Article
Food Science & Technology
Xiaodong Zhang, Yafei Wang, Zhankun Zhou, Yixue Zhang, Xinzhong Wang
Summary: A new method was developed for the multi-source detection of tomato leaf mildew by combining near-infrared hyperspectral imaging and THz time-domain spectroscopy. The models incorporating near-infrared hyperspectral imaging, THz absorbance, and power spectra achieved high recognition rates for different grades of tomato leaf mildew infestation. A fusion diagnosis and health evaluation model of tomato leaf mildew with hyperspectral fusion THz was established and improved the recognition accuracy compared to single detection methods.
Article
Environmental Sciences
Jinnuo Zhang, Dongdong Ma, Xing Wei, Jian Jin
Summary: Remote sensing coupled with hyperspectral technology is increasingly used to study plant growth, health, and productivity. However, diurnal variations in spectral characteristics introduce more data variance, compromising the performance of trait estimation models. In this study, a fixed gantry platform was used to capture VNIR hyperspectral images of corn canopies at consecutive time intervals. Diurnal calibration models were established at every wavelength, and using diurnal calibration in canopy spectra processing effectively reduced spectral variance brought about by varying imaging time.
Article
Biochemistry & Molecular Biology
Hongzhe Jiang, Yilei Hu, Xuesong Jiang, Hongping Zhou
Summary: The maturity stages of Camellia oleifera fruit can be assessed accurately using a hyperspectral imaging system. Principal component analysis and classification models can be used to accurately discriminate different maturity stages. Selecting the correct wavelengths can improve the prediction accuracy.
Article
Food Science & Technology
Sai Xu, Huazhong Lu, Changxiang Fan, Guangjun Qiu, Christopher Ference, Xin Liang, Jian Peng
Summary: This study proposes a visible and near-infrared (VIS/NIR) hyperspectral imaging method to quickly and intelligently detect parasites in sashimi. The research results show that the VIS/NIR spectrums for fish meat and parasite images were different at certain wavelengths. The synthesis between a probabilistic neural network (PNN) and a combination of detection models allows for optimal detection of parasites in sashimi.
LWT-FOOD SCIENCE AND TECHNOLOGY
(2023)
Article
Food Science & Technology
Wenxiang Zhang, Liao Pan, Lixin Lu
Summary: A practical prediction method for evaluating the Total volatile basic nitrogen (TVB-N) content of beef covered by packaging films was proposed using visible-near infrared hyperspectral imaging (HSI). The study demonstrated that the influence of films on the prediction accuracy of TVB-N content can be eliminated by spectral preprocessing and modeling methods. It proved the feasibility of using visible-near infrared hyperspectral technology to predict TVB-N content in packaged beef.
Article
Multidisciplinary Sciences
Shuang Liu, Haiye Yu, Yuanyuan Sui, Haigen Zhou, Junhe Zhang, Lijuan Kong, Jingmin Dang, Lei Zhang
Summary: This study investigated the feasibility of classifying soybean frogeye leaf spot using image processing and dimensionality reduction methods on hyperspectral data. The results showed that a model combining PCA and SI performed well, with certain input variables outperforming full wavelength data in machine learning classifiers. The classification accuracies were significantly improved using the selected datasets.
Article
Computer Science, Information Systems
Yunan He, Chenxuan Yang, Sheng Jiang, Zhiji Deng, Peng Zhao, Ye Li
Summary: By combining hyperspectral imaging and mixed convolutional neural networks, a method for fast and efficient non-destructive identification of bloodstains is proposed, achieving high accuracy and efficiency in bloodstain identification in complex scenes.
Article
Agriculture, Multidisciplinary
Ji 'An Xia, WenYu Zhang, WeiXin Zhang, YuWang Yang, GuangYong Hu, DaoKuo Ge, Hong Liu, HongXin Cao
Summary: This study evaluated the potential of cloud computing technology for classifying protected tomato plants under different watering treatments. Different spectral datasets and machine-learning classifiers were applied to analyze the data, showing that the MLPC had higher classification accuracy than the ORC. The operating efficiency of the cloud computing platform was significantly improved with increased size of spectral dataset or number of nodes.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2021)
Article
Engineering, Geological
Young-Sun Son, Sang-Gun Noh, Eun-Seok Bang, Kwang-Eun Kim, Seong-Jun Cho, Hyunseob Baik
Summary: Coastal cliffs are prone to erosion and weathering due to strong waves and sea winds, leading to stability and environmental conservation issues. This study used ground-based hyperspectral imaging techniques to analyze volcanic island cliffs and found that support vector machine (SVM) outperformed mixture-tuned matched filtering (MTMF) in classifying volcanic rocks and weathering minerals. However, distinguishing volcanic rocks with similar compositions and textures proved to be challenging using both methods. This research highlights the effectiveness of ground-based hyperspectral imaging analysis in predicting geomorphological changes and ensuring safety on volcanic islands.
ENGINEERING GEOLOGY
(2022)
Article
Chemistry, Multidisciplinary
Soo Chung, Seung-Chul Yoon
Summary: By combining two hyperspectral imaging modalities, the Fusion model demonstrated higher accuracy in detecting foreign material on poultry products compared to single modalities, with a detected accuracy increase of 18% to 38% when compared to VNIR- and SWIR-based detection models.
APPLIED SCIENCES-BASEL
(2021)
Article
Chemistry, Applied
Songhao Li, Huilin Wu, Jing Zhao, Yu Liu, Yunpeng Li, Houcheng Liu, Yiting Zhang, Yubin Lan, Xinglong Zhang, Yutao Liu, Yongbing Long
Summary: This study developed a method using near infrared hyperspectral imaging (NIR-HSI) technology combined with machine learning to classify and identify different species of hybrid cherry tomato plants. The results showed that the linear discriminant analysis (LDA) model achieved the highest classification accuracy among the three machine learning algorithms, and the standard normal variate (SNV) preprocessing method had a greater improvement in model accuracy compared to other methods. Furthermore, using the mesophyll region or the whole leaf as regions of interest (ROI) for extracting reflectance spectra improved the classification accuracy of the leaf model. The LDA model combined with the SNV preprocessing method achieved high accuracy in both the training and test sets.
JOURNAL OF NEAR INFRARED SPECTROSCOPY
(2023)
Article
Chemistry, Applied
Antoni Femenias, Ferran Gatius, Antonio J. Ramos, Vicente Sanchis, Sonia Marin
Summary: The present study successfully evaluated the presence of DON and ergosterol in wheat samples using HSI-NIR spectroscopy and established prediction and classification models. The results indicate that this method can effectively quantify ergosterol and classify DON in samples according to the EU legal limit.
Article
Environmental Sciences
S. Junttila, T. Holtta, N. Saarinen, V. Kankare, T. Yrttimaa, J. Hyyppa, M. Vastaranta
Summary: The study investigated the use of novel small hyperspectral sensors for non-destructive estimation of leaf water content. Results showed that the sensors captured variations in equivalent water thickness and relative water content, providing detailed insights into the dynamics of leaf water content. The study concluded that close-range hyperspectral spectroscopy can be a novel tool for continuous measurement of leaf water content and better understanding of plant responses to environmental conditions.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Instruments & Instrumentation
Xiaoyun Chen, Kshitish A. Patankar, Matthew Larive
Summary: Polyurethane foams are widely used in various fields, and monitoring PU reactions with NIR HSI technology can effectively extract kinetics information. The advantages of NIR HSI over conventional FT-NIR systems include faster spectral acquisition time and higher spatial resolution.
APPLIED SPECTROSCOPY
(2021)
Review
Chemistry, Multidisciplinary
Zhiwei Zhang, Wenhui Wang, Michael O'Hagan, Jinghong Dai, Junji Zhang, He Tian
Summary: This review highlights recent progress in the development of red-shifted photoswitches that can be activated by visible and near-infrared light and exhibit different photochromic reaction mechanisms. These red-shifted photoswitches have great potential in biotechnology and materials chemistry applications.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2022)
Article
Engineering, Chemical
Ningqiu Tang, Jun Sun, Kunshan Yao, Xin Zhou, Yan Tian, Yan Cao, Adria Nirere
Summary: A fast nondestructive detection method based on hyperspectral imaging technology was proposed to distinguish different varieties of Lycium barbarum. By preprocessing, extracting characteristic wavelengths using CARS, and utilizing SVM model, the classification effect was improved with high accuracy rates. Additionally, the introduction of the whale optimization algorithm further enhanced the classification accuracy.
JOURNAL OF FOOD PROCESS ENGINEERING
(2021)
Article
Engineering, Chemical
Kunshan Yao, Jun Sun, Ningqiu Tang, Min Xu, Yan Cao, Lvhui Fu, Xin Zhou, Xiaohong Wu
Summary: This study explores the feasibility of using hyperspectral imaging technology to detect grades of Panax notoginseng powder. By combining CARS and PCA methods to process the spectral data, the MPA-LSSVM model shows higher accuracy and robustness in grade detection.
JOURNAL OF FOOD PROCESS ENGINEERING
(2021)
Article
Engineering, Chemical
Jun Sun, Lin Zhang, Xin Zhou, Kunshan Yao, Yan Tian, Adria Nirere
Summary: Accurate and rapid identification of rice seed varieties is crucial for agriculture and food security. The method proposed in this study, based on information fusion and artificial fish swarm algorithm combined with hyperspectral imaging, achieved high accuracy through feature selection and model construction.
JOURNAL OF FOOD PROCESS ENGINEERING
(2021)
Article
Agriculture, Multidisciplinary
Jun Sun, Kaifeng Yang, Chen Chen, Jifeng Shen, Yu Yang, Xiaohong Wu, Tomas Norton
Summary: In this paper, an improved wheat head counting network (WHCnet) was proposed to effectively count wheat heads from the top view. The proposed method achieved better results compared to other methods and met the requirements of wheat head counting in the field environment.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Instruments & Instrumentation
Min Xu, Jun Sun, Kunshan Yao, Qiang Cai, Jifeng Shen, Yan Tian, Xin Zhou
Summary: This study aimed to predict firmness and pH of Kyoho grape using hyperspectral imaging and a deep learning approach. The SAE-LSSVM model achieved optimal performance for firmness, while the SAE-PLS model yielded satisfactory accuracy for pH.
INFRARED PHYSICS & TECHNOLOGY
(2022)
Article
Food Science & Technology
Min Xu, Jun Sun, Kunshan Yao, Xiaohong Wu, Jifeng Shen, Yan Cao, Xin Zhou
Summary: In this study, a novel method involving variational mode decomposition and regression coefficients (VMD-RC) was proposed for nondestructive detection of TSS in grapes using hyperspectral imaging (HSI). The VMD-RC-LSSVM model showed the best prediction accuracy for TSS. The overall results suggest that the VMD-RC algorithm can effectively handle high-dimensional hyperspectral data and HSI has great potential for rapid evaluation of fruit quality attributes.
JOURNAL OF FOOD SCIENCE
(2022)
Article
Computer Science, Information Systems
Jun Sun, Kaifeng Yang, Xiaofei He, Yuanqiu Luo, Xiaohong Wu, Jifeng Shen
Summary: This study proposed a novel depth fusion algorithm based on visible and near-infrared imagery to improve the recognition of beet seedlings and weeds. By utilizing an improved region-based fully convolutional network (R-FCN) model, deformable convolution, and online hard example mining, the average precision of the optimal model was significantly enhanced. The study can serve as a theoretical basis for the development of intelligent weed control robots under weak light conditions.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Xin Zuo, Zhi Wang, Yue Liu, Jifeng Shen, Haoran Wang
Summary: Balancing accuracy and efficiency is crucial for multispectral pedestrian detection. A light-weight anchor-free detection pipeline and a mixed attention mechanism are proposed to achieve faster speed and improved accuracy. Experiments show significant performance improvement in terms of MR compared to other methods on different datasets.
NEURAL PROCESSING LETTERS
(2023)
Article
Agronomy
Weidong Zhu, Jun Sun, Simin Wang, Jifeng Shen, Kaifeng Yang, Xin Zhou
Summary: This paper proposes an accurate and efficient disease identification model for crops, which analyzes both local and global features and improves the separability between similar diseases. Experimental results show that the model has good generalization ability on different datasets and achieves a balance between identification accuracy and parameter quantity.
Article
Computer Science, Hardware & Architecture
Jifeng Shen, Yue Liu, Yifei Chen, Xin Zuo, Jun Li, Wankou Yang
Summary: This paper proposes a novel explicit feature modulation solution for multi-task learning of object detection and box-level segmentation. The proposed solution includes semantic feature enhancement of the backbone and confidence score enhancement of the detection head. Experimental results demonstrate that this modulation method significantly improves the performance of the tasks and achieves good results on multiple datasets.
COMPUTERS & ELECTRICAL ENGINEERING
(2022)
Article
Engineering, Chemical
Kunshan Yao, Jun Sun, Jiehong Cheng, Min Xu, Chen Chen, Xin Zhou
Summary: The feasibility of using a low-cost and portable NIR spectrometer to detect the S-ovalbumin content of eggs was investigated in this study. A model population analysis based competitive adaptive reweighted sampling (MPA-CARS) algorithm was proposed to reduce the dimensionality of spectral data. The results showed that MPA-CARS had better feature extraction performance than CARS and required fewer selected feature wavelengths. The simplified XGBoost model based on MPA-CARS feature wavelengths yielded the best performance for predicting S-ovalbumin content.
JOURNAL OF FOOD PROCESS ENGINEERING
(2023)
Article
Computer Science, Information Systems
Weidong Zhu, Jun Sun, Simin Wang, Kaifeng Yang, Jifeng Shen, Xin Zhou
Summary: This paper proposes an improved model based on convolutional neural networks for accurate segmentation and recognition of various objects in sweet pepper images captured at night. The experimental results show that the proposed method achieves higher segmentation performance compared to other models and has good generalization performance when facing unforeseen picking situations.
MULTIMEDIA SYSTEMS
(2023)
Article
Agronomy
Xin Zuo, Jiao Chu, Jifeng Shen, Jun Sun
Summary: This study proposes a multi-granularity feature aggregation method for accurately identifying disease types and crop species, as well as better understanding the disease-affected regions. The method achieves high classification accuracies and F1 scores on multiple datasets, while maintaining low complexity, making it suitable for precision agricultural applications.
Article
Computer Science, Artificial Intelligence
Xin Zuo, Zhi Wang, Jifeng Shen, Wankou Yang
Summary: A scale-aware permutated attention module and an adjacent-branch feature aggregation module are proposed to improve feature fusion quality and miss rate in a multispectral pedestrian detection system. Experimental results demonstrate superior performance.
IET COMPUTER VISION
(2022)
Article
Spectroscopy
Xin Zhou, Chunjiang Zhao, Jun Sun, Kunshan Yao, Min Xu
Summary: The evaluation capability of hyperspectral imaging technology for forecasting heavy metal lead concentration in oilseed rape plants was studied. A transfer stacked auto-encoder (T-SAE) algorithm, including dual-model and single-model T-SAE, was proposed. The hyper -spectral images of oilseed rape leaf and root under different Pb stress concentrations were acquired. Preprocessing methods like SNV and 1st Der were used to extract the spectral data, and PCA algorithm was employed for dimensionality reduction. Deep learning networks were built and T-SAE models were obtained through transfer learning. The results showed high accuracy in predicting Pb stress gradient and content in oilseed rape plants.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2023)
Article
Spectroscopy
Zh. E. Ozbekova, A. A. Abdyldaev, A. A. Kulmyrzaev
Summary: This study compared two drying methods for cow and yak muscles, finding that freeze drying caused less discoloration. Additionally, analysis of fluorescence spectra allowed for accurate prediction of chemical composition and color characteristics of the muscles.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2024)
Article
Spectroscopy
Leo Mandic, Ivan Ljubic, Iva Dzeba
Summary: In this study, a combined experimental and computational approach was used to investigate the photoexcitation and photodegradation mechanisms of Doxazosin (DOX). The results provide valuable insights into the primary events following the photoexcitation of DOX and its potential applications.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2024)
Article
Spectroscopy
Xiufeng Wang, Yao Jin, Wenhui Ai, Siqi Wang, Zhiqing Zhang, Ting Zhou, Fang Wang, Guodong Zhang
Summary: This study successfully synthesized near infrared fluorescence Ag2S quantum dots (QDs) and developed a dual-mode sensor for sulfide anion using the excellent oxidase-like characteristics of manganese dioxide (MnO2) nanosheets. The sensor showed a wider detection range, higher sensitivity, and shorter reaction time, making it suitable for highly selective detection of sulfide in different concentration ranges.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2024)
Article
Spectroscopy
Yafei Li, Yanming Ma, Chuantao Zheng, Di Yu, Lien Hu, Shuo Yang, Fang Song, Yadan Li, Shuanghai Liu, Zhanrui Zhang, Yu Zhang, Yiding Wang, Frank K. Tittel
Summary: To effectively monitor gas explosion and coal spontaneous combustion in coal mine, an intrinsically safe and explosion-proof dual-gas sensor system was developed for methane (CH4) and carbon monoxide (CO) measurement. The system achieved different measurement ranges using laser scanning and gas cells, and improved stability and accuracy through gas pre-treatment and temperature compensation algorithm.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2024)
Article
Spectroscopy
Pei-Rong Chen, Li-Kang Chu
Summary: In this study, the hydrates of glyoxal were investigated using infrared absorption spectrometry. The results showed that at low concentrations, glyoxal mainly exists as monomeric dihydrate. These findings provide suitable detection windows for further research on the roles of glyoxal and its hydrates in atmospheric and aerosol chemistry, as well as the relevant reaction kinetics.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2024)
Article
Spectroscopy
Nichole O'Neill, Thamires A. Lima, Fabio Furlan Ferreira, Nicolas J. Alvarez, Reinhard Schweitzer-Stenner
Summary: This study determines the main fibril axis of GHG gel-forming fibrils using various techniques and compares the results with simulated data. The analysis suggests that the hydrophobic xz-surfaces of GHG fibrils could be a good target for the adsorption of hydrophobic drugs.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2024)
Article
Spectroscopy
Mengyuan Liu, Hanchuang Zhu, Yikun Fang, Caiyun Liu, Xinke Li, Xiaohui Zhang, Lixue Ma, Kun Wang, Miaohui Yu, Wenlong Sheng, Baocun Zhu
Summary: ABHS is an efficient fluorescent probe that can accurately and sensitively detect Al3+ with strong resistance to interference. It also demonstrates excellent detection and imaging capabilities in complex real samples.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2024)
Article
Spectroscopy
Ahmed S. El-Shafie, Evana Rahman, Yasser Gadelhak, Rehab Mahmoud, Marwa El-Azary
Summary: The recycling of waste mandarin peels into biochar (MRBC) has been used as a high performance and cost-effective adsorbent for treating polluted wastewater effluents. Batch adsorption studies were conducted to analyze the adsorption competency of MRBC on two dyes, methylene blue (MB) and basic fuchsin (BF), either in individual solutions or binary combinations. The results showed that MRBC was capable of effectively removing a high percentage of both dyes. However, the adsorption capacity decreased when the dyes were combined. The cost estimation of MRBC production and wastewater treatment indicated that both were relatively low.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2024)
Article
Spectroscopy
Anindita Bhatta, Jahnabi Upadhyaya, Dipak Chamlagai, Lincoln Dkhar, Pynskhemborlang T. Phanrang, Mohan Rao Kollipara, Sivaprasad Mitra
Summary: Derivatives of thiazole-pyrazole fused benzo-coumarin compounds were synthesized and their photophysical properties were investigated. The synthesized coumarin compounds showed potential as therapeutic agents for Alzheimer's disease, inhibiting acetylcholinesterase activity. The presence of human serum albumin was found to affect the inhibition activity.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2024)
Article
Spectroscopy
Yongwei Duan, Quancheng Liu, Yiju Zhu, Qi Zhang, Xiaohui Duan, Hu Deng, Liping Shang
Summary: In this study, the phase transition of CL-20 was observed using terahertz spectroscopy, and quantum chemical calculations were employed to analyze the vibrations. The results indicated changes in the vibrations of CL-20 before and after phase transition.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2024)
Article
Spectroscopy
Yuefeng Gao, Sai Xu, Baojiu Chen
Summary: This study synthesized Cs2NaInCl6 nanocrystals co-doped with Sb3+ and Tb3+ ions as probes for copper ions detection in lubricating oil. The introduction of Sb3+ effectively reduced the band gap of the host material and enabled energy transfer pathway for Tb3+ emission. The doped Tb3+ ions resulted in the suppression of emission due to electron transfer. The Cs2NaInCl6: 2.5 %Sb3+, 40 %Tb3+ NCs exhibited superior sensitivity and selectivity for copper ions detection.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2024)
Article
Spectroscopy
Yu Liu, Yue Zhang, Changyao Liu, Ce Wang, Baocai Xu, Li Zhao
Summary: A highly sensitive detection platform for heparin was developed using a cationic fluorescent dye (cresyl violet acetate) as a fluorescence probe. The platform demonstrated high selectivity towards heparin and achieved detection in both HEPES solution and serum.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2024)
Article
Spectroscopy
Lopamudra Roy, Nivedita Pan, Susmita Mondal, Ria Ghosh, Md. Nur Hasan, Neha Bhattacharyya, Soumendra Singh, Kallol Bhattacharyya, Arpita Chattopadhyay, Samir Kumar Pal
Summary: The study focuses on the interaction between reactive oxygen species (ROS) and a spectroscopic probe called Rose Bengal (RB), encapsulated in nanoscopic sodium dodecyl sulphate (SDS) micelles and entrapped in microscopic nylon 66 solid matrix. The research demonstrates efficient interaction between ROS and RB-SDS, and investigates the mechanism of hydroxyl radicals generation. Based on these findings, a prototype device utilizing RB embedded in a nylon thin film for quantification of ROS in extracellular fluids and food materials was developed.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2024)
Article
Spectroscopy
Xiaosong Sun, Qihao Cui, Wenyue Dong, Qian Duan, Teng Fei
Summary: Conjugated porous polymers (CPPs) are promising sensing materials and their application in aqueous media is limited. In this study, we synthesized CPPs with porous structure and prepared nanoparticles, enabling efficient photoluminescence sensing of nitroaromatic explosives in aqueous phase.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2024)
Article
Spectroscopy
Maria Cristina Caggiani, Germana Barone, Paolo Mazzoleni
Summary: Raman spectroscopy is commonly used for studying glassy materials in cultural heritage, but it is more difficult to interpret the spectra and apply the technique with portable instruments. In contrast, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) can be used in archaeometric investigations as it is portable and non-invasive. However, there is limited application of this technique to historical glasses. This exploratory work demonstrates the potential of DRIFTS, in combination with portable X-ray Fluorescence (pXRF) and EDS microanalyses, for studying the composition and alteration of glass samples in cultural heritage.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2024)
