Machine Learning in Catalyst Design and Synthesis
A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Materials Chemistry".
Deadline for manuscript submissions: 30 June 2025 | Viewed by 191
Special Issue Editor
Interests: electronic structure; electrocatalysis; semiconductor; computational chemistry
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The Special Issue "Machine Learning in Catalyst Design and Synthesis" aims at highlighting the transformative impact of machine learning (ML) on the field of catalysis. ML techniques have revolutionized the way researchers approach catalyst design and synthesis, enabling the rapid discovery of new materials and the optimization of reaction conditions. By integrating computational modeling, experimental data, and advanced ML algorithms, this interdisciplinary field is accelerating breakthroughs in areas such as CO2 reduction, hydrogen production, and sustainable chemical processes. This Special Issue welcomes original research articles, reviews, and perspectives that explore the application of ML in catalyst design, including the development of predictive models, the optimization of synthesis protocols, and the discovery of novel catalytic materials. Through this collection, we aim at showcasing cutting-edge advancements and fostering collaboration across computational and experimental domains, advancing the frontiers of catalysis research.
Dr. Shiru Lin
Guest Editor
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. Molecules is an international peer-reviewed open access semimonthly 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
- machine learning
- catalyst design
- catalytic synthesis
- predictive modeling
- computational chemistry
- material discovery
- reaction optimization
- sustainable catalysis
- CO2 reduction
- energy-conversion catalysis
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