illumination during the fluorescence test, that is, the phenomenon of photochromism has arisen, resulting in photoinduced electron transfer to cause fluorescence quenching. The reason for the fluorescence quenching of metal complexes is usually photoelectron transfer, and the direction of electron transfer is the transfer of electrons in the ligand to the metal orbit (LMCT). The red shift or blue shift of the maximum emission peak after complex formation is caused by the change of electron distribution in the molecule resulting from electron transfer, which gives rise to the decrease or increase of the HOMO-LUMO energy gap. The fluorescence spectrum of the compound is red-shifted compared to the fluorescence spectrum of the ligand. Furthermore, electron paramagnetic resonance spectrometer manifests that owing to the electron transfer of the BINDI ligands in the compound to form free radicals under ultraviolet and visible light irradiation, and the polyoxometallate under light excitation, the occurrence of W5+→W6+ further promotes the photochromism of the compound. Therefore, the compound has extremely acute photochromic properties.

Thermal stability could significantly affect the processing and sensory properties of milk. Accurately determining the thermal stability of milk is of great significance for optimizing the processing conditions of liquid dairy products. However, the current stability evaluation method on liquid milk is mainly through the observation of stratification, precipitation, or dynamic light scattering technology. There is no fast and reliable and quantitative evaluation standard, which seriously restricts the selection efficiency of the heat treatment process of liquid milk. Turbiscan multiple light technology can test the stability of the fluid without pre-processing the samples. It can monitor the backscattered light and transmitted light intensity of the samples timely, and calculate the migration rate of the internal particles and the thickness of the precipitate layer. In this study, the dynamic light scattering test results were used as control. The Turbiscan multiplex light technique was used to measure the heat stability of skim milk treated with different pre-heating pH values, including pH 6.3, 6.5, 6.7 and 6.9 at 80 ℃ for 30 min. The concentration of CaCl2 before heating was 0, 20, 40, 60 and 80 mmol·L-1, respectively. The results showed that when the CaCl2 increased from 20 to 80 mmol·L-1, the z-average diameter of skim milk changed from 152.7 to 1 284 nm, and the instability index values (after 20 h) increased from 0.98 to 17.04; the backscattered light intensity change value decreased from -4.3 to -37.4, and the backscattered light intensity change value from the bottom end increased from 2.2 to 14.7. When the pH values were 6.3, 6.5, 6.7 and 6.9, respectively, the z-average diameters of skim milk were 148.1, 152.7, 132.4 and 122.4 nm, respectively, and the instability index values 1.20, 1.32, 1.02, 0.98 and 1.41, respectively; the backscattered light intensity values at the top of the sample were -3.1, -4.7, -4.2 and -5.6, the backscattered light intensity changes at the bottom were 5.7, 3.4, 4.1, and 6.8, respectively. The results showed the heat stability of milk can be significantly influenced by the CaCl2, while the pH value has little effect on the thermal stability of skim milk. At the same time, it is also found that compared with dynamic light scattering technology, Turbiscan multiple light scattering technology was more accurately, conveniently and quickly to obtain the stability index, such as milk backscattered light intensity value and instability index. This research has important guiding significance for optimizing dairy processing technology. The Turbiscan multiplex light technology is more convenient and faster than the dynamic light scattering technique.

Silicone rubber composite insulators are key equipment of HV transmission lines. Their surfaces will gradually deteriorate after running under a harsh environmental condition for a long time, and become chalked, faded, more rough and tough. As one of the characteristics of aging, surface roughness measuring is always difficult in power transmission line condition monitoring. Laser induced breakdown spectroscopy(LIBS) is suitable for remote condition monitoring in power system, but the influence of roughness on LIBS signal hasn't been systematically studied, and taking advantage of this matrix effect for insulator surface roughness testing hasn't been reported yet. New silicone rubber samples with different surface roughness were made, compared with those retired from a 500 kV power transmission line. The influence of roughness of new silicone rubber material on LIBS signal was studied and the results showed that when roughness increases, the spectral line intensity increases, while the ratio of different element line intensity(Si 288.2 nm/C 247 nm and Al 394 nm/Si 288.2 nm) decreases. It showed that roughness has a significant effect on LIBS signal. However, since there had been no obvious linear relationship between intensity and roughness or intensity ratio and roughness, it was hard to measure roughness by these relationships.The major elements of silicone rubber material were Si, Al, C, O and so on. Si was selected as the analytical element considering element content and spectral line selection convenience. Two atomic line of Si（SiⅠ288.2 nm, SiⅠ250.7 nm） was selected as the analytical line whose upper energy levels were nearly the same (Eki=40 991.88 and 39 955.05 cm-1). When the laser induced plasma satisfies LTE and optically thin condition, the ratio of line intensity should be constant, but the ablation process is affected by material surface roughness, and then the plasma state and intensity ratio will be changed. A calibration line of roughness and the above ratio was established and the linear correlation coefficient was 0.88. As for the aged silicone rubber material retired from the 500kV transmission line, the surface was precipitated by some ATH fillers because of the aging process, leading to a more inhomogeneous content in the matrix and a rougher surface. So it is not practical to measure roughness by only one couple of spectral lines. Therefor it is necessary to introduce Al atomic lines (Al Ⅰ 305.7 nm, Al Ⅰ 305.9 nm) in the calculation model besides Si atomic lines for the aged silicone rubber material. Multivariate regression was carried on with 3 sets of spectral intensity ratios, and then 2 agedsilicone rubber material were measured by LIBS whose actual roughness were 2.659 and 2.523 μm. The relative error was 0.218 and 0.189, respectively. The results show that roughness cannot be ignored in LIBS measurement for material with the same constitution, and the exploitation of this matrix effect for the remote measuring of composite insulators is meaningful for the checking and operation of HV transmission lines.

In-stu chemical analysis requires sampling and ionization/excitation of sample in an open environment. The atmospheric pressure micro-plasma system is in a simpler structure and more advantageous for miniaturization than laser cutting or laser induced breakdown. Therefore, in-stu chemical analysis technology based on atmospheric pressure micro-plasma has attracted widespread attention in the industry. The micro-plasma sources produced by different excitation supplies have different parameter characteristics and sampling characteristics. In order to determine the appropriate micro-plasma source for in-stu element detecting, it is necessary to further understand the sampling and characteristics of the micro-plasma under each discharge mode and operating parameters. This paper focuses on the optical emission spectra of direct current(DC) glow and pulsed arc plasmas acting on iron samples in ambient atmosphere. The on-line detection of high melting point metal samples in an open environment was realized, and we also found that the arc discharge micro-plasma combined with the spectral analysis source has higher sampling efficiency. The high sampling efficiency of the arc discharge microplasma source provides a new method for the detection of metals and difficult to dissociate samples. At the same time, complex sample preparation and sample transfer processes were avoided compared to conventional sampling devices. The experimental device adopts a typical needle-plate discharge structure, which has the advantages of low price, convenient operation and quick analysis. Arc discharge and glow discharge are realized by using a high voltage pulse power source and a DC power source respectively. The sampling results of the two ways indicate that at the input of similar discharge power, the optical emission spectrum of the sample iron stimulated by the arc discharge micro-plasma, sample element lines occupies dominant position in the spectrum, accompanied by the line of nitrogen in the air. And the relative intensity of the iron ion (FeⅡ) line is higher than the relative intensity of the nitrogen molecule line. In the DC glow discharge, the relative intensity of the sample iron atom (FeⅠ) line is very weak. This shows that the micro-plasma generated by the arc discharge has higher sampling efficiency. The sputtering crater left on the surface of the sample can draw the same conclusion. The glow discharge current was increased to 25 mA, the spectral line of the sample elemental iron was still not significantly enhanced. At the same time, the effect of sampling spacing on the two sampling modes was also studied. Experimental results show that the spacing has no significant effect on the both sampling spectra of the two modes. In this paper, the above-mentioned comparative experiment was also carried out using the alloy aluminum foil whose main component is aluminum, and the same conclusion was obtained. It is concluded that the arc discharge micro-plasma is more suitable as a source of spectral analysis to achieve real-time rapid detection of metal samples.

The aim of this study was to investigate the mechanism of interaction between cinnamaldehyde and zein by fluorescence spectroscopy, UV spectroscopy, circular dichroism spectroscopy, infrared spectroscopy, and nuclear magnetic resonance spectroscopy, so as to provide research basis for improving the mechanical properties, antibacterial properties, and antioxidant properties of zein films. Through three-dimensional fluorescence spectroscopy, it was found that cinnamaldehyde has obvious fluorescence quenching effect on zein, and solvent ethanol has an effect on quenching. When UV-spectroscopy was used to explore the mechanism, it was observed that the absorption intensity of zein in the UV region at 278 nm increased with the increasing concentration of cinnamaldehyde, but the increasing range was not proportional, and the characteristic absorption peak positions of the amino acid residues was not changed. Before and after addition of cinnamaldehyde, the two curves exhibited by circular dichroism were nearly coincident. Using the attenuated total reflection ATR appendage for Fourier transform infrared spectroscopy, we found that after the addition of cinnamaldehyde, the absorption peak at 1 650 cm-1 indicates CO stretching vibration, and 1 538 cm-1 indicates the NH bending vibration in plane. The peak positions at these two sites did not change significantly, but there were obvious acromion peaks at 1 625 cm-1, reflecting the absorption of cinnamaldehyde carbon-carbon double bonds. The peak at 879.44 cm-1 of the fingerprint area disappeared, and a new peak appeared at 973.46 cm-1, reflecting the absorption of the cinnamaldehyde trans double bond, indicating that a non-bonding of zein with cinnamaldehyde. The self-deconvolution calculation of the amide Ⅰ band revealed that the α-helix structure of the zein secondary structure changed little and the β-turn changed significantly. By means of NMR, the chemical shift of proton H in 4 positions changed only 0.01, and after 1 hour and 4 hours of cinnamaldehyde addition, the change of chemical displacement was equal, indicating that the binding reaction of cinnamaldehyde to zein occurred on the surface of the protein and did not cause changes in the secondary structure of zein. The thermodynamic parameters of the system were calculated. It was found that the spontaneous binding reaction occurred between cinnamaldehyde and zein, and the binding ratio of them was 1∶1. When the concentration of cinnamaldehyde was low, the quenching constant decreases with the increase of temperature, but the change was not significant; when the binding constant was very large, the order of magnitude reached 105, and decrease with the increase of temperature. The determination of the fluorescence lifetime of zein in the presence or absence of cinnamaldehyde further confirmed that static quenching occurred between cinnamaldehyde and zein. Comprehensive analysis of various spectra showed that cinnamaldehyde and zein was mainly π—π stacked on the outside of the aromatic region, and it was a combination of electrostatic forces, was static quenching mechanism, and was independent of the action time. The results showed that the combination of cinnamaldehyde and zein do not significantly affect the secondary structure of zein.

The flat-plate solar collectors (FPSCs) provide hot water for people’s daily life, and the minute heavy metals and impurities come out from inside collectors with hot water. Heavy metals have a potential impact on the environment, meanwhile, it also threatens people’s health. So it is necessary to detect the stagnant water samples of FPSCs. To improve the reliability of the test results of FPSC water samples, the ultra pure water was used for the stagnation of the FPSC. The ultra pure water was used to wash the FPSCs before stagnation to reduce the effect of pipe impurities on the results. The pipes materials of FPSC were made of TP2 phosphorous deoxy copper. The standard solution contains 21 kinds of heavy metal elements, such as As, Ca, Cu, Mg, Ni, Zn and so on. The concentration gradients of the standard solution were 0.2, 0.4, 0.8 and 1.6 mg·L-1, respectively. The blank sample and standard solution should be analyzed before testing the water sample. The water samples of different aluminum substrate FPSC (the blue-film coating, the black chromium coating and the anode oxidizing coating) were analyzed, and the content of heavy metal elements in water samples were also detected by ICP-OES method. Moreover, the best analytical spectrum of the 21 heavy metal elements were ensured by relevant parameters. The best analytical spectrum of partial heavy metal elements of the standardsolution were respectively (nm): As(188.979), Ca(317.933), Zn(206.200), V(290.880), Cu(327.393), Ni(231.604), Sb(206.836), Pb(220.353). It was shown that ICP-OES can simultaneously detect the content of various heavy metal elements in water samples accurately. The higher content of heavy metal elements in water samples, the greater the amplitude of the spectrum. There were not 12 heavy metal elements (Be, Co, Cd, Cr, Fe, Li, Mn, Mo, Se, Sr, Tl, Ti) in the water samples of three kinds of FPSCs, but 9 heavy metal elements (As, Ni, Cu, Ca, Mg, V, Pb, Zn, Sb) were detected in the same experiments. The changeable rule of heavy metal content in water samples showed that the heavy metal content increases with the FPSCs stagnation time, the heavy metal content increases to the peak value and then decreases with the FPSCs stagnation time, and then it decreases to the lower content gradually. The changeable rule of heavy metal content with the stagnation time was obtained with the analysis of the stagnant water samples of the FPSCs, and the superscalar and the excessive stagnation time of different heavy metal elements were also given too. The limit value of water quality standards for urban water supply (CJ/T 206—2005) for heavy metal elements was taken as reference, so these heavy metals elements (Cu, Ni, Zn) of water samples of three kinds of FPSCs were not more than that of the limit of the national standard. However, the contents of As, Pb and Sb in water samples of three kinds of FPSCs exceeded the limit of the standard after 8 days stagnation. The maximum superscalar of As, Pb and Sb elements were 0.007, 0.006 and 0.004 mg·L-1, respectively. And the superscalar of the As elements was the highest in the water samples of the blue-film coating collector and the anode oxidizing coating collector, and the superscalar of the Pb elements was the highest in the water samples of the black chromium coating collector. The detection results had certain reference significance to the manufacturers and the customers, and the technology of FPSC’s pipes should be further improved to reduce the precipitation of heavy metals. The research results can also provide some references for the research of the FPSC and the establishment of national standards.

In order to study the detection sensitivity of Na elements in water, the Na elements in NaCl solution were detected by laser induced breakdown spectroscopy. Choosing NaⅠ589.0 nm and NaⅠ589.6 nm as analytical spectral lines, we used the NaCl solution with 6 kinds of concentration and adopted external standard method, internal standard method and wavelet transformation noise reduction method to present NaCl solution Na element calibration curve, finding that the linear correlation coefficient r of calibration curve obtained by using internal standard method is 0.998, better than that of calibration curve obtained by using external standard method (r=0.985), and is superior to the external standard method after wavelet noise reduction (r=0.986). In contrast, the wavelet transformation reduced the RSD from 5.68% to 1.61%, thereby reducing the LOD value from 50.8 to 19.54 μg·mL-1. The internal standard method selects the NaⅠ589.0 nm and NaⅠ589.6 nm sodium atomic line and the internal standard reference line HⅠ656.2 nm hydrogen atom line intensity ratio can effectively overcome the impact of experimental conditions fluctuations, therefore, the linear correlation coefficient of the calibration curve of Na element in NaCl solution obtained by using the internal standard method is the largest. For the wavelet transformation noise reduction processing method, the noise caused by the continuous background of the LIBS spectrum can be effectively reduced, and the influence of the experimental condition fluctuation on the LIBS spectral information cannot be overcome. Therefore, the wavelet variation noise reduction method can improve the RSD of the LIBS, but has little effect on -the improvement of the linear correlation coefficient of the calibration curve given by the external standard method after noise processing. It is indicated that the internal standard method effectively improves the detection sensitivity and reduces the influence of fluctuations in experimental conditions. The calibration curve has a better linear correlation. The wavelet transformation noise reduction process effectively reduces the continuous background spectral noise in the LIBS spectrum, and the LIBS detection limit becomes lower. The RSD and LOD values obtained by analyzing the line of NaⅠ589.0 nm are smaller than those of the line with the line NaⅠ589.6 nm. The upper levels of the two lines of NaⅠ589.0 nm and NaⅠ589.6 nm are 2.104 and 2.102 eV respectively. It was found that the upper level of the analytical line has an effect on the RSD and LOD values of the Na element in the NaCl solution, and the upper level is large, while the RSD and LOD values are small. The results of this study showed that LIBS technology can realize rapid detection of heavy metal elements in solution, and has potential application prospect in environmental water pollution detection.

The rapid and in-situ detection of compound fertilizer components was of great significance to the production process control and product quality control of chemical fertilizer production enterprises. In the production of fertilizer companies, compound fertilizer samples were collected on the production line and sent to the laboratory for analysis. The time required for detecting was long, which can’t meet the compound fertilizer company’s production line for testing. Compared with the existing detection methods of compound fertilizer components, the detection time of laser-induced breakdown spectroscopy (LIBS) was several minutes. And the measurement of compound fertilizer components can be completed in one measurement, with almost no need for compound fertilizer samples. LIBS technique was very suitable for the rapid and on situ detection of compound fertilizer components. In the LIBS detection system, the laser beam output from the solid-state pulse laser (100 mJ, 1 064 nm, 1 Hz) was converted from horizontal to vertical by a 45°-mirror. The laser beam was focused onto the target using a lens (focal length=40 mm). The sample was placed at a rotating platform. The light emitted by the plasma was collected by an optical fiber spectrometer (Avantes, 195～500 nm) with a delay time of 1.28 μs and an integration time of 1.05 ms. The spectrometer was triggered by the signal of laser’s Q-switched. The LIBS spectrum of the compound fertilizer sample was finally obtained. In the experiment, 20 compound fertilizer samples were provided by Anhui Huilong Group. The reference concentration of phosphorus element was measured by the enterprise using the national standard method. The samples were ground into powder and sieved. Three grams of every sample was pressed pellets under a pressure of 8 MPa. During the experiment, a small fan was used to continuously purge the surface of sample to form a stable airflow environment. Each sample was repeatedly measured 10 times, and each spectrum was formed by 20 shot average to reduce the heterogeneity of the sample. 15 samples were selected as calibration set to train regression model, and 5 samples were chosen to test the model. The compound fertilizer was a complex mixture of components, in which the nitrogen, phosphorus, and potassium were all present as compounds. The traditional quantitative analysis method of LIBS was based on the intensity of a single characteristic line of the measured element. The influence of other elements was not considered, which greatly reduced the accuracy of the analysis results. In this paper, LIBS technology and multiple linear regression calibration were used in combination to determine the phosphorus concentration in compound fertilizer. Three feature spectral lines of P element detected by LIBS were 213.6, 214.9 and 215.4 nm. As the concentration of silicon in the phosphate rock was relatively stable. And near the spectral feature line of P element, there were many characteristic lines of Si element, such as 212.4, 220.8, 221.1 and 221.7 nm. The analysis was carried out based on unary, binary, ternary, and quaternary linear regression calibration curves, respectively. It turned out that the unary linear regression method hardly served the quantitative analysis for compound fertilizer sample only using the intensity of P Ⅰ 214.9 nm as variable, and the correlation coefficient between the LIBS prediction value and the reference concentration was only 0.083. When using the intensity of P Ⅰ: 214.9 nm and the sum of three characteristic lines (P Ⅰ: 213.6, 214.9 and 215.4 nm) as input variables to establish the binary linear regression, the correlation coefficient increased to 0.856 and the average absolute error decreased from 1.32% to 0.16%. When introducing the line intensity of Si Ⅰ: 212.4 nm into the binary linear regression equation, the ternary linear regression was established, and the correlation coefficient was only increased to 0.869. In order to further improve the accuracy of phosphorus concentration measurement in compound fertilizers, the quaternary linear regression equation was established. The sum of the Si Ⅰ: Si 2.4: 222.4, 220.8, 221.1 and 221.7 nm line intensities was used as an independent variable to add into ternary linear regression equation. The correlation coefficient was increased to 0.980. The relative error ranges were 0.06%～1.31% and 0.13%～1.26% for 15 calibration samples 5 validation samples, respectively. The results demonstrated that using the quaternary liner regression calibration method can improve the accuracy of phosphorus concentration measurement in compound fertilizers.

The uncertainty of laboratory calibrated spectroradiometers used in field was analyzed. Ambient temperature is one of the most important factors limiting the accuracy of outdoor measurements. Currently, the laboratory calibrations are generally performed at room temperature ［(25±1.0) ℃］. However, the spectrometers applied in earth observation and remote sensing is usually operated in the field under different ambient temperature conditions. The calibration coefficients determined under room temperature are not applicable to data collected in field conditions. In this paper, the experimental measurement system was set up, which was used to investigate the temperature effects. The sensitivity of spectroradiometers (CR-280) at different wavelengths was affected differently by ambient temperature. The deviation of 400～700 nm between measured and calibrated value at 40° is about ±5%. The deviation of near-infrared wavelengths (1 050 nm) is about ±15%, this spectral range is close to the band edge of the silicon, which is highly temperature sensitive, and the silicon band edge moved to longer wavelengths as increasing temperature. It is important to reduce the deviation of measured results in field after laboratory calibration. Here, a temperature correction method by matrix calculation for different kinds of spectroradiometers was proposed, which calculated the spectroradiometer response at each pixel. The correction method was also verified with a randomly selected temperature. It can reduce the deviation of CR-280 from ±10% to ±1% in the near-infrared wavelengths (about 950 nm). The temperature correction method can be easily used for spectral radiometry measurement in the field, which can be greatly improves the accuracy of spectral radiometry measurement. Also, the other two kinds of spectroradiometers (Avantes, SVC H-1024) were used to verify this correction method. The result showed the deviation of Avantes (VIS/NIR) between measured and calibrated value (about 1 060 nm) is reduced from ±17% to ±1%. At different ambient temperatures, the deviations between the measured and calibrated values of SVC HR-1024 are different. The instrument consists of three detectors: Si, cooled InGaAs and extended InGaAs. Si detector is greatly affected by temperature, and the deviation of the measured and calibrated value (950～1 000 nm) is as high as ±10%. The cooled InGaAs can effectively control the detector temperature. However, as the ambient temperature increases, the InGaAs detector is affected (the optimal working environment for cooling is about 20 ℃), and the deviation of measuredand calibrated value results is 1%~3%. The temperature correction formulas were used to correct the measured results. The deviation of SVC HR-1024 can be reduced to ±1%.

The intensity of photoacoustic signal is proportional to optical power. However, high power laser source has many disadvantages, such as high power consumption, complex driving and controlling circuit, the lasers with high quality and lower cost laser can't be attained easily. These kinds of laser source mostly focus on the band over 6 micron, which makes it difficult to detect the molecule in fundamental absorption band of 2～6 micron effectively. Moreover, photoacoustic gas sensors based on commercial driving and controlling instruments are more likely to have large volume, which can’t meet the needs of multi-points and continuous mobile monitoring. In this paper, nmol·mol-1 level measurement applied to molecule concentrations was realized in 3～4 micron band using low output power interband cascade laser (ICL) and a detection method which based on quartz tuning fork and photoacoustic spectroscopy. The ICL was used to target a strong ethane absorption ling at 2 996.88 cm-1 in its fundamental absorption band. High sensitive detection and system volume reduction were realized by using self-developed digital lock-in amplifier and digital laser driving and controlling method, as well as wavelength modulation spectroscopy technology. Moreover, data acquisition and processing process were simplified effectively. Firstly, system scheme and designing details of optical and electrical modules were introduced in sequence according to the system principle and structure. Simulations of target gas absorption and interference from other gases have been analyzed. Broadening and overlap conditions of absorption lines under different pressures have also been described. Working pressure of the system was determined to be 200 Torr finally. Secondly, the minimum detection limit (MDL) was deduced <100 nmol·mol-1 through performance test and analysis of one-circle spectrum scanning of ethane with 6 concentration levels (100～1 000 nmol·mol-1). The linear performance of this sensor was evaluated through ~10 min 2f peak value extraction test using aforementioned samples. The results indicated that the correlation was 0.999 65, and the relationship between gas concentration and the amplitude of 2f signal was clear. Finally, system noise was determined to be ~0.347 V by means of continuous 1 h test applied to nitrogen, thus the SNR and sensitivity were estimated to be ~28.56 and ~40 nmol·mol-1, respectively. The new mid-infrared C2H6 sensor introduced in this paper not only realized nmol·mol-1 level measurement but also greatly reduced the volume occupied by commercial instruments by use of digital driver and lock-in amplifier, which laid the foundation for realizing the goal of miniaturization and mobile measurement. In addition, for the applications with unlimited power consumption, sensor sensitivity can be further improved by using more powerful laser source or improving the performance of system modules such as lock-in and preamplifier, which can be applied in more fields.

With the decrease of global resources and environmental deterioration, energy saving and emission reduction have become a hot topic and Low-E glass with thermal insulation performance is becoming the research focus. To improve the thermal insulation performance of glass, the simplest and most effective method is plating low-emissivity coatings on the surface of them. . The Al doped ZnO (AZO) film is the most potential low-emissivity layer for Low-E glass, due to rich raw materials, high conductivity and high transparency and so on. Effects of temperature on the infrared emission performance of AZO films were researched and mechanisms of changes were analyzed in this study. The change of infrared emissivity of AZO film kept at a certain temperature for some time was studied firstly, and then the change of infrared emissivity in variable temperature environment was studied. 500 nm-thick AZO films were deposited on glass substrates at room temperature by direct current magnetron sputtering and then were put in muffle furnace for heat treatment. Films were kept at 100～400 ℃ for 1 h in air and then cooled to room temperature in the furnace. The phase of AZO films was analyzed by X-ray diffraction and the surface morphology was observed by scanning electron microscope. The resistivity was measured by four probe method and the infrared emissivity was measured using infrared emissivity measurement instrument. Visible spectrum was measured by visible spectrophotometer. The results showed that AZO film before and after annealed all show hexagonal wurtzite structure and (002) preferred orientation. With the annealing temperature rising to 300 ℃, the intensity of (002) diffraction peak increases, the full width of half maximum (FWHM) narrows down and grain size increases. With the increase of annealing temperature, the resistivity decreases firstly and then increase. The film annealed at 200 ℃ shows the lowest resistivity of 0.9×10-3 Ω·cm. The decrease of resistivity is attributed to the growth of grains. The film annealed at higher temperature in air will absorb oxygen, resulting in the decrease of resistivity. The change of the infrared emissivity with annealing temperature agrees to that of resistivity. The film annealed at 200 ℃ shows the lowest emissivity of 0.48. Infrared photons are strongly reflected by free electrons. When the resistivity is low and the concentration of free electrons is high, more infrared photons are reflected, the infrared radiation weakens, and the infrared emissivity decreases. The transmittance decreases firstly and then increases. It is the lowest at 200 ℃ but still up to 82%. This change is caused by the change of free electron concentration. Free electron strongly reflects visible light. The infrared emissivities of the films as-deposited and annealed at 200 ℃ were measured during the process of heating and cooling between room temperature and 350 ℃. The sample was fixed on the heated stage and its emissivity was recorded every 25 ℃. It was found that the infrared emissivity increases with the increase of temperature during the heating process, and decreases during the cooling process. After the whole process, the infrared emissivity of the AZO film increases.

The composition of coal ash refers to complete combustion of the minerals in the coal, producing a variety of metals and non-metallic oxides and salts, which is an important parameter when using coal. Coal has been widely used in the production and people’s life, as an important energy substance. A large amount of coal dust (coal ash) from coal combustion was released into the atmosphere and interacted with various substances in the atmosphere to form haze. A series of physico-chemical reactions take place between metal oxides in coal ash and small droplets in the air, which result in the formation of haze. In this study, laser induced breakdown spectroscopy (LIBS) was employed to analyze the elements in coal ash. The experimental samples were provided from a steel company, which was divided into seven parts. Distilled water and 0.1‰, 0.2‰, 0.2%, 0.4%, 0.8%, 1% zinc sulfate solution were added into samples, which were labeled with number 1～7 respectively. In order to obtain a better LIBS signal, the sample was powdered. The water in the solution was used to thoroughly mix zinc with coal ash. In the experiment, the coal ash was pressed into 10mm diameter and 10 mm thick coal ash blocks by using a tabletting machine. In order to get accurate elemental results, X-ray fluorescence spectroscopy were also employed for reference, and the original sample did not contain zinc. Due to the uncertainty of spectral analysis and wavelength shift phenomenon, qualitative analysis of element was inaccurate. To solve this problem, four kinds of high-purity elements including iron, calcium, titanium and aluminum were separately selected. Under the same experimental conditions, four measured elemental spectral lines were compared with the corresponding spectra in the NIST atomic spectral database. All the spectra in the experiment were corrected according to the wavelength difference or shift. At this point, the elemental spectrum of pure elements can be aligned with the samples’ spectrum. The samples then can be identified and confirmed when the characteristic line in the elemental spectrum is aligned with the spectrum in the samples. Because Al has similar chemical and physical property with target element, and Al is one of the major elements in coal ash and the crust, and has moderate spectral intensities. For quantitative analysis, the internal standard calibration method was used to determine the concentration of zinc in the samples. The results of simulating zinc-containing atmospheric aerosols were achieved by adding zinc to coal ash. Some other related metal elements, including iron, calcium, manganese, titanium and aluminum were also used to spike into coal ash to simulate atmospheric aerosols. The relative difference between the two methods is 1.78%, 3.39%, 5.17%, 0.20%. The reason for the difference may be due to the lack of resolution of the spectrometer or the impact of background noise, which could lead to the measurement error. Due to the limitations of laboratory conditions, we can’t be sure whether the influence of matrix will affect the experiment results, and which will be further confirmed by future experiments.The linear correlation coefficient of zinc in coal ash was determined to be 0.995 72, indicating that the rough estimation of zinc content can be achieved by the intensity of zinc in the spectrum. The experiment concluded that LIBS technology can be used for the rapid detection of metal elements in coal ash, and this work provides a novel method for the detection of atmospheric environment based on the content of zinc.After establishing the calibration curve of the elements, the LIBS technique can be used to conduct a rapid and accurate quantitative analysis in the future.

Soil moisture has strong absorption in near infrared spectroscopy (NIRS) and causes interference in the prediction of the soil organic matter (SOM) content. In this paper, 41 dry soil samples were used to establish the SOM calibration model by PLSR, and 9 samples were used as the prediction set. All soil samples were rewetted to four different moisture contents (5%, 10%, 15% and 17%). The slope/bias (S/B) and direct standardization (DS) algorithms were used to correct SOM prediction results and whole-spectra obtained by different moisture content, eliminating the differences caused by soil moisture. The results showed that the bias reduced and prediction performances of the model were improved, with Rp higher than 0.89 and RMSEP lower than 0.885%. The study indicated that S/B and DS algorithm corrections could effectively remove the influence of soil moisture in NIRS and improve the accuracy of SOM predictions.