Chemometrics for Analytical Chemistry: Second Edition

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

Deadline for manuscript submissions: 30 June 2024 | Viewed by 758

Special Issue Editors


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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
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 have become mandatory in several applications. Chemometrics is a prominent field that manipulates data from chemical processes utilizing mathematics and statistic fundamentals. The advancement of electronics and computer science have allowed for 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, is highest in 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, a revolution occurred—the rapid growth of computing power, allowing powerful algorithms to become routine tools for the laboratory chemist. Simultaneously, there was the growth of rapid automated instruments leading to the generation of large datasets, using approaches such as hyphenated and multidimensional chromatography or NMR. In modern society, chemometrics is not only used to solve qualitative and quantitative problems, but also focuses more on pattern recognition. Applications included biomedical data, especially metabolomics and food chemistry, as well as more recently developing areas including forensics and cultural heritage studies among others. Chemometrics has developed both as a significant tool for applied analytical chemistry and a theoretical method to assist in the improvement and development of instrumental methods. In this Special Issue, ‘Chemometrics for Analytical Chemistry: Second Edition’, we aim to feature articles on chemometrics, including sampling, experimental design, data preprocessing and data fusion strategies, projection methods for data exploration and factor analysis, multiway calibration, and 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

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

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

Published Papers (1 paper)

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Research

13 pages, 2214 KiB  
Article
A New X-ray Diffraction Spectrum-Based Untargeted Strategy for Accurately Identifying Ancient Painted Pottery from Various Dynasties and Locations in China
by Jing-Jing Song, Yang-Yang Wang, Wen-Cheng Tong, Feng-Lian Ma, Jia-Nan Wang and Yong-Jie Yu
Chemosensors 2024, 12(4), 64; https://0-doi-org.brum.beds.ac.uk/10.3390/chemosensors12040064 - 15 Apr 2024
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Abstract
X-ray diffraction (XRD) is extensively used in archaeometric investigation. Herein, we provide a novel XRD spectrum-based untargeted strategy for the classification of ancient painted pottery for various dynasties. It was accomplished using the original spectrum without a phase identification. To eliminate the influence [...] Read more.
X-ray diffraction (XRD) is extensively used in archaeometric investigation. Herein, we provide a novel XRD spectrum-based untargeted strategy for the classification of ancient painted pottery for various dynasties. It was accomplished using the original spectrum without a phase identification. To eliminate the influence of baseline drift, a new baseline drift correction algorithm was specifically designed for XRD spectra. The algorithm was implemented using local minimum values in the analyzed signal in an iterative optimization manner. The results indicated that with the aid of the algorithm, the baseline drift problem can be successfully resolved, and the classification of ancient painted pottery can be greatly improved. Finally, the developed strategy was successfully used to discriminate ancient painted pottery from the Han and Tang dynasties in the cities of Guyuan and Zhongwei, China. The developed untargeted strategy had the remarkable advantage of almost automatic data analysis. The toolbox of our strategy can be obtained from the authors. Full article
(This article belongs to the Special Issue Chemometrics for Analytical Chemistry: Second Edition)
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