Artificial Intelligence in Spectroscopic Techniques: From Data Processing to Discovery
A special issue of AI Chemistry (ISSN 3042-6723).
Deadline for manuscript submissions: 28 February 2026 | Viewed by 122
Special Issue Editors
Interests: nanostructure/thin film fabrication and characterization; metamaterials and plasmonic nanostructures; chemical and biological sensors; nano-photocatalysts; antimicrobial materials; nanomotors and their applications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Spectroscopic techniques such as Raman, IR, UV-Vis, NMR, XPS, and mass spectrometry generate high-dimensional, information-rich data that are essential for chemical, biological, environmental, and material sciences. However, extracting meaningful patterns, reducing noise, interpreting complex spectra, and correlating spectral signatures with structural or functional properties remain challenging tasks. In recent years, artificial intelligence (AI) has emerged as a transformative tool for spectroscopic analysis. Techniques such as machine learning, deep learning, and generative modeling are reshaping how spectra are processed, interpreted, and applied—from enhanced preprocessing and feature extraction to classification, quantification, inverse design, and autonomous experimentation.
This Special Issue aims to showcase cutting-edge research at the intersection of AI and spectroscopy, highlighting both foundational methods and real-world applications. We welcome contributions that focus on AI-enhanced spectral data processing, spectral interpretation, compound identification, predictive modeling, the simulation of spectral data, and autonomous sensing systems across chemical, biomedical, environmental, and industrial domains.
This Special Issue aligns well the scope of AI Chemistry by emphasizing the application of data-centric, AI-enabled strategies to accelerate spectroscopic discovery, interpretation, and decision-making in chemical research.
Prof. Dr. Yiping Zhao
Prof. Dr. Bo Hu
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. AI Chemistry is an international peer-reviewed open access quarterly 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 1000 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
- artificial intelligence
- machine learning
- spectroscopy
- data analysis
- signal processing
- SERS/Raman spectroscopy
- spectral simulation
- deep learning
- spectral classification and quantification
- spectral dimixing
- inverse spectral design
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