In order to realize the fast and non-contact detection of oil film thickness on water surface, a system based on laser Raman spectroscopy technologywas introduced in this paper. The 532 nm laser was used as the exciting source, and the result shows there is obvious difference between the Raman spectra of diesel and gasoline on water surfacewhich have the same oil film thickness, the spectral intensity of 97# gasoline is stronger than that of 90# gasoline at 1 651 cm-1. With the increase of oil film thickness, the spectral intensities of 316, 1 451 and 1 651 cm-1 are enhanced, the calculation factor rfilm of oil film thickness shows a decreasing trend. The experiment result shows that the Raman spectroscopy can be used as a reference for oil film thickness inthe application.

Dy3+ doped fluoride borate glass phosphors are prepared with high temperature melting method. In addition, the fluorescence spectra of glass phosphors are determined under the 453nm blue laser using an integrating sphere test system, and the related absolute fluorescence parameters of glass phosphors are obtained. Experimental and calculation results reveal that net emission spectrum power, net emission photon number and the quantum yield are identified to be 286.91 μW, 17.17×1014 cps and 25.86% in 1.0 Wt% Dy2O3 doped fluoride borate glass phosphor under the excitation of blue laser with 15.81 mW, respectively. In order to improve the quality of white light combination, 1.5 Wt% Dy2O3 doped glass phosphor is synthesized to increase the utilization of pump laser and reduce residual blue laser. The white-light emission is obtained under the excitation of blue laser with high powers, and color coordinates of white luminescence are derived to (0.316, 0.287) and (0.303, 0.268) under the excitation of pumping laser with 56.0 and 252.7 mW exciting powers, respectively. The efficient white luminescence under the laser excitation indicates that Dy3+ doped fluoride borate glass phosphors have good application prospect in laser illumination area.

As the technique of tunable diode laser absorptionscopy (TDLAS) is employed for trace gas detection, the second-harmonic background signal drifts with the changeof the temperature of semiconductor laser shells. It results in unstability of the second-harmonic signal. Its drifting can cause measurement errors. Based on the principle of TDLAS, the cause of the second harmonic of the background signal is explained. Then the causes of the background signal and its drifting influence on measurement results are analyzed. In addition, the standard second-harmonic signal is obtained after the rejection of background signal. Finally a high-accuracy temperature control systemis designed and it is equipped with air cooling and water cooling modules for auxiliary temperature control. The control precision is between ±0.1 ℃. Moreover, 1 796 and 1 653 nm wavelength distrubuted feedback lasers are selected. By controlling the temperature of the two laser shells from 20 to 44 ℃ reversally, the temperature interval is 2 ℃, the experimental results of the second-harmonic background signal are studied. The test results indicate that: As the temperature of semiconductor laser shells rises, the background signal red-shifts; otherwise it blue-shifts. While testing the background signals of the 1 796 and 1 653 nm DFB lasers drift about 3.2 and 2.67 pm respectively at each temperature change of 2 degrees cenigrade. With the constant temperature control of semiconductor laser shells, it can effectively eliminate the influence of the background signal drifting when room temperature changes and enhance the stability of measurement system. The accuracy of trace gas detection is improved.

Plasma produced through dielectric barrier discharge can react with hydrocarbon molecules in the fuel by collision cracking reaction, causing fuel molecules to be decomposed into hydrogen and small molecule hydrocarbons that are more prone to detonate, which will improve the ignition properties of the continuous rotating detonation engine with liquid fuel. In this paper, the spectral test of volume dielectric barrier discharge (DBD) was carried out in vacuum chamber in order to analyze how the electron excitation temperature and electron density of volume DBD change with the applied voltage under atmospheric pressure argon. In addition, the electron excitation temperature of filamentous discharge was calculated by the Boltzmann slope method, and the electron density was calculated by Stark broadening method. It was found that all of the emission lines arose from electronically excited argon atoms 4p-4s transitions. The intensities of the lines increased with the increase of the applied voltage and had a linear relationship with the voltage basically. For the atmospheric filamentous discharge, the load voltage has no obvious effect on the electron excitation temperature and the electron density. When the applied voltage is in the range of 12.5～14.5 kV, the electron excitation temperature is stabilized around 3 400 K, and the electron density is on the order of 1025 m-3.

Terahertz wave (THz), which exists between microwave and far infrared, has made the terahertz spectroscopy and imaging technology develop rapidly in recent years because of its non-damage property and high stability. The unique feature of non-invasive detection of terahertz wave has a perfect prospect in the field of security detection, and has attracted the attention of scholars. Although THz images obtained by terahertz imaging system can identify hidden weapons or other metal products, the THz image contrast and clarity are poor, which can not completely accord with human visual effect, and is not conducive to machine recognition. At present, the enhancement and improvement of terahertz image quality are the key to the long-term development and wide application of THz imaging technology. By using terahertz projection imaging system with scanning step 0.5mm, we imagine the objects of the metal pendant and metal arrow hidden in clothes at the same experimental conditions. Because of the system defects such as terahertz light source, energy fluctuation as well as the complexity and interference of the external environment, the imaging of the imaging system we get has serious background noise and blurred boundary, and the imaging quality is poor. This paper presents an algorithm of Canny equalization based on double threshold for THz image enhancement. According to the property limitations of terahertz image itself, this algorithm determines the relevant thresholds and the range of image equalization to realize the image denoising. The algorithm introduces the double threshold Canny algorithm and the gradient amplitude algorithm to improve the contrast and clarity of the image, preserve and highlight the detail information of the terahertz image, as well as obtain the high resolution and clear edge image. The experimental results show that we successfully obtain the terahertz images with improved definition, lower noise and fully detailed information from tow low-resolution (LR) terahertz images. The quality of images is improved.This work also enhances the discrimination ability and perspective capability for the hidden defects or hidden objects in the terahertz images, which demonstrates the enormous potential that the terahertz imaging provides the application in the security check.

The major component of atmospheric pollutants is volatile organic compounds (VOCs), Fourier transform infrared spectroscopy (FTIR) is a widely used VOCs on-line measurement method at the present stage. The infrared spectrum obtained by open path (OP-FTIR) is easily to be polluted by various noise. Therefore, the development of effective and rapid methods to remove the noise in infrared spectrum is a crucial problem in the research of on-line atmospheric real-time monitoring system. The lifting wavelet transform (LWT) has the advantages of simple structure, and low computation; the least mean square algorithm (LMS) adaptive filter has the performance of automatically adjusts parameters to achieve optimal filtering. From above algorithm performance we proposes a infrared spectroscopy denoising algorithm combined with improved threshold LWT denoising and LMS adaptive filter. The algorithm first uses improved threshold LWT denoising preserve more spectral information and then uses the LWT decomposition of the high-frequency coefficients to reconstruct the noise correlation signal. Take this noise as the reference input of the LMS adaptive filter, the final denoising signal is effective for the removal of the noise signal overlap with spectral spectrum. In the experimental part, the standard infrared spectrum plus noise and the measured infrared spectrum of open optical channel over Hefei city were denoised respectively, the results show that the signal-to-noise ratio of the spectral signal processed by the proposed algorithm is about 3dB higher than that of the traditional soft threshold wavelet denoising. The root mean square error (RSME) is also reduced by about 30%, and the running time is reduced by 46% or so. Experimental results show that the algorithm is simple and fast in operation, and has important practical significance for the real-time noise elimination system of atmospheric environment monitoring.

Detection of dural hematoma based on multi-channel near-infrared differential absorbance has the advantages of rapidity and non-invasion. In addition, the reasonable setting of the detection array can reduce the morbidity of the model and improve the prediction accuracy of the absorption coefficient. In this paper, variable importance in the projection (VIP) analysis, an ancillary technique of pls, is used to select the detection array. A preliminary modeling for the prediction of dural position μa was established using light absorbance information from 30 detectors located at 2.0~5.0 cm from the light source with a 0.1 cm interval. After VIP screening, the detection array of 4 detection positions is determined, and the optical density information obtained by this array is used for modeling. Moreover, the relative error of the prediction result is reduced from 4.08% to 2.06%. After VIP detector screening, the prediction model still showed good prediction of the epidural position μa. This study provides a new approach and important reference for the selection of detector location in near-infrared dural hematoma detection.

The multi-component synergy is one of the important pathways for the pharmacological effects of traditional Chinese medicine (TCM) due to the complicated chemical compositions. Therefore, it is necessary to control and reflect the quality of TCM comprehensively in order to ensure its efficacy and safety. In Chinese Pharmacopoeia, the contents of three saponins were selected as indicators to ensure the quality of P. notoginseng. However, a single type indicator was limited to evaluate the quality of P. notoginseng comprehensively. In this study, the total polysaccharides content of P. notoginseng was determined by using ultraviolet-visible (UV-Vis) spectroscopy and phenol sulfuric acid reaction, and a prediction model of total polysaccharides content was established to provide some basic researches for rapid and comprehensive quality assessment of P. notoginseng based on Fourier transform infrared (FTIR) spectroscopy combined with support vector regression (SVR). In addition, a total of 60 FTIR spectra of P. notoginseng originated from 12 regions were collected. The absorbance of UV-Vis spectra at 490 nm which was contributed by polysaccharide extraction solution was recorded, and the content of total polysaccharides was calculated based on standard linear equation of glucose. Moreover, optimization procedures of spectra data were calculated by second derivative (2D), orthogonal signal correction (OSC), wavelet transform (WT), and variable importance for the projection (VIP). 2/3 of the 60 individuals were selected to develop the calibration set by using SPXY algorithm, and the rest samples were used as validation set. Calibration set data was used to establish the SVR model and grid search, genetic algorithm (GA) and particle swarm optimization algorithm (PSO) were used for screening optimal parameters which were utilized to verify the accuracy and reliability of the SVR model. Results showed that: (1) Maximum absorption peaks of glucose and total polysaccharides were both at 490 nm, and therefore the absorbance of UV-Vis spectra at 490 nm could be used for calculating the content of total polysaccharides. (2) The P. notoginseng from Qiubei, Shizong and Mengzi origins contained higher content of total polysaccharides (more than 25 mg·g-1) than other producing origins. (3) By analyzing the root mean square error of estimation (RMSEE) and the root mean square error of prediction (RMSEP) of optimization model, we found that the grid search model were under-fitting and the GA model were over-fitting compared with PSO model. (4) PSO model showed an excellent predictive effect with RMSEP and R2pre of 3.120 6 and 83.13% respectively, which indicated the predicted values were close to the detection values. The result indicated that FTIR combined with PSO-SVR could accurately predict the content of total polysaccharides, which could provide a research basis for the comprehensive quality control as well as ensure the stable, safe and effective medicinal use of P. notoginseng.

The detection of active ingredient contents is to evaluate the quality of medicinal plants, and different harvesting time has a significant influence on effective component contents of medicinal plants. In this study, Fourier transform infrared (FTIR) spectroscopy combined with chemometrics was used to establish a rapid method for predicting the total flavonoids content in dendrobium officinale at different harvesting time, in order to provide a basis for the rapid quality evaluation of this species. From January to December in 2014, a total of 111 samples were collected, dried and crushed. In addition, the content of total flavonoids in D. officinale was determined by using traditional method and the accumulation regularity of total flavonoids in D. officinale was studied. Moreover, the infrared spectra of the samples were recorded and their bands were identified. The original spectra were pre-processed by combining the first derivative, second derivative, standard normal variable, multiple scattering correction and orthogonal signal correction. Processed FTIR spectra were set as variable X and the contents of total flavonoids were set as variable Y. The PLS model was established to predict the total flavonoids content. The results showed that: (1) Both the sample and the standard rutin had a common absorption peak near 270 nm. In this experiment, the total flavonoid was measured at 270 nm. The standard curve equation of total flavonoids was y=6.076 5x+0.055 8, r=0.996 6 and the precision, reproducibility and stability of relative standard deviation (RSD) were 0.37%, 1.00% and 0.28%, respectively. (2) The content of total flavonoids increased with time at first and then decreased, and the content of total flavonoids was higher than 64.10 mg·g-1 from June to August. (3) The FTIR data was integrated with the total flavonoid content of D. officinale by partial least squares regression analysis (PLSR). The results showed that the optimal pretreatment method was 2D+SG5+SNV+OSC-PLSR, the r and RMSEE of the training set were 0.979 0 and 2.438 2, respectively while R2 and RMSEP of validation set were 0.882 4 and 4.169 9, respectively. The predicted and the measured value of total flavonoid content was close to each other, indicating that PLS model can be used for rapid prediction of total flavonoid content. FTIR combined with chemometrics can accurately predict the total flavonoids content in D. officinale and provide a rapid and effective method for the quality evaluation of D. officinale.

BiOCl was prepared by solvothermal method, and the reflection of BiOCl to near-infrared light was studied. The crystal structure and chemical composition of BiOCl were characterized by X-ray diffraction (XRD) and electron spectroscopy (EDS). Under the observation of scanning electron microscopy (SEM), BiOCl exhibited homogeneous flower-like microspheres with outer diameter of 3~5 μm, composing by intertwined nano-sheets with open channels. The absorption and reflection spectra of BiOCl were analyzed by UV-Vis-NIR spectrometer in the wavelength range of 220~2 500 nm. Its forbidden band width is 3.69 eV, which is greater than the calculated value of 2.62 eV. The results indicated that the photocatalytic concentration of BiOCl has changed, and the absorption edge was blue shifted. The reflectivity in the visible region (300~750 nm) is 67.3%, and it is over 99.8% in the near infrared region of 750~2 500 nm. Finally, BiOCl particles were dispersed in polyvinyl alcohol (PVA) solution to prepare film by coating process. With the increase of BiOCl content, the heat-insulation properties of BiOCl/PVA was improved accordingly. When the amount of BiOCl was 1.5%, the temperature inside of the insulation box decreased 4.5 ℃, the reason is the incident frequency of near-infrared light is higher than that of BiOCl particles, resulting in a high reflection. For the energy distribution in the near infrared region has been impeded and reflected, the temperature inside the insulation box was then reduced.

High quality cotton seeds are the basis of precision seeding technique. In this paper, near-infrared hyperspectral imaging technology is used to realize the visible identification of micro-damaged cotton seeds, which lays a theoretical foundation for the development of cotton seeds selection equipment. Near-infrared hyperspectral images of two kinds of 540 cotton seeds, undamaged and micro-damaged, were acquired, of which 405 samples were used as the calibration set, and 135 samples were used as prediction set. After analyzing the original spectral curve of the full wave band, the noise at both ends was removed. Firstly, KS algorithm was used to divide samples, and the spectra was pretreated by smoothing algorithm( Savitsky-Golay), respectively using the second derivative spectra (2nd spectra) method, principal component analysis loading (PCA-loading) method and successive projection algorithm (SPA) method to extract the feature wavelength, then partial least squares discriminant analysis (PLS-DA) model, K nearest neighbor (KNN) model and support vector machine (SVM) model ware used to analyze the characteristic spectrum. By comparing the analysis results, SPA-PLS-DA was selected as the model, the discrimination rate of the calibration set and the prediction set is up to 91.50% and 90.33%, respectively. Finally, the SPA-PLS-DA model is used to identify the mixed images of undamaged and micro-damaged cotton seeds. The identification results were identified by different colors,the corresponding visual identification figure is generated, and good recognition results were obtained. Moreover, the recognition rate of micro-damaged cotton seeds was above 90%. The result indicates that the near-infrared hyperspectral technology and image processing technology can be used to realize the visual identification of the micro-damaged cottonseeds.

Tea, as a kind of healthy drink, is loved by many people. But its function and effect vary from different varieties. Therefore, it is of great significance to find a fast, easy and simple method for the identification of tea varieties. In order to classify different tea varieties quickly and accurately, fuzzy uncorrelated discriminant c-means clustering algorithm (FUDCM) was proposed based on the fuzzy uncorrelated discriminant transformation (FUDT) algorithm and fuzzy c-means clustering (FCM) algorithm in this paper. FUDCM can extract the fuzzy uncorrelated discriminant information from spectral data dynamically in the process of fuzzy clustering. To start with, Fourier transform infrared spectroscopy (FTIR) data of three kinds of tea samples (i. e. Emeishan Maofeng, high quality Leshan trimeresurus and low quality Leshan trimeresurus) was collected using FTIR-7600 spectrometer in the wave number range of 4 001.569～401.121 1 cm-1,. Secondly, multiple scattering correction (MSC) was applied to preprocess these spectra. Thirdly, principal component analysis (PCA) was employed to reduce the dimensionality of spectral data from 1 868 to 20 and linear discriminant analysis (LDA) was used to extract the identification information of the spectral data. Finally, FCM and FUDCM were performed to identify the tea varieties respectively. The experimental results showed that when the weight index m=2, the clustering accuracy rate of FCM was 63.64% and that of FUDCM was 83.33%. After 67 iterations, FCM achieved convergence while FUDCM did that after only 17 iterations. Tea varieties could be quickly and efficiently identified by combining FTIR technology with PCA, LDA and FUDCM, and the identification accuracy of FUDCM was higher than that of FCM.

In this paper, near infrared spectroscopy was applied to build an identification model to predict four types of defects on the surface of wood boards. A calibration set and a prediction set made of 50 and 30 samples were built randomly and respectively. In addition, a near infrared spectrometer, ranging from 900 to 1 700 nm was used to collect the spectra of the surface of the boards. The original spectra were pre-treated by SNV algorithm to eliminate the influence of solid particle size, surface scattering, and the change of optical path of diffused reflectance spectra. Afterwards, a training model was built by partial binary tree of support vector machine (PBT-SVM), and parameters were optimized by simulated annealing (SA) algorithm to find the optimal parameters and band characteristics. Then an identification model was built based on optimal parameters, band characteristics, and the identification of prediction set. The results showed that the performance of polynomial kernel function was obtained with the parameters setting as γ=28.63, coef=18.69, d=1 and, C=12.03. The recognition rate of crack and live knot was 100%, while the recognition rate of dead knot and wormhole was 93.33%. The mean accuracy of identification reached 96.65% with an average recognition time of 0.002 s. The approach was feasible to classify the four types of defects on the surface of solid wood effectively.

Traditional target segmentation based on transition region is sensitive to noise, which can affect the accuracy of the extraction. Compared with the visible image, the thermal noise caused by the detector in infrared image would degrade the detection rate of traditional target extraction method. In addition, although the target can be accurately positioned through the edge, it is impossible to obtain the complete edge of the target. However, the gray distribution of the transition region can solve the problem of edge. Therefore, in order to improve its anti-noise and target extraction performance, an adaptive target extraction method of infrared image utilizing edge and transition region is proposed. First of all, the pixel’s density with inform of spatial neighbors is calculated to reduce noise and obtain edges. After that, the separation between object and background is made to get transition region with edge, which is utilized to grow up the whole object. Finally, performance of anti-noise is estimated by extracting objects in several complex infrared scenes. The results show that the proposed algorithm is effective under man-added noise conditions.

Raman spectra of Li2B4O7 at different temperatures up to 1 373 K were recorded by using in situ high temperature Raman spectroscopic technique. With the increase of temperature, Raman spectra of crystal broaden and decrease in wavenumber and intensity. During the melting process, ［B4O9］ rings which consist of two ［BO4］ and two ［BO3］ turned into (B3O6)3- six-membered ring and ［BO3］, ［BO4］ species decreased and then disappeared. In addition, the vibrational modes of the Li2B4O7 crystal were simulated and assigned by using density functional theory(DFT)method. Raman spectra of x(Li2B4O7)(x=2, 3, …, 9) rings which consist of (B3O6-BO3) were calculated by using quantum chemistry ab initio method, to analyze the cluster in melt. It can be concluded that there exists super ring structure which contains three (B3O6-BO3) rings connected with each other.

As enhanced substrates, precious metal nanoparticles have been widely used in the study of the SERS.The traditional precious metal nanoparticles were still to be improved in the preparation methods, enhancement ability and accuracy. In this paper, simple and efficient method was developed to prepare a new membrane-like nanoparticles substrate. PVP was used as protectant and binder, gold nanoparticles were perpared by chemical reduction method. The effects of the reaction conditions on the reaction were investigated, including species of reducing agent, the temperature of the reaction, pH of the reaction system and the concentration of reducing agent. In addition, a new membrane-like nanoparticles substrate which had the best enhanced effect was prepared. The SERS characteristic of the substrate was inspected by rhodamine B. Its enhancement factor could reach to 6.5×105.The shape of gold nanoparticles was characterized by SEM. The results showed that it has a membrane structure and a large specific surface area which is conducive to molecular absorption. Compared with the traditional precious metal nanoparticles substrate, the new membrane-like gold nanoparticles substrate had a better enhanced effect and higher detection sensitivity and accuracy. All in all, it has a wide application prospect.

In this paper, the Au@Ag core-shell composite bimetallic nanorods (Au@AgNRs) with good monodispersity were loaded into filter paper by electrostatic interaction to prepare composite filter paper. Moreover, the distribution of Au@AgNRs on the composite filter paper was observed by scanning electron microscopy (SEM), and the number of Au@AgNRs in the filter paper per unit area was statistically counted. In addition, the prepared Au@AgNRs loading composite filter paper was used as a surface-enhanced Raman spectroscopy (SERS) substrate, and trace amount of tetramethylthiuram disulfide adsorbed on slide was detected by using the paper to wipen its surface. It can be seen that the composite filter paper prepared with 150 nmol·L-1 Au @ AgNRs solution has better enhancement effect and detection repeatability. The relative standard deviation of the results of ten repeated tests is 3.1%, and the linear detection range was 10-14~10-7 mol·L-1. The prepared Au@AgNRs loading composite filter paper as a SERS substrate can be used for the detection of pesticide residues on fruits and vegetables like apple.

Graphite is one of the most common inclusion in diamond, it can be divided into protogenetic, syngenetic and epigenetic on the basis of sequence of graphite inclusion formation. The formation environment of the diamond and its late change are indicated by protogenetic/syngenetic and epigenetic graphite. In-situ microscopic laser Raman spectroscopy, we carried out on graphite inclusions in 13 gem-grade and semiprecious alluvial diamonds from the the Yuanjiang Basin in Hunan province(Yangtze Craton). The results showed that the graphite inclusions whether protogenetic/syngenetic or epigenetic Raman shift in position of the G band and D band toward high frequency region and Show low ordered structures and defects. Raman shift of the protogentic/syngenetic graphite G band range from 1 591 to 1 600 cm-1, the shift of the G band of epigenetic graphite is wide rang from 1 575 to 1 588 cm-1, it is thought that forming pressure for diamond in Yuanjiang Basin(Yangtze Craton)is lower and its crystallization pressure have great varying range. We calculated the pressure are rang from 4.01 to 5.88 GPa according to Raman shift of the protogentic/syngenetic graphite G band range. It is consistent with what result of calculation in Raman shift of the olivine in Hunan diamonds, the D band rang from 1 350～1 368 cm-1 andthe G band and D band intensity ofprotogenetic/syngeneticgraphite inclusions of Hunan diamonds between 0.36 to 0.82, it indicatethat those area diamondswereformed depth is shallow and may be formed in a lithospheric mantle containing abundant eclogite. In these cases, the diamonds may have formed diamond-graphite boundary and diamond stability field. The graphite inclusion Raman shift of diamond is one of effective approach to explore the formation environment of the diamond primary area.

The green minerals in Anorthitic Jade were considered to be uvarovite, which is a very rare member in natural garnet group. Uvarovite is very rare in natural conditions, the color is emerald green, uvarovite of high quality can be compared with Jade and Emerald. Predecessors have done some researches on the other end members of the garnets. However, little researches have been done on the uvarovite, no reports have been obtained about the spectrum characteristics of the uvarovite in Anorthitic Jade. The composition of this garnet was Uvt49.66Grs36.04Adr13.58Prp0.67Sps0.06 by using the JXA-8230 Electron Probe. Using the Bruker R200L Raman spectrometer, the Raman shifts we got of the sample were 1 000, 890, 879, 830, 618, 589, 530, 508, 399, 370, 270, 240 and 176 cm-1, respectively, which have been influenced by the interaction of different trivalent cations Cr3+, Al3+ and Fe3+; Measurement of the infrared vibration frequency was performed using the Bruker V80 infrared spectrometer, acquiring the results of 1 019, 951, 908, 844, 826, 721, 669, 608, 538, 496, 462, 430 and 413 cm-1, respectively, the regular vibration excursion occurs due to the influence of the unit cell volume and the mass fraction of the trivalent cations; With the Jasco MSV-5200, the Micro-UV-Vis-NIR spectra shows that absorption peaks caused by electron transition of Cr3+were at 439, 613, 453 and 685 nm absorption were acromion, while a acromion absorption peaks caused by electron transition of Fe3+ was at 371 nm, the colored ion of the uvarovite is mainly Cr3+. The detailed spectrum study of the uvarovite in Anorthitic Jade provides rich spectral data for the identification of the garnet, and distinguishing from the similar traditional Dushan jade.

Raman scattering experiment and density functional theory calculation have been applied to investigate the vibrational modes of perovskite (C6H5CH2NH3)2PbBr4 in the spectral range of 450～1 700 cm-1. Comparing the experimental Raman spectrum and theoretical calculated result, it was found that density functional theory can be well applied to simulate the vibration modes oforganic part of (C6H5CH2NH3)2PbBr4. Furthermore, the origins of the observed Raman peaks in the spectral range of 450～1 700 cm-1 have been assigned by comparing the results of density functional theory calculation and literature reports. In addition, it was found that the Raman peaks in this spectral range are mainly originated from the vibrational modes of organic part of (C6H5CH2NH3)2PbBr4.

In recent years, many researchers have studied the measurement methods of fruit sugar and other internal quality by near-infrared (NIR) spectroscopy and some commercial instruments have been produced. However, due to the complexity of the NIR spectra, the transitivity of the models established with NIR is often poorly performed. The model is only built for a particular species or even a certain variety. Random forest (RF) is an integrated algorithm based on decision tree, which improves the prediction accuracy by integrating the classification regression tree (CART) model. Compared with partial least squares (PLS), multiple linear regression (MLR) and other methods, RF algorithm has the strong analytical ability of nonlinear data. Taking into account the randomness of the RF model, the model is optimized by debugging the number of decision tree (ntree) and the number of split variables (mtry). In this study, we used RF to predict the sugar content in different types of fruits (apple and pear). Experimental results showed that for the same kind of fruit, the modeling and predicting results of RF and PLS were better. However, for different types of fruits, RF significantly increased the prediction ability of the model. The R2 of PLS model was 0.878 and the R2 of RF model was increased to 0.999. The RMSEC of PLS model and RF model were respectively 0.453 and 0.015. In addition, the optimal RF model was tested by independent test set samples, the R2 of PLS model was 0.731 and the R2 of RF model was increased to 0.888. The RMSEC of PLS model and RF model were respectively 1.148 and 0.334. RF showed a significant advantage in predicting a variety of fruit sugar. This research proved that the RF method could be applied to detect the sugar content in fruits by NIR spectroscopy, thus solving the model problem of universality and transitivity.

Ethanol diesel as a clean fuel is a good substitute for diesel fuel. Different content of ethanol diesel oil viscosity is different, and the ethanol in the ethanol content of diesel fuel affects the quality of combustion, so we need have an instrument or method to achieve Ethanol Diesel Ingredients and Main Indicators Online Monitoring. In this paper, Savitzkv-Golay smoothing (SG), multiple scattering correction (MSC), differential processing (1stD and 2ndD), standard normal variable correction (SNV), and so on were used to calculate the original Raman spectra . The PLSR model of ethanol diesel density, viscosity and ethanol content was established by using different pretreatment methods for the original Raman spectra of different concentrations of ethanolic diesel. Compared with different pretreatment methods, the ethanol content and viscosity of PLSR model established by S-G+2ndD pretreatment has the best effect, the prediction set Rp is 0.930 and 0.918 respectively, RMSEP is 1.237 and 0.034 respectively. The PLSR model of ethanol diesel density after SG+1stD pretreatment is the best method. The optimal set of Rp is 0.962, RMSEP is 0.14×10-2. The wavelength model was selected by Recursive partial least squares(RPLS), Uninformative variables elimination(UVE), Compctitive Adaotive Reweighted Sampling(CRES), Successive Projections Algorithm (SPA) wavelength screening method after S-G+2ndD pretreatment, and the PLSR model was established. The prediction model of ethanol content of ethanol diesel oil was optimized by SPA-CARS wavelength screening method. The Rp and RMSEP were 0.978 1 and 0.825 5. The results show that the method can be used to predict the main indexes such as density, viscosity and ethanol content of ethanol diesel.

In this paper, spectral and imaging technique were used as effective tools of evaluation for quality of fruits and vegetables, in order to ensure safety of food and health of consumers. In addition, external information was acquired by imaging technique, internal information was acquired by spectral technique. In order to track national and international progress of research, application of spectral and imaging technique was summarized, including prediction of external quality (surface defect, colour, etc.), internal quality (single or comprehensive quality), maturity, shelf-life and storage period, tracing back to the source, growing monitoring , safety (pesticide residue, infestation of diseases and pests, recognition of transgenic product, etc.) and design of optical systems. Afterwards, some problems were analyzed, such as the weakness of spectral libraries, complex algorithm of analyses for mixed data, intricate factors of calibration model, an so on. Finally, the trend of development was discussed. This review indicated that the following aspects were identified as direction of future research, including visualization analysis of constituents, establishing scientific system of comprehensive evaluation, analyzing the mechanism of interaction between different compositions, application of optical theories and properties(analyzing the mechanism of interaction between the light and tissue of fruits and vegetables, inversions of optical parameter, etc.) , application of new algorithms and the combination of many algorithms, enhancing dependability and stabilization of different algorithms, the establishment of stable and universal model, the commercial development and application of low-cost as well as handheld optical instruments. This review shows spectral and imaging technique have the potential to assess quality and safety of fruits and vegetables.

Chemical composition and vibrational spectral characteristics of ensignia actinolite jade from Guangxi, China were investigated using electron microprobe(EPMA), Fourier transform infrared spectrometer(FT-IR) and laser Raman spectrometer(Raman). The site occupancy situation of metal cations with small ionic radii in the crystal structure of actinolite was discussed as well. The result indicates that ensignia actinolite jade from Guangxi is primarily composed of Fe-rich actinolite and minor ferroactinolite, and the high content of FeOT(Wt%: 18.596%~26.791%)is the main reason for its high refractive index(1.64), density(3.12 g·cm-3) as well as black color in natural light and green color in transmission light. Due to the influence of Mg2+—Fe2+ isomorphous substitution in the crystal structure, the infrared absorption bands in 1 400~400 cm-1 and Raman peaks in 100~1 200 cm-1 all shift towards the low-frequency region with various frequency differences. In addition, four vibration bands(MgMgMg)OH(band A), (MgMgFe2+)OH(band B), (MgFe2+Fe2+)OH(band C), and (Fe2+Fe2+Fe2+)OH(band D)are displayed in mid- and near-infrared spectra as well as Raman spectra, among which the bands related to M—OH fundamental frequency vibrations appear at nearly 3 674, 3 660, 3 644 and 3 625 cm-1, respectively. While the bands related to M—OH multiple frequency vibrations appear at nearly 7 183, 7 154, 7 118 and 7 077 cm-1, respectively, and their relative intensity is A＜D＜B＜C. In addition, calculation based on chemical composition and integral area of M—OH infrared vibration bands reveals that Mg2+ and Fe2+ occupy firstly M2 and M1 sites respectively in the crystal lattice of ensignia actinolite jade from Guangxi. The distribution state of Mg2+ and Fe2+ in M1 and M3 sites is relatively orderly and the site-occupancy factors are close to 1. Comprehensive analysis demonstrates that the metamorphic grade of ensignia actinolite jade from Guangxi should belong to the greenschist facies category.

Rare earth fluoride nanomaterials and their precious metal complexes have unique optical, electrical and magnetic properties, which have been widely used in biomarker, optical storage, display and security. It has become one of the hotspots in the field of materials science. In this paper, the NaYF4∶Yb3+, Ho3+, NaYF4∶Yb3+, and Ho3+ @Au composites were prepared by using microemulsion method. The results show that NaYF4∶Yb3+, Ho3+@Au composites were directly formed in the microemulsion system. The XRD shows that the NaYF4∶Yb3+, Ho3+ is cubic phase, and there is no impurity peaks. Moreover, the diffraction peaks of NaYF4∶Yb3+, Ho3+ @Au contain both NaYF4 and Au. It can be seen from the SEM that the nanoparticles are uniform spherical whose particle size is about 58 nm. In the up-conversion spectra, the high luminous intensity at 484, 682 and 767 nm are corresponding to 5S2→5I8, 5F5→5I8, 5S2→5I7 transition of Ho3+.

Quantitative description of the tongue proper and tongue coat isperceivedas the important content for tongue diagnosis in traditional Chinese medicine, which directly affects the accuracy of clinical diagnosis. A new method fortongue proper and tongue coat separationusing spectrum dissimilarity index (SDI) by double-wavelength ratio is presented, which isbased on hyper spectroscopy and theory of biomedical photonics. The 343 wavelengths of hyperspectral tongue information of subjects is obtained in the range of 371.200 to 992.956 nm. Moreover, the hyperspectral data of 15 subjects is selected randomly for spectral characteristics analysis. By comparison with the spectral curve of the wavelength range, it can be seen that optical spectrum characteristic dissimilarity between tongue proper and tongue coat is resemble the optical characteristic of hemoglobin, since the surface of the tongue is full of blood vessels and the absorption of water is small in the range of 500 to 750 nm. In addition, double wavelength optic reflection ratio is used to extract optical spectrum characteristic dissimilarity index of tongue proper and tongue coat based on spectral absorption features of hemoglobin atthe wavelength of 573 and 700 nm, finally tongue proper and tongue coat is separated. It is can be seen that the SDI with tongue proper and tongue coat of one subject is a certain difference and has the obvious difference index line between tongue proper and tongue coat. The experiment results show that spectrum dissimilarity indexis very helpful for tongue coat and tongue proper separation in traditional Chinese medicine, and this new analysis approach may providean objective standard for TCM tongue diagnosis.

Accurate on-line prediction of endpoint carbon is of significance for achieving control of end points, improving the quality of steel products, reducing energy consumption and reducing exhaust emissions. In order to solve the problems of endpoint control and carbon content measurement in converter smelting, a novel non-contact on-line method for detecting carbon content was proposed in this paper. The method realized BOF endpoint prediction and carbon content detection based on radiation spectrum with support vector regression. Firstly, a remote spectrum acquisition system was adopted to obtain flame information. Changes of flame radiation spectrum in smelting process were analyzed and spectral width and background radiation peak which characterize the overall spectral and intensity values of wavelength 600, 630 and 775 nm corresponding to emission peaks were extracted respectively and then used as inputs of support vector machines, combining decarburization theory and measured carbon value, the decarburization curve was reconstructed as output of support vector machine. The relationship model between spectral distribution and carbon content was established by support vector regression. The optimal parameters of the model were determined by training the sample set and the test set. The designed instrument and the optimized model have been installed in the converter production control room, field experiment results show that the accuracy of end-point carbon content prediction is 90.2%, and the measurement time is 0.3 s. It can be detected online in real time, and meet the production needs. The method provides an important basis for the precise endpoint control of the BOF.

In this paper, the graft terpolymer, which is called Chitosan-based heavy metal capture flocculant CSC-P(AM-AA), of carboxymethyl chitosan (CSC) and acrylamide (AM) and acrylic acid (AA) were successfully prepared by photopolymerization. In order to demonstrate the successful preparation and characterization of the graft copolymer, the IR spectra, XRD, TG-DSC, and scanning electron microscopy (SEM) were used to characterize the product polymer. The results showed that the graft copolymer of CSC-P (AM-AA) was successfully prepared, and the graft copolymer had good soluble ability. In addition, P (AM-AA) had a structural characteristics that were significantly different from those of P(AM-AA), due to the graft polymerization of carboxymethyl chitosan. The flocculation results showed that CSC-P(AM-AA) had good heavy metal removal performance. At pH 8, dosage of 8 mg·L-1, and rotation speed of 150 r·min-1, the optimal removal rate of Cu2+ by CSC-P(AM-AA) was 87.0%.

Solar thermal power generation is one of the effective ways to utilize solar energy. It plays an important role in alleviating energy crisis and environmental pollution and has far-reaching social significance. The selective absorption coating is an important part of solar collecting tube, and the key factor to determine the conversion efficiency of solar energy and heat energy. In order to characterize the optical properties of solar selective absorption coatings under high temperature conditions, a new method for measuring the spectral absorptivity of high temperature metal-ceramic selective absorption coatings was proposed. Based on Fourier spectrometer with double detector and integrating sphere with heating function, a high-vacuum measurement device was developed, which has the function of high temperature oxidation resistance and working temperature simulation. The Mo-SiO2 selective absorption coating with the typical double absorption layer, prepared by magnetron sputtering, was used as the sample for measurement. In addition, the solar spectral absorptivity of sample at different temperature was measured in the spectral range of 0.3～2.5 μm and temperature range from room temperature to 700 ℃. Measurement values at the room temperature were compared to the values calculated from the effective medium theory and matrix formula, and results show a good consistency. Because the maximum deviation is only 2.9%, the feasibility of measurement method is verified. The measurement of high temperature spectral absorptivity has important guiding significance and promoting function for optimization of design parameters and enhancement of absorption performance.

Water-soluble pitch containing more than 70% of hydrophilic groups were prepared from the oxidation of coal tar pitch in the presence of acid, the product can be applied in the preparation of composite carbon materials in aqueous medium owing to a variety of introduced polarity groups and normal condensed rings. Moreover, the molecular structure was analyzed using Fluorescence, IR, UV, NMR and Yen-Mullins model. The results indicated that the fraction of N, O, S were increased by 1.06%, 11.64%, 0.79% to 6.78%, 29.59% and 2.41% respectively. In addition, the hydrophilicity of the desired pitch enhanced that was attributed to the O percent increased. Hetero-atoms (N, O, S) exist in the form of Ar—NO2, Ar—OH, Ar—SO3H and CO were characterized by infrared spectroscopy. Three fused aromatic rings called “Island structure” were identified by fluorescence and Yen-Mullins model, substitutions on aromatic rings were oxidized to a single C-atom group as shown by 1H-NMR and 13C-NMR spectra, this group and “Island structure” can be seen as the basic composition of water-soluble pitch’s framework. It was found that pitch was soluble in alkaline aqueous solution can be explained by elemental analysis combined with infrared spectroscopy, and fluorescence spectrum combined with Yen-Mullins model gave the main structure information from a microcosmic view, thus enabling a general method for different properties pitch determination.

Anew technology of metal surface modification-QPQ (Quench-Polish-Quench) Salt bath compound heat treatment technology can improve theabradability and anticorrosion of metal surface. The CNO-ion plays a very important role in the quality control of QPQ technology. A sequential injection spectrophotometric method is proposed for the determination of CNO-ion. In addition, the indirect detection method of converting CNO-ion into ammonium ion (NH+4) in the condition of high temperature and high pressure is studied; a 697 nm line is selected as the characteristic wavelength. The measuring range of this experiment setup is 0. 02~0. 6 mg·kg-1, and the limit of detection (LOD) is 0.018 mg·kg-1. Based on the sequential injection, the setup can completely automatic on-situ test the concentration of CNO-ion in the quench-polish-quench (techniques for heat treatment of salt bath) process. Measure mean relative error and relative standard variance is 1.31%, 0.92% respectively. Compared with the traditional standard measurement method, a high precision and good repeatability result meets the requirements, which provides theoretical and technical support for the development of the fully automatic in-situ measurement instrument for the treatment of the salt bath compound heat treatment technology.

Alum gelatin solution is the traditional Chinese materials for paper relics, but excessive use of alum will cause XUAN paper to varying degrees of acidification. In order to understand the effects of alum in alum gelatin solution on different ingredients in XUAN paper, the effect of alum on cellulose, calcium carbonate and gelatin in Xuan paper was studied. The effect of alum on celluloseand calcium carbonate in XUAN paper was studied by attenuated total reflectance Fourier transfer infrared (ATR-FTIR) spectroscopy and X-ray diffraction(XRD). For the first time, the effect of alum on gelatin in Xuan paper was studied by Fourier self-deconvolution and curve-fitting techniques. XRD and ATR-FTIR results showed that the alum dissolved cellulose and calcium carbonate in the paper and produced calcium sulfate. When the concentration of alum exceeded 5 Wt%, the composition changed the most violently; Fourier self-deconvolution and curve-fitting results showed that alum would change the secondary structure of gelatin protein on XUAN paper, α-helix, β-turn and γ-random structures were transformed into β-sheet structures. When the concentration of alum exceeded 5 Wt%, the secondary protein structure changed the most violently. In this paper, the effect of alum on different ingredients in Xuan paper was expounded, and the dosage range of alum was given on the basis of minimum interference principle. In addition, a new method has been introduced to study the secondary structure of protein in paper relics, and the application range of ATR-FTIR in paper relics has been expanded.

Hyperspectra remote sensing technique was applied to detect photosynthetic parameters (PP) in cotton leaf defected Verticillium wilt. The reflectance data about 207 was acquired in 350～2 500 nm bands in different dates and severity level of cotton leaves, and PP were measured by photosynthetic instrument. Analysis of variance and relationship analysis were used to process the PP character, extra spectral sensitive bands and selected character parameters of spectra with PP linear and nor-linear models were applied to product PP of cotton leaf of disease and tested. The result showed: with the disease condition increase, the data was increased to leaf net photosynthetic rate (A), transpiration rate (E), stomatal conductance (GH2O), howeverintercellular CO2 (CI) firstly decreased and then up, and the difference was significant between severity levels and PP. The relationship became better between severity level and PP, which r were -0.97, -0.957, -0.886, 0.715, respectively. New spectral parameters, R704, R706, R699, R690, FD688, FD732, FD690, FD731, FD681 were built on the base of sensitive bands together with tradition spectral parameters to established revise models of A, E, GH2O, CI of cotton leaves with disease. Those models as PRI［FD732, FD688］), R706, RVI［890, 670］), R690 for the independent variable had the highest accuracy to estimate A, E, GH2O, CI, R2 of prediction, which were 0.827, 0.810, 0.658 and 0.573 respectively; RMSE were 5.466, 2.801, 109.500 and 63.500 respectively; RE were 0.041, 0.137, 0.158 and 0.021 respectively, which can realize the inversion of photosynthetic physiological parameters of cotton by remote sensing.

Chlorophyll content reflects plant health status. Studying on spectral characteristics and regularity of tree leaves at different SPAD values can provide theoretical support for band recognition of chlorophyll hyperspectral monitoring and trees species health management. Nine tree species from shrub and arbor in Langya Mountain scenic spots were selected to explore the spectral characteristics of the same tree species with the SPAD values changing and the spectral differences of different tree species with the same SPAD values in this paper. At the same time, the relationship between different tree leaves chlorophyll content (SPAD) and the original spectrum, the inverse of the spectrum, the first order differential of the spectrum, the second order differential of the spectrum and the various band combinations of the spectrum such as difference index, normalization vegetation index, ratio index, first order differential normalization vegetation index, first order differential ratio index were discussed in depth. The results showed that the spectral characteristics of nine kinds of tree species leaves were distinct with the SPAD values changing, and the distinction was evident in the visible band, in general, the leaves SPAD values with the highest spectral reflectance was lower. In addition, the spectral reflectance of osmanthus leaves was higher than that of the other species in the visible band, and the spectral reflectance of Magnolia grandiflora leaves was always the first three in 780~1 350 nm band when the chlorophyll SPAD value was the same, but the changing law was not obvious in other bands. Moreover, the second order differential of the original spectrum had the highest correlation coefficient with the SPAD value of Pittosporum leaves, as the first order differential had the highest correlation with the others. The spectral indices with the highest correlation coefficient of SPAD value of shrubs and deciduous tree leaves were differential index and normalized vegetation index of first order differential of the spectrum, otherwise, evergreen trees and trees regardless of species were of the highest correlation coefficient with ratio index of the first order differential of the spectrum.

The existing model of soil heavy metal content reversal model by hyperspectral remote sensing technology is mostly based on the limited sample points of the same study area. However, considering the practical application requirements, whether the model has a good migrate ability is an urgent question. If it is not feasible, is there any other feasible means for soil heavy metal pollution assessment? In order to answer the above-mentioned questions, this paper selects two lead-zinc mines in Chenzhou City and Hengyang City as research areas. The quantitative inversion and qualitative classification of heavy metals Pb and Zn were carried out using the sampling sites in Chenzhou area to compare the two models in Hengyang City of the migrate ability. Experiments show that: (1) Quantitative inversion model based on Partial least squares regression (PLSR) has poor migration ability. The regression model was established by four spectral preprocessing methods. It was found that the prediction accuracy of the model was very low, and it was difficult to correctly invert the contents of Pb and Zn in Hengyang research area. (2) Support vector machine (SVM) classification of qualitative inversion model has a certain ability to migrate. Based on Chenzhou area sampling data, training SVM classification model can effectively predict the Hengyang research area Pb and Zn pollution situation, the prediction accuracies are 84.78% and 86.96%, respectively. The results show that qualitative classification is a more practical way to detect soil heavy metal pollution rapidly.

The aim of this study is to investigate the effect of Ca-bentonite (CB) on organic matter transformation during pig manure (PM) composting. In this paper, five treatments representing different CB concentrations(0%CB, 2.5%CB, 5%CB, 7.5%CB and 10%CB of dry PM weight basis) were mixed with initial feed stock composting system. Moreover, various spectroscopic approaches like UV-Vis spectra, fluorescencespectra (FS) and FTIR were used to characterize the evolution of water-extractable organic matter transformation during PM composting. In addition, on the basis of spectroscopic characterization, multivariate statistical analysis was performed to investigate the correction among the different parameters related to organic matter transformation. The results showed that the concentration of DOC decreased along with the increase of CB dosage during the PM composting, and among all the treatments the degradation rate of DOC concentration was 49.11%~62.92%. Meanwhile, it was observed from spectra results that the peak intensity of humic substance increased and the position was red shift during composting. As compost ended, the SUVA254, SUVA280 and the amount of increase related to humification coefficient (λ) of all treatments were higher than control, the amount of increase were 16.51%~47.72%, 8.58%~44.02% and 23.16%~88.22% in order, and the maximum was observed in 5%CB applied treatment. And FTIR spectra revealed the same result. The correlation analysis showed that SUVA254 reflected the change of compost maturity best in all spectral parameters studied in this paper. Overall, the results indicated that adding 5%CB considerably enhanced the organic matter degradation and the humification during PM composting.

Aiming at the issues that there may exist uneven illuminance conditions and complicated background on the disease spots images captured in real greenhouse field, this paper presented a segmenting method for greenhouse cucumber downy mildew images based on visual spectral and support vector machine. Firstly, a novel combination of the visible color features and its detection method were presented, based on which the support vector machine and SURF features were integrated to segment the disease spot from images. The combination of the visible color features combined ExR, H component of HSV color space and b* component of L*a*b* color space. Because ExR was very likely to be influenced by illuminance conditions, an ExR parameter was adopted to reduce the influence from illuminance conditions to the disease spots segmentation. On the basis of combination of the visible color features, initial segmentation results can be achieved by using RBF based SVM classifier. Then the initial segmentation results were further optimized by using SURF features to eliminate the background noises. Finally, the segmentation results were compared with K mean clustering, OTSU thresholding and decision tree. The results showed that the accuracy rate of OTSU+H*0.2, K-means+H+b*, DT+H+b* and proposed method were 19.44%, 40.19%, 16.27% and 7.37%, respectively. The accuracy rate of proposed method was obviously higher than that of the other three methods, which indicated that the proposed method can meet the data requirement of the following diagnosis for greenhouse cucumber downy mildew.

4-Ethyl-2-methoxyphenol is a widely used food additive, but it also has toxicity. In order to investigate the effect of 4-Ethyl-2-methoxyphenol on the body, the interaction between 4-Ethyl-2-methoxyphenol and human serum albumin (HSA) was studied by combining a variety of spectroscopic techniques and molecular simulation techniques in this paper. UV absorption spectra results indicated that 4-Ethyl-2-methoxyphenol formed a new complex with human serum albumin. In addition, the fluorescence spectra results showed that the presence of 4-Ethyl-2-methoxyphenol can enhance the fluorescence intensity of HSA. 15 nm synchronous fluorescence and fluorescence enhancement effect equations can be used to calculate the binding constants between 4-Ethyl-2-methoxyphenol and HSA, and their binding constants decreased with the increasing of temperature. Thermodynamic parameters showed that 4-Ethyl-2-methoxyphenol was mainly bonded with HSA by hydrogen bonding and hydrophobic interaction. Moreover, synchronous fluorescence, three-dimensional fluorescence and circular spectra revealed that 4-Ethyl-2-methoxyphenol modified the conformation of HSA. The molecular docking technique demonstrated that 4-Ethyl-2-methoxyphenol was bonded in the IB hydrophobic region of HSA.

Laser-induced breakdown spectroscopy has the characteristics of small-invasive, in situ and rapid analysis. It has wide application prospects in the field of sample identification and component analysis. In order to explore the feasibility of the technology in the automatic identification of natural geological samples, a method of identifying and sorting LIBS spectral of natural geological samples by self-organizing feature map neural network combined with correlation is proposed in this paper. In order to reduce the interference of unrelated data such as background noise in the whole spectrum and the computational complexity, the feature spectral line is extracted on the basis of elemental to achieve the dimensionality reduction of high dimensional spectral data. The network training model is established by using the feature spectrum data as input, then the weight vectors which have the feature of input samples are obtained. Finally the geological sample classification is achieved by the correlation analysis between the weight vectors and the samples to be tested. The classification results of the 16 kinds of natural geological samples prove that the feature spectrum is superior to full spectrum and PCA dimension reduction, especially in the aspects of descending dimension and extracting the main features of data. The algorithm proposed in this paper has a better classification effect on the feature spectrum data of 16 samples than SVM and SOM neural network algorithm. Moreover, the validity of the proposed method is initially verified in this paper.

At present, more and more phosphorus is entering the water, which seriously affects the ecological environment and human health, however, the traditional methods of phosphorus analysis are complex and require multiple reagents. In this paper, total phosphorus in water is determined by inductively coupled plasma-atomic emission spectrometry (ICP-AES). In this paper, the instrument working conditions were discussed. The results showed that the optimum instrument working conditions were as follows: the analytical line was 213.617 nm, the RF power was 1 300 W, the nebulizer flow rate was 0.5 L·min-1, the observation height was 15 mm, the peristaltic pump speed was 1.2 mL·min-1, and the observation way was radial. Under the optimum working conditions, the detection limit, precision and recovery of phosphorus were studied. The results showed that the instrument detection limit and method detection limit of phosphorus were 0.028 and 0.084 mg·L-1, the relative standard deviation was between 0.6% and 3.9% in the accuracy test, recovery rates were between 102.3% and 103.0%. In addition, this method was compared with phosphor molybdenum blue spectrophotometry, and the results were basically consistent. This method is quick and easy with good precision and recovery, which is suitable for the analysis of actual samples.

Arsenic (As) is a ubiquitous, toxic and carcinogenic element, and As compounds can pose significant health risks to human and animals. The toxicity of As depends on both the total concentrations and the chemical species as well. Therefore, much attention has been paid to As speciation analysis in the environmental and biological samples. Previous studies claimed that methanol-water solvent system is one of the most frequently utilized methods for extraction of arsenic in samples, and methanol can improve As sensitivity by ICP-MS. However, the effect of methanol addition on As speciation analysis is largely unknown. In this study, the potential As speciation changes in methanol-water solvent mixture covering the range of 0~100% were investigated. Moreover, an optimized condition was employed by using high-performance liquid chromatography inductively coupled plasma mass spectrometry (HPLC-ICP-MS) for simultaneous determination of six As species including AsC, AsB, As(Ⅲ), DMA, MMA and As(Ⅴ). In accordance with previous studies, the HPLC separation was performed on anion-exchange column using a mobile phase of 30 mmol·L-1 (NH4)2CO3 at pH=9.3. The ICP-MS on-line detection of As (AsO+, m/z=91) in eluting compounds was accomplished using the dynamic reaction cell (DRC) technology with oxygen as reaction gas. In addition, the method validation with optimized conditions indicated that the coefficients were above 0.998 9 for all As species. The results indicate that the peak area measured in the chromatographic signal for As(Ⅲ) and DMA increased significantly with the methanol contents, indicating significant impact of methanol contents on As speciation analysis. A test with comparison of 25% methanol solvent mixture, which showed the minimum effects on As speciation changes, and purified water, was further performed, and the results showed that As(Ⅲ) and DMA concentration increased markedly compared to those diluted by purified water but little change for the other four As species. Thus, the elimination of methanol plays an important role in As speciation analysis.

In our experiment, studies have found that the content of Zn is the highest in the filtered water and surface sediments of Taihu Lake, and Cd has the strongest ecological hazards on surface sediments. Therefore, in this paper, the adsorption and desorption characteristics of Cd2+ and Zn2+ on the surface sediments of Suzhou Bay Bridge East (marked as SES) of Taihu Lake were investigated by using inductively coupled plasma mass spectrometry (ICP-MS) under the optimized experimental conditions. Adsorption kinetics results showed that the adsorption capacity of Cd2+ was similar to that of Zn2+, adsorption was a rapid process within 120 min, and when t≥120 min, the result was the opposite and the adsorption reached to dynamic balance. In addition, the adsorption of Cd2+ and Zn2+ were corresponding to the pseudo-second-order kinetics model. Adsorption thermodynamics experiments showed that the adsorption of Cd2+ on the sediments was in accordance with the Freundlich model, while the adsorption of Zn2+ on the sediments were conformed to the Langmuir model. The assay of desorption kinetics of Cd2+ and Zn2+ in sediments found, both of which were more in accordance with the Elovich equation and belonged to the heterogeneous diffusion. When the pH increased, the desorption of Cd2+ and Zn2+ in the sediments decreased gradually, and tended to stabiliz at pH=9. Combination with the adsorption-desorption characteristics of Cd2+ and Zn2+, the adsorption rates of Cd2+ and Zn2+ were much larger than desorption rates of Cd2+ and Zn2+, which was consistent with the results of our previous studies. This study revealed the mechanism of adsorption and desorption of Cd2+ and Zn2+ on surface sediments of Taihu Lake and the effect of different factors on the adsorption-desorption behavior. It is of great significance to study the distribution of heavy metals and the remediation of polluted water in the solid-liquid interface of Taihu Lake.

Jadeite-jade originates in subduciton-related HP/LT metamorphic zone, thus study of it is of great importantance for shedding lights in subduction research. Zircon is often used to determine the age of rocks, and it’s usually applied to the investigation of genesis and formation time of jadeite-jade. Myanmar is the most primary origin of high quality jadeite-jade, of which zircon is a common accessory mineral. To explore the genesis and formation time of Myanmar jadeite-jade, raw jadeite-jade rock with enriched zircon inclusions were studied. In addition, Cathodoluminescence (CL) images were obtained to characterize distribution of colors and diversity of oscillating zones from well-crystallized zircons. Moreover, trace elements composition and U-Pb ages of these zircons were further determined using Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) according to characteristic CL images. The results showed that zircons with different colors and oscillating zones shapes have different trace elements distributions. The overall performance was that: chondrite-normalized REE pattern of zircons displays depleted LREE, enriched HREE, with edivdent Ce(Ce/Ce*=19.2-74.2) positive anomalies and slight Eu(Eu/Eu*=0.49-0.72) negative anomalie. High total REE (∑REE=810～3 984 μg·g-1), (Yb/Sm)N values ranged from 23.1 to 195.1 (most of them less than 100), and Th/U ratios 0.28 to 1.18. These zircons can be classified into magmatic zircons, originated from mafic basalt magma in the upper mantle wedge of subduction zone. This type of magma was formed by partial melting of subcontinental peridotite which reacted with fluids released from the subduction process. Moreover, Ti thermometer reveals that the forming temperatures of those zircons ranged from 762 to 923 ℃. The mean 206Pb/238U age is (157.3±1.3) Ma, which represents the formation time of these zircons. Distribution of colors and diversity of oscillating zones in CL images are irrelevant to forming ages of studied zircons. This distribution might be caused by trace element imparity in zircons, which reflects the dynamic evolution of magmatic melt compositions during zircon formation.

In this paper, the accurate identification problem of energy dispersive X-ray fluorescence (EDXRF) characteristic peak position was studied. Based on the characteristic spectra character of the different metal components, the choosing rule of the characteristic spectra was analyzed. According to the theories of singular value analysis and modulus maxima, the extraction method of modulus maxima was analyzed which based on the wavelet decomposition coefficients of characteristic spectra. Moreover, the feature of the characteristic spectra wavelet decomposition coefficients and their propagation were analyzed in detail. The method of the interval characteristic peak selection was put forward based on the propagation of modulus maxima. And this method was applied to the actual measurement spectra. The result showed that the wavelet transform of four levels was applied to full energy spectra data using the basis function of bior4.4 wavelet. For the full energy spectra, the phase step influence of the some superimposed noise could be eliminated using the propagation of modulus maxima. In order to increase the identification probability of characteristic spectra, the decomposition coefficients were compressed which were less than the threshold value. In addition, 667 peak positions were identified for the fourth level wavelet decomposition coefficients of EDXRF spectra which were not processed. 186 peak positions were identified when they were compressed. Then the method of interval characteristic peak selection using modulus maxima propagation feature was applied and the initial value of the screening interval was set 600 eV. The identified result of the characteristic peak position was 27. The experimental result showed that the accurate rate of peak location identification was enhanced effectively.

LA-ICP-MS was used to calibrate 26 turquoise samples with relatively clean and uniform color on each surface. We selected 9 points on each sample to test the homogeneity of their chemical composition. The results showed that the average error coefficients of Al, P, K, Cu, Fe, V, Cr and Zn in turquoise samples are below 5.4%, while the average error coefficients of CaO and SiO2 are 34.8% and 16.2% respectively, suggesting that the elements of Si and Ca in turquoise were heterogeneity. The turquoise working curve can be established by the energy dispersive X-ray fluorescence spectrometer (EDXRF). We used 21 samples as the standard sample for reference and 5 as unknown samples to determine the composition of turquoise. Results showed that the correlation coefficients of Al, P and Cu of the main element are between 92.3% and 94.3%, with an average relative error of 4.6%~9.7%. The correlation coefficients of Fe, Cr, Zn micro-elements are more than 0.990, while the correlation coefficients of both K and V elements are 0.939 and 0.972. And the average relative error of those five micro-elements ranges from 7.2% to 13.9%. However, the correlation coefficients of Si and Ca are 0.958 and 0.866, the average relative error of which is 348% and 27.8% in the five unknown turquoise samples. The high average relative errors of Si and Ca may be influenced by the low content and the heterogeneity of Si and Ca in turquoise, also related to the detection limit of this instrument method. The repeatability test showed that the relative standard deviations (RSDs) of Al, P, Cu, Fe, Zn elements are within 1%, suggesting that the accuracy of the test results is respectively high. While the RSDs of V, Cr, K, Ca, Si elements range from 1.34% to 10.17%. The study provides a new idea and method for determining the quantify of the elements of Al, P, Cu, Fe, Cr, Zn and V in turquoise quickly, accurately and losslessly, which can be applied to test and identify turquoise in laboratory.

ncreasing the ratio of peak to back (P/B)value is of great importance when using energy dispersive X-ray fluorescence spectrometry to detect heavy metal elements in the light-matrix. Setting up the filters is one way to solve this problem. In the paper the choices (material elements and thickness) for primary filter(it can be divided into One primary filter and Two primary filter) and secondary filter(balance filter) were analyzed, then the Monte Carlo simulation was carried out by MC software, and the accuracy of theoretical analysis was verified by comparing the P/B value before and after setting up. The One primary filter simulation sets up Fe and Cu two kinds of materials. The results show that the biggest P/B values all increases two times after setting up primary filters while the value is 1.36 before setting up; The Two primary filter simulation sets up Te and Ba two kinds of materials. The biggest P/B values are 14.88 and 13.58, which all significantly increase almost 10 times than the previous setting up; The balance filter sets up Rh and Ru two filters, the balancepassband is obtained through two count subtraction. The results show that in the passband the transmission rate of the characteristic peaks is 83.1%, while outside the band the background value is reduced to almost 0, and the P/B values increase greatly. It is found that setting up the three kinds of filters effectively increases the P/B values, in which the balance filter is the most powerful, the Two primary filter is the second, and the One primary filter is the least. The three kinds of filters can be set up at the same time in order to further increase the P/B value in theory, but the Cd amounts in light matrix are trace, so that the low count result will greatly increase the radioactive statistical fluctuation error, therefore, in the practical application, this point should also be considered to decide whether two filters are set up at the same time, or three are set up at the same time. The innovation of this paper lies in the application of the Two primary filter in addition to the traditional two filters.

With the vigorous development of the astronomical spectral big data acquired, such as LAMOST, assessments of the automated data reduction and analysis are necessary. The above work uses the Euclidean distance analysis to determine the similarity between LAMOST spectra and the template. The accuracy of star classification depends on the high-quality template spectra. Classification results from LAMOST 1D pipeline depend on the 183 templates, of which the dependencies should be inspected. In this paper, we calculate both Euclidean and Mahalanobis distances for each pair of templates, using these methods to get the template mean and maximum of A, F, G, K, M stars’. By completing the correlation analysis, we find that the distances averagely show similarity except for several templates. The Mahalanobis distances can even detect the difference between adjacent pairs. They can further identify that the slight differences between the similar templates have better discriminating effects. We conclude from our experiment that most of the LAMOST spectra are correctly classified, while some outstanding templates should be checked as the basis of the optimization for improving the accuracy and reliability of LAMOST templates.

Multi-source data fusion is a powerful method to combine data from multiple sources to improve the potential values and interpretation performances of the source data. Multi-payload collaborative analysis is regularly used to detect the same target in planetary exploration. Therefore, it is of great significance and potential application to use spectral fusion to establish a more accurate and robust clustering analysis model for Martian minerals identification. In this paper, the spectral characteristics of the main Martian-related minerals were analyzed by using both visible near-infrared (Vis-NIR) reflectance spectroscopy and Raman spectroscopy. And some data pre-processing methods such as baseline correction, Savitzky-Golay smoothing, standard normal variate (SNV) scaling were used to produce a high-quality representation of the spectral data. Firstly, the information-rich spectral bands with higher signal-to-noise ratio and less overlapping were selected (i. e., Vis-NIR: 430～2 430 nm; Raman: 130～1 100 cm-1) for the clustering analysis. Secondly, soft independent method of class analogy (SIMCA) and principal component analysis-K-nearest neighbor (PCA-KNN), were respectively built based on selected Vis-NIR, Raman and two kinds of their fusion data(i. e., coaddition fusion and concatenation fusion), respectively. The accuracy of SIMCA model was enhanced from 72.6% (Vis-NIR) and 90.7% (Raman) to 96.3% (coaddition fusion) and 98. 1% (concatenation fusion). The accuracy of PCA-KNN model was improved from 68.9% (Vis-NIR) and 72.9% (Raman) to 80.3% (coaddition fusion) and 92.6% (concatenation fusion), respectively. The results indicate that the fused Raman/Vis-NIR data can improve the classification model’s accuracy of Martian-related minerals which will lay the foundation of quick rock classification for future Mars exploration.

In order to meet professional requirements for the portable and high-performance Raman spectrometer, a small near-infrared (NIR) Raman spectrometer for biomedical detection was built in this work. In addition, assembly system was completed through the theoretical calculation, geometric optical path design. Differences from the traditional structure with reflective collimation were shown as below. (1) Transmission-based collimation method was adopted in dispersion system of the spectrometer, so the collimated scattering light projected onto the grating for dispersion. (2) Following dichroic mirror for reflection and penetration, objective lens converging the incident light and collecting the scattered light, the Raman spectrometer was designed to meet confocal plane at the slit between the collection unit and dispersion system, which is useful to collect the Raman signal and remove the stray light. (3) The spectrometer system achieves the high-resolution (3 cm-1), high repeatability and high sensitivity for spectral detection ranging of 500~2 200 cm-1 (785 excitation). (4) The entire optical system was designed in the size of ca. 240 mm×200 mm×130 mm, therefore achieving miniaturization for this NIR Raman spectrometer and flexible assembly of components. It was then used to measure Raman spectra of glucose and knee cartilage and get excellent results by comparing with that obtained by huge commercial Raman spectrometer. The results show that the spectrometer has high resolution, high reproducibility and high sensitivity, etc, thus it can be flexibly applied in biomedical and other research fields.

In this paper, the standard zinc coloring reagent and zinc color reaction result in water-insoluble flocculent complex. In addition, the absorbance was measured by spectrophotometer, the characteristic spectrum and the absorbance were studied, and the mathematical model was established between the concentration and the absorbance of characteristic wavelength. In this paper, color reagent mainly makes complexing reaction with zinc, copper, cadmium, nickel ion, so this study mainly explores the absorbance of four kinds of ions, such as high concentration and low concentration. Finally, through capturing the relationship between the concentration of zinc ions and the absorbance of the zinc ion, and getting the relationship between the concentration of zinc ions and the absorbance of the zinc ion as well as the absorbance of the four kinds of ions with four wavelengths, the relationship between the absorbance and the total absorbance of the zinc ion is given. During the experiment, the color reaction can meet the requirements of spectrophotometry, which is mainly because of the nature of the reagent, while the color reaction conditions are also essential. In the color reaction process, it is mainly zinc ions and zinc coloring agent complexation react to form complex ions, and flocculent complex. The ion is generally stable, but there is also ionization balance in the aqueous solution, that is when the color conditions change, the formation of complex ions may also occur in the decomposition of complex ions, thus affecting the degree of complex reaction . Color conditions include the amount of reagent, PH value, reaction temperature, color time, the salinity of the solution and turbidity. In conclusion, this paper focuses on the salinity of the solution to be measured on the measurement of zinc ion concentration, and gives the influence rule and calibration model through experiments.

We propose a new pH sensing technology using fluorescence sensing based on quantum dots combined with optical fiber sensing based on evanescent wave, which owns the advantages of high sensitivity, fast testing, suitability for micro-environment measurement, remote detection, real-time monitoring, in situ analysis and so on. In this paper, we detail the preparation method of the combined taper-and-cylinder optical fiber probe for evanescent wave sensing, the modification process of quantum dots onto the surface of the optical fiber probe, the construction of two fiber pH sensing platforms based on spectrum and intensity, and the evaluation of the performance of CdSe/ZnS quantum dots applied for optical fiber pH sensing from the aspects of response range, linearity, repeatability and stability, respectively. The results show that in the pH range of 2 to 12, the fluorescence spectrum peak position of CdSe/ZnS quantum dots will produce a red shift in strong acid and alkaline, and the amount of the red shift has a linear relationship with the pH value. The fluorescence intensity of the CdSe/ZnS quantum dots also reduces linearly with the decreasing of pH value. Moreover, the alternating tests under the strong acid and strong alkali indicate that it is of good repeatability. The real-time monitoring experiment through the intensity sensing platform indicates that it has good stability. Therefore, it is feasible to combine CdSe/ZnS quantum dots and evanescent wave for fiber pH sensing, and this kind of fiber pH sensor would have a promising future for pH detection in the field of biochemistry, environmental monitoring, clinical medicine and food safety.

In this paper, the spectral modulation by the quantum-cutting luminescence of Er3+Yb3+ ion-pairs in nanophase oxyfluoride vitroceramics is studied. We obtained X-ray diffraction spectra, surface topographies, excitation, absorption, and luminescence spectra of Er3+Yb3+ nanophase oxyfluoride vitroceramics, and compared them with the corresponding parameters of a Tb3+Yb3+-codoped sample. We find that the 652.0 nm wavelength red luminescence intensity is enhanced by the factors of 680.85 and 303.80 for (A) Er(1%)Yb(8.0%)∶FOV and (B) Er(0.5%)Yb(3.0%)∶FOV, respectively, when they are excited by 378 nm light than when they are excited by 522 nm light. It is also found that the 652.0 nm red luminescence intensity is enhanced 491.05 and 184.12 times for (A) Er(1%)Yb(8.0%)∶FOV and (B) Er(0.5%)Yb(3.0%)∶FOV than (C) Er(0.5%)∶FOV when they are both being excited by 378 nm light. the results show that the {978.0 and 1 012.0 nm} infrared luminescence intensities of (A) Er(1%)Yb(8.0%)∶FOV and (B) Er(0.5%)Yb(3.0%)∶FOV are {58.00 and 293.62} and {25.11 and 67.50} times, respectively, larger than the corresponding ones of (C) Er(0.5%)∶FOV when both excited with 378 nm light. And further, the intensities of the 378.5 nm excitation peak of (A) Er(1%)Yb(8.0%)∶FOV and (B) Er(0.5%)Yb(3.0%)∶FOV are about 606.02 time and 199.83 times, respectively, larger than (C) Er(0.5%)∶FOV when 652.0 nm luminescence wavelength is selected as the fluorescence receiving wavelength to measure the visible excitation spectra in the range of 250～628 nm. Meanwhile, we also find that the first-order quantum-cutting infrared 1 012 or 978 nm luminescence intensities of (A) Er(1%)Yb(8.0%)∶FOV and (B) Er(0.5%)Yb(3.0%)∶FOV are about 101.38 and 29.19 times larger than the second-order quantum-cutting infrared 976 nm luminescence intensity of (D) Tb(0.7%)Yb(5.0%)∶FOV. To the best of our knowledge, present quantum-cutting obtained in our study is the most intense quantum-cutting reported to date. Therefore, we believe that present first-order quantum-cutting luminescence of Er3+Yb3+-codoped oxyfluoride vitroceramics may be intense for the material’s use as a quantum-cutting layer to enhance the photovoltaic conversion efficiency of crystal silicon solar cell. The results can facilitate the probing of next-generation environmentally friendly spectral-modulation solar cells, which are currently the focus of global attention.

For the high combustion temperature measurement in harsh environment, the radiation spectroscopy method was proposed to realize the online measurement of combustion temperature of solid rocket propellant. The radiation spectrums in the range of 200~1 100 nm of solid rocket propellant flame in high pressure experimental combustor were obtained by fiber-optic spectrometer. Their representative characteristics were summarized, and the corresponding combustion temperature was determined by the Planck radiation law and the spectral fitting method. The paper provides important reference for combustion diagnostics and mechanism of solid rocket propellant.

In the present work, the experimental and the theoretical spectroscopic properties of 1-Methyl-6-Nitro-1H- Benzimidazole were investigated. The FT-IR (400~4 000 cm-1) and FT-Raman spectra (100~4 000 cm-1) of 1-Methyl-6-Nitro-1H- Benzimidazole in the solid phase were recorded. Also, experimental NMR and UV spectra of titled molecule were measured. To interpret the experimental data, geometric parameters, vibrational frequencies, NMR, UV spectra and NLO analysis of the optimized molecule were calculated using ab initio Hartree–Fock (HF) method and density functional theory (B3LYP) method with the 6-31++G(d,p) and 6-311++G(d,p) basis sets. Vibrational bands were assigned based on the potential energy distribution using the VEDA 4 program. The theoretical results showed good agreement with the experimental values.

The effect of various metal ions on the DNA mediated energy transfer between simultaneously bound drugs was investigated using spectroscopic methods. It was found that addition of divalent metal ions (Mg2+, Ca2+, Mn2+, Co2+ and Ni2+) resulted in further decrease of the ethidium fluorescence intensity, while a small increase was observed in the TMPyP emission band, implying that the energy of excited ethidium was transferred to TMPyP. This DNA-mediated quenching efficiency between ethidium and TMPyP was significantly enhanced by the presence of all metal ions. Among the divalent metal ions, alkali earth metal ions and Mn2+ displayed higher quenching efficiencies than other transition metal ions. The distances required to permit the energy transfer between the two drugs in DNA were calculated as 68, 66, 62, 48 and 38  in the presence of 100 μmol·L-1 of Mg2+, Ca2+, Mn2+, Co2+ and Ni2+ ion, respectively. The disturbed binding conformation of TMPyP in DNA by metal ions presumably accounts for the difference.

A spectral characterization model based on dimension reduction is proposed to guarantee the precision of color conversion of the multi-color printer and improve its operation efficiency. Color space division theory and LabPQR nonlinear dimensionality reduction method are adopted in the new model. Moreover, the forward model is created based on Lookup Table, and the backward model is created through cell search algorithm and inverse tetrahedral interpolation algorithm. Firstly, the high dimensional spectral reflectance is reduced to six dimensional space values (LabPQR). Then the cell space of the target color is searched using cell search algorithm. Finally, the LabPQR values of the target color are calculated with the inverse tetrahedral interpolation algorithm, and the output values of the multi-color printer channel signals are obtained. The experimental data of the tested color samples shows that the average color difference of the forward model and the backward model are 0.714 NBS and 1.016 NBS respectively, and the corresponding running time of the models are 2.03 and 9.05 s. New algorithm could realize the accurate inter-conversion between the spectral reflectance of a multi-color printer and its channel-signal values.

An angle scanning prism-based SPR sensor system is proposed in this paper. With the structure of reflex parallel light path, the system has been simplified, which mainly consists of light source, CCD sensor, parallel light path structure, rotation and temperature control module. With the motor scanning incidence angle and temperature control, an effective measurement of glucose refractive index (RI) mass concentration property can be achieved. Moreover, a theoretical model has been established to explain the existence of a sensitivity matrix, which enables both the RI and temperature to be measured and obtained from proof-of-concept experiment. This approach paves a way for conventional SPR-based sensors to discriminate between RI-induced and temperature-induced SPR changes and provides a reference for the correction of temperature interference.

Neutral beam injection (NBI) is one of the most effective means of plasma heating and current driving. There are three basic processes in neutral beam injector: generation of ion beam,neutralization of ion beam and transmission of neutral beam, among which neutralization of ion beam is the key link. The gas target thickness in neutralizer directly affects the neutralization process, and further affects neutral beam transmission efficiency.A new diagnostic technique for the determination of gas target thickness, based on the Doppler shift effect, is presented and applied to neutral beam injector operating on Experimental Advanced Superconducting Tokamak (EAST) NBI testbed. The basis of the method is the process of beam component evolution with gas target thickness.The gas target thickness is estimated by the value of Dalpha spectral line intensity. The method is applied to the EAST NBI of Institute of Plasma physics, Chinese Academy of Sciences (ASIPP). Gas target thickness in the range of 0.16~0.22×1016 cm-2 are measured close to the exit of neutralizer,and gas target thickness measured with this novel technique correlate very well with the extracted beam current. According to the law of conservation of mass, a rough calculation of gas target thickness is basically consistent with the calculation of the novel technique, which verifies its correctness. Experimental results show that spectrum method based on the Doppler shift effect can be applied to estimate neutralizer gas target thickness.