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Chemometrics for Analytical Chemistry
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Chemometrics for Analytical Chemistry

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

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 30908

Special Issue Editors

Prof. Dr. Hailong Wu

E-Mail Website
Guest Editor
State Key Laboratory of Chemo/Biosensing & Chemometrics, College of Chemistry and Chemical Engineering Hunan University, Changsha 410082, China
Interests: chemical sensors; flow injection analysis; HPLC-DAD; excitation–emission matrix fluorescence; LC-MS; environmental monitoring; drug analysis; food safety analysis; chemometrics; novel applications of multiway data analysis and multiway calibration methodologies for analytical, environmental, biological, drug, medical, food and life sciences; quantitative analysis of proteins, metabonomics; multiway data analysis in automation and control systems
Special Issues, Collections and Topics in MDPI journals
Dr. Tong Wang

E-Mail Website
Guest Editor
State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, China
Interests: multi-way data analysis; multi-way calibration; chemical pattern recognition; machine learning; deep learning; food quality and safety analysis; drug analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the rapid technological progress of instrumental techniques for analytical purposes, multivariate methods applied to chemical data are mandatory in several applications. Chemometrics is a prominent field that manipulates data from chemical processes utilizing mathematics and statistic fundamentals. The advancement of the electronics and computer science have allowed a constant growth of Chemometrics, expanding the applications of this discipline in practically all sub-areas of chemistry. Chemometrics is a highly interdisciplinary field whose relevance among the chemical disciplines, in general, analytical chemistry. The early applications of Chemometrics were primarily in quantitative analytical chemistry such as NIR calibration, HPLC resolution and UV/Vis deconvolution. In the twenty-first century, another revolution occurred—the rapid growth of computing power, allowing powerful algorithms to become routine tools for the laboratory chemist. Hand in hand with this was the growth of rapid, automated, instruments so large datasets could be generated, using approaches such as hyphenated and multidimensional chromatography or NMR. In modern society, chemometrics was no longer primarily focused on improving the quantitative performance of analytical instruments. Pattern recognition became a widespread tool. Applications included biomedical data, especially metabolomics but also food chemistry as well as more recently developing areas including forensics and cultural heritage studies among others. Chemometrics has developed as a widespread tool for the applied analytical chemist as well as a more theoretical method to assist the improvement and development of instrumental methods. We are looking forward to feature articles on chemometrics, including sampling, experimental design, data preprocessing and data fusion strategies, and projection methods for data exploration and factor analysis, multiway calibration, higher-dimensional pattern recognition. Many of these aspects are closely related with analytical chemistry and its goals.

Prof. Dr. Hailong Wu
Dr. Tong Wang
Guest Editors

Manuscript Submission Information

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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

  • chemometrics
  • sampling, experimental design, data preprocessing and data fusion strategies
  • projection methods for data exploration and factor analysis
  • multiway calibration
  • higher-dimensional pattern recognition

Published Papers (16 papers)

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Research

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17 pages, 5089 KiB  
Article
Assessing the Effects of Cadmium Stress on the Growth, Physiological Characteristics, and Metabolic Profiling of Rice (Oryza sativa L.) Using HPLC-QTOF/MS
by Zhenni Lan, Qing He, Mingxia Zhang, Huahong Liu, Liusen Fang and Jinfang Nie
Chemosensors 2023, 11(11), 558; https://doi.org/10.3390/chemosensors11110558 - 7 Nov 2023
Viewed by 1631
Abstract
Cadmium (Cd) pollution is an important environmental problem, as it is easily absorbed by plants and gradually accumulates in the human body through the food chain. This study aimed to elucidate the changes in the metabolic response of the rice cultivar “TanLiangYou215” under [...] Read more.
Cadmium (Cd) pollution is an important environmental problem, as it is easily absorbed by plants and gradually accumulates in the human body through the food chain. This study aimed to elucidate the changes in the metabolic response of the rice cultivar “TanLiangYou215” under Cd stress. Rice was grown in soil culture at 0 (Control), 2 (Low group), and 10 (High group) mg/kg CdCl2 for 90 days. The ultrastructural, Cd content, antioxidant activity, and metabolic changes to the rice in different tissues were analyzed. Phenotypic characterization and ultrastructure showed that the rice roots and leaves were significantly damaged and plant growth was inhibited in the High group, while plant growth was promoted in the Low group. Overall, Cd showed a regularity of “low promotion and high inhibition”. Physiological indices revealed that rice was significantly affected by Cd stress. Compared to the Control, Cd stress resulted in higher antioxidant enzyme activities, and the Low group suffered less oxidative damage than the High group. Metabolomic studies revealed that Cd stress significantly altered the metabolic profiles of rice plants. Rice responded to Cd stress by upregulating amino acids and regulating related pathways, including alanine, aspartate and glutamate metabolism, and arginine and proline metabolism. The significant expression of flavonoids with antioxidant properties helped rice resist the oxidative damage caused by Cd accumulation in the root tissue; Cd stress significantly downregulated glycerophospholipid metabolism in the stem and leaf tissues, which affected the cellular activities in rice stem and leaf tissues. We investigated the effects of Cd stress on ultrastructure, antioxidant activity, and metabolic changes in different tissues of the rice variety TLY215. Moreover, the different tissues of TLY215 can regulate these metabolic pathways to resist Cd stress, which provides valuable insights into the response of TLY215 to different concentrations of Cd. Full article
(This article belongs to the Special Issue Chemometrics for Analytical Chemistry)
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10 pages, 2257 KiB  
Article
Origin Authentication of European and American Ash (Fraxinus spp.) Based on Stable Isotope Ratio and Elemental Characteristics Combined with Chemometrics Methods
by Haibo Wang, Huahong Liu, Bo Lu, Ming Ma, Jianguo Chen and Jinfang Nie
Chemosensors 2023, 11(10), 536; https://doi.org/10.3390/chemosensors11100536 - 12 Oct 2023
Viewed by 1301
Abstract
The research into and applications of wood origin traceability technology are of great significance for promoting the standardization and legality of the global timber trade. This paper focuses on analyzing the content of ten mineral elements and the ratios of stable isotopes δ [...] Read more.
The research into and applications of wood origin traceability technology are of great significance for promoting the standardization and legality of the global timber trade. This paper focuses on analyzing the content of ten mineral elements and the ratios of stable isotopes δ13C and δ15N in ash samples. Furthermore, multivariate statistical analysis was conducted to assess the clusters and differences in mineral elements, as well as δ13C and δ15N, among the samples, for identifying the different factors used to trace the origin of ash imported from different regions. Through unsupervised clustering and supervised discriminant modeling, a highly accurate method for discriminant analysis was developed. The results reveal significant differences (p < 0.05) in the contents of Mg, Cu, and Sr, as well as δ15N, between European and American samples. Additionally, the normalized results of mineral elements and isotope ratios were then subjected to partial least squares–discriminant analysis (PLS-DA), resulting in the highest level of separation. This analysis achieved an overall accuracy of 96.2% in discriminating between samples of European and American ash. The chemometrics analysis method integrating stable isotope analysis with elemental analysis exhibited potential for discriminating between samples from European and American ash. Full article
(This article belongs to the Special Issue Chemometrics for Analytical Chemistry)
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13 pages, 3099 KiB  
Article
Hierarchical Modeling to Enhance Spectrophotometry Measurements—Overcoming Dynamic Range Limitations for Remote Monitoring of Neptunium
by Hunter B. Andrews and Luke R. Sadergaski
Chemosensors 2023, 11(5), 274; https://doi.org/10.3390/chemosensors11050274 - 2 May 2023
Cited by 1 | Viewed by 1148
Abstract
A robust hierarchical model has been demonstrated for monitoring a wide range of neptunium concentrations (0.75–890 mM) and varying temperatures (10–80 °C) using chemometrics and feature selection. The visible–near infrared electronic absorption spectrum (400–1700 nm) of monocharged neptunyl dioxocation (Np(V) = NpO2 [...] Read more.
A robust hierarchical model has been demonstrated for monitoring a wide range of neptunium concentrations (0.75–890 mM) and varying temperatures (10–80 °C) using chemometrics and feature selection. The visible–near infrared electronic absorption spectrum (400–1700 nm) of monocharged neptunyl dioxocation (Np(V) = NpO2+) includes many bands, which have molar absorption coefficients that differ by nearly 2 orders of magnitude. The shape, position, and intensity of these bands differ with chemical interactions and changing temperature. These challenges make traditional quantification by univariate methods unfeasible. Measuring Np(V) concentration over several orders of magnitude would typically necessitate cells with varying path length, optical switches, and/or multiple spectrophotometers. Alternatively, the differences in the molar extinction coefficients for multiple absorption bands can be used to quantify Np(V) concentration over 3 orders of magnitude with a single optical path length (1 mm) and a hierarchical multivariate model. In this work, principal component analysis was used to distinguish the concentration regime of the sample, directing it to the relevant partial least squares regression submodels. Each submodel was optimized with unique feature selection filters that were selected by a genetic algorithm to enhance predictions. Through this approach, the percent root mean square error of prediction values were ≤1.05% for Np(V) concentrations and ≤4% for temperatures. This approach may be applied to other nuclear fuel cycle and environmental applications requiring real-time spectroscopic measurements over a wide range of conditions. Full article
(This article belongs to the Special Issue Chemometrics for Analytical Chemistry)
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14 pages, 3304 KiB  
Article
A Strategy for Differentiating Oak Barrel Aged and Non-Oak Barrel Aged Wines by Using UHPLC–HRMS Combined with Chemometrics
by Yi Lv, Feng-Lian Ma, Jia-Nan Wang, Yao Zhang, Yuan Jiang, Qian Ge and Yong-Jie Yu
Chemosensors 2023, 11(3), 165; https://doi.org/10.3390/chemosensors11030165 - 1 Mar 2023
Cited by 1 | Viewed by 1345
Abstract
The time involved and the high economic cost of using oak barrels to age wines have led to a significant price difference compared to non-oak barrel aged wines and may lead to some fraudulent sales in the market. In this study, an untargeted [...] Read more.
The time involved and the high economic cost of using oak barrels to age wines have led to a significant price difference compared to non-oak barrel aged wines and may lead to some fraudulent sales in the market. In this study, an untargeted metabolomic strategy was developed to detect the metabolite composition of oak barrel aged and non-oak barrel aged wines in both positive and negative ion modes by using UHPLC–HRMS combined with the recently developed chemometric method AntDAS. The results of partial least squares discrimination analysis (PLS-DA) showed that the samples were characterized into two categories. Finally, 51 compounds were identified in positive ion mode, while 26 compounds were identified in negative ion mode. The results indicate that combining UHPLC–HRMS with AntDAS can reveal the material basis of wines and has excellent potential to differentiate between oak barrel aged and non-oak barrel aged wines. Full article
(This article belongs to the Special Issue Chemometrics for Analytical Chemistry)
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8 pages, 2271 KiB  
Communication
Direct Determination of Three PAHs in Drill Cuttings Recycling Products by Solid-Surface 3D Fluorescence Coupled with Chemometrics
by Tao Geng, Zhuozhuang Liu, Xianzhe Guo, Zhansheng Wang, Xingchun Li and Wu Chen
Chemosensors 2023, 11(2), 150; https://doi.org/10.3390/chemosensors11020150 - 20 Feb 2023
Viewed by 1265
Abstract
In this work, the feasibility of solid-surface three-dimensional fluorescence (SSTF) in combination with chemometrics to rapidly and directly determine three PAHs in drill cuttings recycling products was studied for the first time. Due to the nondestructive characteristics of SSTF and the “mathematical separation” [...] Read more.
In this work, the feasibility of solid-surface three-dimensional fluorescence (SSTF) in combination with chemometrics to rapidly and directly determine three PAHs in drill cuttings recycling products was studied for the first time. Due to the nondestructive characteristics of SSTF and the “mathematical separation” of chemometric three-way calibration, neither time-consuming sample pretreatments nor toxic organic reagents were involved in the determination. By using the smart “mathematical separation” function of the parallel factor analysis (PARAFAC) algorithm, clear spectral profiles together with reasonable quantitative results for the three target PAHs were successfully extracted from the total SSTF signals of drill cuttings recycling products without the need for chromatographic separation. The linearity of the calibration models was good (R2 > 0.96) and the average spiked recoveries of three target PAHs were between 88.1–102.7% with a relative standard deviation less than 20%. Nevertheless, given the green, fast, low-cost, and nondestructive advantages of the proposed strategy, it has the potential to be used as a fast screening approach and allow for a quick survey of PAHs in drill cuttings recycling products. Full article
(This article belongs to the Special Issue Chemometrics for Analytical Chemistry)
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21 pages, 3880 KiB  
Article
A Fast and Robust Third-Order Multivariate Calibration Approach Coupled with Excitation–Emission Matrix Phosphorescence for the Quantification and Oxidation Kinetic Study of Fluorene in Wastewater Samples
by Xiang-Dong Qing, Xiao-Hua Zhang, Rong An, Jin Zhang, Ling Xu and Ludovic Duponchel
Chemosensors 2023, 11(1), 53; https://doi.org/10.3390/chemosensors11010053 - 7 Jan 2023
Cited by 1 | Viewed by 1181
Abstract
Human activity today produces a large number of pollutants that end up in the environment, such as soil, water, and airborne particles. The first objective of this work is to introduce a new third-order multivariate calibration approach called self-weighted alternating quadrilinear decomposition (SWAQLD) [...] Read more.
Human activity today produces a large number of pollutants that end up in the environment, such as soil, water, and airborne particles. The first objective of this work is to introduce a new third-order multivariate calibration approach called self-weighted alternating quadrilinear decomposition (SWAQLD) for the analysis of organic pollutant of fluorene (FLU) in different water systems. One simulated and two real four-way data sets are used to study the potential of the proposed approach in comparison with two classical algorithms, namely alternating quadrilinear decomposition (AQLD) and parallel factor analysis (PARAFAC). The results of simulated data show that SWAQLD inherits the advantages of PARAFAC in terms of not only tolerance to experimental noise but also a fast convergence and a certain robustness to overestimation of the rank of the models from AQLD. The second objective of this work is to propose a new way of generating third-order data using excitation–emission matrix phosphorescence (EEMP) at room temperature for the study of the kinetic process of oxidation of FLU in complex chemical systems. The obtained rate constant and half-life of the FLU oxidation, on average, are 0.015 min−1 and 45.5 min for free-interference water and 0.017 min−1 and 40.0 min for wastewater, respectively. Research results show that SWAQLD coupled with EEMP allows the quantification and kinetic monitoring of FLU in analytical conditions of different complexities with excellent robustness to the choice of the number of model components. Full article
(This article belongs to the Special Issue Chemometrics for Analytical Chemistry)
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13 pages, 1924 KiB  
Article
Hierarchical Modelling of Raman Spectroscopic Data Demonstrates the Potential for Manufacturer and Caliber Differentiation of Smokeless Powders
by Shelby R. Khandasammy, Nathan R. Bartlett, Lenka Halámková and Igor K. Lednev
Chemosensors 2023, 11(1), 11; https://doi.org/10.3390/chemosensors11010011 - 22 Dec 2022
Cited by 1 | Viewed by 1982
Abstract
Gunshot residue (GSR) is an important type of forensic trace evidence produced when a firearm is discharged. Currently, inorganic GSR particles are used for establishing the fact of shooting. The organic gunshot residue (OGSR) has been recently shown to have great potential for [...] Read more.
Gunshot residue (GSR) is an important type of forensic trace evidence produced when a firearm is discharged. Currently, inorganic GSR particles are used for establishing the fact of shooting. The organic gunshot residue (OGSR) has been recently shown to have great potential for providing additional information vital for the crime scene investigation. Smokeless powder is the precursor to OGSR and one of its chemical components. In this study, Raman spectroscopy and chemometric modeling were used to analyze smokeless powder extracted from ammunition cartridge cases. The proposed hierarchical model demonstrated great potential for determining the manufacture and the bullet type based on the analysis of smokeless powder. Expanding the developed approach to the analysis of OGSR will be needed to make it a useful tool for law enforcement agencies. Full article
(This article belongs to the Special Issue Chemometrics for Analytical Chemistry)
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15 pages, 3012 KiB  
Article
Accurate Traceability of Stable C, H, O, N Isotope Ratios and Multi-Element Analysis Combined with Chemometrics for Chrysanthemi Flos ‘Hangbaiju’ from Different Origins
by Xiuyun Bai, Hengye Chen, Wanjun Long, Wei Lan, Siyu Wang, Guanghua Lei, Yuting Guan, Jian Yang and Haiyan Fu
Chemosensors 2022, 10(12), 529; https://doi.org/10.3390/chemosensors10120529 - 12 Dec 2022
Cited by 2 | Viewed by 1682
Abstract
Chrysanthemi Flos ‘Hangbaiju’ (HBJ) is a common Chinese medicinal material with the same origin as the medicinal and edible cognate plant in China, whose quality is seriously affected by the place of origin. In this study, four stable isotope ratios (δ15N, [...] Read more.
Chrysanthemi Flos ‘Hangbaiju’ (HBJ) is a common Chinese medicinal material with the same origin as the medicinal and edible cognate plant in China, whose quality is seriously affected by the place of origin. In this study, four stable isotope ratios (δ15N, δ2H, δ13C, and δ18O) and 44 elements were detected and analyzed in 191 HBJ flower samples from six locations in China to trace the origin of HBJ. An ANOVA analysis of δ15N, δ2H, δ13C, and δ18O values, as well as milti-elements, showed that there were significant differences among the six places of origin. Partial least squares discriminant analysis (PLSDA) and one-class partial least squares discriminant analysis (OPLS-DA) models were established to trace the origin of HBJ from these six locations. The results showed that the classification effect of the PLSDA model is poor; however, the established OPLS-DA model can distinguish between products of national geographic origin (Tongxiang City, Zhejiang Province, China) and samples from other origins, among which Ni, Mo, δ13C, Cu, and Ce elements (VIP > 1) contribute the most to this classification. Therefore, this study provides a new method for tracing the origins of HBJ, which is of great significance for the protection of origin labeling of products. Full article
(This article belongs to the Special Issue Chemometrics for Analytical Chemistry)
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11 pages, 4556 KiB  
Communication
Detection of Carbon Content from Pulverized Coal Using LIBS Coupled with DSC-PLS Method
by Congrong Guan, Tianyu Wu, Jiwen Chen and Ming Li
Chemosensors 2022, 10(11), 490; https://doi.org/10.3390/chemosensors10110490 - 17 Nov 2022
Cited by 1 | Viewed by 1612
Abstract
The dust from pulverized coal weakens the acquired signal and increases the analysis difficulty for the quantitative analysis of the carbon content of pulverized coal when using laser-induced breakdown spectroscopy (LIBS). Moreover, there is a serious matrix effect and a self-absorption phenomenon. To [...] Read more.
The dust from pulverized coal weakens the acquired signal and increases the analysis difficulty for the quantitative analysis of the carbon content of pulverized coal when using laser-induced breakdown spectroscopy (LIBS). Moreover, there is a serious matrix effect and a self-absorption phenomenon. To improve the analysis accuracy, the DSC-PLS (double spectral correction-partial-least-squares) method was proposed to predict the carbon content of pulverized coal. Initially, the LIBS signal was corrected twice using P-operation-assisted adaptive iterative-weighted penalized-least-squares (P-airPLS), plasma temperature compensation, and spectral normalization algorithms. The goodness of fit of the carbon element was improved from nonlinearity to above 0.948. The modified signal was then used to establish DCS-PLS models for predicting unknown samples. In comparison to the conventional PLS model, the DSC-PLS method proposed in this paper significantly improves the ability to predict carbon content. The prediction error of the developed method was dropped from an average of 4.66% to about 0.41%, with the goodness of fit R2 of around 0.991. Full article
(This article belongs to the Special Issue Chemometrics for Analytical Chemistry)
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19 pages, 3547 KiB  
Article
Electronic Nose Analysis and Statistical Methods for Investigating Volatile Organic Compounds and Yield of Mint Essential Oils Obtained by Hydrodistillation
by Sepideh Zorpeykar, Esmaeil Mirzaee-Ghaleh, Hamed Karami, Zeynab Ramedani and Alphus Dan Wilson
Chemosensors 2022, 10(11), 486; https://doi.org/10.3390/chemosensors10110486 - 16 Nov 2022
Cited by 7 | Viewed by 1869
Abstract
A major problem associated with the development of medicinal plant products is the lack of quick, easy, and inexpensive methods to assess and monitor product quality. Essential oils are natural plant-derived volatile substances used worldwide for numerous applications. The important uses of these [...] Read more.
A major problem associated with the development of medicinal plant products is the lack of quick, easy, and inexpensive methods to assess and monitor product quality. Essential oils are natural plant-derived volatile substances used worldwide for numerous applications. The important uses of these valuable products often induce producers to create fraudulent or lower quality products. As a result, consumers place a high value on authentic and certified products. Mint is valued for essential oil used in the food, pharmaceutical, cosmetic, and health industries. This study investigated the use of an experimental electronic nose (e-nose) for the detection of steam-distilled essential oils. The e-nose was used to evaluate and analyze VOC emissions from essential oil (EO) and distilled water extracts (DWEs) obtained from mint plants of different ages and for leaves dried in the shade or in the sun prior to hydrodistillation. Principal component analysis (PCA), linear discriminant analysis (LDA), and artificial neural networks (ANN) were performed on electrical signals generated from electronic nose sensors for the classification of VOC emissions. More accurate discriminations were obtained for DWEs sample VOCs than for EO VOCs. The electronic nose proved to be a reliable and fast tool for identifying plant EO. The age of plants had no statistically significant effect on the EO concentration extracted from mint leaves. Full article
(This article belongs to the Special Issue Chemometrics for Analytical Chemistry)
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19 pages, 2008 KiB  
Article
Applying Two-Dimensional Correlation Spectroscopy and Principal Component Analysis to Understand How Temperature Affects the Neptunium(V) Absorption Spectrum
by Luke R. Sadergaski and Kyle Morgan
Chemosensors 2022, 10(11), 475; https://doi.org/10.3390/chemosensors10110475 - 12 Nov 2022
Cited by 4 | Viewed by 1613
Abstract
The visible-near infrared (Vis-NIR) electronic absorption spectrum of neptunium(V) (NpO2+) comprises numerous f-f electronic transitions with mostly undocumented temperature dependencies. The effect of temperature on the absorption spectrum of the pentavalent neptunyl dioxocation (NpO2+) is an important [...] Read more.
The visible-near infrared (Vis-NIR) electronic absorption spectrum of neptunium(V) (NpO2+) comprises numerous f-f electronic transitions with mostly undocumented temperature dependencies. The effect of temperature on the absorption spectrum of the pentavalent neptunyl dioxocation (NpO2+) is an important factor to consider with spectrophotometric applications but has often been overlooked. Optical Vis-NIR absorption spectra (400–1700 nm) of Np(V) (0.017–0.89 M) in 1 M nitric acid were evaluated with varying temperatures (T = 10–80 °C). The intensity, position, and overall shape of the bands were sensitive to interactions with the solvent and coordination environment. Numerous temperature-induced isosbestic points were identified resulting from dynamic, overlapping peak shifts. Spectral variations were characterized using principal component analysis (PCA) and 2D correlation spectroscopy (COS). 2D-COS revealed that the absorption band near 1095 nm likely consists of two bands centered near 1087 and 1096 nm, which cannot be explained by current computational methods. 2D-COS analysis also provided an unambiguous assignment of unresolved peaks in the visible region for comparison with computational predictions. PCA was used to identify nonlinearity in the spectral response at elevated Np(V) concentrations ≥ 0.5 M. This unique experimental data and interpretation will foster a deeper understanding of the absorption spectra for complex actinyl ions. Full article
(This article belongs to the Special Issue Chemometrics for Analytical Chemistry)
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18 pages, 7899 KiB  
Article
Machine Learning-Based Multi-Level Fusion Framework for a Hybrid Voltammetric and Impedimetric Metal Ions Electronic Tongue
by Tianqi Lu, Ammar Al-Hamry, Junfeng Hao, Yang Liu, Yunze Qu and Olfa Kanoun
Chemosensors 2022, 10(11), 474; https://doi.org/10.3390/chemosensors10110474 - 12 Nov 2022
Cited by 1 | Viewed by 1863
Abstract
Electronic tongues and artificial gustation for crucial analytes in the environment, such as metal ions, are becoming increasingly important. In this contribution, we propose a multi-level fusion framework for a hybrid impedimetric and voltammetric electronic tongue to enhance the accuracy of K+ [...] Read more.
Electronic tongues and artificial gustation for crucial analytes in the environment, such as metal ions, are becoming increasingly important. In this contribution, we propose a multi-level fusion framework for a hybrid impedimetric and voltammetric electronic tongue to enhance the accuracy of K+, Mg2+, and Ca2+ detection in an extensive concentration range (100.0 nM–1.0 mM). The proposed framework extracts electrochemical-based features and separately fuses, in the first step, impedimetric features, which are characteristic points and fixed frequency features, and the voltammetric features, which are current and potential features, for data reduction by LDA and classification by kNN. Then, in a second step, a decision fusion is carried out to combine the results for both measurement methods based on Dempster–Shafer (DS) evidence theory. The classification results reach an accuracy of 80.98% and 81.48% for voltammetric measurements and impedimetric measurements, respectively. The decision fusion based on DS evidence theory improves the total recognition accuracy to 91.60%, thus realizing significantly high accuracy in comparison to the state-of-the-art. In comparison, the feature fusion for both voltammetric and impedimetric features in one step reaches an accuracy of only 89.13%. The proposed hierarchical framework considers for the first time the fusion of impedimetric and voltammetric data and features from multiple electrochemical sensor arrays. The developed approach can be implemented for several further applications of pattern fusion, e.g., for electronic noses, measurement of environmental contaminants such as heavy metal ions, pesticides, explosives, and measurement of biomarkers, such as for the detection of cancers and diabetes. Full article
(This article belongs to the Special Issue Chemometrics for Analytical Chemistry)
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11 pages, 1846 KiB  
Article
High-Performance Liquid Chromatography–Diode Array Detection Combined with Chemometrics for Simultaneous Quantitative Analysis of Five Active Constituents in a Chinese Medicine Formula Wen-Qing-Yin
by Jun-Chen Chen, Hai-Long Wu, Tong Wang, Ming-Yue Dong, Yue Chen and Ru-Qin Yu
Chemosensors 2022, 10(7), 238; https://doi.org/10.3390/chemosensors10070238 - 23 Jun 2022
Cited by 4 | Viewed by 2026
Abstract
In this work, a simple analytical strategy combining high-performance liquid chromatography–diode array detection (HPLC-DAD) and the chemometric method was developed for the simultaneous quantification of 5-hydroxymethyl-2-furfural (HMF), paeoniflorin (PAE), ferulic acid (FER), baicalin (BAI), and berberine (BER) in a Chinese medicine formula Wen-Qing-Yin [...] Read more.
In this work, a simple analytical strategy combining high-performance liquid chromatography–diode array detection (HPLC-DAD) and the chemometric method was developed for the simultaneous quantification of 5-hydroxymethyl-2-furfural (HMF), paeoniflorin (PAE), ferulic acid (FER), baicalin (BAI), and berberine (BER) in a Chinese medicine formula Wen-Qing-Yin (WQY). The alternating trilinear decomposition (ATLD) algorithm and alternating trilinear decomposition assisted multivariate curve resolution (ATLD-MCR) algorithm were used to realize the separation and rapid determination of five target analytes under the presence of time shifts, solvent peaks, peak overlaps, and unknown interferences. All analytes were eluted within 10 min and the linear correlation coefficients of calibration sets were between 0.9969 and 0.9996. In addition, the average recoveries of the five active compounds obtained by ATLD and ATLD-MCR analysis were in the range of 91.8–112.5% and 88.6–101.6%, respectively. For investigating the accuracy and reliability of the proposed method, figures of merit including limit of detection (LOD), limit of quantitation (LOQ), sensitivity (SEN), and selectivity (SEL) were calculated. The proposed analytical strategy has the advantages of being fast, simple, and sensitive, and can be used for the qualitative and quantitative analysis of WQY, providing a feasible option for the quality monitoring of the traditional Chinese medicine formula. Full article
(This article belongs to the Special Issue Chemometrics for Analytical Chemistry)
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Review

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33 pages, 5429 KiB  
Review
Extracting Information and Enhancing the Quality of Separation Data: A Review on Chemometrics-Assisted Analysis of Volatile, Soluble and Colloidal Samples
by Alessandro Zappi, Valentina Marassi, Stefano Giordani, Nicholas Kassouf, Barbara Roda, Andrea Zattoni, Pierluigi Reschiglian and Dora Melucci
Chemosensors 2023, 11(1), 45; https://doi.org/10.3390/chemosensors11010045 - 4 Jan 2023
Cited by 10 | Viewed by 2786
Abstract
Instrument automation, technological advancements and improved computational power made separation science an extremely data-rich approach, requiring the use of statistical and data analysis tools that are able to optimize processes and combine multiple outputs. The use of chemometrics is growing, greatly improving the [...] Read more.
Instrument automation, technological advancements and improved computational power made separation science an extremely data-rich approach, requiring the use of statistical and data analysis tools that are able to optimize processes and combine multiple outputs. The use of chemometrics is growing, greatly improving the ability to extract meaningful information. Separation–multidetection generates multidimensional data, whose elaboration should not be left to the discretion of the operator. However, some applications or techniques still suffer from the lack of method optimization through DoE and downstream multivariate analysis, limiting their potential. This review aims at summarizing how chemometrics can assist analytical chemists in terms of data elaboration and method design, focusing on what can be achieved by applying chemometric approaches to separation science. Recent applications of chemometrics in separation analyses, in particular in gas, liquid and size-exclusion chromatography, together with field flow fractionation, will be detailed to visualize the state of the art of separation chemometrics, encompassing volatile, soluble and solid (colloidal) analytes. The samples considered will range from food chemistry and environmental chemistry to bio/pharmaceutical science. Full article
(This article belongs to the Special Issue Chemometrics for Analytical Chemistry)
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15 pages, 2356 KiB  
Review
Wavelet Transform Makes Water an Outstanding Near-Infrared Spectroscopic Probe
by Mian Wang, Hongle An, Wensheng Cai and Xueguang Shao
Chemosensors 2023, 11(1), 37; https://doi.org/10.3390/chemosensors11010037 - 2 Jan 2023
Cited by 5 | Viewed by 1943
Abstract
Wavelet transform (WT) has been proven to be a powerful chemometric method for processing analytical data. In this review, works on the application of WT in processing near-infrared (NIR) spectrum were summarized, emphasizing the structural analysis of water in aqueous systems. The spectral [...] Read more.
Wavelet transform (WT) has been proven to be a powerful chemometric method for processing analytical data. In this review, works on the application of WT in processing near-infrared (NIR) spectrum were summarized, emphasizing the structural analysis of water in aqueous systems. The spectral features of water can be obtained from the resolution-enhanced NIR spectrum with the help of WT. Taking advantage of WT in resolution enhancement and the sensitivity of NIR spectroscopy for water, the spectral features for different water structures can be obtained, which makes water to be a potential NIR spectroscopic probe to detect the structural information of water and analyte in aqueous systems. Using the spectral variation of water with temperature, the interaction of water and solutes, and the role of water in chemical and bio-processes, such as the aggregation of proteins and polymers, was demonstrated. The spectral changes of the NIR spectrum with temperature were found able to reflect the structural changes of biomolecules or polymers in the analyzing systems. Full article
(This article belongs to the Special Issue Chemometrics for Analytical Chemistry)
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22 pages, 2049 KiB  
Review
How Chemometrics Revives the UV-Vis Spectroscopy Applications as an Analytical Sensor for Spectralprint (Nontargeted) Analysis
by Rocío Ríos-Reina and Silvana M. Azcarate
Chemosensors 2023, 11(1), 8; https://doi.org/10.3390/chemosensors11010008 - 22 Dec 2022
Cited by 17 | Viewed by 4315
Abstract
In recent years, methodologies based on spectral analysis, using ultraviolet–visible (UV-Vis) radiation, have experienced an amazing development and have been widely applied in various fields such as agricultural, food, pharmaceutical, and environmental sciences. This straightforward technique has re-emerged with novel and challenging proposals [...] Read more.
In recent years, methodologies based on spectral analysis, using ultraviolet–visible (UV-Vis) radiation, have experienced an amazing development and have been widely applied in various fields such as agricultural, food, pharmaceutical, and environmental sciences. This straightforward technique has re-emerged with novel and challenging proposals to solve, in a direct and fast way, a wide variety of problems. These reaches would not have been possible without the essential support of chemometrics. In this sense, under the general background of the development in data and computer science, and other technologies, the emergence of innovative ideas, approaches, and strategies endows UV-Vis spectroscopy with a new vitality as an analytical sensor with the capability of significantly improving both the robustness and accuracy of results. This review presents modern UV-Vis spectral analysis, which is on the rise, associated with comprehensive chemometric methods that have become known in the last six years, especially from the perspective of practicability, including spectral preprocessing, wavelength (variable) selection, data dimension reduction, quantitative calibration, pattern recognition, and multispectral data fusion. Most importantly, it will foresee future trends of UV-Vis spectroscopy as an analytical sensor for a spectralprint (nontargeted) analysis. Full article
(This article belongs to the Special Issue Chemometrics for Analytical Chemistry)
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