Nuclear Magnetic Resonance (NMR) can provide real-time, in-situ high-resolution molecular and biological information, and has been wildly applied in determining the structures of highly complex molecules and biological imaging. Its low sensitivity, however, hindered its further application. An effective way to increase the sensitivity of NMR is transferring hyperpolarized spin-orders of exogenous particles to the substrates. The main drawbacks of current methods are high cost of equipment and complicated procedures. Parahydrogen-induced polarization (PHIP) is a potential candidate to increase sensitivity of NMR due to its low cost, simple procedure and high polarization efficiency. By transferring the spin-order of parahydrogen into substrate, the sensitivity of NMR can be increased by at least 3 orders. This review will briefly introduce the basic principles of PHIP, physical and chemical procedures involved and its application in chemistry and biological imaging. The two hydrogen atoms in parahydrogen are in opposite spin states, and can be enriched at low temperature with the help of catalyst. Enriched parahydrogen is relatively stable even when returned to room temperature. Spin-order of parahydrogen can be transferred to substrate by two approaches. First, addition of parahydrogen into unsaturated groups in substrates, which can be used directly, or transfer spin-order to adjacent heteronucleus (13C, 15N, 19F et al). Second, signal amplification by reversible exchange (SABRE), through which parahydrogen and substrates are reversibly coordinated into metal complex and the spin-order is transferred from parahydrogen to substrates. Choosing the right catalysts is crucial for the enhancement of NMR sensitivity, and this manuscript summarized the types of catalyst used in this technique and their structures. Moreover, methods to transfer the hyperpolarized spin-order of parahydrogen, which are important for enhancing the sensitivity of heteronucleus, were also summarized. PHIP has shown great potential in many applications due to its high increase in sensitivity. First, this technique requires much lower sample concentration (μmol·L-1 or even lower) than normal NMR, which makes determination of low concentration species such as reaction intermediate or trace analysis. Second, hyperpolarized substrates are good candidates for NMR imaging contrast agent. Nevertheless, realizinglong-lived imaging contrast agent with high polarization and good solubility in water is still challenging.

The hyperspectral imaging technology is significant in the field of evidence examination. Because of the spectral characteristics and spatial distribution characteristics, non-destructive, rapid and positioning analysis of material evidence can be realized. The spectral detection range of hyperspectral imaging in evidence examination usually concentrates on visible-near infrared region. However, the existing material evidence testing equipment based on hyperspectral imaging technology can only cover visible or near infrared band alone, which cannot meet the wide-band detection requirements. In order to widen the detection band so that the accuracy of evidence examination can be improved, this paper firstly analyses the composition, structure and working principle of push-broom imaging spectrometer, secondly analyses the technical difficulty and high cost of developing wide-band imaging spectrometer, and finally puts forward the idea of combining the visible imaging spectrometer and the near infrared imaging spectrometer to achieve a wide band range. Two independent equipments are combined as one equipment by matching the line-of-sight of two imaging spectrometer. The calibration board is used to realize the pixel-level splicing of line-of-sight so that the error caused by equipment splicing is reduced to the extent that it does not affect the output results. Finally, an evidence detection device of visible-near infrared wide-band hyperspectral imaging spectrometer with a band range of 400~1 700 nm is developed. Two independent short-band hyperspectral imaging spectrometers are fixed, and a moving platform is used to drive the sample along the direction perpendicular to the line-of-sight. The obtained data cube has a broad spectral range of 400~1 700 nm, the spectral resolution of 400~1 000 nm is 2.5 nm, and the spectral resolution of 1 000~1 700 nm is 4 nm. The experimental results show that the method is feasible which has guiding significance for the development of broad band hyperspectral imaging spectrometer. It makes the imaging spectrometer have higher application value and wider application scope in the field of evidence examination.

Penetration detection is an important link to realize the on-line control of high power laser welding quality. However, because the penetration region has the characteristics of low radiation and mesoscopic scale, which is generated from the bottom of the laser keyhole, its signal is completely masked by the ejected materials from the keyhole and the surrounding interference signals. As the penetration state is difficult to be directly obtained, the conventional measurements mainly use indirect measurement. In this paper, a coaxial synergistic extraction method of laser welding penetration characteristic signal is proposed by combining technologies of spectral perspective, infrared microscopic imaging, photoelectric sensing and spatial location extraction. It uses the fluorescence source as the direct detection signal, which is excited by high power laser in the inner wall of the keyhole, and by using the spectral characteristics of different luminescent materials in the infrared spectrum, separates and suppresses the strong interference signals such as plasma, metal vapor flame, particle cluster and so on over the keyhole. So as to enhance the infrared fluorescence signal in the keyhole effectively and realize the effect of spectral fluoroscopy. At the same time, by using the self-developed microscopic optical system with long focus in coaxial laser welding, which is according to the principle of infrared microscopic imaging, the real images of the stimulated radiation behavior which inside the keyhole are extracted. On this basis, the correlation between penetration state of high power laser welding and internal image features of keyhole is studied. The phenomenon of low radiation value and its existing position directly related to penetration state are found. After that, by means of visual assisted positioning adjustment and penetration characteristic position test experiments, that can improve the positioning accuracy successively, until the sensor photoelectric sensor chip is positioned to the penetration characteristic region in the fluorescence radiation real image with high precision. Therefore, by layer-by-layer optical separation method of spectral perspective, microscopic imaging and mesoscopic location signal extraction, accurate extraction and maximization of keyhole penetration data can be realized. The experiments results show that the coaxial synergistic extraction method of penetration characteristics of high power solid laser welding, which is based on composite applications of multiple spectral and optical processing methods, is effective and can be used as a new method for on-line detecting penetration of high power laser welding.

Trace dissolved gas in transformer oil is a key feature for monitoring the transformers’ status and for estimation of early failure, therefore there is an urgent need for the development of cost-effective on line gas detection methods. As a non-destructive testing method, photoacoustic spectroscopy (PAS) technology is well-known for the advantages of high sensitivity, large dynamic range, and robustness of implementation, which has the potential for the on-line detection of trace dissolved gas detection. A T-resonator enhanced Fourier transform infrared photoacoustic spectroscopic (FTIR-PAS) system is established for the analysis of multiple trace dissolved gases in this paper. The presented T-resonator mainly consists of absorption and resonance cylinders which are perpendicular to each other. A microphone is placed on top of the resonance cylinder away from the incident light path, thus the spurious signal caused by scattered light is avoided and the noise level of the FTIR-PAS configuration is only limited by the microphone itself. The T-cell resonance frequency is determined by the dimension of the resonance cylinder, which results in a solution for the conflicting requirements of low frequency and the limited space of the FTIR compartment. The photoacoustic spectra of the mixture of 380 μL·L-1 CO2∶1 000 μL·L-1 C2H2∶N2 with 6 cm-1 resolution are collected to verify the wavenumber accuracy and multiple trace gas detection ability of the FTIR-PAS technology. The fact that the four absorption bands of CO2 and C2H2 are obviously distinguishable exhibits the good performance for simultaneous multi-dissolved gases detection of the T-resonator enhanced FTIR-PAS configuration. The results show the detection sensitivity yields 4 μL·L-1 for CO2 (light intensity 12.6 μW at 2 349 cm-1) and 5 μL·L-1 for C2H2 (30 μW at 1 360 cm-1) under STP conditions. The minimum detection limits of both gases match the national standards for transformers. By virtue of its broadband nature and high sensitivity, the T-resonator enhanced FTIR-PAS methodology is shown to be suitable for simultaneous multiple trace dissolved gas detection in transformer oil.

In view of the frequent occurrence of sudden accidents, haze and other pollution phenomena in recent years, the harm scope is wide and the harm degree is deep. Therefore, it is urgent to grasp the region, the scope and the intensity of the pollution, as well as the trend of the pollution diffusion. The two-dimensional fast imaging distribution of pollution sources has an absolute advantage indetermining the location of gas leakage source, identifying emergencies and identifying the scope and impact of pollution. In this paper, the fast imaging measurement about the plume from the power plant in Fengtai is realized by ultraviolet filter based on a planar CCD detector. The concentration of SO2 obtained by the flue gas on-line monitoring technology is used as the reference concentration. The imaging system is calibrated after the reference concentration is transformed. The calibration result shows that the SO2 column density presents a linear relationship with the optical intensity, the correlation coefficient is 0.958, and the prerequisite that the imaging theory can be analyzed is satisfied. Considering that the angle of view of the imaging system is small, the background is taken as lens deviates from the plume area upwind. The background intensity indicates that the upwind intensity is uniform and there is no other influence. The 310 nm filter identifying the target gas and the 330 nm filter dispelling the influence of aerosol are used alternately to image for the smoke plume in order to reduce the error of the plume change during the measurement process. At last, the two-dimensional distribution and the sequence diagram of SO2 slant column density are obtained according to the linear least squares fitting at about 12:30 on May 20, 2017. The results show that SO2 slant column density is high near the chimney exit, and high SO2 concentration of inclined column is approximately 1.7×1017 molec·cm-2. The figure of slant column density distribution displays visually diffusion trend of SO2 concentration, showing that SO2 inclined column density decreases slowly along the axial diffusion of the plume under the direction of the wind, and under the direction of the perpendicular to the plume diffusion, the figure tells that inclined column of SO2 above the axisis less than its concentration below because of the air buoyancy, fluid dynamics about plume and the direction of wind. However the basic trend of diffusion is that both sides of the SO2 inclined column perpendicular to the axis decrease quickly. In the 28 meters away from the center of the chimney from downwind direction, the concentration of SO2 inclined column and gauss curve are taken for fitting, and the fitting coefficient is 0.747, which indicates that the concentration diffusion of SO2 inclined column in wind direction basically follows gauss diffusion. The plume velocity is about 1.2 m·s-1 according to the time series diagram about SO2 column density. The gauss diffusion model is used to verify the feasibility of ultraviolet non-dispersive imaging system on the basis of the known plume SO2 emissions (9.2 g·s-1), smoke plume speed (1.2 m·s-1), smoke plume height (140 m) and the surrounding environment. Comparing the results about the imaging system with the plume model, it is shown that SO2 slant column density measured and the diffusion trend are consistent with theoretical predictions. This paper for the first time uses rapid imaging method based on filter to image SO2 slant column density from fixed point pollution source, and finally the distribution and diffusion of SO2 in plume are obtained successfully. The consistency between measurement results and model simulation indicates that this imaging method is expected to provide measurement basis for quantitative and qualitative assessment of pollution hazards.

Hydrostatic pressure is a very important physical parameter. Application of hydrostatic pressure to molecular systems can adjust the distances and forces of the molecules and atoms, which can result in new structure and conformation change. Normal alkanols H(CH2)nOH are among the simplest substituted organic matters, in which a single OH group replaces a hydrogen atom at the end of the aliphatic chain. Normal alcohols are held together by the interplay between the hydrogen bond and the alkyl chain, and are called hydrogen bonded liquids. Hydrogen bonds are far weaker, so application of hydrostatic pressure to hydrogen-bonded organic molecules can compress hydrogen bonds. Large modifications can be observed in hydrogen bonds, including breakage and rearrangement. The changes in hydrogen bonds can lead to variations of crystal structures and symmetry, which will affect the properties of materials. N-pentanol (C5H12O) is short chain alcohol. It is simple in structure, but it can be a typical representative of alkyl chain organic compounds. However, the properties researches on n-pentanol under high pressure are scarce, especially studies on the conformational changes and hydrogen bonds under pressure have not been reported. So it is necessary to investigate n-pentanol at higher pressure, which is helpful to probe more information. Raman and IR spectroscopy are common spectral measurement techniques in high pressure research. They are useful for observing and providing interesting insights into the changes of the molecule. They are crucial tools, in studying structures, conformations and hydrogen bonds. Thus, in this paper, hydrogen-bonding and phase transitions of n-pentanol (C5H12O) have been investigated under high pressure usingRaman and Infrared spectroscopy. The high pressure Raman and IR spectrum have been collected as a function of high pressure to 12.0 GPa by using the diamond anvil cell (DAC). The experiment results have been discussed in section 3. In the first part, the Raman spectrum of n-pentanol have been measured under high pressure. The Raman spectrum showed that the characteristic peaks become sharpened, characteristic peaks split and new modes appear at 3.2 GPa. These results indicated that n-pentanol might experience a liquid to solid transition at 3.2 GPa. In the second part, the influence of high pressure on conformational behavior of n-pentanol has been analyzed. N-pentanol has two characteristic conformers, including TTTt conformer and GTTt conformer. The changes of characteristic peaks with pressure have been studied. The data analysis showed that conformational change between trans and gauche is observed accompanied by the phase transitions. It was concluded that the gauche conformation is the main form in the liquid n-pentanol and the trans conformation in solid state. In the last part, the effect of high pressure on hydrogen-bond of n-pentanol has been investigated. The red shift of O—H stretching modes indicates that the H-bond is strengthened with increasing in pressure. The O—H stretching modes split into multiple peaks, which implied that new clusters and hydrogen bonding network of n-pentanol have formed. With the pressure increasing, the cluster structure of n-pentanol has become more stable and bigger. These results suggested that hydrogen bond is sensitive to pressure and plays an important role in promoting the stability of n-pentanol crystal structure. The high-pressure study on n-pentanol can provide a theoretical basis for the study of physical and chemical properties of similar or complex molecular systems.

In order to improve the efficiency of solution-processed, blue fluorescent organic light emitting diodes (OLEDs), we propose the use of exciplex hosts with thermal-activated delayed fluorescence (TADF). The TADF exciplex hosts can utilize upconverted singlet excitons by reverse intersystem crossing and then transfer the energy to the guest to improve efficiency of the blue fluorescent OLEDs, which enables the full utilization of triplet and singlet excitons. Here, blue fluorescent material 1-4-Di-［4-(N,N-diphenyl) amino］styryl-benzene (DSA-ph) issued as the guest emitting material, 4,4′,4″-Tris(arbazol-9-yl)t-riphenylamine (TCTA) doped 1,3,5-Tri(1-phenyl-1H-cbenzo［d］imidazol-2-yl)phenyl) (TPBi) was used as the TADF exciplex hosts, and the emitting layer was fabricated by solution process. From the photoluminescence (PL) spectra of TCBi, TPBi and TCTA doped TPBi films, it was found that the emission peak of TCTA doped TPBi film was significantly red-shifted compared to that of pristine TCTA or TPBi films (peak wavelength changes to 437 nm). Meanwhile, the spectrum broadens, which proves the existence of exciplex. The PL spectra of DSA-ph doped exciplex hosts and DSA-ph doped poly(methyl methacrylate) (PMMA) films were found to be the same and both of the photol-uminescence peaks were derived from DSA-ph, which proved that exciplex hosts transfer energy to DSA-ph. The absorption spectrum of DSA-ph overlaped greatly with the PL spectrum of exciplex hosts, which also proved that the exciplex hosts transfer energy to DSA-ph effectively. Time-resolved PL measurements were performed on exciplex hosts doped with different concent-rations of the DSA-ph guest. It was found that the lifetime of the DSA-ph doped exciplex hosts becomes longer compared to that of the pure DSA-ph. The lifetime of pure DSA-ph is only 1.19 ns. The fluorescence decay curve of DSA-ph doped exciplex hosts is similar to that of exciplex hosts, which further demonstrates that the exciplex hosts transfer energy to the DSA-ph. We investigated the effects of the presence of TADF exciplex hosts and the DSA-ph con-centration on the device performance. The parameters such as brightness, current density, voltage, current efficiency, electroluminescence spectra of the devices were measured. The perfor-mance of the OLEDs using exciplex hosts were notably improved, compared to standard OLE-Ds without exciplex hosts. In the condition of 10% DSA-ph, the luminescence increased from 2 133.6 cd·m-2 (for pristine DSA-ph) to 3 597.6 cd·m-2, and the current efficiency increased from 1.44 cd·A-1 (for pristine DSA-ph) to 3.15 cd·A-1. All of the electroluminescence peaks were only derived from DSA-ph. The concept of using TADF exciplex hosts provided a facile way to achieve high performance solution-processed blue fluorescent OLEDs.

Noise-immune cavity-enhanced optical heterodyne molecular spectroscopy (NICE-OHMS) is the most sensitive laser absorption spectroscopy technology. It has obtained dozens of impressive detection sensitivities in a low pressure environment. However, when the measurement is taken at atmospheric pressure, its detection sensitivity becomes much worse. One of the dominant reasons is that the conditions for obtaining the maximum amplitude of NICE-OHMS signal at atmosphereare different from those under low pressure. In this paper, the theory of NICE-OHMS at atmospheric pressure is analyzed. The parametersthat affect the amplitude of the signal, including cavity length (L), modulation factor (β), and detection phase (θ), have been analyzed in order to figure out the best experimental conditions. Among them, due to the use of DeVoe-Brewer technology in NICE-OHMS, the modulation frequency (νｍ) is locked to the free spectral region (FSR) of the Fabry-Parot (FP) cavity. As a result, the cavity lengthnot only affects the NICE-OHMS signal amplitude, but also determines the value of νｍ. The results show that when the cavity length increases, the spectral components of the carrier and the sidebands overlap with each other due to the decrease of νｍ, which results in the decease of the amplitude of lineshape functions. And the amplitude of the NICE-OHMS signal at absorption phase increases gradually with the increase of the cavity length. While the amplitude at dispersion phase increases at the beginning, and reaches the maximum value when the cavity length is equal to 8 cm, then decreases with the cavity length. Modulation coefficient β affects the magnitude of laser carrier and sidebands, as consequence, affects the signal lineshape. As the cavity length increases, the β value for the maximum signal amplitude also increases. At the same cavity length, the β value for the maximum amplitude of the dispersion signal is smaller than that for absorption signal, which is easier to achieve by using an electro-optic modulator. Finally, the feasibility of the parameters has been analyzed. The half-width at half-maximumof spectrum at atmospheric is determined by the pressure broadening, which isaround 3 GHz, and the spectral coverage is larger than 10 GHz. The frequency tuning range of the distributed feedback semiconductor laser (DFB) and external cavity diode laser (ECDL) can reach to 30 GHz, whiletheirlarge laser line width deteriorates the PDH locking performance. The line width of whispering wall mode laser (WGM) and erbium-doped fiber laser (EDFL), the conventional light source in high-sensitive NICE-OHMS system, is in the order of 100 Hz. However, as so far, the frequency tuning range of NICE-OHMS system based on WGM is only 5 GHz, while that based on EDFL is only 3 GHz. When the cavity length is longer than 8 cm, a WGM laser can be used. When the cavity length is greater than 25 cm, an EDFL laser can be used. For a PZT with a flexible length of 25 μm, which is commonly used in the design of optical cavities, the frequency range of the corresponding cavity mode gradually decreases as the cavity length increases. At a typical cavity length of 40 cm, the frequency sweep range is greater than 12 GHz.

Atmospheric aerosols range in diameter from a few nanometers to tens of micrometers, with direct or indirect effects on atmospheric radiation assessments, global climate change, local air quality and visibility, and human health. Especially during the high season of smog in autumn and winter, it’s more conducive to the formation, transformation and accumulation of atmospheric aerosols. At present, there are many technologies for aerosol observation, including laser radar, solar photometer, canopy meter, and satellite remote sensing, etc. Multi-axis differential optical absorption spectroscopy (MAX-DOAS) technology is a passive and telemetry spectroscopy instrument. In addition to the characteristics of stable and real-time continuous monitoring, it can simultaneously acquire the concentration information of various trace gases and further retrieve the aerosol optical thickness (AOD) and aerosol profile. This paper introduces the method of aerosol retrieval by retrieving O4 column concentration information based on MAX-DOAS technology. Ground-based MAX-DOAS measurements were carried out at Science Island, Hefei from December 2017 to January 2018. The spectra were recorded with an azimuth of 0 degrees (north) and 10 elevation angles from low to high in the vertical direction for each scanning cycle. The zenith direction measured the spectrum as a reference spectrum. In the 337～370 nm band, we calculated the total amount of oxygen dimer (O4) differential slant column densities (DSCD) using QDOAS software, and retrieved aerosol optical thickness (AOD) and aerosol extinction coefficient (AE) using the aerosol profile inversion algorithm (PriAM). We compared the results with the AOD measured by the solar photometer CE318, and the correlation coefficient between the hourly mean and the daily average was 0.91. The results showed that MAX-DOAS has high reliability in obtaining aerosol information. In addition, we also compared the near-surface aerosol extinction coefficient obtained by MAX-DOAS with the PM2.5 concentration measured by the point instrument at the ground station. The correlation coefficient r of the daily mean and hourly mean linear fit was 0.83 and 0.62, respectively, which further verified the reliability of MAX-DOAS for obtaining aerosol information. Since winter is a time for high incidence of haze, the AOD value is higher. We studied a smog process from December 3 to 6, 2017, and found the aerosol was mainly distributed below 1 km. Combining with the wind field information and the airflow backward trajectory map during the period of haze, it can be seen that the pollution is caused by the transportation of polluted air masses in the northwest.

In recent years, China’s economy has developed rapidly, industrialization has become higher and higher, and atmospheric pollution has intensified, seriously affecting people’s daily lives. Therefore, real-time monitoring and research on atmospheric pollutants is particularly important. The interaction of various pollution sources in the atmosphere of the urban boundary layer makes the pollution problem complex and variable, especially the vertical distribution and change of pollutants in the atmosphere during heavy pollution. Imaging differential absorption spectroscopy (I-DOAS) is used to detect the spatial distribution of pollutants. The research at home and abroad is based on ground-based scanning, airborne and space-borne platforms. Because of its long-distance, multi-component, high-resolution and continuous real-time observation, the observation range can be extended from small scale to large area, which can provide important data support for analyzing the current situation of the atmospheric environment. Ground-based imaging differential absorption spectroscopy is generally used to detect a certain pollution source. This paper mainly studies its detection method for urban atmospheric boundary layer pollutant distribution. It introduces the principle of differential absorption spectroscopy (DOAS) based on Beer-Lambert law, and introduces the imaging principle of imaging system based on “push-broom”. Taking the common pollutant NO2 in the atmosphere as an example, on June 12, 2018, the imaging telemetry experiment of NO2 in the boundary layer was carried out in Science Island of Hefei City. The front end of the multi-core fiber bundle was coupled with the ultraviolet lens, and the back end was connected to the slit of the spectrometer. The ultraviolet lens was mounted on the two-dimensional rotating motor. Set the appropriate elevation angle of the two-dimensional rotating electric machine, and rotated it from 0° to 90° in the horizontal direction. The observation area included the suburb, power plant area and urban area. The zenith solar spectrum was selected as the reference spectrum, and the corresponding multi-channel spectra were combined and extracted for the measured spectrum and the reference spectrum. 38 spectra were obtained for each acquisition. Data inversion of all measured spectra was performed using the DOAS inversion method to obtain the differential slant column density (DSCD) of 38×90 NO2, and the density information was matched with the pixels on the spatial dimension according to the geometric model of the observation angle. After deducting the complex background, the two-dimensional distribution images of the NO2 differential slant column density in the boundary layer of Hefei City were obtained, according to the scanning direction. Compared with the MAX-DOAS data observed at the same time, the correlation coefficients of the two in the suburbs, power plant area and urban area were 0.86, 0.87 and 0.83, respectively. The results showed that the system can effectively obtain the distribution information of atmospheric pollutant concentration in urban boundary layer.

Alum is an illegal additive that can improve the fragile characteristics of vermicelli. If the content of alum is excessive, it will directly affect the health of the body. This paper combines terahertz spectroscopy to explore a rapid detection method for alum in sweet potato starch. The spectral data of sweet potato starch, alum and their mixtures in the range of 0.5～7 THz were obtained by Terahertz Time Domain Spectroscopy （THz-TDS） at room temperature. Since the spectrum measured by 0～0.5 THz is noise, the absorption coefficient of the high-band region is large, and the signal-to-noise ratio is low, the absorption coefficient spectrum and the refractive index spectrum of the 0.5～2 THz band were selected for analysis. It was found that alum has obvious characteristic absorption peaks in terahertz band, which can be used as fingerprint features for material identification. Savitzky-Golay convolution smoothing, Baseline, Normalization were used for spectral pretreatment, and combined with partial least squares（PLS） a prediction model for alum content in sweet potato starch was established. The results showed that the principal component factors of the PLS model were 3, 3, 3, 2 using the original, SG smoothing, Baseline, Normalization spectral data, respectively. The correlation coefficient of calibration（rc） were 0.982, 0.980, 0.982, 0.984, respectively. The correlation coefficient of prediction （rp） were 0.982, 0.979, 0.982, and 0.987, respectively. The root mean square error of correction （RMSEC） were 0.011, 0.012, 0.012, and 0.011, respectively. The root mean square error of prediction (RMSEP) were 0.013, 0.014, 0.013, and 0.012, respectively. The PLS model had the best effect after normalization pretreatment. In order to compare and analyze the prediction accuracy of linear (PLS) and nonlinear (LS-SVM) quantitative model methods, the least square support vector machine was established using the spectral data of alum in the sweet potato starch after the same pretreatment method. For the prediction model, the radial basis function was chosen as the kernel function. The results showed that the LS-SVM model is the best after normalization preprocessing. The RMSEP of the prediction set was 0.004 7, and the correlation coefficient of the prediction set was 0.997 2. It was found that the LS-SVM prediction model for the alum content in sweet potato starch was more stable and more accurate. The content of alum in sweet potato starch was quantitatively analyzed by terahertz time domain spectroscopy combined with LS-SVM and PLS. The results showed that the LS-SVM with normalized pretreatment has better prediction effect than the PLS, which may be more nonlinear information in the mixture of sweet potato starch and alum. Studies have shown that terahertz time-domain spectroscopy combined with chemometric methods can provide a fast and accurate analytical method for the quantitative analysis of alum in sweet potato starch.

Terahertz filter is an indispensable functional device in terahertz communication, terahertz imaging and terahertz detection systems. According to different classification methods, there are different kinds of filters. Common filters can be divided into high-pass filter, low-pass filter, band-stop filter and band-pass filter according to frequency selection function. In order to achieve the filtering effect in terahertz band, researchers around the world use different structures, materials and control methods to achieve terahertz filters with different functions. However, considering that the designed devices are to be applied to terahertz system, the low cost, simple structure and superior performance of terahertz filters have always been the pursuit of researchers. Fractal concept has developed rapidly in many research fields since it was proposed, but its application in terahertz band is not very common, especially in the design of terahertz functional devices. A novel terahertz bandpass filter is designed and fabricated by introducing the concept of Koch curve in fractal. The filter etches the fractal structure of Koch curve on the metal film. When the terahertz wave is incident perpendicularly to the filter, the narrowband filter in terahertz band is realized. In the process of filter design, the combination of theory and experiment is pursued. Firstly, the Koch curve fractal structure filter model is established in electromagnetic simulation software to calculate, and the feasibility of applying fractal structure to terahertz band filtering is explored. After many calculations, the optimized size and structure are obtained. Then, the Koch curve fractal structure is processed according to the optimized size. Sample of terahertz filter is constructed and measured in terahertz time domain spectroscopy system. The experimental data are obtained and compared with the simulation results. The finite difference time domain method is used to simulate the transmission characteristics of THz bandpass filter with Koch curve fractal structure. The optimized simulation results show that the resonant frequency of the filter is 0.715 THz, the transmission coefficient can reach 0.92, and the bandwidth of -3 dB is 21.9 GHz. The electromagnetic parameters of the THz filter sample are obtained by inversion of the simulated scattering parameters with S parameters, which is analyzed theoretically in the reason of transmission enhancement of terahertz wave at resonance point. Sample of THz bandpass filter with fractal structure of Koch curve optimized is fabricatedby femtosecond laser microfabrication system. The transmission characteristics of the sample are tested by THz time domain spectroscopy system. Frequency domain data are obtained after fast Fourier transform of the experimental time domain data. Frequency domain data are normalized and combined with previous electromagnetic simulation results. By comparing the results, it is found that the experimental results are in good agreement with those obtained by electromagnetic software simulation.

Perovskite oxide NaNbO3 is an environmentally friendly piezoelectric material with great potential applications. Thus, it has been studied by many researchers using various methods. Although several high pressure studies on structural phase transition of NaNbO3 have been carried out but there are still many disputes regarding the phase transition sequence and the crystal structure of the phase transition near 2 GPa and above 12 GPa. Previous Raman studies on structural phase transition of NaNbO3 were mainly focused on the high frequency side of the spectrum related to the internal vibration of NbO6, and did not cover the lattice vibration in low frequency region. Therefore, we studied the structural phase transition of NaNbO3 by Raman spectroscopy at high pressure using diamond anvil cell technique from 0~22 GPa. In this study, we used a mixture of 16∶3∶1 methanol, ethanol and water as the pressure transmitting medium. We obtained the Raman spectra from 40 to 1 000 cm-1, so that the obtained spectrum fully covered the phonons related to the Na+ displacement, librational, translational and vibrational modes of NbO6 in the unit cell. Our results showed that the Raman spectra of NaNbO3 under pressure drastically changed near 2, 7 and 9 GPa, which was related to the structural phase transition. During compression, the intensity of three peaks at 180~210, 221.2 cm-1 increased rapidly, whereas the two shoulder peaks at 204.1 and 252.8 cm-1 disappeared near 2 GPa. Also the ν1 and ν3 modes showed softening at the same pressure. These results indicated that NaNbO3 transformed from Pbma phase to HP-Ⅰ phase at 2 GPa. Further increasing pressure to 6.6 GPa, the Raman modes at 122.3, 155.5, 196.2, 228.2 and 279.4 cm-1 at ambient pressure disappeared, while the peak intensity of high frequency Raman modes decreased and the peaks became broad, indicating that the second structural phase transition (HP-Ⅰ~Pbnm) of NaNbO3 occurred near 7 GPa. At 9.7 GPa, Raman modes below 125 cm-1 disappeared completely, showing a strong background like feature. However, at intermediate frequency range, new peaks at 182.2, 261.4 and 517.7 cm-1 appeared, whereas the Raman mode at 559.1 cm-1 disappeared, indicating another structural phase transition from Pbnm to HP-Ⅲ phase near 9 GPa. Up to 22 GPa, the Raman spectra did not change much as a function of pressure, and showed very sharp spectral characteristics, indicating that the HP-Ⅲ phase remained stable up to the 22 GPa. Thus, our result did not support the appearance of the cubic paraelectric phase above 12 GPa as reported by other researchers. From our result, we can estimate the Tc temperature decreased from 614 ℃ to RT at least at the rate of dT/dP=27.9 ℃·GPa, much less than that calculated by Shen et al. During decompression, below 7 GPa, the Raman spectra of HP-Ⅰ phase were significantly different from the spectra observed at increasing pressure cycle. This result showed the irreversibility of the structural disorder caused by Na+ displacement, indicating the crystal structure within this pressure range may be coexistence of HP-Ⅰ and Pbnm phase. After releasing the pressure, the ambient structure of NaNbO3 was basically recoverable. Therefore, it can be seen that the lattice vibration induced by Na+ displacement in low frequency range has a great importance for the high-pressure phase transition studies on NaNbO3, which can provide a reference for the future study on structural phase transition of other perovskite materials.

As a new-type drug, methamphetamine has been spreading rapidly in recent years and its social harm has become increasingly serious, which has brought severe challenges to the relevant regulatory authorities. How to provide a non-destructive, fast and accurate drug detection method has important practical and application value. Based on the above conditions, Raman spectroscopy is a novel method. However, due to the differences of methamphetamine molecules, the Raman spectra detected are different, which affect the on-site methamphetamine detection, and even cause misjudgment, and bring great difficulties to the establishment of the database of Raman spectra of methamphetamine. Therefore, according to the density functional theory, the Becke-3-Lee-Yang-Parr (B3LYP) hybrid functional method was used to determine the three dihedral angles of the methamphetamine molecules 1, 2 and 3 on the 6-31G basis. In the range of 0°～360°, the potential energy surface scanning was performed in steps of 10° respectively, and 12 different stable conformations of methamphetamine molecule were obtained based on minimal energy points. Besides those, four lower energy conformations were further optimized and their vibration frequencies were calculated on the 6-31G++(d, p) basis set. Finally the theoretical Raman spectra obtained were compared with the experimental spectra. The results showed that the differences of methamphetamine conformations produced various shifts on peak positions at 746, 837 and 1 356 cm-1 in Raman spectra, however, the Raman peaks positions at 632, 1 003, 1 180 and 1 312 cm-1 were basically unaffected. Therefore, when we identify suspicious samples, those unaffected peaks could be used as the identifier spectra of methamphetamine, and the matching method by identifier Raman spectra is obviously faster than most traditional correlation coefficient matching algorithms. Meanwhile, in the four lower energy conformations selected, the calculated results from the conformation IX were the closest to the experimental values. Therefore, in order to assign the experimental Raman identifier spectra of methamphetamine, the IX’ result was combined with the potential energy distribution of each vibration frequency and related literature. In those results, 1 003 cm-1 was the strongest identifier peak of methamphetamine, which was assigned to the aromatic respiration vibration. The Raman peak at 837 cm-1 was assigned to NH rocking vibration. In addition, the Raman peak at 1 180 cm-1 was attributed to CN stretching vibration and 1 312 cm-1 belonged to CH2 wagging vibration. These researches have the potential to provide useful references for drug detection, database of drug Raman spectra establishment and theoretical calculation of Raman spectroscopy of drug molecular in future.

Mussels are widely distributed in global waters, from offshore shallow waters to hydrothermal vents and cold seeps in the deep oceans. Mussels secrete calcium carbonate and form shells to protect their soft tissues. The nancomposite properties of mussel shell and the application prospects in biomaterial, tissue engineering and bionics have attracted much attention of scientists. The Raman spectroscopy is a kind of non-destructive, non-contact, simultaneous multi-component analysis detection technique, and can provide mineral information of samples. The mineral composition and distribution patterns of the shells and the nacre layers of the mussels collected from four different study sites (cold seeps in the Southwest of Taiwan, Desmos hydrothermal Field, Laboratory rearing, and Dalian-offshore) were obtained using the confocal Raman technique. The results showed that both of the prismatic layer and the nacre layers of the mussels are calcium carbonate. The Raman shifts of the primatic layers locate at 711 and 281 cm-1 indicating the mineral composition of prismatic layer is calcite. The mineral composition of nacre exists difference in different environment although the shell nacre is mainly calcium carbonate: the mineral of nacre in Dalian-offshore is aragonite. The Raman shifts of aragonite are at 706 and 206 cm-1. Aragonite crystallizes poor. The mineral of nacre layers grown in hydrothermal field and cultured in laboratory are aragonite (706 and 206 cm-1) with good crystallization. The mineral of mussel nacre in cold seep is aragonite (706 and 206 cm-1) and contains a little calcite. The Raman shifts of calcite are at 711 and 281 cm-1. Taking the living environment conditions into consideration, the results suggested that difference in the mineral composition and distribution patterns in the mussel shells are probably caused by different physical and chemical properties within the four environments. Moreover the nacre layers is more sensitive to the pressure change of living environment. Our work also showed that the Raman spectroscopy is a quick and effective technique that can be used to analyze the mineral composition of mussels in different environments and may shine some lights on the study of the life processes and adaptive mechanisms of mussels in deep oceans.

Mussels are widely distributed in various marine environments, from shallow seas to cold seeps and hydrothermal vents in the deep oceans, because of its excellent adaptabilityin different physicochemical conditions. Mussels anchor themselves on the tough substrate exposed on the seabed, such authigenic carbonate crusts or rock outcrops with adhesive protein secreted by mussel foot. This protein is a natural renewable biological adhesive available in various marine environments and mussel byssus presents such as high adhesive, high toughness and resistance to water. The adhesive protein has great potential and application prospect in biotechnology and medicine field, and it has become a research hotspot nowadays. Raman spectroscopy is a kind of non-destructive and non-invasive detection technique which can provide molecular biochemical information of organisms. In this paper, SEM and confocal Raman micro-spectroscopy are used to investigatethe apparent difference of mussel foot byssus, the secreted protein composition and distribution characteristics of mussel foot gland. Based on the apparent morphological differences of deep-sea mussels and sallow-sea mussels by SEM, two kind of mussels foot tissues are detected with confocal Raman micro-spectroscopy and acquire Raman spectra and 2D Raman color-coded image of three glands. The components and relative distribution of three glands of two mussels are compared and byssus differences caused by the glands distribution are analyzed. Meanwhile, considering the living environments of the two kind of mussels, we think that the mussel byssus appearance difference and foot glands distribution is a kind of adaptation mechanism to the environment. The Raman spectra suggest the components of two mussels foot glands: the higher intensity at 1 242 and 1 269 cm-1to the other two peaks (1 318 and 1 337 cm-1) of the amide Ⅲ signals indicates that the core gland is a higher degree of conformational order protein. The proteins that comprise theplaque and cuticle enrich amino acid tyrosine (Tyr) at 643, 830, 850 and 1 615 cm-1 and post-translationally converted to 3,4-dihydroxyphenylalanine (DOPA) at 785 cm-1; shallow-sea mussels present high intensity collagen protein at 1 043 cm-1. Raman imaging shows the glands distribution feature: deep-sea mussels foot glands distribution concentration and shallow-sea mussels foot glands distribution dispersion, which suggests that the glands distribution may be a kind of mechanism for the mussels to adapt different environments. The results indicate that confocal Raman micro-spectroscopy can be used in the analysis of the mussel foot glands distribution characteristics in different environments, and has great prospect to be applied in the micro-analysis of the biological samples.

With the development of the concept of green textile, more and more attention has been paid to the toxic chemicals used in textiles. Phthalic acid esters (PAEs) having reproductive toxicity, mutagenicity and carcinogenicity, which are frequently used as plasticizers in textiles, will enter the human body via air, water and food and jeopardize human health. Therefore, theirpotential and adverse impacts on ecosystem functioning and onpublic health have aroused considerable and growing attentionin recent years. The determination of PAEs is largely based on chromatographic and chromatograph-mass spectrometer. These methods are sensitive, accurate, but have some limitations including high costs, long detection time, and the need of trained personnel. Other methods, such as ELISAs are less studied, which have some limitations including interference of matrix and false positives. Therefore, developing efficient method for the analysis of PAEs is of significant importance. Surface-enhanced Raman spectrum(SERS) can provide rich molecular structure information and has a very high sensitivity, which has been widely used in food safety, environmental monitoring and national security and other fields. In this paper, using a portable Raman spectrometer, a rapid and quantitative SERS method has been developed for the detection of PAEs. In this method, PAEs are first converted into phthalhydrazide, which is then adsorbed on the SERS substrates (Au sols). Using such a method, various PAEs can be rapidly detected. Furthermore, a good linear relationship between the concentration of PAEs and their Raman intensity has been obtained in the range of 5~150 mg·L-1. The linear regressionequation is Y=139.04X+5 465.32, with a correlation coefficient of 0.993 0 and a detection limit of 5 mg·L-1. Using such a method, various PAEs in textiles are quantitatively detected with a recovery of >80%. The work demonstrates that the SERS method developed here is very simple, cost-effective and accurate thus is suitable for the rapid detection of the total amount of PAEs in textiles.

Recently, Surface Enhanced Raman Scattering (SERS) has attracted much attention due to its advantages innondestructive, ultra-sensitive and rapid detection analysis. It has great potential in chemical and biological sensing applications. SERS substrates with high sensitivity, repeatability and stability are of great significance to the application in trace analysis and biological diagnosis. Polymer materials with micro/nanostructure have excellent mechanical and optical properties and chemical resistance. In this work, a highly ordered polycarbonate (PC) nanocone array was fabricated by template imprinting on the surface of PC using porous anodic alumina (AAO). Then a silver film was deposited on the nanocone array by thermal evaporation technology, and alarge area of ordered polymer nanocone array modified by Ag nanoparticles was prepared. A large number of SRES “hot spots” can be generated by the narrow nano-gap between silver particles and particles at the top of the high curvature nano-needle structure. SERS active substrates with uniform, repeatable, large area and high enhancement were obtained by this method. The SERS characteristics of silver films with different thickness were further studied. Scanning electron microscopy (SEM) was used to characterize the structure. Crystal violet was used as a probe molecule in this study. The results show that the intensity of Raman signal increases first and then decreases with the increase of silver thickness. The Raman enhancement factor is of ~5.4×106, and the RSD of the main Raman peak intensity of CV is 10%, indicating good sensitivity and repeatability. In addition, after 40 days storage, the substrate still maintained high SERS performance under the same conditions, showing good stability. The whole preparation process is simple, reproducible, very cheap, and can be prepared on a large scale. It can be easily used as an active substrate for SERS research, and will have broad research and application prospects.

Goat milk β-casein is more easily digested and absorbed by infants than bovine milk β-casein, and the principal reason for this difference is the diversity of their structure. Recently, many investigations have reported the structure of bovine milk β-casein, however, the structure of goat milk β-casein and the difference between the structure of goat milk β-casein and bovine milk β-casein still needs to be studied in detail. The information of protein secondary structure can be obtained by spectroscopy technique, Circular dichroism is a method to characterize the structure of protein in solution state by using different optical active chromophores to absorb circularly polarized light in the left and right planes, which can make the protein conformation closer to its physiological state, and has the advantages of being rapid, simple and sensitive to conformational changes; Fourier transformation infrared spectroscopy is a method to characterize the structure of protein in solid state by using different chemical bonds or functional groups in the process of the vibration, which has the advantages of fast scanning speed, high resolution, wide measuring wavelength range, and is not easily affected by the molecular size and external conditions of protein samples. Circular dichroism and Fourier transformation infrared spectroscopy have been widely used in the study of protein conformation, but these two spectroscopy techniques to analyze the structure of β-casein has been rarely reported. Thus, this study used Circular dichroism and Fourier transformation infrared spectroscopy to compare the structural characteristics of the goat milk β-casein and bovine milk β-casein, and the sulfhydryl content and solubility of the two proteins were analyzed by spectrophotometry. Circular dichroism showed that random coil was the main secondary structure of goat milk β-casein and bovine milk β-casein, but the content of random coil of goat milk β-casein (50.2%±0.16%) was significantly higher than bovine milk β-casein (43.8%±0.14%), the content of α-helix (2.7%±0.21%) and β-fold (15.3%±0.08%) in the ordered structure were significantly lower than bovine milk β-casein (4.3%±0.13%, 19.5%±0.12%), the content of β-turn was 31.8%±0.11%, 32.4%±0.09%, respectively and the difference was not significant; Fourier transformation infrared spectroscopy showed that the content of α-helix, β-fold, β-turn in the secondary structure of goat milk β-casein were lower than bovine milk β-casein by 18%~20%, 9%~10%, 0.6%~1%, respectively and the content of random coil was higher than bovine milk β-casein by 17%~19%. The functional properties of the two proteins showed that the surface sulfhydryl content of goat milk β-casein and bovine milk β-casein were basically consistent with 19~20 μmol·g-1, but the total sulfhydryl content of goat milk β-casein (28.35±0.13 μmol·g-1) was significantly lower than bovine milk β-casein (46.72±0.21 μmol·g-1); the isoelectric point of goat milk β-casein was similar to bovine milk β-casein (pH 4~5), and the solubility of goat milk β-casein was lower than bovine milk β-casein near the isoelectric point, but higher than bovine milk β-casein far from the isoelectric point. The results showed that compared with the bovine milk β-casein, the disorder and flexibility of the goat milk β-casein were higher, and the internal structure of micelle was softer and looser.

Polyphenol is one of important factors that cause the changes of taste and color in fruit-wine. To ensure the quality of fruit-wine, it is necessary to develop a fast measurement that monitors the change of polyphenol content during the fermentation. The ripe blueberry and mulberry were collected from different harvest batches. They were crushed respectively into juice, and their mixed juice was also mixed in certain ratio for fermentation in the small fermentation tanks. Those fermenting liquors from the different fermenting periods were collected through the off-line sampling access. The supernate was obtained by centrifugation pretreatment and totally 48 fermenting samples were preserved in the brown bottles for later use. The supernate were injected into three paralleled cuvettes, whose transmission spectrums were scanned by FT-NIR spectrometer, and their repeated readings were averaged for the spectral signals. Then, the total phenol content was measured by the national standard method (i.e. the standard curve was established between the absorbance value and the standard solution), and all samples were divided into the calibration and prediction set in a ratio of 2∶1 by duplex algorithm, which was used to calculate the spectral distance from the divided sample to the center of the rest samples. Interval partial least square (iPLS) was used to construct series of quantitative models between the transmission spectra and the total phenol contents in the training set, and the number of intervals was successively changed from 2 to 60. The innovate point in this work was that the consensual rule was used to integrate the calibrated member models (here referring to the iPLS model) into a consensus model and distribute the weighting coefficients. The linear combinations of member models were optimized to minimize the mean squared error (MSE) in the consensus model through the residual errors from the cross validation and their correlations. The weighted coefficient of each member model was solved by Lagrange multiplier method, so as to minimize the root mean square error of the consensus model. Compared with the global model of partial least squares (PLS), interval partial least-squares (iPLS) model with different number of spectral intervals, the consensual iPLS (C_iPLS) model commonly obtained a better performance. When the full spectra were divided into 39 intervals, the C_iPLS model, composed of three iPLS members models (those were 14th, 16th, 18th iPLS model respectively), got the minimum root mean squared error of cross validation (RMSECV) of 124.2, as well as the correlation coefficient of cross validation (Rcv) of 0.944, and the samples in prediction set were tested well with root mean square of prediction (RMSEP) of 163.4, as well as the correlation coefficient (Rp) of prediction of 0.931. In addition, the successive projection algorithm and the uninformative variable elimination were used to optimize the spectral model, but the predictive performances were not better than the proposed consensus model. By analyzing the correlation between the predicted residuals of each iPLS model, it was found that the consensus model commonly screened these member models featured with high prediction performance and low correlation between member models. Results showed that the spectral analysis technology combined with the consensus method could improve the prediction accuracy of the regression model, reduce the modeling number of variables, and could be employed off-line for the rapid detection of total phenol content in fruit wine.

There are many studies on the preparation of superhydrophobic coatings, among which silicon derivative coating is a key point. However, there are a few reports on the formation mechanism of silicon derivatives.In this paper, sodium silicate and ethylene triethoxysilane (VTES) were used as reactants of silicon derivatives. The reaction mechanism of silicon derivatives was studied by near infrared spectroscopy (NIR) and two dimensional correlation analysis (2DCorr). Firstly, the spectral information of samples was collected by MPA Fourier near infrared spectrometer of Bruker Company,Germany. The molecular structure changes of 17 Wt% sodium silicate, 97 Wt% VTES and their blend of 1∶5 molar ratio were analyzed. The results showed that the absorption peaks of Si—O—H and Si—O—Si groups appeared in the range of 5 176~4 250 cm-1 in sodium silicate/VTES blend, which indicated that the hydrolysis and condensation reaction took place after the solutions were mixed. In addition, the free hydroxyl groups at 10 262 cm-1 decreased and shifted to low frequency, and hydroxyl groups associated with hydrogen bond increased at 8 905 cm-1. Secondly, sodium silicate and VTES were mixed and stirred into sol-gel shape according to seven different molar ratios. The spectral information of the samples was also collected by near infrared spectrometer, and the absorption peaks of the related groups in sodium silicate/VTES blend were assigned.The results showed that with the increase of VTES ratio, the number of free hydroxyl groups and alcohols containing hydrogen bond decreased, while the number of combined hydroxyl groups and silicon groups increased. Finally, the spectral data of sodium silicate/VTES blend with different molar ratios were corrected by baseline correction,and the two-dimensional correlation spectra based on molar proportion disturbance were calculated by using the software Matlab 6.5. So, the resolution of the near infrared spectrum was improved and the change sequence among different functional groups was analyzed. The results showed that the change of absorption peak at 10 262 cm-1 was prior than that at 8 905 cm-1, the change of absorption peak at 7 026(6 846) cm-1 was later than that at 5 859 cm-1, the change of absorption peak at 5 264(5 176) cm-1 was later than that at 4 397 cm-1, and the change of absorption peak at 4 667 cm-1 was later than that at 4 397 cm-1. The variation order of absorption peak at different wavenumber corresponded to the variation order of functional group assigned to them, which further revealed the reason for the change of functional groups in near infrared spectra. The sol-gel formed by blending two solutions of sodium silicate and VTES is a silicon-polymer with three-dimensional network structure. The polymer has hydrophobic properties and can be widely used. The results will be helpful to understand the hydrolysis and condensation reaction process and molecular structure changes of sodium silicate /VTES blend, and provide reference for further research and application.

The change of chemical structure of coals with different rank is of great significance to the study of macromolecular structure evolution in coal. The chemical structures of Hequ candle coal, Liulin coking coal and Jincheng anthracite coal are characterized by means of fourier transform infrared spectroscopy. From the four parts of the infrared spectrum, each part has undergone certain changes. In the aromatic structure, the Hequ coal has five peaks, and the Liulin coal is reduced to three peaks, and then the Jincheng coal is increased to five peaks. In the oxygen-containing functional group, as the coal rank increases, the peak area of the wave number between 1 100 and 1 350 cm-1 gradually decreases. And peaks tend to be flatter which indicates that coalification is a process of being carbon-rich and deoxidized. In aliphatic hydrocarbons, in the spectrum, the shoulder number of the wave number near 2 952 cm-1 is widened, which shows an increase in the content of methyl groups. The peak shape near the wave number of 2 895 cm-1 gradually slows down, indicating that the content of methine is decreased. In the range of hydrogen bonding, with the increase of coal rank, the spectrum becomes slower and then steeper, and the wave number is more prominent around 3 400 cm-1, indicating that the content of self-associated hydroxyl groups in coal decreases first and then increases. The peak spectrum of the obtained infrared spectrum is fitted and attributed by origin7.5 software. The results show that the substitution of benzene ring is mainly based on tri-substituted, with the deepening of the coal rank, the content of benzene ring tri- or tetra-substituted decreases, and the content of di- and penta-substituted increases; in which the content of the tri-substituted benzene ring is reduced from 63% to 32%, and the content of the benzene ring tetra-substituted is reduced from 17.21% to 12.86%, however, the percentage of di-substituted is from 12.36% to 24.44%, and the percentage of penta-substituted is increased from 6.55% to 26.58%. The ash content in the infrared attribution is higher, and the ash percentage in the industrial analysis is also higher. As the degree of coalification increases, the proportion of the carbon-oxygen single bond decreases from 37.22% to 27.83%. The carbon-carbon double bond content increases from 31.02% to 36.86%, and then decreases to 25.42%, and the carbon-oxygen double bond content changes slightly, from 13.07% to 13.02%, and then increases to 13.81%. In the aliphatic hydrocarbons, with the deepening of the coal rank, the percentage of the methyl symmetric stretching vibration is 11.67%, 11.81% and 12.92% respectively. The percentage of the methyl anti-symmetric stretching vibration is 18.74%, 18.94%, 24.76%, and the methyl content increases. However, the proportion of stretching vibration of methine decreases from 17.38% to 12.53%, and finally decreases to 11.57%. The content of methine decreases. The proportion of methylene symmetric stretching vibration is 18.09%, 18.14% and 15.43% respectively, the proportion of methylene anti-symmetric stretching vibration is 34.41%, 38.58% and 35.32% respectively, and the content of methylene first increases and then decreases. In addition, the hydroxyl-N hydrogen bond is present in the Hequ coal and the Liulin coal, while there is no such hydrogen bond in Jincheng coal, the lower the coal rank, the higher the percentage content, the ring-associated hydrogen bond is reduced from 19.03% to 12.71%, the hydroxyl-ether hydrogen bond is reduced from 27.20% to 16.89%, which is that the content of oxygen-containing functional groups such as carboxylic acid and hydroxyl group in the lower rank coal is higher. The self-associated hydroxyl content decreases from 39.63% to 34.78% and then increases to 37.88%. The content of hydroxy-π hydrogen bond increases from 9.84% to 27.77%. These changes reveal that coalification is a complex evolutionary process of being carbon-rich, dehydrogenation, deoxygenation, and removal of heteroatoms. The research results have reference significance for exploring the evolution characteristics and control mechanism of coal macromolecular structure.

In pulping and papermaking industry, extractives of wood chips influence the impregnation efficiency, pulp energy consumption and pulp yield. But traditional analysis methods for the content of extractives are not applicable for industrial online monitoring because of being time consuming and costly. Therefore, the present study used near infrared (NIR) spectroscopy to predict rapidly extractives content of three species of fast-growing Eucalyptus urophylla×E.grandi chips (DH32-29, DH32-26, DH33-27) grown in China’s Guangxi Province. NIR spectra of 144 fast-growing Eucalyptus were collected using a holographic grating spectrometer equipped with a halogen illumination and array detector. The benzene-alcohol extractives and 1% NaOH extractives content of 144 samples were gravimetrically determined according to the Chinese national standard test method respectively. The near-infrared spectrum were pretreated using smoothing, first derivative, second derivative, vector normalization and multivariate scattering correction in Matlab 8.0, and the models were developed for various pretreatment methods by loading PLS, LASSO, SVR and ANN algorithm. The optimal modeling methods were selected. Genetic algorithm was used to select the bands, which improved the accuracy of the models and optimized the models. In conclusion, in order to develop analysis model of benzene-alcohol extractives, smoothing, MSC and first derivative methods should be used to preprocess the original spectrum, the bands of 1 345.0~1 821.4 and 2 127.8~2 241.3 nm were selected, meanwhile, the partial least squares algorithm was used with the optimal factor 9. The model had the best accuracy for the RMSEP value as low as 0.25%, and the absolute deviation range was -0.39%~0.38%. The optimal bands between 1 345.0~1 821.4 and 2 127.8~2 241.3 nm have been associated with O—H stretching (1st overtone) of phenolic compound (1 410 and 1 447 nm), as well as C—H stretching and CC stretching group frequencies of benzene ring (2 133 nm) and other characteristic absorption. In order to establish the content analysis model of 1% NaOH, smoothing, vector normalization, first derivative should be used to pretreat the original data, the bands between 1 138.2~2 363.0 nm were picked and LASSO was adopted. The model had the best accuracy when the μ value was 12.61, the independent verification show the RMSEP value was 0.37%, and the absolute deviation range was -0.56%~0.53%. The optimal bands between 1 138.2~2 363.0 nm have been associated with C—H stretching (2nd overtone) of COCH3 (1 158 and 1 170 nm), as well as C—H stretching (1st overtone) of —CH3 (1 666, 1 681 and 1 790 nm) and other characteristic absorption. The characteristic absorption of benzene-alcohol extractives and 1% NaOH extractives on the optimal bands was analyzed from the point of view of molecular structure, and the performance of models was explained theoretically. The models can meet the actual demand and can be applied to the analysis of the content of Eucalyptus extractives in pulping and papermaking industry. The results showed that performance of near-infrared models can be developed and optimized by the selection of pretreatment and modeling methods combined with the genetic algorithm for the prediction of Eucalyptus extractives. At the same time, as an emerging algorithm, LASSO algorithm has a good ability to process co-complex linear data in near-infrared spectroscopy, and can establish models with good analysis performance.

In order to effectively simulate the luminescence spectrum of two kinds of phosphor mixed coated white LEDs, the silicate series of green phosphors and high-viscosity series of red phosphors were selected. Fluorescence spectra of green phosphors and red phosphors were measured by the British FLS920P fluorescence spectrometer. The emission peak of green phosphor was 527 nm and the emission peak of red phosphor was 641 nm. Totally, there were 144 samples, which have a concentration ranging from 7% to 17% and a proportion of 3∶1 to 3∶2. The HAAS-2000 high-precision spectroradiometer from Hangzhou Yuanfang Spectrum Co., Ltd. was used to measure the LED luminescence spectrum. Finally, the data were processed to obtain the fitting function. Based on these functions, the spectral equation was constructed. This spectral equation is a systematic method of simulating the concentration and proportion of two phosphors. In order to accurately predict the luminescence spectrum of the two kinds of phosphors mixed and applied to the blue chip, a three-dimensional surface fitting was performed on the data in the experiment, and the relationship between the concentration and proportion of the phosphor and the green correction coefficient and the red correction coefficient was obtained. Applying the obtained functional relationship between the green correction coefficient and the red correction coefficient to the spectral equation, a new method for finally simulating the luminescence spectrum of white LEDs was obtained. Moreover, the simulated spectra of the two groups were compared with the actual experimental spectra, and the results of the two spectra were found to be good. This new method of simulating white LEDs is indeed feasible, and the predicted phosphorescence spectra of the two phosphors coated on the blue chip are more accurate. This method relates the specific phosphor mass ratio and concentration to the luminescence spectrum of the LED, and most previous studies have linked the spectral power distribution to the LED luminescence spectrum, the mass ratio and concentration of the phosphor are not involved, and the specific breakthrough is compared. After the specific spectral equation is established, the final simulated white light spectrum can be directly obtained according to the mass proportion of the two phosphors and the concentration after mixed with the AB glue without the experimental instrument and without the actual experiment. Get rid of the limitations of experimental instruments and other factors. And it provides a new idea for the preparation of white LED with specific spectral characteristics, which has certain practical value.

The rapid detection of 2,4,6-trinitrophenol (TNP) has attracted more and more attention in recent years, due to its powerful explosive hazard and environmental toxicity. In this study, TNP fluorescent probe based on perylene imide was synthesized by one-step synthesis, and the rapid detection of TNP was realized by the fluorescent spectra of the probe. The fluorescence characteristics were investigated, and the fluorescence intensity was high in aqueous solution, stimulated at 493 nm at the emission wavelength of 547 nm. The emission spectra of the fluorescent probe system decreased obviously after the interaction with TNP, which might be due to the fluorescence quenching after the combination of the fluorescent probe and TNP, changing the aggregation state. The fluorescence changes of the probe system after the interaction with TNP could also be observed under the 365 nm handheld ultraviolet lamp, and the results could also be judged by naked eye. In the experiment, different concentrations of TNP solution were tested and the fluorescence spectra analysis showed that TNP had good quenching effect on the fluorescent probe system. The fluorescence intensity of the probe system at 547 nm, I547 value, presented a good linear relationship in the concentration of 20～80 μmol·L-1 with the regression equation of I547=907 521.6-9 955c(R2=0.992 1), and the detection limit was calculated to be 4.55 μmol·L-1. The fluorescence spectra of the probe were stable after 1 minute of interaction with TNP and the response time was short. The fluorescence spectra of the probe were not affected by structure-like interfering compounds, such as phenol (PHE), 2,4-dinitrotoluene (DNT), 2,4,6-trinitrotoluene (TNT), 2,4-dinitrophenol (DNP), 4-nitrophenol (NP) and common anions and cations(Ca2+, K+, Ba2+, Cl-, SO2-4, NO-3). The interference of the dust matrix on fluorescence spectra was also investigated. Simulated explosive dust samples with TNP were made in the laboratory and fluorescence spectra were detected by the fluorescent probe system. The experiment showed that the fluorescence spectra of the probe and the interaction with TNP are not disturbed by dust. The fluorescence emission spectra can be applied to the quantitative analysis of TNP in dust and has good practical application prospects.

Silicoaluminate substrates doped with Dy at different concentrations are synthesized by high temperature solid state method. X-ray diffraction phase analysis shows that one of the main phases is Dy3Al2(AlO4)3. By Raman spectroscopy analysis, the intensity of the Raman peak is at 874.5 cm-1, which is related to the stretching vibration of Dy-［AlO4］. With the increase of Dy doping content, the intensity of Raman peaks increases first and then decreases. The peak at 419.9 cm-1 is related to the bending vibration of Dy-［AlO4］. With the increase of Dy doping content, the intensity of Raman vibration peak, the peaks of fluorescence spectrum measured by fluorescence spectrophotometer and the photoluminescence spectrum measured by Raman spectrophotometer all show the rule of first increasing and then decreasing. The matching amount of Dy-［AlO4］ increases gradually, and when the amount of Dy doping exceeds a certain limit, concentration quenching occurs in the system, which results in the decrease of fluorescence properties. Compared with Tb system, the Raman spectra of the two systems have great similarities and slight differences. The Raman vibration peaks of Tb doped materials are 870.0 and 408.0 cm-1. The fluorescence intensity of two kinds of fluorescent materials doped with different elements are consistent, which indicates that the matching amount of rare earth elements with Al (Si) oxygen tetrahedron is the key factor to determine the fluorescence properties of the materials.

Based on the fluorescence enhancement effect of Zn2+ on bilirubin (BR), this work proposes a new method for the detection of Zn2+ concentration, and a systematically investigation of BR as a Zn2+ probe by using ultraviolet-visible light absorption and steady-state fluorescence spectroscopy has been conducted. Compared with the general single-wavelength fluorescence intensity method, this new detection method eliminates the impacts of the non-target effects of factors such as concentration variation of BR and the excitation light intensity, etc., and achieves a more accurate measurement capability in Zn2+ detection. Especially, for the first time we adopt the BR fluorescence intensities ratio at the emission wavelengths 663 and 600 nm, and investigate the dependence between this ratio and the Zn2+ concentration in the range from 0 to 90 μmol·L-1. The recognition behavior of BR probe to Zn2+ indicates that the BR fluorescence intensity ratio I663 nm/I600 nm increases linearly with the Zn2+ concentration in the range of 0~20 μmol·L-1. In particular, in the range 0~10 μmol·L-1 of Zn2+ concentration, the linear correlation coefficient r is 0.999 87, which demonstrates the linear dependence, and the detection limit is 0.1 μmol·L-1. In the Zn2+ concentration range from 20 to 90 μmol·L-1, the probe BR fluorescence intensity ratio is saturated. Accordingly, there is a positive prospect of BR fluorescence in the real-time human body Zn2+ detection.

Berberine (BBR) is widely used and of significant importance in medical field, and its quantitative analysis is of great value in guiding clinical treatment. There still be some shortcomings remaining in the determination of berberine by traditional methods, such as less sensitivity, narrow response range, or high testing cost. In this study, we found that hematoporphyrin monomethyl ether (HMME) with negative groups had a high fluorescence quenching effect on Tetra (trimethylammonia) aluminum phthalocyanine (TTMAAlPc), a cationic phthalocyanine compound emitting strong red fluorescence, due to the formation of an almost non-fluorescent ion associate. Interestingly, it was found that the fluorescence of TTMAAlPc-HMME associate re-emitted in the presence of berberine. The recovery of fluorescence of TTMAAlPc was positively correlated with the concentration of berberine. The mechanism of the above-mentioned phenomena was discussed. We believed that the high-efficiency fluorescence quenching effect of HMME on TTMAAlPc can be attributed to the formation of associate consisting of hematoporphyrin monomethyl ether and the cationic aluminium phthalocyanine (HMME-TTMAAlPc) through supramolecular interactions including planar hydrophobic interaction, π-bond stacking, electrostatic interaction and hydrogen bonding mediated by water molecules. The fluorescence recovery was due to the strong competitive binding to release the cationic aluminum phthalocyanine from the associate by berberine with a molecular structure matches TTMAAlPc. A new fluorescence-enhanced quantitative analysis method for berberine was established based on the above-findings. The factors including pH, sorts of buffer, reaction temperature, usages of HMME and TTMAAlPc and reaction time that affected the determination were investigated. Under the optimum conditions, the equation of calibration curve was If=12.85c+66.30 with a correlation coefficient (R) of 0.997 2, the linear range was 0.3~69.0 mg·L-1, and the detection limit was 0.01~5.0 mg·L-1. The study indicated that this method bears the merits of strong specificity, simple operation and low cost. The established method has been applied to the determination of practical samples with satisfactory results. This study not only presents a new strategy for the construction of phthalocyanine-based optical probes, but also opens up the application of red-emitting phthalocyanines in the field of drug analysis.

Organic pollutants are the main source of water pollution. The degree of organic pollution in water bodies can be comprehensively reflected by chemical oxygen demand (COD) indicator. Compared with the traditional methods, which are highly time-consuming and cause secondary pollution, remote sensing techniques can detect water COD quickly and effectively, particularly over large areas. However, due to complex composition of COD, detecting water CODusing remote sensing technology is still insufficient, and the spectral response mechanism of COD in the visible-short-wave infrared range is not yet clear. To clarify the spectral response mechanism of water COD, the reflectance spectra of 45 different concentrations of COD standard solution (potassium hydrogen phthalate) were measured by using PSR hyperspectral instrument in the laboratory simulation environment in this study. The continuum removal and reflectance normalization methods were used to analyze the spectral characteristics of COD standard solution with different concentrations, and results showed that with the increasing of COD concentration, the water reflectance spectra increased gradually in the visible-short-wave infrared range, as well as the spectral response increased rapidly in the range of 540～580 and 1 000～1 060 nm, showing the three-stage frequency doubling of —OH stretching vibration and the combined frequency absorption characteristics of —CH stretching vibration and deformation vibration. In order to further verify the effectiveness of sensitive bands, the partial least squares (PLS) regression models were developed by using sensitive bands and full bands, respectively. The correlation coefficient and RMSE of COD standard solution based on the sensitive bands were 0.972 and 39.629 mg·L-1, respectively, while the correlation coefficient and RMSE based on full bands were 0.961 and 46.639 mg·L-1, respectively. It showed that for COD standard solution that is not interfered byexternal factors, high accuracy can be achieved with only a small number of sensitive bands, even higher than the full bands model. The model retrieval accuracy based on the sensitive bands was also significantly better than the accuracy based on full bands when the model are applied to the field-measured water spectra. The results suggested that using the 540～580 and 1 000～1 060 nm sensitive bands can effectively improve the accuracy of detecting water COD, and significantly advance our ability for large-area rapid monitoring of COD using remote sensing in practical cases.

Malachite green (MG), one of the toxic triphenylmethane chemicals, has been used worldwide in aquaculture because of its low cost and high efficacy in bacteriostasis. However, the residue of MG may cause carcinogenic, teratogenic and mutagenic effects. Traditional methods for MG detection are relatively complex, which require complicated operations of pretreatment, take a lot of time -, and need expensive instruments. Thus a rapid and simple detection method needs to be developed. Aptamers are the functional single stranded DNA or RNA molecules which have high-affinity and specificity in binding capabilities towards a vast range of targets. Therefore, aptamers have been widely applied as recognition elements for biosensor in recent years. Gold nanoparticles (AuNPs) with high extinction coefficient and surface plasmon resonance have been used in colorimetric detection systems. In this work, a facile colorimetric aptasensor for highly sensitive detection of MG based on aptamer and AuNPs was developed. In the absence of salt, AuNPs agglomerated in salt with the absorption peak of UV-vis spectrum shifted from 520 nm to 690 nm, and the solution color changed from red to blue. However, the complexation of RNA aptamer with AuNPs prevented the nanoparticles from aggregation in a high-salt solution because of the electrostatic interaction between RNA aptamer and AuNPs. In the presence of MG, RNA aptamer could specifically bind with MG, causing AuNPs aggregation with blue in color in salt. With the increases of MG concentrations, the values of A520 decreased and the values of A690 increased, and the color of the solution gradually changed from red to blue. Taking advantage of this sensing technique, MG could be detected by naked eyes or UV-Vis spectroscopy within one hour. The differences of A690/A520 with and without MG in the detection systems were used as the detection signals. The results showed that the linear range of MG was 0.6 to 12.5 μmol·L-1 at the optimum conditions of 0.2 mol·L-1 NaCl, 10 μmol·L-1 RNA and 7 nmol·L-1 AuNPs. A linear equation of Δ(A690/A520)=0.06C-0.01 was obtained with a correlation coefficient (R2) of 0.993. The detection limit was 0.04 μmol·L-1 (3α/κ, n=9). The method had good selectivity for MG detection. Furthermore, the developed method was successfully applied to the detection of MG in aquaculture water with excellent accuracies. The results indicated that the developed method has significant potentials for trace MG detection in real samples.

With the goal of climate change prediction and disaster weather prevention, high accurate spectral radiance calibration is required in earth observation. Array spectroradiometers have problems such as internal structural defects and unsatisfactory optical components, resulting in stray lights, which seriously affect the spectral radiance measurements. In this paper, the stray lights of various typical array spectroradiometers were measured. The different spectrums of solar radiance and the laboratory calibration lamp were analyzed. Ultraviolet stray light correction methods were studies by using bandpass filters and tunable lasers, respectively. First, bandpass filters with specific transmittances were used to measure ultraviolet stray light signals. The mathematical correction model was established to realize the efficient evaluation and simple correction. The ultraviolet stray light of the solar radiance in ground-based verification site was obviously reduced by using this method. For the continuously distributed wide-spectrum light sources, the correction method with bandpass filter is of simple experimental conditions and efficient work process. However, it is difficult to complete the high accurate stray light correction for the discontinuous distribution or narrow-band light source. Therefore, the stray light measurement system based on tunable laser was established, which can measure the stray light line-spread function of each pixel by changing the output wavelength of the tunable laser, and then the stray light correction results of each pixel are calculated by MATLAB matrix operations. The correction method was verified by different types of array spectroradiometers. For measuring the non-continuously distributed narrow-band source, the stray light signal was reduced by an order of magnitude, and the inter-reflection peaks beside the light source were significantly eliminated. Here, two stray light correction methods with complementary advantages were established for different spectral distribution light sources, which effectively decreased the deviation of the UV measurement results of array spectroradiometers, further ensuring the accuracy of Chinese earth observation data.

To improve real-time performance of fiber distributed sensing based on Brillouin scattering, and at the same time, ensure high measurement accuracy, the topic about Brillouin frequency shift extraction with high accuracy and less computational burden is investigated. The computer programs about Brillouin frequency shift extraction algorithms are based on quadratic polynomial fit and typical Lorentz, Gaussian, pseudo-Voigt and Voigt models are written. Brillouin spectra in a single-mode fiber are measured by the BOTDR (Brillouin Optical Time Domain Reflectometry). The Brillouin frequency shift about these spectra is extracted by the above algorithms. The results reveal that the computational burden of the algorithm based on quadratic polynomial fit is much less than those of the typical algorithms. Its computation time is only 1.15%, 1.80%, 1.51% and 0.51% of those of the typical algorithms. However, its error is much larger than that of the typical algorithms which will obstruct its application. The above results are consistent with the results of the corresponding numerically generated Brillouin spectra. To improve the accuracy in the quadratic polynomial fit algorithm, the influences of frequency sweep span, number of frequency sweep, signal to noise ratio (SNR), linewidth and deviation of frequency sweep span on the error in the extracted Brillouin frequency shift. The results reveal that if the number of frequency sweep is fixed, the error initially decreases with increasing frequency scanning range. Once the minimum error is reached, it may do the very opposite. The optimal frequency scanning scope equals to linewidth. The error varies as a power of the number of frequency sweep. The error also reduces exponentially with SNR (dB). The error is proportional to linewidth. The error increases with increasing deviation of frequency sweep span. Therefore, the spectra used for Brillouin frequency shift extraction should be symmetric about Brillouin frequency shift. According to the above results, a modified Brillouin frequency shift extraction algorithms based on quadratic polynomial fit is proposed. The algorithm selects Brillouin spectra with one linewidth and symmetric about maximum Brillouin gain and used to extract Brillouin frequency shift. The proposed algorithm can considerably decrease computation time relative to the typical algorithm, and at the same time, the accuracy is similar to that of the typical algorithms. The proposed algorithm is validated by the measured spectra and numerically generated spectra. The proposed algorithm not only can significantly improve real-time performance of fiber distributed sensing based on Brillouin scattering.

With the intensification of human activities, refractory organic compounds have become one of the groundwater pollutants. groundwater is a nutrient-poor and anaerobic environment, which will aggravate the long-term risk of refractory organic matter. Therefore, the remediation of groundwater contaminated by 2,4-dinitrotoluene has been a difficult and hot issue in the field of environment. Currently, Fe0 activated persulfate technology is widely used to repair 2,4-DNT in groundwater. In order to identify the degradation process, mass spectrometry is generally used to identify the intermediate products and degradation products of oxidative degradation and the order of formation. However, it is unable to effectively identify the change order of organic functional groups in the process of oxidative degradation. Therefore, three-dimensional excitation emission matrix fluorescence spectroscopy (3D-EEM), Fourier transform infrared spectroscopy (FTIR), and two-dimensional correlation analysis were applied to investigate the composition of products and the variation of functional groups over time in the persulfate oxidation system. The results showed that 2,4-dinitrotoluene showed no fluorescence peak, but its products with fluorescence groups were generated. As the benzene ring broken down in the reaction, the unsaturated fatty acids might generated. With the increase of reaction time, the products with the structure of fulvic acid degraded continuously, while the products with the structure of humic-like degraded gradually in the later stage. The proportion of zone II and IV increased, which was mainly due to the increasing content of 2,4-diaminotoluene in the products. Infrared absorption peaks were mainly 3 334, 2 844, 2 954, 2 357, 2 126, 1 643, 1 410, 1 110 and 700 cm-1. The functional groups of the products were mainly amino, methylene, carboxyl, phenol hydroxyl and olefin methyl. But the difference of infrared absorption peak was not significantly with time. Two-dimensional correlation analysis was performed on FTIR during the time change process. Four auto-peaks were observed at the λ1/λ2 wavelength pairs of 3 334/3 334, 1 643/1 643, 1 015/1 015 and 700/700 in the synchronous map, and there were six positively correlated cross peaks at 1 643/3 334, 1 015/3 334, 700/3 334, 1 015/1 634, 700/1 634 and 700/1 015, all of which were positive, and the change direction of spectral band strength was consistent. The above four functional groups generated over time in the system, and the transformation/degradation was synchronous. Only cross-peaks were detected in the asynchronous maps. The asynchronous spectrum had 5 negative correlation cross peaks and 1 positive correlation peak at the same position in the synchronous spectrum. The spectral features could lead to an interpretation of the changes in the following sequence: 3 334＞1 634＞1 015＞700. Therefore, with the increase of time, the order of groups in the 2,4-DNT degradation systemwas amino>carboxyl>olefin>phenolic hydroxyl. The above indicated that in the degradation process, the nitro group on the benzene ring was firstly converted to —NH2, and then the methyl group on the benzene ring was oxidized to —COOH. The phenolic hydroxyl group and olefin should be the carbon chain transformation after the destruction of the benzene ring structure. The results were important to understand persulfate oxidized organic matter.

Based on the theory of mode interference and the sensing characteristics of fiber Bragg grating, a combined sensor composed of a single modefiber (SMF)-few mode fiber Bragg grating (FBG)-SMF structure is proposed. The SFS structure interferometer is constructed by fusing a certain length of few mode fiber (FMF)between two SMFs with afiber fusionsplicer, and then FBG is etched on FMF. The transmission spectrum is obtained by the optical spectrum analyzer after the interaction of mode interference and coupling. Firstly, the sensing principle is analyzed. Since the change of environment will cause the effective refractive indexchange of the core mode in FMF, which will cause the wavelength shift of interference spectrum and FBG, the measured parameters can be realized by detecting the wavelength shift of transmission spectrum. Then the effects of FMF length on interference spectrum are simulated. The longer FMF is, the more obvious the interference spectrum is and the smaller the free spectrum range is. In order to observe the transmission spectrum of the combined sensor, the length of FMF is chosen as 110 mm for sensing experiment. FMF can stably transmit four modes with LP01, LP11, LP21 and LP02. By comparing and analyzing the interference and coupling between different modes, it is determined that the interference spectrum is formed by LP01-LP11, and the transmission spectrum of FBG is formed by LP02-LP02, LP11-LP11, LP01-LP02 and LP01-LP01. Finally, the temperature and refractive index sensing experiments are carried out. The results show that the interference spectrum of SFS structure appears obvious blue shift and the transmission spectrum of FBG appears red shift with the increase of temperature. Their temperature response sensitivities are -62.04 and 10.87 pm·℃-1 respectively with good linearity. When the cladding of FMF is corroded to 22 μm, there is no obvious shift phenomenon in the transmission spectrum within therange of 1.366~1.455 andthe maximum sensitivity is only 3.933 nm·RIU-1. The interference peak and transmission peak are used to monitor the environment changes at the same time, which improves the detection accuracy and reduces the accidental errors. The structure has the advantages of novel structure, high sensitivity, easy preparation, and the four resonance peaks of FBG have strong sensing consistency, which makes the sensing more flexible and convenient.

Activated carbon with developed porous structure and abundant specific surface area was prepared from wood, bamboo and other biological resources, which has the problems of high production cost, being unfavorable to the sustainable development of ecological environment, short service life and being easy to cause secondary pollution of indoor environment after failure. Metallurgical solid waste and biomass waste as a major by-product of industrial production and agricultural production, their use is difficult to achieve, with low added value and high cost, leading to the fact that a large number of metallurgical solid waste and biomass waste cannot be disposed in direct stacking and landfill, causing not only the pollution of ecological environment, but also a great waste of potential resources. In the face of the above problems, the development of low price and superior performance of ecological activated carbon with metallurgical solid waste and biomass waste has become not only one of main methods to achieve the high value-added utilization of metallurgical solid waste and biomass waste and the sustainable development of resources, but also one of main methods to achieve the great reduction of the production cost of modified activated carbon and improve economic benefits. In this paper, walnut shell and electric furnace slag were studied firstly, ecological activated carbon for formaldehyde degradation was prepared by metal oxides contained in the electric furnace slag modified to treat the biomass waste, and performance of ecological activated carbon was tested by referring to Indoor decorating and refurbishing materials-Limit of formaldehyde emission of wood-based panels and finishing products (GB18580—2017). Element content was characterized and analyzed by X-ray photoelectron spectroscopy (XPS), chemical component was characterized and analyzed by X-ray fluorescence spectrometer (XRF), composition structure was characterized and analyzed by fourier transform infrared spectrometer (FTIR), mineral composition was characterized and analyzed by X-ray diffractometer (XRD), microstructure was characterized and analyzed by scanning electron microscope (SEM), particle size distribution was characterized and analyzed by laser particle analyzer (LPSA) and pore structure was characterized and analyzed by specific surface area and pore size distribution analyzer (BET), so as to reveal the mechanism of preparing ecological activated carbon from walnut shell and electric furnace slag, and the degradation mechanism of formaldehyde by ecological activated carbon. The results showed that ecological activated carbon with good degradation performance of formaldehyde is prepared by walnut shell ultrafine powder and electric furnace slag ultrafine powder, not only realizing the high value-added utilization of metallurgical solid waste and biomass waste, but also putting forward the new indoor air formaldehyde management concept of “treating danger by waste”. Electric furnace slag ultrafine powder is well wrapped in the layered structure of ecological activated carbon, to promote the pulverization rate of ecological activated carbon and forming particles with small particle size can improve the degradation area of ecological activated carbon and formaldehyde. Fe element, Mn element and Ti element are contained in electric furnace slag ultrafine powder; the magnetic property of Fe element induces the formation and enrichment of large amounts of formaldehyde on the pore structure surface of biomass activated carbon, and Mn element and Ti element catalyze the degradation of the enriched formaldehyde, realizing the synergistic effect of adsorption degradation and catalytic degradation.

As a new detection method, near infrared spectroscopy (NIR) has been applied to the rapid compositional analysis of cement raw meal. However, environmental factors such as humidity may have a potential impact on its detection. In order to improve the accuracy of the detection, we studied compensation method based on the impact of humidity upon near infrared spectroscopy of cement raw meal. Twenty four cement raw meal samples were obtained from cement factories. Eighteen of them were used as the calibration set; six of them were used as the validation set. The effective ingredients in cement raw meal were SiO2, Al2O3, Fe2O3, and CaCO3. The standard value of the contents of each ingredient was measured by X-ray fluorescence analysis. Firstly, eighteen samples of calibration set were repeatly measured five times, and ninety spectra were obtained, which were used to establish model Ⅰ. Then five humidity gradients were made for eighteen samples of calibration set. The process to generate the humidity gradient sample was as follows: first, the samples were placed on an electric heating platform, flattened with glass rod and heated at 180 ℃ for 30 minutes, then the samples were placed on the radiation fin to cool. When the sample restored to room temperature, they were taken out and a spectrum was obtained. The samples were placed in the agitator, sprayed with deionized water for two times, and then stirred for 30 seconds to be mixed evenly. After that, the mixed sample was measured to get the next spectrum. Five spectra with certain humidity gradients were obtained by repeating the process. The humidity of all samples was measured by drying method. The range of humidity change was within 0.6%～2%. Each sample with certain humidity was measured once, and these ninety spectra were used to establish the model Ⅱ. Then, five humidity gradients were made for the validation set in the same way as the calibration set. Thirty spectra were obtained by detecting each humidity gradient sample in the validation set. All spectra were pre-processed by multivariate scattering correction, and the fitting band was 4 000～5 000 cm-1. Partial least squares method was used for modeling. Comparing the five humidity gradients of the same sample, we could see that the spectra have the greatest differences at 5 200 cm-1, and there were also obvious differences at other locations, so the humidity change has a significant impact on the whole spectrum. Finally, the root mean square error of prediction (RMSEP) of the 30 spectra in model Ⅰ and model Ⅱ were compared. The RMSEP of SiO2, AlO3, Fe2O3 and CaCO3 in model Ⅱ was reduced by 25%, 31.3%, 33.3% and 25% compared with model Ⅰ. The experimental results show that the humidity of cement raw meal sample has a certain influence on the prediction results of near infrared spectroscopy model. Modeling with humidity gradient samples can effectively reduce the influence of humidity on the prediction results.

Studying the gene control pattern of interested traits after control pollination is one of the key fields in exploring the law of gene recombination in eucalypt improvement. The accuracy of conventional quantitative analysis for that is often low, and the DNA analysis for that has high professional requirements, and is time consuming and laborious commonly. The aim of the current study is to study the relationship among different genotypes of hybrids, parents, hybrids and their parents in eucalypt based on the near infrared spectroscopy (NIRs) of foliage, and to discuss the practicability and the accuracy of the NIRs discriminant model for the classifying of eucalypt hybrids and their parents. The genetical materials in the study contained three eucalypt parents and their F1 progenies by control pollination. Fresh and healthy leaves from middle to upper crowns in a tree from their field testing trials were collected, and 10 individuals were chosen per genotype. The handheld portable near infrared spectrometer Phazir Px (1624) was used to scan the NIRs of foliage collected. 10 healthy current-year leaves were chosen per individual tree, five scans for NIRs from each side of the middle part of the frontal vein of the leaves were taken, calculated the average of 50 scans as the NIRs data of a leaf, thus 10 NIRs were got for every genotype in totally. The transform of S.G first derivative with second order polynomial fit was performed for the raw NIRs in present study. The successive multivariate analysis was conducted after NIRs pretreatment. To demonstrate the classification of different genotypes by the principal component analysis (PCA) with the NIRs data of hybrids and the patents in eucalypt. Then, two supervised discriminant models, soft independent modeling of class analogy (SIMCA) and partial least squares-discriminant analysis (PLS-DA) pattern recognition, were used to test the accuracy of NIRs model in the classifying for eucalypt hybrids and their cross parents. The scores plot of PC1 and PC2 in PCA demonstrated strong groups among different genotypes, such as cross parents, hybrids, and between hybrids and their parents. The sample distance to parents PCA model in the SIMCA analysis showed that the hybrids to be distinguished can form a clear group differentiated with their parents, and demonstrated the genetic similarity between parents and their progenies directly. The PLS-DA pattern recognition analysis indicated that the hybrids can be discriminated with cross parents by the response values of hybrids predicted by the parents PLS model. All the findings in present study showed that NIRs information of eucalypt leave truly reflects the transmission of genetic information occurring in the process of control pollination, and different genotypes including hybrids and their parents can be discriminated accurately by NIRs models, suggesting that NIRs can be used not only for qualitative identification between eucalypt hybrids and the cross parents, but also for assessing the extent of additive genetic effects in gene recombination, which can provide theoretical reference for the genetic basis analysis and breeding improvement in eucalypt.

Rice height, an important index of rice growth monitoring, is a comprehensive reflection of rice itself, soil, hydrology and meteorology. So accurate, efficient, and large-scale inversion of rice crop height can provide reliable basis for rice identification, phenological monitoring, pest and yield estimation. Synthetic Aperture Radar (SAR), because of its all-weather day-night imaging capability, has been proven to be one of the important means for inversion of rice height. Based on polarimetric SARinterferometry (PolInSAR), the inversion algorithm of scattering model has the characteristics of support of rigorous physical model and high inversion accuracy, which has become a hot spot of inversion of vegetation height. In this paper, based on PolInSAR technology, a new method based on Random Volume over Ground (RVoG) model for rice height inversion was proposed. The inversion experiment of rice height was carried out using the TanDEM-X PolInSAR data of 9 time phases in the rice growing season of 2015. First of all, 8 complex coherence coefficients were obtained based on PolInSAR data in each phase. and these were used for a product of decorrelation under the consideration of satellite dual-station mode. Then, the RVoG model was established for the characteristics of paddy fields. Moreover, using this model, an iterative algorithm of rice height inversion was constructed. Finally, the rice height inversion and precision evaluation using TanDEM-X data of 9 time phases were carried out. The results showedthat when rice height was higher than 0.4 m, a coefficient of determination (R2) of was 0.86 and RMSE was 6.69 cm. When rice height was low (rice height was less than 40 cm), inversion resultswith inversion error of 0.1～0.8 m were significantly overestimated. Through analysis, on the premise that TanDEM X data reflect volume scattering of rice plants well, the inversion algorithm of rice height based on RVOG model can invert the rice height between 0.33～1.2 m with high precision.

Ammonia volatilization is an important path of nitrogen loss from farmland into the environment, and is also the main factor of PM2.5 formation, which has serial disadvantageous effect on the ecological environment and agricultural production. Previously, most of the traditional methods for ammonia emission measurement collected atmospheric ammonia by an acid absorbent. However, these techniques were labor intensive, making it difficult to determine diurnal variation of ammonia volatilization. The open-path tunable diode laser absorption spectroscopy is a reliable tool with high precision, high selectivity, and fast response time for continuous and nonintrusive monitoring of ammonia concentrations over distances from tens to hundreds of meters under field conditions. Currently, the combination of tunable diode laser absorption spectroscopy and micrometeorological backward Lagrangian stochastic diffusion model (TDLAS-BLS) has become a popular technique in the measurement of ammonia volatilization in the field. The objectives of the study are first, to compare TDLAS-BLS technique with the micrometeorological integrated horizontal flux method for its accuracy and applicability for quantitatively measuring ammonia emission from large area of farmland through field experiments. Second, determine the dynamics of ammonia volatilization via high-temporal resolution data and identify the factors that govern ammonia volatilization from urea applied to winter wheat. The results indicated that the estimates made by TDLAS-BLS method were statistically equivalent to those made by the IHF method (regression gradient=0.97, R2=0.97, n=14). The ammonia emission rates and total ammonia loss estimated by the TDLAS-BLS technique were only 3% and 6% lower than those from the IHF method, respectively. This implied that TDLAS-BLS technique can be used to quantitatively estimate ammonia emission from large area of farmland during topdressing period of winter wheat with acceptable accuracy. Ammonia concentration was higher in daytime than in the night at topdressing stage of winter wheat, due to wind speed fluctuation causing it to fluctuate greatly. Ammonia volatilization rate increased slowly after fertilization, and reached a maximum value at the sixth day after fertilization and then decreased gradually after 15 days. This was mainly concentrated in the 5～8 days after fertilization, and accounted for 69% of the total during the overall monitoring period. During this period, the total loss determined by TDLAS-BLS method was 8.8 kg N·ha-1 (6.3% of the total applied N). The lower loss was related due to furrow application of urea and low temperature. This demonstrated the ability of the TDLAS-BLS method to characterize the diurnal patterns of ammonia emission and the environmental influences on ammonia emission from cropland via high-temporal resolution data. Ammonia volatilization showed large diurnal variability during the daytime, which was coincident with temperature, wind speed and solar radiation. Wind speed, solar radiation, soil temperature and precipitation are significantly correlated with ammonia volatilization. Meteorological factor (such as precipitation) are the main factors influencing ammonia volatilization in abnormal weather.

Fast and nondestructive monitoring of leaf water content (LWC) is critical to crop drought diagnosis and irrigation decision. In order to quantify and predict the LWC with hyperspectral remote sensing data, field experiments of winter wheat with different water-deficit stress levels were conducted for two consecutive years (2016—2017 and 2017—2018). Hyperspectral reflectance was recorded at four growth stages. Then, normalized difference spectral index (NDSI) and ratio spectral index (RSI) were calculated in all possible combinations within 350-2500 nm, and their correlations with LWC were quantified to identify the best indices. Spectral data were also used to build partial least squares regression (PLSR) and competitive adaptive reweighted sampling- partial least squares regression (CARS-PLSR) model to calculate LWC. Two different data forms (original and first derivative reflectance) and two different observation scales (leaf and canopy) were used to explore the suitability of these three algorithms on estimating LWC for winter wheat. Additionally, in order to avoid sampling uncertainty when constructing calibration and validation datasets, a method of increasing the number of sampling times was proposed to improve the robustness of prediction models. The results showed that the best spectral indices for estimating LWC of winter wheat were NDSI (R1 162, R1 321) and RSI（R1 162, R1 321） with R2 of 0.871 and 0.872 respectively, which were both based on original leaf reflectance. RSI models had higher estimation accuracy than NDSI models under the same situation. The PLSR model based on original leaf reflectance obtained the best performance for predicting LWC with R2 of 0.953. CARS-PLSR based on the first derivative leaf reflectance was the most accurate model (R2=0.969; RMSE=0.164; RRMSE=6%). It was indicated that in terms of different forms of hyperspectral data, the original spectral-based models were better than the first derivative spectral-based models in two-band vegetation index and PLSR models, but the results were reversed for the CARS-PLSR model. While for different observation scales, LWC had stronger correlations with leaf reflectance-based models than that of the canopy based models. Overall, CARS-PLSR delivered better performance than the other two methods. In light of this, CARS was a feasible band selection algorithm and the prediction accuracy of CARS-PLSR model for LWC estimation of winter wheat was better than that of the other two models. CARS-PLSR method provides a promising approach for accurate and rapid monitoring of winter wheat drought.

The continuous time series of Leaf Area Index (LAI) can reflect the growth of winter wheat, and the prediction of future LAI is important for guiding agricultural production. The crop growth models, such as the World Food Studies (WOFOST), can predict the future LAI by simulating the growth and development of winter wheat. But the simulation depends on numerous input parameters, such as future meteorological data, which is difficult to obtain. Due to the continuity and regularity of LAI variations of winter wheat, the future LAI can be predicted with historical LAI through deep learning methods. However, deep learning methods require a large number of samples with labels to build training dataset. The scarcity of training dataset limits the application of deep learning methods in practice. To solve the above problems, we used data assimilation framework to combine remote sensing data with WOFOST model and constructed 15-year time series dataset of winter wheat LAI in Hebei province. Shuffled Complex Evolution (SCE) algorithm was applied to minimize difference between corrected MODIS LAI and simulated LAI for optimizing initial parameters of WOFOST. Based on the dataset, multiple LAI prediction models with different input lengths of historical LAI were established by using the Long Short-Term Memory (LSTM). The abilities of different prediction models to delineate LAI variations of winter wheat were evaluated. Results showed that the LSTM-based models can predict the future LAI of winter wheat effectively. The prediction model with an input length of 20 days achieved the highest accuracy. and RMSE of the prediction model were 0.986 5 and 0.183 6 after winter wheat returned green. For different stages of winter wheat growth, the accuracy was higher before winter wheat bloomed and reduced slightly after winter wheat bloomed. Therefore, it could be concluded that the method of constructing training dataset proposed in this study could be a reference for the application of deep learning methods in similar problems. The prediction models built in this study also verified the effectiveness of the LSTM, which provided a helpful way for predicting the future LAI of crops.

Hyperspectral images of rice from northeast/non-northeast regions were collected, and spectral images at characteristic wavelengths were screened. The clustering combination of image features and pattern recognition method was established to quickly and accurately identify northeast/non-northeast rice origin. Northeast rice is mainly japonica rice, and the typical northeastern rice varieties include long-grain, round-grain, rice flower and Xiaoding rice. Considering the practicability and applicability of rice origin identification model, samples of 10 origins and 4 varieties above were collected to form the original sample set. Among them, there are five northeastern origins, including Heilongjiang (1), Jilin (2), Liaoning (2), and five non-northeastern origins, including Hebei (1), Zhejiang (1), Jiangsu (2) and Anhui (1). 100 samples were selected randomly from each producing area. Hyperspectral images of 100×10 rice samples were collected using SisuCHEMA hyperspectral imaging system （Specim, Finland）in the range of 900～1 700 nm. Extracting the average spectra of a single rice sample by selecting the region of interest according to the rice contour, Kennard-Stone method was used to divide training set and test set according to the ratio of 4∶1. Eight characteristic wavelengths were screened by Successive Projections Algorithm（SPA）: 1 460.30, 1 400.20, 1 424.92, 945.98, 1 315.62, 1 220.87, 1 705.91, 942.53 nm. The eight models were built respectively by HOG features extracted from single characteristic wavelength Image and SVM to identify the rice origin whether it was from northeast or non-northeast China. The recognition accuracy was as follows: 85.5%, 77.5%, 76.5%, 73.5%, 71%, 68.5%, 67%, 65.5%. In view of the low recognition rate of single model, a strategy of establishing model cluster based on single characteristic wavelength image model to synthetically discriminate rice origin was proposed. According to the recognition rate of single model from high to low, the cluster models were established by respectively combining three, five and seven the signal models above. While the probability of the sample judged to be true predicted by the conjunctive model is greater than 50%, the sample will be judged to be true, otherwise it will be false. The experimental results showed that the recognition rate of the test set samples can reach 90.5% by combining the model sets of 1 460.30, 1 400.20, 1 424.92, 945.98, 1 315.62, 1 220.87 and 1 705.91 nm bands. This study shows that hyperspectral technology combined with the strategy of conjunctive model consensus can provide feasible and effective methods to establish a robust and wide applicability model to recognize the rice origin (northeast/non-northeast) rapidly.

In this study, beef variety was identified by hyperspectral imaging technology which contains abundant spectral and spatial information in an object. Firstly, hyperspectral images of beef samples in the visible and near infrared (400-1000 nm) regions were acquired by the hyperspectral imaging system which contain 252 samples of five varieties of Angus, Limuzan, Qinchuan, Simmental, and Holstein cows. The binary mask image was successfully determined with a certain threshold from ENVI, and ROI (Region of Interest) of beefsample was determined by using the binary mask image. The visual distribution map of reflectance index in beef sample was plotted by pseudo-color map. Samples were dividedby using KS method, which is to improve the prediction performance of the model; The spectral pretreatment method wasutilized, such as SG, Area normalize, Bseline, FD, SNV, MSC and so on; Feature wavelengths were extracted by using competitive adaptive weighting algorithm (CARS). The color characteristics were represented by used color moment for different beef sample images; Principal component analysis was performed on the original hyperspectral image. The image textural information was described by extracting main texture features by the gray level co-occurrence matrix (GLCM) algorithm of the beef sample. Then spectral data from CARS, color feature and texture feature (from three principle component images) were utilized to develop different partial least squares discrimination (PLS-DA)models to identify beef samples respectively. The samples were divided into calibration set and prediction set by KS method, and calibration samples was 190, and prediction samples was 62; The spectral pretreatment was studied by the 7 methods. The results showed that the model effect of FD methods pretreatment was the best; A total of 22 characteristic wavelengths were extracted by the CARS method for spectral data using FD method; A total of 9 color features were extracted by color moments, and the GLCM algorithm was used to extract 48 texture features of each beef sample. Fusion models of spectral data, color feature, texture feature were established to identify beef samples. The results showed that, the model based on spectral data combined texture feature was the best with the correction set and prediction set recognition rate of 98.42% and 93.55%, respectively, which were higher than the recognition rate of feature spectral data. The texture feature made the expression of classification information more comprehensive. The recognition rate of the model correction set was increased by increasing color features, but the recognition rate of the prediction set was relatively poor. This meant the color features had some valid information, but the correlation between color features and the beef sample was not well, so the recognition rate of prediction set was reduced. Therefore, it is an important way to find color features that are more relevant to beef samples which could improve the recognition rate of models. This study provided valuable information for rapid destructive beef samples.

Near-infrared spectroscopy (NIR) analysis is considered as a promising chemical analysis technique because its advantages of convenient-testing, no damaging and fast response. However, due to the many unknown factors in the band distribution and structural analysis of the near-infrared spectrum, there are many difficulties in extracting the characteristic spectral information. Nowadays, although a variety of spectral data dimensionality reduction methods have been widely used, the traditional data dimensionality reduction methods have a limitation that the dimensionality reduction is restricted in one dataset. The results of data dimensionality reduction are often not ideal when there are many factors in dataset . This problem makes the data establish dimensionality reduction model extremely hard in near-infrared spectrum. Comparative Principal Component Analysis (cPCA) is an improved algorithm based on principal component analysis (PCA), which originated from Comparative Learning and applied to genomic information analysis. The advantage of the cPCA algorithm is that it can realize the dimensionality reduction between two related data sets. In this paper, the cPCA algorithm is applied to near-infrared spectroscopy for the first time and establish an accurate spectral dimensionality reduction model. In the experimental, we used the cPCA algorithm to analyze the surface of different types of fruits (apples and pears) with pesticide residues and without pesticide residues . The result showed that the PCA algorithm just distinguishes different fruit types, while the cPCA algorithm classifies the fruits with or without pesticides due to the constraint of the background dataset. This showed that cPCA outperforms in data dimensionality reduction of near-infrared spectra. It solves the problem of dataset limitation and feature information extraction in the near-infrared spectral data dimensionality, and cPCA could establish an accurate spectral data dimensionality reduction model.

Cultivar variability influences the near-infrared modeling and analysis of the internal quality of the fruit due to the different cell structure, composition and optical transmission characteristics of the fruit so that the original model can not predict the fruit quality parameters with high precision. The feasibility of a multi-cultivar model’s development for the online determination of the internal quality of apple including “Candy Heart”, “Red Fuji” and “Crystal Fuji” was investigated. Near infrared diffuse transmittance spectra of each cultivar were collected by the fruit sorting equipment under the condition of the interval time of 100 ms and motion speed of 5 s-1. The spectral curves of all the cultivars were similar where the prominent absorption peaks were near 650, 709 and 810 nm, and troughs were near 670, 750 and 830 nm, and their variations were mainly reflected in the spectral absorption intensity. The spectral pre-process methods including multiplicative scatter correction, Savitzky-Golay smoothing and normalization were employed to filter out the variations in signals caused by the cultivars. Partial least squares regression method was used to establish the common model for the soluble solid content where the calibration sets of the total samples were combined. Uninformative variable elimination was used to select the modeling variables whose number of effective variables selected was 155, and the performance of the UVE-PLS model resulted in greater coefficient of determination for prediction of 0.80, lower root mean square error of 0.61% and higher residual prediction deviation of 2.21. Successive projections algorithm was employed to select the variables in the wavelengths selected by UVE and the number of variables selected was 22. Multivariable linear regression was used to establish the simplified model, which resulted in coefficient of determination for prediction of 0.78 and root mean square error of prediction of 0.64%. The test sets of all the cultivars were used to access the performance of best universal model, which resulted in latent variables of 6~10, coefficient of determination for prediction of 0.77~0.79 and root mean square error of 0.45%~0.75%. The results highlighted the potential of dynamic on-line sorting instruments for the testing of internal qualities of apples. The prediction range of the single cultivar model was expanded, and the robustness of prediction model among different cultivars were improved by establishing the common model. Appropriate variable selection methods can decrease the number of model variables, reduce the complexity of the model and ultimately increase the model rate. The development of the universal model of different cultivars for predicting internal quality has a good potential application in wavelength-limited near infrared spectroscopy equipment.

The exploration and development of petroleum is spread all over the country, and the application of its products is inseparable from the industrial and agricultural production and the daily life of the people. In the use of petroleum and petroleum products, they leak into the soil and accumulate, which will destroy the ecological environment. Laser-Induced fluorescence （LIF） is an important method to detect petroleum hydrocarbon organic pollutants in soil. Laser pulse energy is an important experimental condition of LIF. It has a significant impact on detection sensitivity and stability. In order to explore the characteristics of LIF signal of petroleum hydrocarbons in soil with the pulse energy of excitation light, taking oil as an example, soil samples with machineoil concentration of 0.5%～6% were prepared in the laboratory. The Nd∶YAG laser was used as an excitation source with a wavelength of 266 nm. The fluorescence spectrum of the oily soil at different energy densities was obtained by changing the pulse energy of the 266 nm laser. The experimental results showed that the fluorescence intensity of the oil in the soil had a good linear relationship with its concentration at different energy densities. The fluorescence intensity of the machineoil in the soil itself and in the soil increased as the laser pulse energy increased. The experiment found that as the laser energy density decreased, the average relative error of the LIF system when measuring the oil first decreased first and then increased. The reason was that when the laser energy density was less than a certain range, the signal-to-noise ratio of the signal decreased. Therefore, the average relative error of the measurement gradually increased; when the laser energy density was larger than a certain range, although the signal-to-noise ratio of the signal increased, it had gradually exceeded the optimal measurement range of the system, so the average relative error of the measurement gradually increased. When the laser energy density wasin 2.4~4.0 mJ·cm-2, the fluorescence intensity of the oil in the soil increased linearly with the laser pulse energy density, and the measurement error of the machine oil concentration was less than 2.5%. At this time, the system limited the detection of machineoil to between 200~300 mg·kg-1. When the energy density was greater than 4.0 mJ·cm-2, the increase of the fluorescence intensity of the machineoil was significantly reduced, and the measurement error also increased. Therefore, taking into account the system to measure the average relative error of the machineoil in the soil and the measurement limit, the laser pulse energy was preferably 2.4~4.0 mJ·cm-2. In this paper, the characteristics of the fluorescence signal of the machine oil in the soil as a function of the excitation light energy were studied. The method could be extended to study the fluorescence signals of other petroleum hydrocarbons in soil. This paper provided a reference for the formation of LIF system to measure petroleum hydrocarbons in the site and select better laser energy conditions.

In the present study, the bioleaching of arsenopyrite by the moderately thermoacidophilic strain Sulfobacillus thermosulfidooxidans YN-22 was investigated based on iron, arsenic, and sulfur speciation analysis by synchrotron radiation As/S K-, and Fe L- edge X-ray absorption near edge structure (XANES) spectroscopy, X-ray diffraction (SR-XRD), accompanied by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), andinductively coupled plasma-atomic emission spectroscopy (ICP-AES) with the determination of the leaching parameters. The results showed that the presence of bacteria significantly promoted the dissolution of arsenopyrite, and dissolved As and Fe in the bioleaching solutions mainly existed as As(Ⅴ) and Fe3+, while were mainly As(Ⅲ) and Fe2+in the chemical leaching. Extracellular polymeric substances (EPS) plays a critical role in the interactions between bacteria and minerals during bioleaching, and the FTIR analysis of the EPS showed that the contents of protein and polysaccharides of the adhered cells were higher than those of the free cells. Results of SEM showed that the surface of the arsenopyrite was gradually corroded, and some secondary products were formed during bioleaching, while for the sterile control experiment, the mineral surface was only slightly corroded, and only a few products were found after 10 days of chemical leaching. The results of SR-XRD showed that elemental sulfur (S0), jarosite and ferric arsenate were detected after day 4, and gradually developed into the main components of the residues in the bioleaching experiment. Fe L-edge XANES analysis showed that during the bioleaching of arsenopyrite by Sulfobacillus thermosulfidooxidans, the Fe(Ⅱ) species was gradually converted to Fe(Ⅲ) species with time. As K-edge XANES analysis showed that valences of arsenic in the bioleached residues included As(-Ⅰ), As(Ⅲ) and As(Ⅴ), the fitted results of the As K-edge XANES spectra showed that the residue composition of arsenic species for the same leached time(10 days) consisted of 18.6% arsenopyrite, 23.5% orpiment and 57.9% ferric arsenate in the bioleaching assay, and of 93.8% arsenopyrite and 6.2% ferric arsenate in the chemical leaching. The fitted results of the S K-edge XANES spectra showed that after 10 days bioleaching, the residue composition of sulfur species consisted of 15.3% arsenopyrite, 23.7% S0, 3.5% thiosulfate, 11.3% schwertmannite and 46.2% jarosite, while only a small amount of S0 (7.8%) was found as the sulfur intermediate at day 10 in the sterile control experiment. Based on these results, it could be concluded that the chemical speciation transformation of iron, arsenic and sulfur were performed in the pathways: Fe(Ⅱ)-Fe(Ⅲ), As(-I)-As(Ⅲ)-As(Ⅴ), and S-→S0→S2O2-3→SO2-4, respectively. Based on the observations of leaching behavior, it was found that as a massive accumulation of S0, jarosite, ferric arsenate, and As2S3 occurred the dissolution of arsenopyrite was severely hindered. Moreover, the formation of thiosulfate-like species during bioleaching indicated that arsenopyrite was dissolved in the similar way to that of pyrite.

Dendrobium is a commonly used Chinese herbal medicine, often using fresh or dry stems into the medicine, beneficial to the stomach, nourishing yin and clearing heat. In recent years, pharmacological studies have found that Dendrobium has the functions of anti-cataract, anti-oxidation, anti-tumor and improving immunity. It has remarkable effects in many cases, which has attracted the attention of scholars at domestic and abroad. However, the contents of amino acids and trace elements in Dendrobium collected at different times are different, and their medicinal value and price are different. So the study of price grade discrimination of Dendrobium is of great significance. In order to quickly identify Dendrobium with different price and efficacy, the random forest classification modela combined with laser induced breakdown spectroscopy (Laser-induced Breakdown Spectroscopy, LIBS) was developed to model the price grade of Dendrobium. In this paper, five samples of Dendrobium were selected for modeling. In order to analyze the samples accurately and stably, all Dendrobium samples were pressed to reduce the experimental error. The Nd∶YAG pulse laser with 1 064 nm wavelength was used as the excitation light source, the detection delay of 50 mJ, laser pulse energy was set to 1 μs, the spectral data of five grades of Dendrobium were collected, 40 sets of spectra were collected from each grade of samples, and a total of 200 sets of data were collected. Normalized processing was used to convert all spectral data from -1 to 1. The principal component analysis (PCA) was used to analyze the normalized spectral data. The score matrix of the first seven principal components was obtained by principal component analysis, and the cumulative interpretation of the total spectral information was 95.24%. So seven principal components were selected as input, and a random forest identification model with 220～880 nm was established. The number of Dendrobium samples was disrupted, and 50% spectral data were randomly selected as training sets, and 50% spectral data were left as test sets. The default number of decision trees (ntree) was 500, and the number of attributes in the split attribute set (mtry) was 5. The model was established to classify Dendrobium in different grades. And the recognition rates of grades one, two, three, four and five were 95.45%, 100%, 78.26%, respectively. 94.12%, 85%, with an average recognition rate of 90.57%. In order to improve the recognition rate, the influence of different ntree and mtry on the classification model was studied, and the two parameters of the random forest were optimized by using the out-of-bag data error rate estimation. The ntree was 300, the mtry was 1, the recognition rates of grade one, two, three, four and five were 100%, 100%, 92.31%, 100%, 90%, the average recognition rate was 96.46%, and the recognition rate was increased by 5.89%. In conclusion, it is feasible to identify the Dendrobium classification by LIBS technology combined with the optimized random forest model, which provides a feasible discrimination system for the rapid identification of Dendrobium classification with different prices in the future.

A simple, rapid and wide-ranging analytical method is urgently needed for the detection and control of inorganic multi-element in foodstuff. Therefore, in this work, an analytical methodology using suspension sampling in combination with a low power benchtop total reflection X-ray fluorescence (TXRF) system has been developed for multi-elemental analysis of foodstuff samples．The effect of different dispersants, particle size, sample mass concentration in suspension and internal standard elements on the total reflection X-ray fluorescence spectrometry was investigated. The Milli-Q water, Triton X-100 and nitric acid were chosen for dispersants, under optical microscope Milli-Q water and Triton X-100 were more uniform than HNO3 in morphology, and Milli-Q water was more accurate than Triton X-100 in measuring results by TXRF. Laser diffraction particles were used to determine the particle size before and after grinding, and it was found when the average particle size was small, the results of TXRF were more accurate. Different samples were weighed in the same amount of dispersant, and the dispersion effect and test accuracy would be affected with the increase of the sample mass concentration in the suspension. Ga or Se was used as internal standard elements for quantitative analysis of GBW0857 in the experiment, but because the measured elements As and Se are adjacent elements, which cause overlap of spectral lines, and then Se as internal standard elements would affect the accuracy of quantitative analysis of As elements, in order to avoid the interference of internal standard elements on the measured elements, Ga was selected as internal standard elements in this experiment. An easy and rapid sample preparation consisting in suspending 20 mg of sample in de-ionized water showed to be the most suitable for this kind of samples. Four certified reference materials in foodstuff were employed for the quantitative determination of the inorganic elements. The recovery rate of most elements (except some elements) was concentrated in the range of 80% to 120%, and the RSD was less than 15%. Compared with the methods of ICP-AES and ICP-MS, the method of suspension sample preparation-total reflection X-ray fluorescence analysis is faster and more convenient.

The XRD-Rietveld full-spectrum fitting method (Rietveld method) is an advanced technical method that is widely used in the field of materials science to solve the quantification issue of multiphase mixture samples. Theoretically, the Rietveld method could be applied in the geosciences field, and it can help geologists to get a better result in the analysis of mineral quantification of geoscience samples. However, in practical applications, there are several basic problems needing to be solved, especially concerning the applicability of the method itself and the reliability of analysis data. Regarding to these issues, taking soil samples for example, a simulation experiment was conducted in this study. Prior to application of the Rietveld method, three sets of simulated soil samples were prepared firstly according to the common knowledge of natural soil mineralogy, including quartz+hematite 1∶1 mixture sample, quartz+kaolinite 1∶1 mixture sample and quartz+kaolinite+montmorillonite 1∶1∶1 mixture sample. Using the Rietveld method, we obtained good XRD fitting lines for all simulated soil samples. Specifically, some important indices, including fitting value (Rwp<15%), fitting expectation (Rexp<15%) and goodness of fit (gof<5), could all meet the requirements of applying the Rietveld method. Also, the Rietveld-based mineral quantification data were very close to their real values, with errors only 0.63%, 1.46% and 1.03% for three samples respectively. This result indicated that the application of Rietveld method to quantify the soil mineral composition is feasible and reliable, which can get better results than the traditional “internal standard” method.

Quartzose jade, which is widely distributed and has been mined in more than 10 provinces and regions in China, is an important characteristic jade in the domestic market. It has been used for thousands of years and wasthe predominant jade material inthe pre-Qin period of Lingnan area. The origin distinction of quartzose jade is of great significance in gemology and archaeology. However, due to the similar appearance and composition characteristics for quartzose jades from different mines, there is still a lack of effective origin discrimination methods for quartzose jades, and the study on the origin typomorphic characteristics of quartzose jade is still very weak. Taishan jade, produced in Taishan, Guangdong Province, is a kind of quartzose jade increasingly valued for its Tianhuang-like appearance. On the basis of conventional gemological tests, the spectral characteristics and mineral composition of 6 representative samples of Taishan jade were studied by using X-ray powder diffraction spectrometer (XRD), Fourier transform infrared spectrometer (FTIR) and Raman spectrometer. The results showed that the main mineral of Taishan jade is quartz and the minor mineral is dikite or kaolinite, with other minerals spectroscopycally undetectable. The two kinds of kaolin group minerals do not coexist in Taishan jade. Based on the XRD-Rietveld quantitative analysis, the content of quartz in Taishan jade is less than 85 Wt%, while the content of kaolin group mineralsis between 17 Wt% and 36 Wt%. The absence of 502 cm-1 band, which is the diagnostic Raman band for moganite, in the Raman spectra of Taishan jade indicates that the quartz in Taishan jade has a higher crystallinity than the quartz formed at low temperature, such as chalcedony and agate. Taishan jade can be divided into two types: dickite quartzose jade (the main type) and kaolinite quartzose jade (the secondary type). The infrared spectra of dickite quartzose Taishan jade showed three intense OH-stretching bands at 3 622, 3 653 and 3 703 cm-1, while the Raman spectra showed similar bands at 3 622, 3 644 and 3 706 cm-1, both of which had the characteristics of obvious band splitting and the decrease of peak intensity toward high frequency. There were four OH-stretching bands observed at 3 620, 3 652, 3 670 and 3 695 cm-1 in the infrared spectra of kaolinite quartzose Taishan jade, and another four similar bands found at 3 620, 3 651, 3 670 and 3 687 cm-1 in the Raman spectra, of which the 3 670 cm-1 band was very weak and difficult to identify. The occurrence of well-ordered dickite and kaolinite in Taishan jade indicated that the Al-rich minerals in its protolith have undergone the metasomatic alteration of intermediate-temperature acid hydrothermal solution, and the metallogenic conditions are different from those of quartzose jade such as Huanglong jade, Jinsi jade and Huoshan jade. It can be confirmed that the dickite and kaolinite are the fingerprint minerals of Taishan jade, which are different from quartzose jades from other origins. The results in this study provided an important scientific basis for the origin tracing of Taishan quartzose jade and will be potentially used as a reference for the distinction of quartzose jades from different origins and the provenance study of ancient quartzose jade artifacts in China.

Binding media used in cultural relics was often mixed with pigments or dyes, and the composition was complex. In the long historical preservation environment, the binding media degraded and aged, and the painting layer was seriously damaged. Because of its high artistic, historical and scientific value, the painting contents were of great significance to the study of ancient culture, customs, science and technology, and religious beliefs. Binding medias were usually based on polysaccharides, fatty acids or proteins, and their precise analysis is essential for the identification and preservation of painted artifacts, and also helps to determine the appropriate conservation method. Therefore, The chemical change of binding medias in the aging process and the understanding of its material composition are the hotspots of the conservation community. Due to the non-renewability of cultural relics, the content of the binding media was low, the sample allows micro-loss or non-destructive analysis, and ordinary analytical methods are difficult to meet the sensitivity requirements. As one of the analytical tools for the material and structure of cultural relics, spectroscopy technologies meet the requirements of non-destructive or micro-damage analysis of binding media, overcome the analytical defects of traditional chemical means, and have been widely used in the field of preservation and conservation of cultural heritage. In this paper, the applications of IR, Raman spectroscopy, UV and fluorescence spectroscopy and NMR technology in the analysis of binding media for painting are reviewed. In the IR spectrum, the reflection mode has strong anti-interference, especially the ATR IR spectrum image has high resolution; the synchronous radiation IR spectrum detection area is very small, and the compound can be accurately positioned and separated; the diffuse reflection and the AFM IR spectrum can be performed, for non-invasive characterization and nano-domain imaging, respectively. Raman spectroscopy is specific, sensitive and selective for molecular changes and is an effective detection technique for binding medias. In addition to strong selectivity, fluorescence spectra have many physical parameters and many molecular information of sample is obtained. Fluorescence lifetime imaging can distinguish binding medias. 2D NMR spectroscopy can analyze complex mixtures, and the swelled-state NMR technique is anti-interference, the time of analysis is short and the sample does not need to be pretreated. Electron paramagnetic resonance and edge structure can study the influence of environment on pigments and binding materials. The FORS can be used for in-situ non-destructive analysis, the mid-infrared FORS is an ideal method for analyzing binding medias, and this method is complementary to Raman spectroscopy and distinguishes complex binding medias. Most of the spectroscopy techniques described in this paper can be combined with chemometrics to better conduct binding medias. However, different spectroscopy techniques are limited by the current method, and the sample information obtained are not the same. When the samples are analyzed, multiple spectroscopy techniques can be combined to take advantage of each other, make up for their own testing challenges, complement each other and improve the accuracy of analysis results. In addition, the instrument combination technology is introduced briefly. Finally, the difficulties in the analysis of binding medias are summarized in this paper, and the development and application prospects of spectral technology are expected.

Study on geological provenience of turquoise can reveal a lot about ancient trade, organization of resources and cultural exchanges, thus the origin of turquoise artifacts excavated from Xinjiang has been a hot issue in archaeometry in recent years. At present, there are three major academic hypotheses on the provenience of turquoise objects found in Xinjiang: Central Plains, Xinjiang or Persia. In order to determine the provenience of turquoise excavated from Jiayi and Xigou sites, two cemeteries in the eastern part of Xinjiang have been chosen, and we examined the turquoise samples using LA-ICP-AES to analyze the chemical composition and PCA to compare the results with samples from five regions in the eastern Qinling Mountains (Central Plains). The results of the composition analysis of the objects from these two sites have shown that five of the Jiayi site samples are rare zinc turquoise, while the other samples are similar to those turquoise samples of the Xigou site and contain relatively high level of Fe and Sr. Based on the comparative analysis of the turquoise composition data between these two sites and samples from the Qinling Mountains, it was suggested that the trace elements of turquoise artifacts from Jiayi and Xigou sites are not similar to the turquoise samples in the Central Plains, different in view of higher level of B2O (Wt%) and lower level of BaO (wt%). According to the provenience differentiation model, the samples from these two sites have formed a cluster and are clearly distinguished from the distribution areas of Qinling Mountains. Hence, it can be concluded that the composition of the turquoise artifacts excavated from Jiayi and Xigou sites is different from the minerals of Qinling, Mountains in Central Plains. Based on the discovery of the ancient turquoise mining site in Hami, Xinjiang, the turquoise artifacts found in Jiayi and Xigou sites are barely likely to be from Central Plains.

During the process of building inversion model of water content based on NIR spectrum, it is the key issue to figure out whether the feature set of rock will change along with the differences of lithology or not. Aiming at this problem, firstly conducting a laboratory experiment on water absorbability of rock by intelligent test system of hydrologic action on deep soft rock, this paper measures near infrared spectrum of water-bearing rock in three different lithology at different times. For conglomerate, siltite and rammed soil, we collect 51 pieces, 106 pieces and 149 pieces correspondingly. Afterwards, first-order derivative method is adopted in dealing with pretreatment of original spectrum, avoiding the influence of environmental interference on the spectrum. Next, the geometric feature method is used to extract the spectral features and normalize it to eliminate the influence caused by different dimensions and change amplitudes. Then, the correlation degree between initial characteristic variables and that between initial characteristic variables and water content are analyzed, and the characteristic variables at two strong correlation bands are obtained by referring suppression threshold size and eliminating redundant features. At last, Maximal Information Coefficient （MIC）is used as a metric to compare and analyze the feature selection results on near infrared spectrum of water-bearing rock with different lithology, in order to evaluate the influence of lithology on the spectral characteristics of water-bearing rocks. The results are as shown below: （1）The near infrared spectra of conglomerate, siltstone and rammed soil have obvious absorption peaks near 1 400 and 1 900 nm, and with the change of water content, the absorption intensity becomes much more stronger, which shows a significant correlation with the size of the water content. （2）The maximum correlation coefficient between the characteristic variables of near infrared spectra of conglomerate, siltstone and rammed soil and their water content value shows that the correlation between the near infrared spectrum of rammed soil and water content is the strongest. （3）Each characteristic value of near infrared spectrum of different lithology has different correlation degree with water content, which shows that the peak height near 1400nm, the right shoulder width and the water content all have high correlation. However, the correlation will vary because of different lithology, with the right shoulder width and peak area in the vicinity of 1900nm having higher correlation coefficient with water content, and the correlation degree of right shoulder width being higher than that of peak area. （4）The characteristic variables of near infrared spectrum of water-bearing rock with different lithology are similar to the correlation of water content—peak height, right shoulder width and peak area are the three characteristics with the highest correlation degree.

We report on the application of Laser Induced Breakdown Spectroscopy (LIBS) technique to the study of Ca, P, Zn and Sr evolutions for adult caries-affected teeth using nanosecond laser pulses. The aim of this work is to better understand the behaviors of Zn and Sr as trace-elements in the caries eruption with respect to the behaviors of one of the main compounds of the hydroxyapatite crystal which is the calcium. The study was focused on the investigation of these elements’ evolutions from three parts of the enamel surfaces of twenty two adult caries-affected teeth; the healthy part, the dental plaque part and the caries-affected part. The decrease rates of Zn, Sr and P was, also, compared to the Ca one. Comparison concerned normalized emission line intensities. For every species, normalization was done relatively to the emission line intensities of the healthy part. Results showed that abundances of these elements decrease similarly from the healthy parts to the affected-caries parts. The higher decrease rate was noticed for the calcium. The evolutions of Zn and Sr for the three parts of the teeth surfaces cannot inform about the substitution of the calcium by these trace-elements, however the comparison of their decrease rates to the calcium one can be considered as a valuable index of this substitution.

Herein, this article was focused on the synthesis and discussed the spectroscopic characterizations of four new scandium(Ⅲ) sulfa-drug complexes. The nomenclature and symbols of these drugs were sulfadimidine (sulp-1), sulfanilamide (sulp-2), sulfamethoxazole (sulp-3) and sulfadiazine (sulp-4). The microanalytical and spectroscopic analyses which utilized in this study were micro-analyses, magnetic, FT-IR, UV-Vis techniques. The mid infrared spectra deduced that the four sulfa-drug chelates acts as a bidentate chelates with scandium(Ⅲ) ion via two nitrogen atoms of —NH2-Ar and —NH-SO2 groups. Also, the FTIR spectra of Sc3+ complexes referred to the existed of new medium weak bands in the range of 500～400 cm-1 due to stretching vibration bands of ν(M—N). The elemental analysis technique confirmed the 1∶2 stoichiometry between Sc3+ ions and sulp ligand with molecular formula ［Sc(sulp)2(Cl)2］·Cl. At room temperature, the results of magnetic measurements for the Sc(Ⅲ) complexes indicated that all of the synthesized complexes have a diamagnetic character with octahedral configuration. The electronic spectra of the free sulfa-drug ligands shows band at 275 and 310 nm which are intraligand charge transfer band. The electronic sbsorption spectra of the Sc3+ complexes were recorded using DMSO solvent. The spectra of complexes display bands within 275～388 nm, which attributed to π—π*, n—π* and charge-transfer M-LCT electronic transitions, which strongly favors the octahedral geometry around Sc(Ⅲ) metal ions. 1HNMR spectra of complexes referred to the downfield proton shifts of the —NH2 and NHSO2 groups, which supported the place of coordination. The half maximal inhibitory concentration (IC50) of the ScⅢ complexes was assessed against the human hepato cellular carcinoma (HepG-2) tumor cell line.

Fourier transform microwave spectrometer is the main tool for measuring molecular rotational transitions and an important instrument for researching molecular rotational spectroscopy. Based on quantum mechanics, rotational spectroscopy is essential for the structural analysis of molecules and for deciphering molecular signals from deep space captured by radio telescopes, thus making microwave spectrometers indispensable in those fields. At present, researchers from countries all over the world are working on the instrumentation of microwave spectrometers to improve the resolution, sensitivity, and application range as well, while Chinese researchers are also exploring such instrument development actively, and expect to make due contributions to those fields. In this paper, the design and development of a chirped-pulse Fourier transform microwave spectrometer are presented with a frequency coverage of 1～18 GHz. The broadband chirped pulse of a linear frequency sweep is generated by the arbitrary waveform generator with a sampling rate of 1.25 GS·s-1. After mixing and amplification, the chirped pulse with a certain frequency coverageis broadcast through a feedhorn antenna into the vacuum chamber, where it interacts with a supersonically expanded molecular beam. The free induction decay (FID) signal emitted by the excited molecules is induced and amplified by the receiving circuit and then directly digitized on a high-speed digital oscilloscope. Many electronic devices of the microwave spectrometer are controlled by a personal computer, and their automatic operation can be achieved by a LabVIEW program. The gas nozzle technology is applied to improve the sensitivity of the spectrometer by effectively reducing the rotational temperature of gas samples in the vacuum chamber. Multiple free induction decay (multiple FID’s) technology is also applied to further improve the sensitivity by dramatically increasing the signal sampling rate of the spectrometer. By using this broad-band chirped-pulsed Fourier transform microwave spectrometer developed in the laboratory, a chemical reaction of hydrochloric acid and tertiary butanol was monitored, with the reaction product tert-butyl chloride detected successfully. The rotational spectra of tert-butyl chloride and its singly-substituted 37Cl isotopologue were measured in their natural abundance, and were then fit by the spectrum analysis software to provide accurate spectral parameters (rotational constants, centrifugal distortion constants, and the nuclear quadrupole coupling constants, etc.) and molecular structure. The high accuracy of spectral data measured by the spectrometer was proved by comparison with Gaussian calculation. The spectrometer’s excellent performance in the low frequency range was also demonstrated when compared with the spectral parameters measured by predecessors.