Juliana Ferreira de Santana, A. Mirzahosseini, B. Noszál
1H and 13C NMR measurements were carried out to explore anticipated correlations between chemical shifts versus thiolate basicities and redox potentials of cysteamine, homocysteine, penicillamine, and their homodisulfides. All correlations were analyzed and statistically evaluated. The closest correlation was observed for the αCH nuclei concerning 1H and 13C NMR data. Since neither site-specific basicities nor site-specific redox potentials can be directly measured by any means in peptides and proteins containing several thiol and/or disulfide units, these data provide a simple method and predictive power to estimate the aforementioned site-specific physicochemical parameters for analogous sulfur-containing moieties in related biopolymers.
{"title":"Correlation between the NMR Chemical Shifts and Thiolate Protonation Constants of Cysteamine, Homocysteine, and Penicillamine","authors":"Juliana Ferreira de Santana, A. Mirzahosseini, B. Noszál","doi":"10.1155/2022/9491360","DOIUrl":"https://doi.org/10.1155/2022/9491360","url":null,"abstract":"1H and 13C NMR measurements were carried out to explore anticipated correlations between chemical shifts versus thiolate basicities and redox potentials of cysteamine, homocysteine, penicillamine, and their homodisulfides. All correlations were analyzed and statistically evaluated. The closest correlation was observed for the αCH nuclei concerning 1H and 13C NMR data. Since neither site-specific basicities nor site-specific redox potentials can be directly measured by any means in peptides and proteins containing several thiol and/or disulfide units, these data provide a simple method and predictive power to estimate the aforementioned site-specific physicochemical parameters for analogous sulfur-containing moieties in related biopolymers.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"21 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87926546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bruise may cause spoilage, reduce commodity economic value, and give rise to food quality and safety concerns. Therefore, it is crucial to detect whether a loquat is bruised and when it is bruised to save storage and transportation costs. At present, the bruise of loquats is mainly discriminated by the operator’s naked eye, which is affected by personal habits, light intensity, and subjective psychological factors. The detection method is time-consuming, inaccurate, inefficient, and difficult to identify the bruise’s time of loquats. Due to the fact that the color features can be used to perform the conditions of the darkened and brownish regions in bruise’s loquats, the combined spectral information and the color features method is proposed to accurately detect the storage time of mild bruise’s loquats in this study. In order to reduce economic losses, different methods are used to deal with the loquats at the corresponding bruise’s time. Loquats with four types of bruise’s time, including 6, 12, 24, and 36 h, are studied. Models with four types of characteristics, including spectral information, RGB features combined with spectral information, HSI features combined with spectral information, and mixed color features combined with spectral information (mixed-spectral), are established based on linear discriminant analysis (LDA), support vector machine (SVM), and least-squares support vector machine (LS-SVM). The investigated 400 independent samples with four bruise’s time conditions are utilized to assess the classification ability of the proposed methods. The results indicate that the Mixed-RBF-LS-SVM model has the lowest errors, and the accuracies of storage time of mild bruise’s loquats at 6, 12, 24, and 36 h are 100%, 92%, 92%, and 100%, respectively. The overall accuracy of the LS-SVM model based on mixed-spectral is 96%, and it demonstrates that the combined spectral information and color features method can be used to accurately detect the bruise’s time of loquats. Finally, the LS-SVM model based on mixed-spectral is optimized by UVE, SPA, CARS, and GA, respectively; it is found that the UVE-LS-SVM model based on mixed-spectral is the best, and the overall accuracy is 92%. It also lays a foundation for future studies about detecting the bruise’s time of fruits with a high-precision, rapid, and nondestructive measurement.
碰伤会导致食物变质，降低商品的经济价值，并引起食物的质量和安全问题。因此，检测枇杷是否破损，何时破损，对于节约储运成本至关重要。目前，枇杷瘀伤主要靠操作人员肉眼判别，受个人习惯、光照强度、主观心理等因素的影响。该检测方法耗时长、不准确、效率低，且难以确定枇杷的瘀伤时间。由于颜色特征可用于表征瘀伤枇杷的暗区和褐区情况，因此本研究提出将光谱信息与颜色特征相结合的方法来准确检测轻度瘀伤枇杷的贮藏时间。为了减少经济损失，在相应的损伤时间，对枇杷采取不同的处理方法。研究了6、12、24、36 h四种类型的枇杷瘀伤时间。基于线性判别分析(LDA)、支持向量机(SVM)和最小二乘支持向量机(LS-SVM)，建立光谱信息、RGB特征结合光谱信息、HSI特征结合光谱信息、混合色彩特征结合光谱信息(混合光谱)四种特征的模型。利用调查的400个具有4种瘀伤时间条件的独立样本来评估所提出方法的分类能力。结果表明，混合rbf - ls - svm模型误差最小，6、12、24、36 h轻度淤伤枇杷贮藏时间的准确率分别为100%、92%、92%、100%。基于混合光谱的LS-SVM模型总体准确率为96%，表明光谱信息与颜色特征相结合的方法可以准确检测枇杷的瘀伤时间。最后，分别采用UVE、SPA、CARS和遗传算法对基于混合光谱的LS-SVM模型进行优化;结果表明，基于混合光谱的UVE-LS-SVM模型效果最好，总体准确率达到92%。为今后高精度、快速、无损检测水果损伤时间的研究奠定了基础。
{"title":"Detection Storage Time of Mild Bruise’s Loquats Using Hyperspectral Imaging","authors":"Zhao Han, Bin Li, Qiu Wang, Akun Yang, Yande Liu","doi":"10.1155/2022/9989002","DOIUrl":"https://doi.org/10.1155/2022/9989002","url":null,"abstract":"Bruise may cause spoilage, reduce commodity economic value, and give rise to food quality and safety concerns. Therefore, it is crucial to detect whether a loquat is bruised and when it is bruised to save storage and transportation costs. At present, the bruise of loquats is mainly discriminated by the operator’s naked eye, which is affected by personal habits, light intensity, and subjective psychological factors. The detection method is time-consuming, inaccurate, inefficient, and difficult to identify the bruise’s time of loquats. Due to the fact that the color features can be used to perform the conditions of the darkened and brownish regions in bruise’s loquats, the combined spectral information and the color features method is proposed to accurately detect the storage time of mild bruise’s loquats in this study. In order to reduce economic losses, different methods are used to deal with the loquats at the corresponding bruise’s time. Loquats with four types of bruise’s time, including 6, 12, 24, and 36 h, are studied. Models with four types of characteristics, including spectral information, RGB features combined with spectral information, HSI features combined with spectral information, and mixed color features combined with spectral information (mixed-spectral), are established based on linear discriminant analysis (LDA), support vector machine (SVM), and least-squares support vector machine (LS-SVM). The investigated 400 independent samples with four bruise’s time conditions are utilized to assess the classification ability of the proposed methods. The results indicate that the Mixed-RBF-LS-SVM model has the lowest errors, and the accuracies of storage time of mild bruise’s loquats at 6, 12, 24, and 36 h are 100%, 92%, 92%, and 100%, respectively. The overall accuracy of the LS-SVM model based on mixed-spectral is 96%, and it demonstrates that the combined spectral information and color features method can be used to accurately detect the bruise’s time of loquats. Finally, the LS-SVM model based on mixed-spectral is optimized by UVE, SPA, CARS, and GA, respectively; it is found that the UVE-LS-SVM model based on mixed-spectral is the best, and the overall accuracy is 92%. It also lays a foundation for future studies about detecting the bruise’s time of fruits with a high-precision, rapid, and nondestructive measurement.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"84 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83979416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study, monometallic copper oxide nanoparticles (CuONPs) were synthesized by chemical reduction of copper sulfate (CuSO4) salt through sugar glucose. X-ray diffraction profiles approved the formation of metallic oxide nanoparticles. TEM images showed spherical nanoparticles with an average particle size of 60 nm. The interaction of HEC and copper oxide nanoparticles was investigated by FTIR spectroscopy. The UV-visible absorption spectrum showed a surface plasmon resonance peak at 270 nm. The effect of doping of copper oxide nanoparticles (CuONPs) on the optical and thermal properties of HEC was studied. The results showed that the concentration of CuO nanoparticles has a prominent influence on the optical, structural, and thermal properties of hydroxyethyl cellulose.
{"title":"Characterization and Optical Studies of Hydroxyethyl Cellulose-Copper Oxide Nanocomposites","authors":"A. Alsubaie","doi":"10.1155/2022/8422803","DOIUrl":"https://doi.org/10.1155/2022/8422803","url":null,"abstract":"In this study, monometallic copper oxide nanoparticles (CuONPs) were synthesized by chemical reduction of copper sulfate (CuSO4) salt through sugar glucose. X-ray diffraction profiles approved the formation of metallic oxide nanoparticles. TEM images showed spherical nanoparticles with an average particle size of 60 nm. The interaction of HEC and copper oxide nanoparticles was investigated by FTIR spectroscopy. The UV-visible absorption spectrum showed a surface plasmon resonance peak at 270 nm. The effect of doping of copper oxide nanoparticles (CuONPs) on the optical and thermal properties of HEC was studied. The results showed that the concentration of CuO nanoparticles has a prominent influence on the optical, structural, and thermal properties of hydroxyethyl cellulose.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"10 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91261002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aflatoxin B1 (AFB1) contamination in peanut oil brings about a significant threat to human health. A method based on Fourier transform near-infrared (FT-NIR) spectroscopy was developed for qualitative and quantitative analysis of AFB1 contamination in peanut oil. A total of 94 samples were collected in the transmission mode and processed by a derivative and smoothing filter. Principal component analysis (PCA), discriminant analysis (DA), and partial least squares regression (PLS) were applied to establish the qualitative and quantitative analysis models. It was demonstrated that the qualitative model could distinguish effectively between the positive and negative samples with identification accuracy up to 100%. The correlation coefficient (R2), the root mean square error of calibration (RMSCE), and the relative percent deviation (RPD) for the quantitative model were 0.951, 3.87%, and 4.52, respectively. There was a good linear relationship between the predicted and reference concentrations of the samples with a significant correlation coefficient of 0.981. The qualitative and quantitative analysis models developed in this work may provide reference for researchers engaged in nondestructive testing of food and agricultural products.
{"title":"Rapid Determination of Aflatoxin B1 Contamination in Peanut Oil by Fourier Transform Near-Infrared Spectroscopy","authors":"Wanqing Yao, Ruanshan Liu, Zhaocheng Xu, Yuling Zhang, Yingming Deng, Hongwei Guo","doi":"10.1155/2022/9223424","DOIUrl":"https://doi.org/10.1155/2022/9223424","url":null,"abstract":"Aflatoxin B1 (AFB1) contamination in peanut oil brings about a significant threat to human health. A method based on Fourier transform near-infrared (FT-NIR) spectroscopy was developed for qualitative and quantitative analysis of AFB1 contamination in peanut oil. A total of 94 samples were collected in the transmission mode and processed by a derivative and smoothing filter. Principal component analysis (PCA), discriminant analysis (DA), and partial least squares regression (PLS) were applied to establish the qualitative and quantitative analysis models. It was demonstrated that the qualitative model could distinguish effectively between the positive and negative samples with identification accuracy up to 100%. The correlation coefficient (R2), the root mean square error of calibration (RMSCE), and the relative percent deviation (RPD) for the quantitative model were 0.951, 3.87%, and 4.52, respectively. There was a good linear relationship between the predicted and reference concentrations of the samples with a significant correlation coefficient of 0.981. The qualitative and quantitative analysis models developed in this work may provide reference for researchers engaged in nondestructive testing of food and agricultural products.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"23 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72527182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hubin Liu, Na Liu, Yuhui Yuan, Cihai Zhang, Longlian Zhao, Junhui Li
A reliable and effective qualitative near-infrared (NIR) spectroscopy discrimination method is critical for excellent model building, yet the performance of models built by these methods is highly dependent on valid feature extraction. The goal of feature selection is to associate the selected variables with the property of interest, which many have done successfully. However, many of selection methods focus only on strong association with the analytes or properties of interest, neglecting correlations between variables. A variable selection method based on a fast nondominated-ranking genetic algorithm (NSGA-II) was proposed in this paper for qualitative discrimination of NIR spectra. The method had two objective functions: (1) maximizing the sum of ratios of interclass variance to intraclass variance, (2) minimizing the sum of correlation coefficients between the selected variables. FT-NIR spectra of a total of 124 tobacco samples from different origins and parts in Guizhou Province, China, were used as the experimental objects, and the part-grade discrimination models of tobacco leaves were established by combining this method with partial least squares-based discriminant analysis (PLS-DA), and compared with PLS-DA model based on the full spectrum. The results showed that the performance of PLS-DA model with the NSGA-II was improved, with a comparable or better correct discrimination rate and reasonable discrimination rate, and could discriminate different parts of the tobacco leaves well. It indicates that the NSGA-II can select a few and effective feature variables to build a high-performance qualitative discrimination model and is proved to be a promising algorithm. In addition, the method is not designed exclusively for spectral data. It is a general strategy that could be used for variable selection for other types of data.
{"title":"A Variable Selection Method Based on Fast Nondominated Sorting Genetic Algorithm for Qualitative Discrimination of Near Infrared Spectroscopy","authors":"Hubin Liu, Na Liu, Yuhui Yuan, Cihai Zhang, Longlian Zhao, Junhui Li","doi":"10.1155/2022/2141872","DOIUrl":"https://doi.org/10.1155/2022/2141872","url":null,"abstract":"A reliable and effective qualitative near-infrared (NIR) spectroscopy discrimination method is critical for excellent model building, yet the performance of models built by these methods is highly dependent on valid feature extraction. The goal of feature selection is to associate the selected variables with the property of interest, which many have done successfully. However, many of selection methods focus only on strong association with the analytes or properties of interest, neglecting correlations between variables. A variable selection method based on a fast nondominated-ranking genetic algorithm (NSGA-II) was proposed in this paper for qualitative discrimination of NIR spectra. The method had two objective functions: (1) maximizing the sum of ratios of interclass variance to intraclass variance, (2) minimizing the sum of correlation coefficients between the selected variables. FT-NIR spectra of a total of 124 tobacco samples from different origins and parts in Guizhou Province, China, were used as the experimental objects, and the part-grade discrimination models of tobacco leaves were established by combining this method with partial least squares-based discriminant analysis (PLS-DA), and compared with PLS-DA model based on the full spectrum. The results showed that the performance of PLS-DA model with the NSGA-II was improved, with a comparable or better correct discrimination rate and reasonable discrimination rate, and could discriminate different parts of the tobacco leaves well. It indicates that the NSGA-II can select a few and effective feature variables to build a high-performance qualitative discrimination model and is proved to be a promising algorithm. In addition, the method is not designed exclusively for spectral data. It is a general strategy that could be used for variable selection for other types of data.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"45 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80278241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Buthaina Kamel, Moustafa Sayem El-Daher, W. Bachir, A. Ibrahim, S. Aljalali
Photodynamic therapy (PDT) is a selective and minimally invasive technique for the treatment of tumors. It includes three components such as photosensitizer, light, and molecular oxygen. The purpose of this work is to investigate the effect of the solvents such as methanol, ethanol, acetone, and water on fluorescent spectroscopy produced by one of the BODIPY derivatives in turbid media. A 520 nm laser diode is used for exciting one of the BODIPY derivatives as a photosensitizer in tissue-like optical phantoms. Results show that the photosensitizer studied without absorption and scattering components in the methanol and ethanol solvent has a prominent fluorescence peak at 600 nm, whereas acetone solvent has a prominent fluorescence peak at 546 nm. Experimental results reveal that when absorption and scattering components are present in addition to the studied solvents, the characteristic fluorescence intensity peak is red-shifted to 678 nm.
{"title":"Effect of Solvents on the Fluorescent Spectroscopy of BODIPY-520 Derivative","authors":"Buthaina Kamel, Moustafa Sayem El-Daher, W. Bachir, A. Ibrahim, S. Aljalali","doi":"10.1155/2022/1172183","DOIUrl":"https://doi.org/10.1155/2022/1172183","url":null,"abstract":"Photodynamic therapy (PDT) is a selective and minimally invasive technique for the treatment of tumors. It includes three components such as photosensitizer, light, and molecular oxygen. The purpose of this work is to investigate the effect of the solvents such as methanol, ethanol, acetone, and water on fluorescent spectroscopy produced by one of the BODIPY derivatives in turbid media. A 520 nm laser diode is used for exciting one of the BODIPY derivatives as a photosensitizer in tissue-like optical phantoms. Results show that the photosensitizer studied without absorption and scattering components in the methanol and ethanol solvent has a prominent fluorescence peak at 600 nm, whereas acetone solvent has a prominent fluorescence peak at 546 nm. Experimental results reveal that when absorption and scattering components are present in addition to the studied solvents, the characteristic fluorescence intensity peak is red-shifted to 678 nm.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"349 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75492153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We report a compositional analysis of four coal samples collected from different mines in Pakistan and one Chinese brand. The coal samples were pelletized in the form of a disc and irradiated with a focused laser beam of fundamental (1064 nm) and second (532 nm) harmonics of Nd:YAG laser, which produced plasma on the sample surface. The plasma emissions were recorded using a broadband (200–800 nm), high-resolution spectrometer (LIBS2500plus, Ocean Optics Inc., USA), which shows that the emission spectra from 532 nm, were more intense and dense in comparison with 1064 nm spectra. The compositional analysis of coal samples was performed using the calibration-free LIBS technique, utilizing the plasma temperature and self-absorption corrected emission line intensities. The analysis yields a number of major and trace elements in coal samples, among which the concentration of carbon varies from 642 to 718 g/kg, and sulfur contents were detected as 1.1 to 7.2 g/kg. The heavy metals chromium and lead were detected in the range of 14 to153 and 210 to 252 ppm, respectively. In addition, the gross calorific value (GCV) of all the coal samples was estimated using the concentrations of carbon, hydrogen, nitrogen, oxygen, and sulfur from 26.40 to 27.18 MJ/kg, which is an important parameter to determine the coal quality and burning efficiency.
{"title":"Analysis of Carbon Contents and Heavy Metals in Coal Samples Using Calibration-free LIBS Technique","authors":"M. A. Israr, Q. Abbas, S. Haq, A. Nadeem","doi":"10.1155/2022/3328477","DOIUrl":"https://doi.org/10.1155/2022/3328477","url":null,"abstract":"We report a compositional analysis of four coal samples collected from different mines in Pakistan and one Chinese brand. The coal samples were pelletized in the form of a disc and irradiated with a focused laser beam of fundamental (1064 nm) and second (532 nm) harmonics of Nd:YAG laser, which produced plasma on the sample surface. The plasma emissions were recorded using a broadband (200–800 nm), high-resolution spectrometer (LIBS2500plus, Ocean Optics Inc., USA), which shows that the emission spectra from 532 nm, were more intense and dense in comparison with 1064 nm spectra. The compositional analysis of coal samples was performed using the calibration-free LIBS technique, utilizing the plasma temperature and self-absorption corrected emission line intensities. The analysis yields a number of major and trace elements in coal samples, among which the concentration of carbon varies from 642 to 718 g/kg, and sulfur contents were detected as 1.1 to 7.2 g/kg. The heavy metals chromium and lead were detected in the range of 14 to153 and 210 to 252 ppm, respectively. In addition, the gross calorific value (GCV) of all the coal samples was estimated using the concentrations of carbon, hydrogen, nitrogen, oxygen, and sulfur from 26.40 to 27.18 MJ/kg, which is an important parameter to determine the coal quality and burning efficiency.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"10 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81976862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lei Shi, Yuyue Zhang, Fangyan Li, Yuefan Du, Bo Yao
Radiation heat transfer plays a dominant role in high-temperature flow field. Rapid and reliable calculation of spectral radiation properties is beneficial for thermal analysis and detection of radiation target. In this paper, a multiscale-band k-distribution model is proposed for the study of radiation properties in high-temperature gases. The accurate absorption coefficients are firstly calculated using the line-by-line model. The slope of the accurate absorption coefficient line and its slope threshold are then extracted and analyzed, which act as a basis to divide the absorption coefficient line into multiple segments. For different segments, different bandwidths are chosen for the corresponding band k-distribution model. In the model, the 7-point Gauss–Lobatto method is employed to obtain the optimized absorption coefficients. These optimized absorption coefficients formed the absorption coefficient database. The radiation intensities of gases are finally calculated and analyzed based on the optimized database. Experimental results suggest that the multiscale-band k-distribution model can improve the efficiency up to 35% compared with the widely used narrow-band k-distribution model. Simultaneously, the relative calculation error is less than 5% compared with the most accurate line-by-line model.
{"title":"Multiscale-Band K-Distribution Model for Molecules in High-Temperature Gases","authors":"Lei Shi, Yuyue Zhang, Fangyan Li, Yuefan Du, Bo Yao","doi":"10.1155/2022/5502651","DOIUrl":"https://doi.org/10.1155/2022/5502651","url":null,"abstract":"Radiation heat transfer plays a dominant role in high-temperature flow field. Rapid and reliable calculation of spectral radiation properties is beneficial for thermal analysis and detection of radiation target. In this paper, a multiscale-band k-distribution model is proposed for the study of radiation properties in high-temperature gases. The accurate absorption coefficients are firstly calculated using the line-by-line model. The slope of the accurate absorption coefficient line and its slope threshold are then extracted and analyzed, which act as a basis to divide the absorption coefficient line into multiple segments. For different segments, different bandwidths are chosen for the corresponding band k-distribution model. In the model, the 7-point Gauss–Lobatto method is employed to obtain the optimized absorption coefficients. These optimized absorption coefficients formed the absorption coefficient database. The radiation intensities of gases are finally calculated and analyzed based on the optimized database. Experimental results suggest that the multiscale-band k-distribution model can improve the efficiency up to 35% compared with the widely used narrow-band k-distribution model. Simultaneously, the relative calculation error is less than 5% compared with the most accurate line-by-line model.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"54 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80862962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the present paper, I report on the spectroscopic study for tourmaline color origin, performed red samples from Minas Geras State, Brazil, by gemological routine testing, X-ray diffraction, Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, and X-ray photoelectron spectroscopy. The main goal was the analysis of the optical absorption spectra and the chemical states of transition metal cations in order to better understand the effect of transition metal cations on color of tourmaline. The results showed that the red color was confirmed by the symmetric broad absorption at 527 nm and the narrow absorption at 400 and 450 nm, and the above three absorption bands were caused by the d-d electron transition of Mn3+, which occupied the Y site in the crystal structure and coordinated with F to form bonds. In addition, in principle, the chemical states of the chromogenic ions in tourmaline and their influence on coloration were confirmed, which would be beneficial to assessing the color change and identifying the origin of tourmaline.
{"title":"Spectroscopic Characteristics and Color Origin of Red Tourmaline from Brazil","authors":"Ming Li","doi":"10.1155/2022/1769710","DOIUrl":"https://doi.org/10.1155/2022/1769710","url":null,"abstract":"In the present paper, I report on the spectroscopic study for tourmaline color origin, performed red samples from Minas Geras State, Brazil, by gemological routine testing, X-ray diffraction, Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, and X-ray photoelectron spectroscopy. The main goal was the analysis of the optical absorption spectra and the chemical states of transition metal cations in order to better understand the effect of transition metal cations on color of tourmaline. The results showed that the red color was confirmed by the symmetric broad absorption at 527 nm and the narrow absorption at 400 and 450 nm, and the above three absorption bands were caused by the d-d electron transition of Mn3+, which occupied the Y site in the crystal structure and coordinated with F to form bonds. In addition, in principle, the chemical states of the chromogenic ions in tourmaline and their influence on coloration were confirmed, which would be beneficial to assessing the color change and identifying the origin of tourmaline.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"12 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80929760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The combined terahertz time-domain spectroscopy (THz-TDS) and chemometric technology is used to detect the adulteration of similar substances in Panax notoginseng powder. Four kinds of samples are prepared in the experiment, three kinds of adulterated samples are Panax notoginseng powder adulterating with zedoary turmeric powder, Panax notoginseng powder adulterating with wheat flour, and Panax notoginseng powder adulterating with rice flour, respectively. The values of adulterated concentration are from 5% to 60%, the interval of adulterated concentration is 5%, and the other sample is pure Panax notoginseng powder. The modeling and prediction sets are divided by 3 : 1 by class. The feature information of models is extracted by elimination of uninformative variable (UVE) method and successive projection algorithm (SPA); combining with back propagation neural network (BPNN), the UVE-BPNN and SPA-BPNN qualitative models are established, respectively. The model’s results show that the UVE-BPNN model is better; the classification accuracy of the prediction set of UVE-BPNN is 95%. Then, the least square support vector machine (LS-SVM) algorithm and partial least square (PLS) algorithm are used to establish the quantitative analysis model. The model’s results show that the LS-SVM model is better among the quantitative analysis models of zedoary turmeric powder and wheat flour, the correlation coefficient of prediction (RP) is 0.90 and 0.93 of LS-SVM, respectively, and the root mean square error of prediction (RMSEP) of LS-SVM is 0.072 and 0.068, respectively. Among the quantitative analysis models for rice noodles, the PLS model is better, with the RP of 0.94 and RMSEP of 0.06. The results show that the combined THz-TDS and chemometric technology can be used to determine the adulteration of similar substances in Panax notoginseng powder quickly, accurately, and nondestructively.
{"title":"Detection of Adulteration of Panax Notoginseng Powder by Terahertz Technology","authors":"Bin Li, Hai-Long Yin, Aihong Yang, Aiguo Ouyang","doi":"10.1155/2022/7247941","DOIUrl":"https://doi.org/10.1155/2022/7247941","url":null,"abstract":"The combined terahertz time-domain spectroscopy (THz-TDS) and chemometric technology is used to detect the adulteration of similar substances in Panax notoginseng powder. Four kinds of samples are prepared in the experiment, three kinds of adulterated samples are Panax notoginseng powder adulterating with zedoary turmeric powder, Panax notoginseng powder adulterating with wheat flour, and Panax notoginseng powder adulterating with rice flour, respectively. The values of adulterated concentration are from 5% to 60%, the interval of adulterated concentration is 5%, and the other sample is pure Panax notoginseng powder. The modeling and prediction sets are divided by 3 : 1 by class. The feature information of models is extracted by elimination of uninformative variable (UVE) method and successive projection algorithm (SPA); combining with back propagation neural network (BPNN), the UVE-BPNN and SPA-BPNN qualitative models are established, respectively. The model’s results show that the UVE-BPNN model is better; the classification accuracy of the prediction set of UVE-BPNN is 95%. Then, the least square support vector machine (LS-SVM) algorithm and partial least square (PLS) algorithm are used to establish the quantitative analysis model. The model’s results show that the LS-SVM model is better among the quantitative analysis models of zedoary turmeric powder and wheat flour, the correlation coefficient of prediction (RP) is 0.90 and 0.93 of LS-SVM, respectively, and the root mean square error of prediction (RMSEP) of LS-SVM is 0.072 and 0.068, respectively. Among the quantitative analysis models for rice noodles, the PLS model is better, with the RP of 0.94 and RMSEP of 0.06. The results show that the combined THz-TDS and chemometric technology can be used to determine the adulteration of similar substances in Panax notoginseng powder quickly, accurately, and nondestructively.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"1 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73172941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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