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Chemosensors
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Advanced Spectroscopy Technology for Chemical Qualitative and Quantitative Analysis
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Advanced Spectroscopy Technology for Chemical Qualitative and Quantitative Analysis

A special issue of Chemosensors (ISSN 2227-9040). This special issue belongs to the section "Analytical Methods, Instrumentation and Miniaturization".

Deadline for manuscript submissions: 31 August 2024 | Viewed by 8434

Special Issue Editors

Dr. Xiong Wan

E-Mail Website
Guest Editor
Shanghai Institute of Technical Physics Chinese Academy of Sciences, Shanghai, China
Interests: biophotonics and deep space spectroscopy
Dr. Lei Zhang

E-Mail Website
Guest Editor
State Key Lab of Quantum Optics and Quantum Optics Devices, Institute of Laser Spectroscopy, Shanxi University, Taiyuan, China
Interests: light scattering; spectroscopy technology
Prof. Dr. Jiulin Shi

E-Mail Website
Guest Editor
National Engineering Laboratory for Nondestructive Testing and Optoelectric Sensing Technology and Application, Nanchang Hangkong University, Nanchang 330063, China
Interests: light scattering and spectroscopy technology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Spectroscopy is an interdiscipline mainly involving physics and chemistry, through which the interaction between electromagnetic waves and substances can be studied. According to the form of interaction of light and matter, spectra can generally be divided into absorption spectra, emission spectra, scattering spectra, etc.

Through spectroscopic research, various microscopic and macroscopic properties can be analyzed, including the energy levels and geometric structures of atoms and molecules, the reaction rates of specific chemical processes, the concentration distribution of substances in a specific area of space, etc.

In recent years, with the application of advanced sensing technology and devices in spectral instruments, the wavelength range, spectral resolution, time–space resolution, and other spectral measurement indicators have made considerable progress. The improvement of hardware indicators, combined with advanced chemometrics algorithms, such as artificial intelligence and machine learning, has greatly improved the speed and accuracy of chemical qualitative and quantitative analysis.

This Special Issue aims to collect the latest achievements of advanced spectral technology in the fields of life science, food, the environment, and aerospace.

Dr. Xiong Wan
Dr. Lei Zhang
Prof. Dr. Jiulin Shi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Chemosensors is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • quantitative analysis
  • atomic spectrum
  • molecular spectrum
  • material detection
  • chemometrics

Published Papers (6 papers)

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Research

12 pages, 3949 KiB  
Article
Identification of the Beverage Sotol Adulterated with Ethylene Glycol Using UV-Vis Spectroscopy and Artificial Neural Networks
by Fernando Gaxiola, Jesús Javier Leal, Alain Manzo-Martínez, Iván Salmerón, José Rafael Linares-Morales and Roberto Narro-García
Chemosensors 2024, 12(3), 46; https://doi.org/10.3390/chemosensors12030046 - 13 Mar 2024
Viewed by 1038
Abstract
Sotol is a traditional distilled alcoholic beverage produced in Mexico and the United States. Unfortunately, local authorities have detected that these beverages are sometimes adulterated with toxic substances such as ethylene glycol. This illegal practice of adulteration is dangerous and can cause serious [...] Read more.
Sotol is a traditional distilled alcoholic beverage produced in Mexico and the United States. Unfortunately, local authorities have detected that these beverages are sometimes adulterated with toxic substances such as ethylene glycol. This illegal practice of adulteration is dangerous and can cause serious health problems for the end consumers. In this work, an alternative, reliable, and rapid method is presented for identifying the presence of ethylene glycol in sotol samples using UV-Vis spectroscopy and neural networks with an accuracy of up to 100%. Full article
(This article belongs to the Special Issue Advanced Spectroscopy Technology for Chemical Qualitative and Quantitative Analysis)
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18 pages, 7382 KiB  
Article
Near Infrared and UV-Visible Spectroscopy Coupled with Chemometrics for the Characterization of Flours from Different Starch Origins
by Samuele Pellacani, Marco Borsari, Marina Cocchi, Alessandro D’Alessandro, Caterina Durante, Giulia Farioli and Lorenzo Strani
Chemosensors 2024, 12(1), 1; https://doi.org/10.3390/chemosensors12010001 - 22 Dec 2023
Viewed by 1588
Abstract
This work tested near-infrared (NIR) and UV-visible (UV-Vis) spectroscopy coupled with chemometrics to characterize flours from different starch origins. In particular, eighteen starch-containing flours (e.g., type 00 flour, rye, barley, soybean, chestnut, potato, spelt, buckwheat, oat, millet, rice, durum wheat, amaranth, chickpea, sesame, [...] Read more.
This work tested near-infrared (NIR) and UV-visible (UV-Vis) spectroscopy coupled with chemometrics to characterize flours from different starch origins. In particular, eighteen starch-containing flours (e.g., type 00 flour, rye, barley, soybean, chestnut, potato, spelt, buckwheat, oat, millet, rice, durum wheat, amaranth, chickpea, sesame, corn, hemp and sunflower flours) were analyzed with a twofold objective: chemically characterizing the investigated flours and laying the groundwork for the development of a fast and suitable method that can identify the botanical source of starch in food. This could ensure ingredient traceability and aid in preventing/detecting food fraud. Untargeted approaches were used for this study, involving the simultaneous acquisition of a large amount of chemical information (UV-Vis on extracted starch and NIR signals on raw flours) coupled with chemometric techniques. UV-VIS spectra were acquired between 225 and 800 nm after sample pretreatment to extract starch. NIR spectra were acquired between 900 and 1700 nm using a poliSPEC NIRe portable instrument on the flours without any kind of pretreatments. An initial exploratory investigation was conducted using principal component analysis and cluster analysis, obtaining interesting preliminary information on patterns among the investigated flours. In particular, the UV-Vis model successfully discerned samples such as potato, chestnut, sunflower, durum wheat, sesame, buckwheat, rice, corn, spelt and 00-type flours. PCA model results obtained from the analysis of NIR spectra also provided comparable results with the UV-Vis model, particularly highlighting the differences observed between hemp and potato flours with soybean flour. Some similarities were identified between other flours, such as barley and millet, rye and oats, and chickpea and amaranth. Therefore, some flour samples underwent surface analysis via scanning electron microscope (SEM) using the Nova NanoSEM 450 to detect distinctive morphology. Full article
(This article belongs to the Special Issue Advanced Spectroscopy Technology for Chemical Qualitative and Quantitative Analysis)
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16 pages, 4553 KiB  
Article
Pyrogallol Detection Based on the Cobalt Metal–Organic Framework of Nanomaterial-Enhanced Chemiluminescence
by Yanran Wang, Zhiqiang Wang, Yincheng Liu, Zixuan Liu, Zhan Gao, Kuangjun Li, Dajun Zhao, Jing Wu and Xuanhe Liu
Chemosensors 2023, 11(7), 395; https://doi.org/10.3390/chemosensors11070395 - 14 Jul 2023
Viewed by 1063
Abstract
The cobalt metal–organic framework (Co-MOF) is a kind of crystalline porous material within a periodic network structure, which is formed via the self-assembly of a Co metal center and a bridged organic ligand. In this paper, a Co-MOF was facilely synthesized via an [...] Read more.
The cobalt metal–organic framework (Co-MOF) is a kind of crystalline porous material within a periodic network structure, which is formed via the self-assembly of a Co metal center and a bridged organic ligand. In this paper, a Co-MOF was facilely synthesized via an ultrasonic method and applied to enhance the chemiluminescence (CL) emission of the NaIO4-H2O2 system. The synthesized Co-MOF was nanosheet-like in nature and stacked in 2–3-micrometer flower shapes. Compared to the NaIO4-H2O2 system without a Co-MOF, the CL intensity of the Co-MOF-NaIO4-H2O2 system was enhanced about 70 times. This CL mechanism was determined to be a result of the synergistic effects of chemiluminescence resonance energy transfer (CRET) and electron–hole annihilation (EHA). The Co-MOF not only acted as a catalyst to accelerate the generation of reactive oxygen species in the CL reaction, but also worked as an emitter to further enhance the CL. Based on the Co-MOF-NaIO4-H2O2 system, a highly sensitive CL analysis method was established for pyrogallol (PG) detection. Addition of PG into the CL system generated 1O2*, which could transfer energy to the Co-MOF and further enhance the CL response. The enhanced CL was linear with the PG concentration. The CL analysis method exhibited a linear range of 1 × 10−4 M to 1 × 10−7 M, as well as having a linear correlation coefficient of 0.9995 and a limit of detection of (S/N = 3) of 34 nM. Full article
(This article belongs to the Special Issue Advanced Spectroscopy Technology for Chemical Qualitative and Quantitative Analysis)
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11 pages, 1748 KiB  
Article
Coal Calorific Value Detection Technology Based on NIRS-XRF Fusion Spectroscopy
by Jiaxuan Li, Rui Gao, Yan Zhang, Shuqing Wang, Lei Zhang, Wangbao Yin and Suotang Jia
Chemosensors 2023, 11(7), 363; https://doi.org/10.3390/chemosensors11070363 - 28 Jun 2023
Viewed by 1060
Abstract
Calorific value is an important index for evaluating coal quality, and it is important to achieve the rapid detection of calorific value to improve production efficiency. In this paper, a calorific value detection method based on NIRS-XRF fusion spectroscopy is proposed, which utilizes [...] Read more.
Calorific value is an important index for evaluating coal quality, and it is important to achieve the rapid detection of calorific value to improve production efficiency. In this paper, a calorific value detection method based on NIRS-XRF fusion spectroscopy is proposed, which utilizes NIRS to detect organic functional groups and XRF to detect inorganic ash-forming elements in coal. NIRS, XRF and NIRS-XRF fusion spectrum were separately used to establish partial least squares (PLS) regression models for coal calorific value, and better prediction performance was obtained by using fusion spectrum (the determination coefficient of calibration set (R2) was 0.98, the root mean square error of prediction set (RMSEP) was 0.19 MJ/kg, the average relative deviation for prediction (MARDP) was 0.95%). The variable selection is very important for model performance. The effective variables were extracted using Pearson correlation coefficients to further optimize the prediction model, and the evaluation indexes of the optimized model are R2 = 0.99, RMSEP = 0.16 MJ/kg and MARDP = 0.70%. In addition, the repeatability of the proposed method was briefly evaluated. The results show that the proposed method is an effective analysis method to detect the calorific value of coal, which provides a new idea and technique for coal quality detection. Full article
(This article belongs to the Special Issue Advanced Spectroscopy Technology for Chemical Qualitative and Quantitative Analysis)
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13 pages, 5253 KiB  
Article
LIBS-MLIF Method: Stromatolite Phosphorite Determination
by Hongpeng Wang, Yingjian Xin, Peipei Fang, Jianjun Jia, Liang Zhang, Sicong Liu and Xiong Wan
Chemosensors 2023, 11(5), 301; https://doi.org/10.3390/chemosensors11050301 - 19 May 2023
Cited by 1 | Viewed by 1266
Abstract
The search for biominerals is one of the core targets in the deep space exploration mission. Stromatolite phosphorite is a typical biomineral that preserves early life on Earth. The enrichment of phosphate is closely related to microorganisms and their secretions. Laser-induced breakdown spectroscopy [...] Read more.
The search for biominerals is one of the core targets in the deep space exploration mission. Stromatolite phosphorite is a typical biomineral that preserves early life on Earth. The enrichment of phosphate is closely related to microorganisms and their secretions. Laser-induced breakdown spectroscopy (LIBS) has become an essential payload in deep space exploration with the ability to analyze chemical elements remotely, rapidly, and in situ. This paper aims to evaluate the rapid identification of biological and non-biological minerals through a remote LIBS payload. LIBS is used for element analysis and mineral classification determination, and molecular laser-induced fluorescence (MLIF) is used to detect halogenated element F to support the existence of fluorapatite. This paper analyzes the LIBS-MLIF spectral characteristics of stromatolites and preliminarily evaluates the feasibility of P element quantification. The results show that LIBS technology can recognize biological and non-biological signals. This discovery is significant because it is not limited to detecting and analyzing element composition. It can also realize the detection of molecular spectrum based on selective extraction of CaF molecule. Therefore, the LIBS payload still has the potential to search for biomineral under the condition of adjusting the detection strategy. Full article
(This article belongs to the Special Issue Advanced Spectroscopy Technology for Chemical Qualitative and Quantitative Analysis)
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13 pages, 3591 KiB  
Article
Luminescent Metal-Organic Framework with 2,1,3-Benzothiadiazole Units for Highly Sensitive Gossypol Sensing
by Dmitry I. Pavlov, Xiaolin Yu, Alexey A. Ryadun, Vladimir P. Fedin and Andrei S. Potapov
Chemosensors 2023, 11(1), 52; https://doi.org/10.3390/chemosensors11010052 - 07 Jan 2023
Cited by 6 | Viewed by 1719
Abstract
A new metal–organic framework based on cadmium(II) cations, di(p-carboxyphenyl)sulphone and 4,7-di(imidazol-1-yl)-2,1,3-benzothiadiazole was prepared, and its crystal structure was determined using single-crystal XRD analysis. MOF demonstrated bright luminescence with a maximum near 500 nm and quantum yield reaching 20%. In addition, this MOF demonstrated [...] Read more.
A new metal–organic framework based on cadmium(II) cations, di(p-carboxyphenyl)sulphone and 4,7-di(imidazol-1-yl)-2,1,3-benzothiadiazole was prepared, and its crystal structure was determined using single-crystal XRD analysis. MOF demonstrated bright luminescence with a maximum near 500 nm and quantum yield reaching 20%. In addition, this MOF demonstrated sensing properties towards antibiotics and a toxic natural polyphenol gossypol through effective luminescence quenching in an ethanol suspension. The determined detection limit for gossypol was among the lowest reported so far (0.65 µM), and did not significantly change in the interference experiments with cottonseed oil as background, indicating the possibility of using this MOF as a sensor for the detection and determination of gossypol in real-life samples. Full article
(This article belongs to the Special Issue Advanced Spectroscopy Technology for Chemical Qualitative and Quantitative Analysis)
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