Luminescence decay is an important process of luminescence. It is important to measure the lifetime for the study of luminous mechanism. But there are two flaws in the traditional research on the concepts and methods: firstly in terms of the concepts, luminescence decay is considered as the reduction in the number of the excited states and ignored as the decline of the luminescence intensity, so they are different concepts. Secondly the methods are based on the change rule of the excited states and the boundary conditions without the support of the experiments do not conform to the reality. The traditional method is demanding as to the equipment and photoluminescence is necessary. In order to correct these two flaws and reduce the cost, a new electroluminescence decay measurement system is set up , which could be used for all periodic luminescence. Based on the principle of energy conversion, we use periodic luminescence method, and pulse interval time as a time scale to measure the lifetime easily. The luminescence intensity shows different rules through the comparison between the pulse interval time and the lifetime. A new luminescence measurement system is proposed based on this theory. The experimental result shows that the luminescence intensity keeps invariant and then gradually decline with the increase of excited frequency. We successfully measure the lifetime by measuring the inflexion point and also found a positive correlation between initial luminescence intensity and lifetime. We believe that lifetime is the change of the luminescence intensity. This is a great innovation different from the tradition research on the number of the excited states. At the same time, through the experiment it is proved that the lifetime is related to the initial intensity and increase the understanding of the lifetime.

Solar absorption spectra collected with a high-resolution Fourier transform spectrometer is able to measure the column abundance of CO2 accurately. In the paper, the influence of a model parameters in the forward model on the retrieval of CO2 is analyzed, also the impact of a model parameters on retrieval results under different solar zenith angle and the reasons are discussed. Four model parameters, such as continuum tilt value, internal field of view, zero-level offset and Doppler shift are modified in the forward model and how the results change with the disturbance is studied, based on the spectra collected in two typical days. The results show that, the relative deviations of column-averaged dry air mole fraction of CO2(XCO2) caused by the disturbance of different a model parameters are different. Also, the relative deviations due to the disturbance of the same parameters corresponding to different time for collecting spectra are different. Continuum tilt value has the biggest influence on the retrieval, and the change of this value resulted in the relative deviations of XCO2 between 01%~02%. The changes of other three parameters internal field of view, zero-level offset and Doppler shift have small impact on the retrieval, which leads to the relative deviations of XCO2 in the range of -0045%~-002%, -0045%~0015% and -003%~004%, respectively. Finally, the reasons of the deviations are explained based on the average kernels of CO2. The results provide a basis for how to set the parameters in the retrieval algorithms and improve the measurement accuracy of atmospheric CO2.

In order to explore the application of laser absorption spectroscopy in the non-uniform flow, a new strategy that provides quantitative measurements of gas parameters in non-uniform environments are put forward. After evaluating the range of temperature in the field and choosing the appropriate transitions whose strengths that scale linearly with temperature, the H2O mole-fraction-weighted path-average temperature and geometric path-average H2O mole fraction can be quantitatively measured. The simulated results from two-temperature and Gaussian-temperature distribution model show the availability and reliability of this method. Compared with theoretical value, the relative errors of measured results in the two-temperature distribution model are 082% and 110% while the most relative errors in the Gaussian-temperature distribution model are 09% and 36%.

Terahertz time-domain spectroscopy (THz-TDS), a newly developed far-infrared technique in recent years, has been widely applied for the detection of polar gas and non-polar gas. The principal components in distillation, natural and marsh gas include methane (CH4), ethane (C2H6) and propane (C3H8). The three kinds of alkane gas are separately measured for the frequency domain and phase spectra, and then mixed as a series of two-component systems which are finally measured with THz-TDS. The frequency dependent amplitude and phase spectra prove that C3H8 has stronger absorption in THz range compared with CH4 and C2H6. Such trend is agreement with the polarity intensities of alkanes. In addition, back propagation artificial neural network (BPANN) is employed to quantitatively analyze the contents and total pressure with the frequency-amplitude spectra as the input. The correlation coefficients R between actual and predicted values are calculated in both training and prediction sets, where r range from 0994 to 0999 and from 0981 to 0993, respectively. Therefore, the combination of THz-TDS and BPANN can realize the quantification of multiple properties in alkane mixtures, which would promote the application of THz-TDS technique for gas detection.

In this study, quartz dusts and Pb(Ⅱ), the high siliceous mineral fine particles and main heavy metal pollutants in atmospheric particulate matter, were used as experimental materials to prepare Pb coated onto quartz dusts. Experiments were carried out to examine the oxidative stress response of Escherichia coli to PbCl2 and 16 g·L-1 Pb(Ⅱ) coated onto quartz dusts, and to explore the effect on E. coli surface groups and protein amide Ⅰ band secondary structure. The reduction of cells viability, glutathione depletion with a concomitant increase in reactive oxygen species and malondialdehyde levels demonstrated that Pb(Ⅱ) and Pb coated onto quartz dusts induce oxidative stress leading to cytotoxicity in E. coli. Moreover Pearson correlation analysis showed that there existed significant positive correlation (p<005) between bacteria toxicity and Pb(Ⅱ) exchange state content in the dusts. Exposures to Pb coated onto quartz dusts produced significant increases vs. both single quartz dusts and Pb(Ⅱ) in ROS/MDA (p<005). The influence of Pb(Ⅱ), Pb coated onto quartz dusts on E. coli surface groups focused on phosphate ester groups and surface polysaccharide molecules, amide Ⅰ band characteristic peak (1 600~1 700 cm-1) were fitted by the second derivative, deconvolution and line fitting technology, found that protein amide Ⅰ band beta sheets/alpha helices ratio decreased obviously after infected, the ratio decreased from 141 to 133, 127 and 122, respectively, after effects of Pb (Ⅱ) and Pb coated onto quartz dusts(Q-Pb-0/Q-Pb-3), suggesting that the structure of bacterial surface proteins were changed, which may affect the physiological activities of the bacteria. The results indicate that the oxidative damage effect may be an important toxicity mechanism of Pb(Ⅱ) coated onto quartz dusts, in addition, exposure to Pb(Ⅱ) coated onto quartz dusts can cause association oxidative stress on E. coli than either material alone.

Cellulose nanofibril (CNF) aerogels combine important properties of conventional silica aerogels with their own excellent biocompatibility and biodegradability, which could be applied in various fields. However, applications for cellulose aerogels have been limited by cellulose’s hygroscopicity. In order to improve the hydrophilicity and comprehensive properties of cellulose aerogels, the simple immersion method was used to introduce silica parties into the cellulose matrix to synthesis cellulose nanofibril/silica composite aerogels. The chemical structure of cellulose aerogel and composite aerogels was analyzed with Fourier transform infrared spectroscopy (FTIR). The microstructure of aerogels was observed by scanning electron microscope (SEM). The physical, mechanical properties and contact angle of aerogels were tested and analyzed. The results show that the peaks of —OH located at 3 340 cm-1 in composite aerogels were all weaker compared with cellulose aerogel, which indicates that the formation of Si-OH due to the introduction of silica and also lowered the hydrophilicity of cellulose aerogel. The appearance of the peaks of Si—CH3 and Si—O—Si represents the modification of trimethylchlorosilane (TMCS) and the formation of stable chemical bond between cellulose and silica particles. The silica content of the composite aerogels was affected by the immersion time, and in turn affected the density, BET surface area and porosity of aerogels. The composite aerogel had better comprehensive properties when immersed into silica sol for 10 min. It had homogeneous microstructure and hydrophobicity, with contact angle of 152°. It also had good mechanical properties and low density, the compressive modulus and strength of the composite aerogel were 591 and 138 MPa, respectively. Its density was only 01 g·cm-3.

The method of maize haploid identification plays a significant role in advancing Maize Haploid Breeding Technology. Given to its advantages of cost-effectiveness, high performance and being easy to operate, near-infrared spectroscopy (NIRS) has drawn great attention in the field of agricultural research. At the beginning of the experiment, NIRS data of both haploid and polyploidy maize seeds that are provided by National Maize Improvement Center of China are collected via US JDSU’s near-infrared spectrometer. After pre-processing that the original data were processed by smoothing, first derivative, and vector normalization in order to eliminate the influence of noise, the NIRS data is subsequently mapped in a high-dimensional space, where nonlinear feature extraction take place through Kernel Principal Components Analysis (KPCA) whose kernel function is Gaussian kernel. Then Vector Machines Support (SVM) was used to establish the classification model for it. Finally, based on the result of classified identification test, the experiment makes a prediction of whether maize seeds are haploid. In particular, this paper designs two sets of comparative experiments with average recognition rate being 95% and 9357%. The result indicates that the method based on KPCA is both feasible and valid. The above experiment proves that the process of “high-dimensional spatial mapping—nonlinear feature extraction—modeling classification analysis” is more suitable for studying maize seeds data collected via NIRS. Therefore, this paper may provide some new idea and method for Maize Haploid Identification technology.

The aim of the research is to estimate Fourier transform infrared spectroscopy (FTIR) as a novel diagnostic tool for rectal cancer metastatic lymph nodes. 160 freshly normal and malignant lymph nodes were collected from 80 rectal cancer patients for spectrum analysis. FTIR spectra were generated from tissues samples using infrared wavenumber from 4 000 to 1 000 cm-1 region. The ratios of spectral intensity and relative intensity ratios (I/1 460) were calculated. Principal component analysis (PCA) and Fisher’s Linear discriminant analysis (LDA) were applied to distinguish the malignant from normal. From 4 000 to 1 700 cm-1, principal components 1 (PC1) was 3 260 cm-1 and PC2 was 1 740 cm-1; from 1 700 to 1 000 cm-1, PC1 was 1 640 cm-1 ab PC2 was 1 080 cm-1. Four prominent significant wavenumbers at 1 080 , 1 640, 1 740 and 3 260 cm-1 separated cancer spectra from normal spectra into two distinct groups using PCA. T test associated with relative intensity ratios (I1 080/I1 460, I1 640/I1 460, I3 260/I1 460, I1 740/I1 460) revealed that these wavenumbers were also able to distinguish cancer and normal lymph nodes spectra. The bands 3 260, 1 640, 1 550, 1 080 and 1 740 cm-1, associated with Protein, nucleic acid and lipid. Compared with normal lymph nodes tissues, malignat lymph nodes significant increased (p<0.05), but 1 740 cm-1 decreased. Six parameters (wavenumbers 1 080 and P1 300 cm-1, relative intensity ratios I1 080/I1 460, I1 640/I1 460, I3 260/I1 460, I1 740/I1 460) were selected as independent factors to perform discriminant functions. The sensitivity for PCA/LDA mode in diagnosing lymph nodes was 87.5% by discriminant analysis. The results demonstrate that FTIR is as a useful technique for detection malignant and normal lymph nodes, FTIR may be applied in clinical as a noninvasive, high sensitivity and specificity method for lymph nodes diagnosis.

In terms of the near infrared spectrum data similarity measurement,due to the fact that spectral data is high dimensional, non-linear and overlapping, data processing is full of difficulties failures to measure distance. The traditional method of similarity measurement in high dimensional space presented unadapted,so this paper proposed the spectral similarity measure method based on neighborhood counting. Firstly, using the (NPP) algorithm to handle the original spectral data, as a dimension reduction method, can preserve the original nonlinear spectral data structure and neighborhood information.Then, in the low dimensional space, improved neighborhood counting method is used to realize the similarity measure of the near infrared spectrum data. Experimental results show that the spectral similarity measuring method based on neighborhood counting is effective in the spectral data similarity measurement, which has a good prospect in tobacco style determination and quality analysis. Besides, it provides a good similarity measurement solution in high dimensional spectral data.

In the development process of leather industry, metallurgical industry, electroplating industry, mining industry and other industries, wastewater containing heavy metal ions is discharged to the river and farmland, resulting in environmental pollution. Heavy metal pollution has been paid more and more attention. It is an urgent problem to control the pollution and recover heavy metals. Hg2+ is considered to be the most toxic heavy metal. This article studied the modified PLGA/G5-T fibers to treat the Hg2+ wastewater efficiently. In this study, thymine-1-acetic containing carboxyl reacted with G5.NH2 to form G5-T. Then G5-T was mixed with PLGA for subsequent formation of T-modified electrospun PLGA/G5-T nanofibers. The nanofibers were characterized with fourier transform infrared (FTIR) and scanning electron microscope (SEM), and measured the sorption efficiency and selectivity by inductively coupled plasma-optical emission spectroscopy (ICP-OES). FTIR results showed that the amino groups absorption peak of PLGA/G5-T nanofibers at 3 320 cm-1 was weaker than that of PLGA/G5, the amide groups absorption peak of PLGA/G5-T nanofibers at 1 660 cm-1 was stronger than that of PLGA/G5, suggesting that G5.NH2 reacted with thymine-1-acetic successfully. The results from SEM measurements showed that mean diameter of PLGA/G5-T nanofibers was (751±72) nm, and fiber morphology of PLGA/G5-T was uniform, smooth without adhesion. It was concluded that the thymine modification would not appreciably impact the fibrous morphology of PLGA/G5-T nanofibers when compared with the PLGA/G5 nanofibers. It could be found with ICP-OES that Hg2+ removal efficiency of PLGA/G5-T was significantly higher than that of PLGA/G5 fiber membrane. The good performance on Hg2+ removal was due to the enhanced removal efficiency of thymine; absorbing test of various metal ions showed that only a little ion of Cu2+, Cd2+ and Co2+ was adsorbed on PLGA/G5-T while a lot of Hg2+ ions were adsorbed. It was proven that PLGA/G5-T nanofibers can remove Hg2+ from aqueous solution selectively and efficiently. This study is beneficial to research and development of new Hg2+ adsorbents.

Surface defects of solid wood boards directly affect their mechanical properties and product grade, therefore, to achieve rapid detection of surface defects has important practical significance for online sort of solid wood boards. In view of the low recognition rate of the surface defect of the solid wood boards, a new method for the detection of 900~1 900 nm was proposed.by using a portable near infrared spectrometer First of all, the experiment collected absorption spectra of 180 samples with size of 200 mm×10 mm×10 mm, consisting of 60 samples with live knots, 60 samples with dead knots and 60 defect-free samples. Half of the samples were selected randomly as the training set, and the rest of samples were test set. Secondly, the the collecting NIR spectra of solid wood boards were preprocessed with Gaussian smoothing filter, piecewise multiplicative scatter correction and De-trending to reduce the spectral noise and eliminate the influence of the scattering spectrum; Afterwards, the improved genetic algorithm was utilized to select characteristic waves from the processed spectrum for building a model of defects recognition and classification; Finally, a model for recognizing and classifying the defects of solid wood boards was built through the improved neural network based on Bayesian neural network. The experiments used three types, containing live knots, dead knots and defects free, of solid wood board samples to train and test the model, the results showed that the model of based on Bayesian neural network was able to accurately identify three kinds of them, and the recognition rates were 9220%, 9447% and 9557%, respectively. This study demonstrates that the type of solid wood boards surface defects with its near-infrared absorption spectra are closely related, and the article provides a rapid approach to achieve the accurate positioning of solid wood board defects which is as the next step.

In this paper, 3 914 near infrared spectrums of flue-cured tobacco samples was tested. These tobacco samples were collected in 17 provincial origins, including the NONG (Luzhou) flavor 865 cartons, Intermediate flavor 1 646 cartons and QING flavor (Fen) 1 646 cartons. We used near-Infrared spectroscopy and multiple algorithms fusion to analyze flue-cured tobacco flavor style features. Based on the preliminary classification of tobacco flavor according to different origins, accepting transitional and atypical flavor, tobacco flavor classification models of PPF (Projection of Basing on Principal Component and Fisher Criterion), DPLS (Partial least squares discriminant) and SVM (Support vector machine) were established respectively; and 1st and 2nd discriminant results of each algorithm can be known. Using PPF-DPLS-SVM fusion and discriminant results (1st and 2nd) of each algorithm, prediction results can be refined into typical, transitional and atypical flavor. The numbers of three flavors were 493, 392 and 115, respectively. The discriminant accuracy rate of typical flavor was improved to 927%. And it was improved 302%, 154% and 166% to compared with those achieved using PPF, DPLS and SVM, respectively. The tested samples were collected in main origins of China, which were abundant with great representativeness, therefore, the analysis result had practical application. The analysis method presented greatly improved the discriminant accuracy rate of flue-cured tobacco flavor, which was better than that of the classification according to objective data. The method refining flue-cured tobacco into typical, transitional and atypical flavor, provided guidance to the scientific application and module industrial processing of raw flue-cured tobacco.

Raman spectroscopy provides the fingerprint of the molecules, and is an important and powerful technique for analyzing the chemical composition of biological or non-biological samples. However, in many cases, the existence of the concurrent fluorescence background seriously interferes with Raman measurements. The excitation laser induced fluorescence intensity can be sometimes several orders of magnitudes higher than that of the Raman scattering signals. Such fluorescence backgrounds must be suppressed during the measurement in that Raman spectral fingerprints have to be measured accurately with high signal-to-noise ratio. A variety of techniques have been explored in researches and practical applications for this purpose. In present scientific researches,common methods include Surface Enhanced Raman Spectroscopy, Fourier Transform Raman Spectroscopy, micro-Raman Techniques and High Temperature Raman Spectroscopy Techniques.All these solve the problems such as fluorescence interference and insensitivity,which greatly expands the application range of Raman spectroscopy.These techniques may be generally grouped into the categories of physical/chemical, optical properties, chemometric methods and other unconventional methods. This review briefly describes the fundamental principle and implementation of each group of the methods, and makes comparison between those major categories of techniques.

In this study the surface enhanced Raman spectroscopy (SERS) was employed to study the detection of 2-MBI. The self-assembly silver nanoparticle films on glass slides were used as SERS substrates. SERS spectra were obtained and the characteristic bands were assigned. The time and concentration dependent experiments were conducted and finally the optimized experimental conditions were confirmed to achieve the qualitative and quantitative analysis. The SESR band at 411 cm-1 was selected as the characteristic peak to do the qualitative and quantitative analysis. The results show that there was a linear correlation between the band intensity and the minus logarithm of concentration in the range of I=1 2378logc+8 3263, while the linear correlation coefficient was 0999 8. The relative standard deviation was between 0025~0084. The detection limit was 10-7 mol·L-1. It is concluded that this research has a great potential application in 2-MBI detection.

In this paper, Fe3O4 magnetic nanoparticles were firstly synthesized with co-precipitation method and the Fe3O4/Ag magnetic coating modified material which has high SERS activity was further prepared by reducing sodium citrate. The structure and morphology were characterized with UV-Visible absorption spectroscopy, energy spectroscopy and transmission electron microscopy. It was found that Fe3O4/Ag material with regular morphology and the nanoparticle diameter is about 30~60 nm. Fe3O4/Ag material can easily be collected by magnets to meet the requirements of dispersion, extraction and re-enrichment under magnetic testing. Then, the theoretical and experimental Raman spectra and assignments of oxamyl on Ag surface are obtained by complexes of Oxamyl, Oxamyl-Ag and Oxamyl-Ag4 molecular structure calculation optimization based on density functional theory (DFT). Surface-enhanced Raman spectroscopy (SERS) is used to investigate the adsorption behavior and enhancement effect of oxamyl on Fe3O4/Ag and the enhancement factor of oxamyl on Fe3O4/Ag surface is calculated as 208×105. The results show that Raman spectra of the determination and the theoretical calculation have good consistency, with more Ag atoms bonded to oxamyl when closer to the NRS. Then, oxamyl is absorbed on Fe3O4/Ag by double bond side N atom and S atom. The double bond side N atom is adsorbed on the Ag surface preferentially, then the whole molecule near the Ag surface. At last the double bond side N atom and S atom adsorbed on the Ag surface together. The proposed Fe3O4/Ag magnetic nanocomposites have significant absorption enrichment and Raman enhancement effect, so Fe3O4/Ag can be used as SERS substrate to achieve rapid analysis and detection of pesticide residues oxamyl.

In this paper, polycyclic aromatic hydrocarbons(PAHs)vibrations law was studied based on Group Theory, and Raman polarization reduced the interference of non-characteristics peaks in fingerprint region of PAHs which would improve the Raman discrimination among 16 PAHs. The Group Theory analysis showed that 16 PAHs assigned to Cs, C2v, C2h, D2h point group separately; A′, A1, Ag, Ag vibration modes of the four point group were fully symmetric vibration and the remaining were non-totally symmetric vibration, where fully symmetric vibration of four point groups were Raman-active. Gaussian09 hybrid density functional calculation integrated with group theory analysis indicated that: PAHs Raman spectroscopy of quantum chemical calculations achieved significant consistency with the result of group theory analysis; fully symmetric vibration distributed Raman shift throughout the region, covering all groups vibration mode; in addition, fully symmetric vibration would activated stronger Raman peak which exhibit good stability. Therefore, based on the representativeness, stability and prominence, fully symmetric vibration was set as characteristic vibrations of 16 PAHs. What’s more, the research fund that, the Raman polarization effect was directly related to vibration symmetry, thus, Raman spectroscopic polarization effects was exploited to enhance character Raman peaks and reduce non-feature peak intensity. Signal to noise ratio (SNR) of characteristic Raman peaks was ameliorated as 652%~182% through selective modulation of the Raman polarization effect. The improvement of signal quality demonstrated that the noise elimination method of Raman polarization effect which based group theory was an effective approach to improve the efficiency of the Raman synchronization analysis of PAHs. Accordingly, the method provides a theoretical basis for synchronization Raman spectroscopy determination of 16 PAHs.

The change in material microstructure caused by ferroelectric domain switching under an alternative mechanical and electrical field is considered to be a major cause for degradation and failure of ferroelectric materials. It is shown that Raman spectroscopy could be used as a nondestructive, micro-regional and sensitive technique for in-situ observations of domain switching and microstructure changes for polycrystalline ceramics with home-made experimental apparatuses. The lanthanum-doped lead zirconate titanate (PLZT) ceramics with atomic ratio Zr/Ti=53/47 were prepared with conventional solid state reaction technique. The crystal phase and morphology of the PLZT specimen were characterized with XRD and SEM techniques, with the ferroelectric physical properties with Precision_LC system. The compressive stress was applied to the PLZT specimen and in-situ Raman measurements were carried out through the self made microtest mechanical loading device. The effects of stresses and polarization directions of the scattered light on the Raman spectra intensity and peak position for E(2TO) and E(3TO+2LO)+B1 soft modes were discussed and analyzed. The results revealed that both variations of peak intensity with the polarization degree for E(2TO) and E(3TO+2LO)+B1 soft modes showed an periodicity in a sine type law, which increased to the highest value at 60° and decreased to the lowest value at 150°. With the increase of the compressive stress, the peak intensity for E(2TO) and E(3TO+2LO)+B1 soft modes showed a significant decrease at the polarization degree of 0° and 60°, whiel it remained unchanged at 90° and 150°. The compressive stress has no effects on the peak position for E(2TO) and E(3TO+2LO)+B1 soft modes.

In the present article, normal Raman spectra (NRS) and surface-enhanced Raman spectra (SERS) of L-cysteine (L-Cys) included liquid and solid sample, the unique possessing the reducing group, on the silver nanorodes were analyzed. The results showed that the strengthen of peaks were enhanced relatively. The vibrational and enhanced peaks were assigned. Adsorption models of L-Cys on the silver nanorodes have been investigated. The S—H stretching vibration absorption of solid NRS was found, which was disappeared on the SERS, which showed that the ν(S—H) bond was formed by drawing lone pairs of electrons on the sulfur atoms and silver nanorodes. The vibrations of ν(C—O) and ν(C—N) was enhanced obviously. The results explain that the long pair electrons of L-Cys were adsorbed on the silver nanorodes with moving to the low wave numbers. At the different pH values, all the different shifts were expressed and adsorption behaviors were changed. When the pH values reached number of 6, the vibrations of ν(S—H) were disappeared, it is shown that it was formed the stable vibrations of ν(Ag—S). With the pH values tended an alkalinity, but carboxyl groups were enhanced because of connection with silver nanoeodes. Under the condition of pH values 7, vibrations of ν(Ag—S) were constituted meanwhile had the stable vibrations of ν(C—O) and ν(C—N), so it was selected the pH values 7. In the systems containing different metal salts including Na+, Mg+, Cu2+, etc, it was found that the molecular structure of the L-Cys was changed under adding metal salts with Al3+, Cu2+, Zn2+, Cd2+ and Hg2+, the ability depends on metal ions and carboxyl groups were conjugated. UV-Vis absorption of silver nanorods was observed at 414nm, when it was changed under adding the metal salts. But the maximum absorption peaks were small changed, which had not assembled. Cu2+, Zn2+, Cd2+ and Hg2+ were all created that the groups ν(C—S) was appeared the two weak peaks near for 661 cm-1. The Al3+ came into precipitation with carboxyl groups easily, so the SERS was the weakest to low resolution. With the radius of metals (Cu2+, Zn2+, Cd2+, Hg2+) grow, the interaction was enhanced with sulfur atom. The Cd2+ and Hg2+ belonged to soft acid and S2- to soft base, so both were had large force. The SERS of complexes of cupric ion because of unstable (n-1)d9 electron configurations with L-Cys were reduced because of precipitation combining cupric ion with sulfhydryl groups to obtain the insoluble thiolate salts. The SERS of complexes of mercury ion with L-Cys only appeared the vibrations of ν(C—O), without any other vibration. The structure of L-Cys to join the mercury ion was destroyed completely. Though alternating the condition of pH value, proportion and concentration, the SERS of complexes of metal ions with L-Cysteine was changed. The results show that the strengthen of peaks were decreased as the pH value, proportion and concentration increased, which provides important information for the protein denaturation and heavy metal pollution.

With the continuous progress of society, the food industry has been developing rapidly. At the same time, food safety issues also emerge in endlessly. Due to the low price and good effect on the preservation of food, synthetic antioxidants are often excessively added in food by some food producers, which endangers people’s physical and mental health seriously. Therefore, the detection of synthetic antioxidants in food is very necessary. Butylated hydroxyanisole (BHA) and tertiary butyl hydroquinone (TBHQ) are two common synthetic antioxidants. In the experiment, the Raman spectra of BHA and TBHQ were detected by using Confocal Microprobe Raman Spectroscopy and the Raman scattering spectra of the samples were obtained. In theory, the molecular structures were optimized and the Raman spectra of these samples were calculated by using Density Functional Theory(B3LYP) and 6-31G(d, p) basis set, and the intensity spectral was also obtained. By comparing the theoretical spectra with the experimental spectra, Raman characteristics of BHA and TBHQ were obvious with intensive Raman activities, the vibration frequencies showed a good agreement between experimental and theoretical results. In addition, the infrared activity and Raman activity of BHA and TBHQ molecules and the corresponding vibrational modes of each frequency spectrum were assigned. The results showed that the vibrational frequencies are the characteristic structure of the material, which can be used as the basis for identification and identification. The Raman spectra of BHA and TBHQ were discussed in the paper, and the theoretical mechanisms were analyzed, which provided theoretical and experimental basis for the application of Raman spectroscopy in the field of food additives detection. The study provides a theoretical and experimental basis for the application of Raman spectroscopy in the field of food additives detection.

Laser induced fluorescence technique has been considered as one of the most effective means for the detection of marine oil spills, while its feasibility was limited by the fluorescence signal resulted from chlorophyll and CDOM in natural water. To eliminate those influence during the detection, a LIF polarization experimental setup with 532 nm cw-laser was built up and used to investigate the polarization characteristics of LIF spectra of six oil samples with various densities as well as natural water sampled from the pond. It is found that the LIF spectra of all six oil samples possess obvious polarization characteristics, and are significantly different from that of natural water which is totally unpolarized. With this difference, the interference of chlorophyll and CDOM can be excluded. It also reveals that the polarization characteristics of LIF spectra are distinctive among different samples. With the wavelength increasing, the LIF DOP of oil samples decreases gradually under linearly polarized excitation, and the DOP decrease of heavy and light crude are largest and least respectively while that of diesel remains the same. When the polarization states of excitation laser changes cyclically, it is observed that the LIF DOP of all six oil samples oscillate periodically with it in the same trend. With respect to the variation range of the LIF DOP, the medium samples exceed the light samples but are inferior to the heavy ones. So it can be inferred from the results that the wavelength variation as well as excitation polarization response of the LIF DOP of oil samples are highly likely correlated to the density of the sample, which means the polarization characteristics of LIF spectra can be used as auxiliary parameters with which identification of oil spills might be successfully achieved.

Metal-organic supramolecular with well-defined nanosized molecular cavity is able to encapsulate some special guest substrates so that they have been widely applied in molecular recognition and molecular separations. In this work, a highly sensitive recognition of biological molecular γ-glutamyl-cysteinyl-glycine (GSH) was achieved with a trinuclear zinc-based metal-organic cyclohelicate fluorescence probe M-1, which was assembled with zinc ion and two tridentate (N2O) ligand with dansyl sulfonamide group and hydrogen bond site. The recognition process for GSH with M-1 was determined with 1H NMR, ESI-MS, UV-Vis and fluorescence spectra. To establish the recognition mechanism of GSH, its component amino acids (Cys, Glu, Gly) were investigated by spectroscopic titrations. The results show that the M-1 with trinuclear structure exhibits high stability in a water/DMF 1∶9 solution. UV-Vis adsorption titration revealed that a significant absorbance increase at 303 nm with the addition of GSH to the M-1 solution, but an absorbance decrease was observed at 380 nm. A sharp isobestic point was obtained at 330 nm. In addition, based on the UV-Vis adsorption titration results, ESI-MS analysis of M-1 confirmed that 1∶1 complexation stoichiometry of the host-guest behavior was obtained for GSH and the association constant (log KGSH) was calculated as 462±015. Moreover, 1H NMR titrations of M-1 upon the above amino acids revealed that the Glu residue of GSH was sent into M-1 cavity through the static interactions between the COO- groups and metal ions. In addition, it was found that the fluorescence intensity exhibits a two-fold enhancement, with the emission wavelength red-shifted from 510 to 540 nm upon the addition of GSH into M-1. Upon the addition of Cys and Glu in the solution of M-1, the luminescence intensity exhibits 04 times and 02 times enhancement, respectively, with the emission wavelength not being shifted. On the contrary, no change of the luminescence intensity was observed after adding the Gly to the solution of M-1. Based on the above analysis, it is confirmed that the joint effects of size limitation of the M-1 cavity and the hydrogen bonding interactions between Cys moiety of GSH and the amide groups sited in M-1 molecuar will generate measurable spectral changes, which lead to visualizing the highly sensitive recognition for GSH. The low detection limit was up to 30×10-6 mol·L-1.

In order to realize the on-line measurement of chemical oxygen demand (COD) in dyeing wastewater after sewage treatment, and to overcome the disadvantages of the standard method and the rapid spectrophotometric method, a COD detection method based on UV-Vis spectroscopy with multivariate calibration was developed in this study. The mixtures of dyes were selected as the researching examples. A novel self-developed optical fibre sensor system was used to directly measure UV-Vis spectroscopy of dye solution. The system could realize on-line in-situ detection of the spectrum for higher concentration solution, without sampling and dilution process. In this study, both methods, principal component regression (PCR) and partial least squares (PLS), were used to develop regression models (Absorbance-COD) respectively to predict COD of training set and prediction set after the spectrum preprocessing including z-score, smoothing, 1st derivation, etc. With experiments using mixtures of dyes solution, the results show that PCR model with z-score preprocessing performed best in the three preprocessing methods (0961 for determination coefficient R2, 218 for root mean square error of prediction (RMSEP)). Further study identified that using z-score, PLS model (0974 for R2, 196 for RMSEP) achieved better results than PCR did. The results indicated that without the process of digestion, it was feasible to use UV-Vis combined with z-score preprocessing and PLS calibration for COD detection. The method could apply to the rapid and accurate determination of COD in mixtures dyes solution and proved to be successful in enhancing the prediction performance of COD and showed good potential to be applied in on-line water quality monitoring. The overall results showed that the self-developed system could be applied to on-line detection of COD in mixtures dyes solution. This study laid a foundation for further implementation of on-line in-situ detection of COD and other water quality parameters of dyeing wastewater.

The setup of dynamic synchrotron radiation dichroism spectroscopy (SRCD)is discussed by using continuous flow probe with microfluidic mixer, developed at 4B8 ultraviolet vacuum spectroscopy beamline at Beijing Synchrotron Radiation Facility. The quartz microfluidic mixer was fabricated with deep ion etching with channel depth down to 445 microns. The mixer is designed on serpentine configuration to reach the effective mixing. The mixing efficiency was evaluated based on fluorescence image of the mixing solution under practical high viscous solution condition. Dynamic SRCD measurement with mixer was validated after implementing focus position feedback, since wavelength dispersion of the focusing lens results in the changes of focus spot position during wavelength scan. The time range covers from 45 to 270 ms at present under 500 (L·min-1 flow rate within the wide observation channel. The performance of the time-resolved SRCD is demonstrated in snapshoting the folding of cytochrome c back to 54% at 45 millisecond after completely mixing.

Detection of grey mold on tomato leaves using hyperspectral imaging technique based on competitive adaptive reweighted sampling (CARS) and correlation analysis werestudied in this paper. Hyperspectral images of eighty healthy and eighty infected tomato leaves were captured with hyperspectral imaging systemin the spectral region of 380～1 023 nm. Spectral reflectanceof region of interest (ROI) from corrected hyperspectral image was extracted with ENVI 47 software. The support vector machine (SVM) model was established based on full spectral wavelengths. It obtained a good result with the discriminated accuracy of 100% in both training and testing sets. Two novel wavelength selection methods named CARS and CA were carried out to select effective wavelengths, respectively. Five wavelengths (554, 694, 696, 738 and 880 nm) and four wavelengths (527, 555, 571 and 633 nm) were obtained. Then, CARS-SVM and CA-SVM models were established based on the new wavelengths. CARS-SVM modelobtained good results with the discriminated accuracy of 100% in both training and testing sets. CA-SVM modelalso performed well with the discriminated accuracy of 9159% in the trainingset and 9245% in thetesting set. It demonstrated that hyperspectral imaging technique can be used for detecton of grey mold disease on tomato leaves.

A novel polyphenolic compound, named Oxovitisin, with unique lactone pyranone ring and non-oxonium structures was prepared. In this paper, Oxovitisin A was synthesized with two-step reactions in micro-oxygenation system using carboxypyranoanthocyanins formed from pyruvic acid and anthocyanins. The fraction of Oxovitisin A was isolated by a combination of several chromatographic techniques and identified with HPLC-DAD-EI-MS/MS. The results showed that the purity of Oxovitisin A could reach more than 99% after purification. The study investigated the florescence spectra of Oxovitisin A, the effect of different pH value on UV feature and color parameters. The antioxidant activities of Oxovitisin A were evaluated by using a BPCL Ultra-weak luminescence analyzer in vitro, which were compared with that of Vitisin A, Mv-3-gluc and Vitamin C. The results revealed that Oxovitisin A had an obvious fluorescence peaks under the excitation wavelength of 440 nm, but no intensity of florescence was detected on Vitisin A and Mv-3-gluc. Analysis with UV spectroscopy and color parameter variations method indicated that Oxovitisin A had a higher structural and color stability. All four compounds (Oxovitisin A, Vitisin A, Mv-3-gluc, Vitamin C) showed strong antioxidant activity in scavenging O-2 (IC50 of 714, 307, 19, 28 μg·mL-1, respectively), ·OH (168, 3524, 2854, 8441 μg·mL-1, respectively) and H2O2 (1311, 0409 8, 0288, 3265 μg·mL-1, respectively). However, Oxovitisin A showed the highest antioxidant ability in scavenging free radical compared with Vitisin A, Mv-3-gluc and Vitamin C.

An academic model and a kind of experimental method are built in this paper to efficiently revise influence on results from surroundings and medium in thermometry.This revised method, taking into consideration of the attenuation coefficient of the irradiator from its surrounding, can dramatically improve the precision and universality of thermometry technology based on gray-body. First, accurate fingerprint spectrum of the irradiator in given airborne is obtained via using the multichannel CCD image spectrometer, which is made equivalent to a gray-body model at the same time make it. Then, this irradiator is put into an uncharted environment and medium to measure its radiation spectrum repeatedly.Besides, a gray-body model which contains attenuation properties from determinand is buit. Finally,this paper precisely conclude the temperature of the irradiator in exact environment and medium by comparing the graybodies in two above situations. The paper tests the universality and veracity of this thermometry technology and revised method via a series experiments about the same kind radiators in different environment and medium.

Visible and near infrared (VNIR) has been widely used to estimate various soil properties. The construction of calibration dataset during the VNIR estimation of soil properties not only influences the representative of the calibration dataset, but also on prediction accuracy of models. Current strategy for calibration dataset construction combines VNIR spectra with Kennard-Stone (KS) algorithm. However, this strategy neglects the fact that soil reflectance spectra are a comprehensive reflection of soil properties rather than a specific component. As a result, the constructed dataset from this approach may be not good enough to represent the relationships between soil spectra and the target soil component. Given that different spectral transformations could be helpful to highlight the spectral characteristics of target component, they might be also useful in the selection of samples for model calibration. The aim of the study is to explore the potentials of the combined approach of different spectral transformations and KS algorithm in the construction of calibration dataset and the VNIR estimation of soil total nitrogen (TN). It is hypothesized that the proposed approach could help to better select samples for calibration, which are more representative comparing with those selected by KS algorithm using sample reflectance spectra. A total of 100 samples have been collected from paddy soil in Jianghan Plain of Hubei Province. Five transformation methods, namely the first derivative (FD), Savitzky-Golay (SG), Standard Normal Variate (SNV), Multiple Scatter Correction (MSC) and Harr Wavelet transform have been employed for spectral transformations. Thereafter, KS algorithm is used to construct representative calibration datasets based on the differently transformed spectra. Partial least square regression (PLSR) is then used for model calibration. Whether the different spectral transformation methods can improve the representative of the calibration dataset constructed by KS algorithm is examined. The results illustrate that different spectral transformations can exert different effects on the construction of calibration dataset. The SG and Wavelet spectral transformations do not make a difference for the calibration dataset constructed by KS algorithm using reflectance spectra, with ratio of performance to standard deviate (RPD) of 141 and 127 respectively. The spectral transformations of FD, SNV or MSC do improve the calibration dataset constructed by KS algorithm, with the RPDs improve from 095, 148 and 142 to 113, 178 and 220 respectively. The study indicates that such spectral transformations as SNV and MSC could change the way that KS algorithm constructs calibration dataset and improve its representative relationships between soil spectra and soil TN. Therefore, we conclude that the proposed strategy for calibration dataset construction holds great pontentials to improve the model prediction capability in the VNIR estimation of soil TN.

Forest stock volume (FSV) is an important factor in the investigation of the forest stand and the main indicator to evaluate forest. The traditional methods of forest stock volume measurement are time-consuming and low efficiency. In remote sensing multiple linear regression method the accuracy is low and it is difficult to achieve accurate forestry requirements. As a self-improvement and automatic method which using lots of training data, machine learning can approach any nonlinear system model to improve prediction accuracy. Take into account spectral factor, texture factor, topographical factors in study area JIUFENG forest. BP-FSV, LSSVM-FSV and RF-FSV multi-spectral forest volume estimation models were established using BP neural network (BP), least squares support vector machine (LSSVM), random forest (RF) method in machine learning. Ground-angle gauge plots measured data, forest resource in subcompartment inventory data for management, forest sub-compartment map, model in conjunction Landsat8 OLI multispectral remote sensing data of sub-forest types were used for forest volume inversion. Programming in Matlab 2014a realization, BP-FSV Model of BP neural network and LSSVM least squares support vector mechanism LSSVM-FSV model were compared and analyzed based on R2 and RMSE. The results showed that: the p value tested between the predicted values from BP-FSV, LSSVM-FSV and RF-FSV model and observed values is less than 005. It indicates that there is no significant differences between the predicted and observed values of forest stock volume, It shows that the predicted results with the models are ideal, and it is feasible to predict forest stock volume by the models. The model established can improve the forecasting precision of forest stock volume through inversion combining with image spectral, textural, and terrain factor. RF-FSV model in coniferous forest, broad-leaved forest and mixed forest have shown a strong predictive ability, higher than BP -FSV model, which is above or close to LSSVM-FSV model. the RF-FSV model training and predicting accuracy are the highest among the three models, RF-FSV model in the training phase R2 and RMSE is 0839 and 13953 3 in coniferous forest, in broad-leaved forest is 0924 and 7634 1, for mixed forest 0902 and 12153 9. In the prediction stage R2 and RMSE in coniferous forests is 0816 and 15630 1, in broad-leaved forest 0913 and 4890 2, in mixed forest 0865 and 9344 1, it can provide a new method for forest stock volume prediction with better prospects.

Soil hyperspectral technique was considered to be a fast, non-destructive and cost-effective alternative method for reliably analyzing soil organic matter content (SOMC). Nevertheless, hyperspectral technique challenged to use in the field, because several external environmental factors, such as soil moisture, temperature and texture, were uncontrolled, which could impact spectral reflectance seriously. Furthermore, soil moisture content (SMC) was an prime limiting aspect for hyperspectral field applications, which showed sensitive influence on the Vi-NIR optical domain. With the aim to remove the effect of SMC on the improvement of SOMC prediction, 32 fluvo-aquic soil samples at 0～20 cm depth were collected from Qianjiang in Jianghan Plain, which were rewetted in laboratory. 192 spectral reflectance from 6 levels of SMC were measured using ASD FieldSpec 3 and normalized using standard normal variate (SNV). Meanwhile, the influence of SMC on the soil spectra was analyzed and discussed. Specifically, we would like to investigate the external parameter orthogonalization (EPO) algorithm to remove the SMC effect on the spectral calibration, and the feasibility of EPO corrected spectra for estimating SOMC by comparing the partial least squares regression (PLSR) prediction results of the EPO uncorrected and corrected spectra. Results showed that the SMC had a large influence on soil spectral reflectance, which masked the subtle responses of SOMC on reflectance. The SNV transformation could not correct the differences between the dry soil spectra and the spectra obtained at various of SMC. However, the spectra at different levels of SMC were unified after EPO correction. Using the PLSR model calibrated with the EPO corrected spectra, the model accuracy was significantly improved relative to the EPO uncorrected spectra, and its values of R2, RPD for the predicted model were 084, 250, and the EPO-PLSR model could estimate SOMC comprehensively and stably, which indicated that the effects of SMC on the spectra was successfully eliminated. Thus, in the future, this approach may facilitate the proximally sensed field spectra for rapidly measuring SOMC across this study area.

The pollution concentration prediction model of lubricants based on the principle of reflection spectrum is studied. Pure oil and full pollution oil are chosen as experimental materials. Different concentration samples are gradually prepared by equivalent volume method. The spectrometer of 200~850 nm band range is used to measure the samples. Xenon lamp serves as excitation light source. After adjusting, remain unchanged the distance and geometry azimuth between the detector probe and the sample, spectral measurement can be just conducted. The spectral reflectance experimental results show the higher contamination of the lubricants, the lower intensity of the reflected spectrum. In the variable step size algorithm on the original experimental data sparse sampling based, Correlation Coefficient, PCA, and PCA combined with Correlation Coefficient method (PCA-Correlation Coefficient) are respectively adopted to select advantage characteristic wavelength of lubricating oil in the wide band of 220~780 nm, and the index regression model is established about oil pollution concentration and spectral reflectance. Test results show that when the concentration is greater than 006, the index regression model of pollution concentration and spectral reflectance at 37893 nm which is selected by PCA-Correlation Coefficient can well realize the prediction and estimation of pollution concentration of lubricant oil. So the regression model based on PCA-Correlation Coefficient to select advantage wavelength is suitable for the quality estimation of lubricating oil with high pollution concentration. Because of the specific conditions of the concentration and mixed medium, the model does not obey Lambert-Beer Law, which apply to low concentration, uniform and transparent solution. The paper provides a feasible experimental basis for the further to achieve the working lubricants pollution concentration with reflection spectrum method online, fast and accurate determination.

Accurate color matching of mineral pigments is a key to attaining high-quality restoration and high-fidelity reproduction of the cultural heritage murals. The particle size of mineral pigments is an important factor affecting color information and spectral reflectance. Accurately obtaining the spectral reflectance of mineral pigments on the mural surface facilitates the identification of pigment particle size. However, spectral information which is disturbed cannot match with the spectral database of mineral pigment particle sizes accurately. Therefore, determining the effective particle size from the spectral information is impossible. The ratio derivative method is proposed to compensate for the disturbance. The spectral information is converted from spectral reflectance space to ratio derivative spectrum space, which reduces disturbances and enhances the spectra information characteristics of mineral pigments. Spectral matching is then performed in the ratio derivative spectrum space. In the experiments, Azurite and Malachite mineral pigments, which are frequently used in murals, were utilized as color samples disturbed by substrate and white pigments. The proposed method was used to analyze the experimental sample data. Results of spectral angle measurement and matching of the spectral curve in the ratio derivative space showed that matching accuracy can meet the requirements, verifying the validity of the method. The proposed method solves the problem of inaccurate matching of the disturbed spectral reflectance and provides accurate particle size reference information for color matching of mineral pigments during mural restoration.

Glucose is one of the most important organic molecules in life activities. It is significant to study the absorptive fingerprints of glucose in terahertz band and carry out quantitative and qualitative analysis research. Terahertz is specific for macromolecules. As for the rotational and vibrational modes within a molecule, when terahertz spectra penetrate the macromolecules, they have fingerprints in terahertz wavelength. This feature can be used to identify macromolecules. In this paper, D-glucose anhydrous was selected as the research object. Terahertz time-domain spectrum of D-glucose anhydrous was measured using Terahertz time-domain spectroscopy technique first and then the frequency domain spectrum was calculated with Fast Fourier Transform (FFT). The method of the Dorney and Duvillaret were used to process the frequency spectra to get the absorption coefficient. The absorption features of D-glucose anhydrous samples were studied and then mathematical models of quantitative relations between D-glucose levels and its absorptive spectroscopy were estimated. The results showed that, D-glucose anhydrous has remarkable absorptive fingerprints in terahertz band, and the regression model based on sample fingerprints using multivariate linear regression method performed well when compared with the partial least squares method. Its correlation coefficient and the error of mean square root of the calibration set model was 0977 2 and 0061 6 respectively, and the correlation coefficient and the error of mean square root the of the prediction set model was 0992 7 and 0055 2 respectively, which showed that terahertz time-domain spectroscopy technique can be used for quantitative and qualitative analysis of D-glucose anhydrous. It provides a reference for applications of rapid detection of the glucose content in fruits, vegetables, food and medicine in future using terahertz spectroscopy.

In this paper, spectral diagnosis incorporated with high-speed imaging technology was employed to research arc characteristic of a new proposed process of TIG welding filled with flux-cored wire. The droplet transfer modes were studied by observing the high-speed images. The spectral information was acquired by scanning the spatial points of the arc for marking some elements and the active elements K and Na of the powder were tracked to determine the distribution of the powder composition, and calculating the temperature distribution of the arc by Boltzmann plot method. The arc temperature distribution was analyzed in different droplet transfer modes. The results showed that three typical droplet transfer modes of TIG welding filled by flux-cored wire were obtained: droplet transition (2 mm), slag column transition (5 mm) and bridging transition (7 mm) by adjusting the horizontal distance between wire and tungsten electrode tip. The active elements such as K, Na of the powder were in the arc space above molten pool, and their distribution was affected by the horizontal distance between wire and tungsten electrode tip. The smaller distance means the closer distribution of active elements to tungsten, which leads to the tungsten electrode was polluted. The arc temperature distribution of no filler wire TIG welding was bell-shaped, and the isotherm was approximately symmetrical about the tungsten axis. Compared with no filler wire TIG welding, the distortion of arc temperature distribution was influenced by different droplet transfer modes. The temperature distribution severely distorted under droplet transfer mode accompanied with more spatters during welding. In terms of the droplet transfer mode, smaller distortion of temperature distribution and stable welding process occur in slag column transition and bridging transition which are suitable for the proposed TIG welding process.

It takes a plenty of time for model updating and maintenance when use visible near infrared spectroscopy to measure the soluble solids contents(SSC)of fruits online and each of the fruit varieties need to be modeled separately. This paper aimed to explore the feasibility of establishing the online detection universal mathematical models of thin skinned fruits such as the apples and pears . The online visible near infrared spectroscopy diffuse transmission spectra detection system which was designed by ourselves was applied. Under the condition of integral time 80 ms, single speed 5 s-1 collecting visible near infrared spectroscopy diffuse transmission spectra of Xinli No. 7, Dangshan pear, Yulu pear and Fuji apple. The spectra response characteristics of near infrared diffuse transmission of four kinds of fruit were analyzed by using the variation coefficient method and continuous projection algorithm screened the modeling spectral variables of the universal mathematical mode and establish partial least squares and least squares support vector machine universal mathematical models of apple and pears finally. New samples were used to evaluation the predictive ability of the universal model. The coefficient variation method by screening similar band to established the universal mathematical model of partial least squares spectral had the highest prediction accuracy. Pear and apple pear universal models correlation coefficient (rp) of prediction are 088 and 093 and the root mean square error of prediction (RMSEP) are 049% and 055% respectively; the correlation coefficient of independent model for predict Xinli No7, Yulu pear, Dangshan pear and Fuji apple were 093, 091, 088 and 095, and the root mean square error of prediction are 040%, 042%, 041% and 046% respectively. The prediction accuracy of the universal mathematical model is slightly lower than the independent mathematical model prediction accuracy of each variety, but the generality of universal model is higher than the single model. The experiment results shows that using coefficient variation method combined with partial least squares method to establish the online detection general mathematical model of thin skinned fruit is feasible in achieving four kinds of fruit sugar online detection .

Soluble solids content (SSC) and firmness are not only important indicators for grading of Hami melon but also characteristic factors to determine its maturity. Thus, in order to achieve automatic grading and suitable picking of Hami melon, hyperspectral imaging technology combined with different characteristic wavelengths selection methods were used to simultaneously assess SSC, firmness and maturity of Hami melon. Successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS) and CARS-SPA algorithm were used to select the characteristic wavelengths of SSC and firmness of Hami melon from MSC pretreated spectra. The full spectral variables and selected wavelength variables were used as the inputs to build SVM model for determination of the SSC, firmness and maturity of Hami melon, respectively. The results indicated that the MSC-CARS-SPA-SVM models achieved the optimal performance for SSC and firmness of Hami melon. The correlation coefficient of prediction set (Rpre) , the root mean square error of prediction (RMSEP ) and the relative prediction deviation (RPD) were 0940 4, 0402 7 and 2941 for SSC and 0825 3, 3522 and 1771 for firmness, respectively. At the same time, the full spectrum, selected characteristic wavelengths for SSC or firmness and feature fusion by the principal component analysis (PCA) were used to build SVM discriminatory models for maturity of Hami melon, respectively. The results showed that the discriminant results of CARS-PCA-SVM model was agreement with the FS-SNV-SVM model, the recognition rate of calibration set and prediction set were 95% and 94%. The research indicated that it is the feasible to use hyperspectral imaging technology combined with different characteristic wavelengths selection methods can be used to evaluate SSC, firmness and maturity of Hami melon simultaneously.

Laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) has become one of the major techniques for in situ microanalysis of element and isotopic compositions in earth science and other related fields. Because of the extraordinary short pulse width of femtosecond laser, thermal effect induced elemental fractionations that limit the usage of traditional nanosecond laser ablation are significantly reduced or eliminated in terms of femtosecond laser ablation analyses. There is an increasing trend of developing femtosecond laser ablation analytical technique and its application in earth sciences. In this review, the basic properties of femtosecond laser ablation system (the features and generation of femtosecond laser, the different femtosecond systems) are introduced, the ablation mechanisms of femtosecond laser on geological samples were discussed with emphasis on the way of samples absorbing the laser energy, the generation and distribution of different aerosol particles, the features of ablation pits, and the unique advantages of femtosecond laser ablation. The applications of fs-LA-ICP-MS technique concerning elements and isotope analyses of geological samples over the past ten years are also studied. At last, the prospects of this technique are viewed.

The feasibility of fast detection of caffeine content in coffee beans based on laser induced breakdown spectroscopy (LIBS) combined with chemometrics methods was studied. The coffee beans were grinded. 05 g of powerd material was transformed into a disk by manual tableting machine. 60 disks of coffee bean material were prepared for LIBS data acquiring. The samples were pretreated by acid wet digestion, and actual caffeine content of each sample was obtained by automic absorption spectrometer (AAS). Baseline correction was applied on the original spectral data to eliminate the negative values. Wavelet transform (WT) was used to reduce the noise, wavelet basis function is Daubechies 5 (db5) and decomposition level is 10. Normalization were employed to deal with variations caused by matrix effects and experimental conditions. The partial least squares (PLS) model on full data appeared to over-fitting. Regression coefficients and principal component analysis (PCA) were used to select characteristic variables, respectively. PLS models and back propagation (BP) neural network model were built by the variables selected. In the PLS model on the variables selected by regression coefficients, correlation coefficient of calibration set (Rc) was 096, correlation coefficient of prediction set (Rp) was 091. In the PLS model on the variables selected by PCA, Rc=094, Rp=090. In the BP neural network model on variables selected by PCA, Rc=096, Rp=096. The characteristic variables selected by two methods correspond to C, H, O, N, Na, Mg, Ca, Fe, Mn. The PLS models on the variables selected by regression coefficients and PCA both performed well on prediction samples. It demonstrated the certain relationship existing between the elements and caffeine content and the selected variables were effective. But the precise relationship bwtween C, H, O, N, Na, Mg, Ca, Fe, Mn and caffeine content needs further study. The BP neural network model on variables selected by PCA performed better than the PLS model, which demonstrated the selected variables were suitable for different modeling methods. The study showed LIBS could be applied to fast determination of caffeine content within coffee bean combined with chemometrics methods. The method of caffeine content detection presented by this study is innovative.

Laser-induced breakdown spectroscopy (LIBS) combined with support vector machine (SVM) was adopted to identify 20 kinds of different colored industrial plastics from different manufacturers in open air. The experimental parameters of spectral acquisition were optimized firstly. 100 spectra recorded under optimum conditions were randomly and equally divided into training set and test set. 6 non-metallic characteristic spectral lines were used to avoid the interference with metallic lines. And the training time of SVM model was reduced. The results show that 996 of 1 000 test spectra were identified correctly and the average classification accuracy is reached to 996%. The classification efficiency is improved with 6 non-metallic characteristic spectral lines. The research demonstrates that, when fewer of major non-metallic characteristic spectral lines are used, laser-induced breakdown spectroscopy technique with support vector machine can identify more kinds of plastics with high accuracy and efficiency.

There are many methods to characterize plasma parameters for laser-induced plasma, optical emission spectra method is a very important one to diagnose laser-induced plasma parameters. In this paper, Nd∶YAG solid state laser which output 1 064 nm wavelength interact with aluminum alloy sample, the temporal evolution of spectral line profile, spectral line intensity, continuum intensity, line to background intensity ratio, spectral line broadening and spectral line shift were investigated in detail for laser induced aluminum alloy plasma. The results show that the interaction of electrons between atoms and ions are very intense, which leads to electrons production of laser induced plasma at the early stage. Stark broadening effect of spectra lines are distinct and multiple spectral lines are overlapped. With temporal evolution, the electron density and electron temperature decreased quickly, the multiple spectral lines are separated slowly, and the spectral line profile is becoming thinner and symmetric. For Mg Ⅰ 2852126 nm characteristic spectral line, the intensity increased with temporal evolution at first, the intensity reached maximum value about 100 ns, and then the intensity decreased with temporal evolution, which is due to the fact that electron and ion are dominated at early stage of laser-induced plasma, atomic spectral line is very weak, with temporal evolution, the process of recombination between electrons dominated and the atomic number density increased, when the atomic number density reached maximum value, the spectral line intensity decreased with temporal evolution because excitation temperature decreased quickly. Taking wavelength in NIST database as reference wavelength, the spectral line shift for MgⅠ 285212 7 nm and Zn Ⅱ 206200 4 nm take place red shift at early stage of laser induced plasma, the continuum intensity decreased dramatically by power law with temporal evolution, on the contrary, comparing with continuum intensity and spectral line intensity, continuum intensity attenuate sharply, the line to background intensity ratio increase with temporal evolution. This early phenomenon of laser induced aluminum alloy plasma were discussed in detail from theoretical perspective.

The combination of wavelength dispersive and energy dispersion X-ray fluorescence analysis would take both of advantage of wavelength dispersive and energy dispersive. Now, A combined wavelength dispersive and energy dispersion X-ray fluorescence spectrometer was used in analysis of major, minor and trace elements in the soil samples taken from the fields around a Pb-Zn mine. The WD-ED XRF analytical method performance was evaluated by their uncertainty. The results revealed that (1) WDXRF shows more sensitive to the light elements, such as Na, Mg, Al, Si. (2) The limits of detections (LOD) of Na2O, MgO, Al2O3, P2O5, K2O by WDXRF are lower than those by EDXRF. The LODs of of SiO2, SO3, CaO, MnO and Fe2O3 are lower than those by WDXRF. For the minor and trace elements which have heavy overlap of spectral lines, WDXRF gives lower LOD; (3) For major elements, the analytical accuracy of the elements before K by WDXRF are better than those by EDXRF. For the elements after Ca, the accuracy by EDXRF are better. For minor and trace elements, if there are heavy overlapped spectral lines, WDXRF give more accurate results. Without heavy overlapped spectral lines, the accuracy of EDXRF is better; (4) Powder pellets with wax as binder were used in WD-EDXRF analysis without any observed drop of sample powder. Soil samples were determined. Generally, no significant differences were observed between measured results and certified values. (5) The WD-EDXRF method was applied to the determination of major, minor and trace elements in the surface soils in the mining area, and high concentrations of Cu, Pb and Zn were detectable; (6) The distributions of heavy elements were obtained in soils from the agricultural fields, and the high concentrations of Pb observed, which implies that the agricultural soils may have been polluted by the mining activities. And health risks need to be evaluated further.

As the rise of heritage players market in recent years, “Lvlongjing” jade from Russia has become a favorite new gem varietiy. At present, there are disputes over the main mineral composition of the “Lvlongjing”. In this paper, a more detailed research and analysis of the fundamental nature, chemical composition, infrared absorption spectrum characteristics and mineral composition of the “Lvlongjing” from Russia has been made via conventional gemological test, electronic probe, infrared absorption spectroscopy and X-ray powder diffraction method. The result shows that the “Lvlongjing” from Russia is mainly dark green to gray-green in color, with a special surface radial pattern and the typical silky luster. Its refractive index is about 157, a density about 261 g·cm-3. The SiO2 content of the “Lvlongjing” is about 36177%~36651%, MgO content about 36439%~36730%, Al2O3 content about 11961%~12318%, FeO content about 2304%~2853%, showing a magnesium-rich and iron-poor feature. The Al/(Al+Mg+Fe) in samples studied is 0185 3~0215 9, suggesting the causes of altered mafic rocks. The Si=310~340, Fe2+/R2+=0~0024 8, showing it is a Pennine type. The infrared absorption spectrum is characterized by chlorite vibration peaks. The absorption peak near 3 673 cm-1 in high frequency region is caused by the OH stretching vibration. The absorption peaks near 1 400 cm-1 belong to OH bending frequency. Three peaks near 1 000 cm-1 are caused by the Si—O stretching vibration. The absorption bands between 400 to 600 cm-1 belong Si—O bending vibration. Three split absorption peaks near 1 000 cm-1 in the intermediate frequency region, including 1 051, 1 006 and 968 cm-1 can be identified as key evidence of the Pennines. The analysis results of X-ray powder diffraction are consistent with the chemical composition and infrared absorption spectrometry analysis, showing the major component mineral of “Lvlongjing” from Russia is Pennine, instead of Clinochlore.

In practical applications, such as CT hardening artifacts correction, dual energy CT image reconstruction and CT radiation dose calculation, X-ray energy spectrum information plays an important role. However, due to high ill-condition of system equations of transmission measurement data, statistical fluctuations of X-ray quantum and noise pollution, it is hard to get accurate spectrum estimation using existing methods such as EM method. In this paper, an X-ray energy spectrum estimation method based on adaptive TV normalization is proposed. First, the phantom materials with different K-edge in energy range of spectrum are used to reduce the correlation between the projection measurement equations. Then, the geometric parameters of CT imaging system are used to obtain the accurate transmission length information corresponding to the projection measurement data to reduce the measurement error of the projection equations. Finally, with comprehensive utilization of transmission attenuation measurement data fidelity, continuity of bremsstrahlung emission energy spectrum, discreteness of characteristic radiation energy spectrum, non-negativity and normalization of energy spectrum, average effective attenuation coefficient and other information, objective function was established using weighted TV normalization method. The parameter in normalization model was optimized with L curve guideline and searched in accordance with golden section strategy to get the best estimation result. Experimental results demonstrate that the stability and accuracy of X-ray energy spectrum estimation using the proposed method are significantly improved compared to the EM method.

In recent years, a large amount of black nephrites began to appear in domestic and foreign markets. A new kind of black nephrites was found in Dahua Yao Autonomous County, Guangxi Zhuang Autonomous Region. In order to analyze mineral composition, spectroscopic characteristics and chemical composition of Dahua black nephrites, the standard gemological methods, X-ray powder diffraction, laser Raman spectroscopy, infrared absorption spectroscopy and laser ablation inductively coupled plasma mass spectrometry(LA-ICP-MS) were used. Based on standard gemological testing, the samples showed a spot RI of 164 and a hydrostatic SG of 312. With polarizing microscope, the major constituent mineral for Dahua black nephrites is found to be actinolite(>98%). The main structure of samples is microstructure fibers woven structure. The major constituent mineral of samples is confirmed to be actionolite with XRD testing. The characteristic mesh spacing of actionolite is 8498 3 and 3145 9 . FTIR spectrum of samples are similar to that of tremolite, and main absorption bands are 1 078, 1 026, 925, 765 , 703, 659, 584, 485, 436 cm-1. Infrared absorption bands at 1 078 , 1 026, 925 cm-1 are induced by O—Si—O antisymmetric stretching vibration, Si—O—Si antisymmetric stretching vibration and O—Si—O symmetric stretching vibration. Infrared absorption bands at 765, 703, 659 cm-1 are induced with Si—O—Si symmetric stretching vibration. Infrared absorption bands at 584, 485, 436 cm-1 are induced with Si—O bending vibration. Laser Raman spectroscopy testing results show that Raman peaks of samples are located at 3 500～3 800 and 119～1 054 cm-1. Raman peaks at 1 055, 1 029 and 930 cm-1 are induced by Si—O stretching vibration which is the characteristic vibration of amphibole. Raman peaks at 744 and 671 cm-1 are induced by Si—O—Si stretching vibration. 671 cm-1 is the strongest Raman peak, which represents symmetric stretching vibration of bridge oxygen in silicon-oxy tetrahedron. Raman peaks in the range of 3 800～3 500 cm-1 are induced by M—OH stretching vibration. These Raman peaks reveal bonding vibration information between cations in M1, M3 and OH-. Raman peaks at 3 628, 3 647, 3 664, 3 678 cm-1 are induced by OH- stretching vibration. According to LA-ICP-MS, the chemical compositions of samples are SiO2(524%), FeO(2195%), CaO(125%) and MgO(124%). A spot of Al2O3, MnO, Na2O, P2O5, K2O and TiO2 were found. Having high concentrations of Fe is a notable characteristic of Samples. The result of Mg/(Mg+Fe) is 0504, suggesting that Dahua black nephrites belong to actinolite jade in nephrite series. High-Fe actinolite is responsible for the color of Dahua black nephrites.

Aiming at addressing the technical difficulties in the determination of trace silver in mine tailings, an energy dispersive X-ray fluorescence energy spectrum method based on ultra short optical path is proposed. It improves the measurement resolution of the elements, the efficiency of sample analysis and reduces the power of the light tube. What’s more, it extends the service life of the instrument. Energy spectrum system optimized filter, detector shielding design. Besides, since Teflon has no X-ray scattering as collimator , the detection of trace elements for silver is achieved. In actual tailings test, silver detection limit is up to 1 mg·kg-1. RSD is between 01 percent and 26 percent while accuracy is between 115% and 87%. With the comparison of tailings, ore and concentrate test experiment, it is proved that the energy dispersive X-ray fluorescence spectrum which introduced in the method of ultra short optical path can enhance the system peak/background ratio and satisfy the requirement of the detection of trace element.

Continuum problem is a phenomenon that the continuum of spectra get off their actual continuum even break off due to interstellar extinction and flux calibration, and it will have negative impact on the subsequent process such as spectral line extraction and so on. Due to this problem and considering of the continuum features of the stellar spectra, a method of automatic detection and recognition of the continuum problem in the stellar spectra is proposed, which will improve work efficiency greatly compared with the traditional human eyes examination under the condition of maintaining high accuracy. Firstly in this method, the subclass of the test stellar spectra is confirm by calculating the spectra’s lick indices, and the test stellar spectra are normalized . Secondly, the continuum of the test stellar spectra and the template spectra are fit with the same method. The last step goes to continuum template matching. The flux differences of the test stellar spectra and template spectra at every point of wavelength in the continuum spectra will be calculated to analyze the features of its distribution. The features counted are average (called β) value and standard deviation (called δ). The percentage of points distributed in range β±ɑ*δ will be detected to confirm that if there is continuum problem. In the end, this method has been proven to have a good effect on detecting and recognizing the continuum problem spectra by a great deal of experiments.

Splicing abnormality is a phenomenon of poor continuity spectrum showed in the splicing wavelengths of the red and blue end. In the spectral processing, this problem can be caused by several factors, such as stability of instrument, observation condition, the response function and so on. It has important effect on the spectra quality whether the splicing is normal or not. In the research of this paper we define a tag on the Lamost spectra automatically to evaluate the quality of spectra splicing and it can provide users with a choice when using data. In this paper, a method of automatic detection of splicing abnormality spectra for LAMOST is proposed to improve the work efficiency greatly.With this method, first of all, we get the red end and blue end of the test spectrum in the splicing wavelengths after flux normalized and the feature lines deleted. Then, we fit the continuum in the red and blue end separately. Thirdly, we calculate the differences of flux between the two fitted curves at a series of independent variables with regular intervals. We get the average and standard deviation of the differences and the area of the two curves formed. Based on the statistics above, an evaluation function is presented in this paper which can be used to judge whether the test spectra are normal or not and determine their abnormal class. The method has been proved to have a good effect in the reorganization of splicing abnormality spectra through a mass of experiments.

With the establishment of the theoretical model of passive CPT cesium atomic clock, developing simulation analysis and research on the relationship between the CPT signal and the parameters of cesium vapor cell, combined with the method of design and analysis for cesium vapor cell is established while the optimum design parameters are obtained. When the cesium vapor cell is cylindrical, the diameter is 10 mm, the length of cesium vapor cell is 10 mm, the cesium vapor cell operating temperature is 320 K, the buffer gas pressure is 30 torr, the cesium content is 100 μg. With multi-wavelength Doppler absorption spectroscopy experiment and CPT signal lock and frequency stablish test, it is verified that the theoretical model is correct and providing for the method for the design and parameter optimization of high performance Chip-Scale-Atomic-Clock.

Hollow Waveguides (HWGs) are used in spectroscopic gas sensing devices as both a optical waveguide and gas transmission cell that provide an extended optical pathlength yielding high sensitivity measurements. Their advantages over traditional multipass gas cells are that they have a much smaller sample volume and can provide a faster response time as well as stable and flexible light path with lower cost. The studies recommend three main types of HWGs commonly used for gas sensing, namely Ag/AgI-coated hollow waveguides (Ag/AgI-HWG), photonic bandgaps hollow waveguides (PBG-HWG) and substrate-integrated hollow waveguides (iHWG), respectively. Research and development of spectroscopic gas sensing with HWG modules have been reviewed for the past few years. In addition, the application modes and fields have also been summarized. The studies show that HWGs have been coupled to FTIR, laser absorption spectroscopy (LAS) and Raman spectroscopy to replace conventional multipass gas cells. Now, a series of achievements were made and relevant applications of HWGs based gas sensing included atmospheric environment monitoring, breath diagnostics and industrial process monitoring. Particularly, the HWG sensors based on mid-infrared (MIR) LAS offer a number of advantages over other spectroscopic methods, i. e., relative simple composition, low cost, superior compatibility with various of HWGs and strong adaptability to environment, which are fairly attractive for practical application. To summarize, with the development of laser technology, optical waveguide technology and spectral technology, HWG based spectroscopic gas sensing is developing rapidly, and gradually operated from the laboratory to the field application.

By analyzing the offner spectroscopic optical system, an equation to calculate quickly the initial structural parameters is summed . Based on the calculated initial structural parameters we optimized a set of spectral optics used for short-wave infrared (1 000~2 500 nm), which has been designed with large optics aperture (F/# 22), high spectral resolution (better than 10 nm) and long entrance slit (12 mm).Within the entire field of view and wavelength, the modulation transfer function MTF is greater than 05.The complete imaging spectrometer with smaller size and light weight (less than 5 kg). The instrument test results show that the spectral linearity over the whole spectral range is good, and after spectral calibration the wavelength accuracy is more than 4 nm. The resolution tests of different bands shows that the spectral resolution over the full wavelength range is consistent with the design, and dynamic imaging experiments show that the spectral images are clear and the spectral data has good quality.

A fiber-optic sensor and its corresponding system are presented and evaluated for on-line detection of acoustic emission stress waves generated by partial discharges in high-voltage power transformer. The fiber-optic sensors are placed inside the transformer for acoustic emission stress waves detection according to its properties of small size, light weight, high sensitivity and anti-electromagnetic interference. The sensor employs a distinct Fiber Bragg Grating as sensitive unite and covers it with epoxy for the detection of acoustic emission stress waves. The sensing principle of acoustic emission stress wave detection with fiber-optic sensor is studied in detail. The reflected spectrum of the sensing grating is shifted because of the influence of acoustic emission stress waves, which leads to the reflected light intensity changes at a special frequency point, and thus the detection of the acoustic emission signals can be achieved by the measuring of the changes of reflected light intensity. The experimental model of the acoustic emission sensing system is constructed and a sensing system performance optimizing strategy is presented, by which the sensing system is enable to operate at the half-peak frequency point of the rising or falling edge, and thus the good linear output of the system is obtained. Moreover, the operating point stabilizing technology of the sensing system is studied, and a signal feedback loop is established for automatic tracking of the sensor wavelength drifting, by which the fiber-optic sensor is ensured to operate at half-peak frequency point stably. The performance evaluation on partial discharges detection of transformer is launched and the results have demonstrated that the fiber-optic acoustic emission sensors are capable of detecting acoustic emission signals by partial discharges with high sensitivity and wide bandwidth compared with conventional piezoelectric transducers.

Carbon monoxide, as a kind of dangerous mine gas, can easily accumulate in a complex mine environment poses a serious threat to the safety of miners. This paper presents a compact carbon monoxide detector. This instrument have a mid-infrared quantum cascade laser operating at 465 μm as light source, with mercury cadmium telluride (HgCdTe) detector and 12 m compact absorption path to obtain trace-CO diagnostics. Self-designed high-speed photoelectric signal acquisition system solved the signal chain impedance mismatch problem which caused by commercial oscilloscope. This new acquisition system realized 1 GSPS sampling rate and vertical resolution of 12 bit at 400 MHz sampling bandwidth which improved the detector’s sensitivity and integration effectively. This instrument use long path differential optical absorption spectroscopy (LP-DOAS) theory. The detection limit of the instrument which gives as 108×10-9 is obtained by comparing the residual between the measured spectrum and calculated theoretical spectrum with Voigt broadening. Detector’s measurement error has non-stationary, slowly time-varying characteristics. According to this feature we use Allan deviation to estimated detector’s sensitivity, after about 40 seconds the deviation curve reached the minimum. The Allan deviation value is 61×10-9. In two-hour tests, the stability of the detector is 21×10-3, for up to 12 hours of stability tests, the detector’s stability can still reach 17×10-2. This instrument has high flexibility, through the replacement of different laser with different lasing wavelength; it can be achieved on a variety of trace gas detection.

Based on the multi-spectral technology and the characteristics of CCD two-dimensional temperature field measurement, this paper proposes a colorful CCD two-dimensional temperature field multi-spectral true temperature online multi-point calibration system. With the analysis of multi-spectral measurement model and CCD measurement model, the approximate relation between the true temperature and the brightness of CCD is deduced during the gas combustion. With multi-spectral multi-points temperature measurement technology, the true temperature to calculate the emissivity and the true temperature of multi-points and use values of the true temperature, the corresponding points of CCD array can be calibrated. Applying the two-dimensional temperature field true temperature calibration system in CO2 laser welding flame, we not only get the variation between the emissivity and the wavelength but also two-dimensional true temperature distribution maps of flame of CO2 laser welding. Multi-spectral calibration technology has the feature of real time and flexible and is a really feasible temperature CCD online multi-points calibration and measurement method.

Rotatable retarder fixed polarizer (RRFP) Stokes polarimeters are widely used to detect the state of polarization of light. The orientation error of the retarder is one of important error sources of RRFP Stokes polarimeters. In order to investigate the effect of the orientation errors of retarder on measurement results, a new analytical model is proposed to express the polarimetric error resulted from it, and a methods based on covariance matrix is used to express the polarimetric error. In addition, according to the analytical error model, the optimal polarimeter configuration is obtained. During derivation, we suppose that the angular orientation errors of the retarder obey a uniform Gauss distribution. Based on the analytical model derived, it can be concluded that (1) the measurement errors induced by the angular orientation error of the retarder is inversely proportional to N; (2) the measurement errors are independent to the incident intensity s0, but seriously depend on the incident state of polarization (s1, s2, s3) and the retardance of the retarder δ; (3) the retardance ranging from 10322° to 11613°, whihc results in the minimum measurement errors induced by the orientation errors of the retarder. Finally, simulation is performed to prove that these analytical results derived agree well with simulation results.

Graphene has attracted great attention in nanoelectronics, semiconductor, because of its special structure and performance, however, since its bandgap is zero, its application is limited seriously. The multi-layer graphene is prepared by chemical vapor deposition (CVD), and then doped by Br2 is to investigate and analyze the Br2 effect on graphene bandgap. In order to compare how the Br2 effect on graphene bandgap, the Raman is measured with 633 nm He-Ne laser before and after doped, the relation between graphene bandgap shift and Br2 volume is calculated according to Raman results, the results show that: Br2 doping has influence on G band, and the G band is energy up-shifted with Br2 volume before reaching a stable value; the G/2D intensity ratio also increase with Br2 volume before reaching a stable value. The measured Raman peak position blue-shifts linearly with Fermi energy, the graphene Fermi energy is calculated according to the relation between G band peak position and Fermi energy before analyzing how the Br2 effect on graphene bandgap.

The LaBr3(Ce) detector is a new type of scintillator detector which offers better energy resolution and higher efficiency for high-energy gamma ray in comparison with traditional detectors, for instance, NaI(Tl) detector. The LaBr3(Ce) detector has merits of a high scintillation light output with a fast decay time, a high temporal and spatial resolution, good temperature characteristics and good radiation resistance. So it was researched and applied widely since it was commercially available years ago. This paper reports not only its above-mentioned properties but also its typical application studies. In the nuclear resonance fluorescence, the detector benefitted the nondestructive assay (NDA) method by shortening the detecting time while the energy resolution was still excellent. In the prompt gamma neutron activation analysis, the advantages of it were shown by comparing with the BGO detector. In the nuclear medicine imaging, the detection with the LaBr3(Ce) detector in the myocardial perfusion in mice with sufficiently precision. It had a better ability to distinguish between tumors and normal tissues than NaI(Tl) detector. In the space radiation detection, the detector was used to detect the rays with high energy, and it shows excellent radiation resistance. In neutron detection, it has competitive properties in low neutron energy measurement. After investigating the applications of the detector, we confirm the excellence of this detector and affirm it has a good prospect in the further.

Based on the principle of electronegativity, a reasonable infrared spectrum model is built, and the relationship between the vibration frequency of TiO2 infrared spectrum and the electronegativity of element is investigated. (Fe, N) codoped TiO2 samples were prepared with the sol-gel method. The crystalline phase and IR spectra of the samples were characterized with X-ray diffraction and Fourier infrared spectroscopy (FTIR). XRD phase analysis shows that amorphous structure of TiO2 samples are mainly transformed into anatase structure when the calcination temperature is 600 ℃. As the calcination temperature is increasing, the X-ray diffraction peaks of TiO2 gradually become narrower, with greater intensity, and gradually increasing crystallinity of TiO2. When the calcination temperature is 700 ℃, the diffraction peaks of anatase disappear, only the diffraction peaks of rutile phase can be observed. infrared spectrum indicate that there exists a wider absorption peak in the range of 650～500 cm-1 for (Fe,N) Codoped TiO2. Stretching vibration frequency of (Fe, N) Codoped TiO2 infrared spectra, Fe and N doped location, molecular structure and bond valence feature are obtained by the principle of electronegativity. Firstly, the reduced mass μ is computed. Then according to the relationship between classical mechanics stretching force constant k and frequency ν, molecular vibration frequency of doped rutile or anatase TiO2 with the same oxygen octahedron structure unit via combining with the relationship between the force constant and the electrical negative, the calculation of bond order. The results show that the (Fe, N) Codoped TiO2 infrared spectrum calculated by the principle of electronegativity is in agreement with the stretching vibration frequency by the experimental measurement.

There are several challenges with quantitative analysis of fluorescence components of dissolved organic matter (DOM) stem from the variability of fluorescence intensity, which is known to be highly influenced by metal ions. The quenching effect of metal ions (Cu(Ⅱ), Fe(Ⅲ), Ni(Ⅱ), Sr(Ⅱ), Hg(Ⅱ), K(Ⅰ), Mg(Ⅱ) and Mn(Ⅱ)) on the typical components of DOM in drinking water was explored using fluorescence excitation-emission matrix (EEM) or fluorescence excitation-emission matrix and parallel factor analysis (EEM-PARAFAC). Drinking water samples were collected from various sources. Results show three components (tryptophan-like, fulvic-like, and humic-like), which were identified in the DOM of drinking water samples by parallel factor analysis (PARAFAC), exhibit a linear or an exponential PARAFAC scores decrease with concentration of four metal ions (Fe(Ⅲ), Cu(Ⅱ), Hg(Ⅱ) and Ni(Ⅱ))increasing. Among these four metal ions, Fe(Ⅲ) and Cu(Ⅱ) led to a stronger quenching effect on fulvic-like and humic-like than Hg(Ⅱ) and Ni(Ⅱ). Sr(Ⅱ), K(Ⅰ), Mg(Ⅱ) and Mn(Ⅱ) had almost no effect on three components. Fe(Ⅲ) have good effects to characterize metal ions fluorescence quenching on all PARAFAC-derived components of DOM. Owing to we only consider the effect of Cu(Ⅱ) and Fe(Ⅲ) when we need quantificational measure fulvic-like and humic-like components in drinking water, calibration curves were set up to correct fluorescence data in drinking water containing metal ions. Thus, we can obtain the original fluorescence data in drinking water containing metal ions. Owing to different sources of PARAFAC-derived components scoring attenuation laws are various, the sources of drinking water is also a factor that must be considered when measuring the fluorescent components using the PARAFAC model. The results from this study confirmed the interference of metal ions on the fluorescence intensity of the main components of DOM in drinking water and the factors (Fe(Ⅲ), Cu(Ⅱ) and variability of DOM) need to be considered when measuring the typical components of DOM in drinking water with EEM. This study indicated that the application of EEM-PARAFAC in fluorescence quenching studies is a useful tool to accurately measure fluorescence components of DOM in drinking water.

Dental plaque is one of the main etiologic factors that lead to dental caries and periodontal disease, and the amount of plaque on teeth could be served as reference for the teeth health condition to some extent. Therefore, the detection of dental plaque plays a very important role for maintaining the oral health. However, identification of dental plaque is difficult for both patient and dentist because the tooth and dental plaque often look similar, especially when plaque is present in scanty amounts. Excited by the light source with the wavelength of 405 nm, the auto-fluorescence effect will appear in both dental plaque and dental tissue, but the auto-fluorescence spectrum of dental tissue mainly locates at the wavelength range of blue and green light, while the auto-fluorescence spectrum of dental plaque mainly locates at the wavelength range of red light, and the spectrum intensity caused by the different leveled dental plaque are also diverse. Based on the differences between auto-fluorescence spectra of dental plaque and dental tissues, a potable auto-fluorescence color imaging dental plaque detection system was developed. In the detection system, five surface-mounted LEDs whose central wavelength are all 405 nm are assembled as the excitation source, besides, a long pass optical filter with central wavelength of 520 nm is configured to improve the signal to noise ratio (SNR), and the excited auto-fluorescence was collected and imaged through the imaging lens to the array sensor of a color CCD with a resolution of 640×480. Finally, the amount of dental plaque is analyzed by processing the captured fluorescence images. An experiment was designed to confirm the reliability of the detection system. The anterior teeth auto-fluore