Artificial Intelligence Chemistry – a new open-access journal – has launched a special issue Artificial intelligence in computational chemistry. One of the XACS PIs (Pavlo O. Dral) is on an Editorial Board of the journal and a Guest Editor of the issue.  Submissions to the special issue are open until July 31, 2023. Articles submitted to this issue will be published free of charge. We are looking forward to your submissions!

About the special issue (from the journal’s website)

Artificial intelligence firmly entered the field of computational chemistry. This Special Issue is dedicated to highlight latest advances in application of artificial intelligence/machine learning in all areas of computational chemistry. The topics include, but not limited to, machine learning interatomic potentials, molecular and quantum dynamics with machine learning, extracting chemical insights from simulations with machine learning, virtual materials design, new quantum chemical methods improved with machine learning, design of other new and critical evaluation of existing artificial intelligence methods for computational chemistry.

Guest editors:

Pavlo O. Dral, PhD
Xiamen University, Xiamen, China
(Machine learning in chemistry, Quantum chemistry, Excited states, Electronic structure simulations, Dynamics)

Joel M. Bowman, PhD
Emory University, Atlanta, Georgia, United States of America
(Machine learning potential energy surfaces, vibrational and reaction dynamics)

Feliu Maseras, PhD
Institute of Chemical Research of Catalonia, Tarragona, Spain
(Computational homogeneous catalysis; Quantum mechanics/Molecular mechanics methods; Statistical analysis of computational results)

Fang Liu, PhD
Emory University, Atlanta, Georgia, United States of America
(quantum chemistry, solvent effects, machine learning, excited states)

Manuscript submission information:

You are invited to submit your manuscript at any time before the submission deadline. For any inquiries about the appropriateness of contribution topics, please contact Prof. Pavlo O. Dral via dral@xmu.edu.cn.

The journal’s submission platform (Editorial Manager®) is now available for receiving submissions to this Special Issue. Please refer to the Guide for Authors to prepare your manuscript and select the article type of “VSI: AICompChem” when submitting your manuscript online. The special issue is a 100% waived Special Issue and you will not receive any APC if your paper is accepted for publication. Both the Guide for Authors and the submission portal could be found on the Journal Homepage here: https://www.journals.elsevier.com/artificial-intelligence-chemistry

Submission Deadline: July 31, 2023

Keywords:

Machine learning potentials, materials design with machine learning, quantum chemical methods improved with machine learning, analysis of simulations, molecular dynamics, quantum dynamics.

Why publish in this Special Issue?

• Special Issue articles are published together on ScienceDirect, making it incredibly easy for other researchers to discover your work.
• Special content articles are downloaded on ScienceDirect twice as often within the first 24 months than articles published in regular issues.
• Special content articles attract 20% more citations in the first 24 months than articles published in regular issues.
• All articles in this special issue will be reviewed by no fewer than two independent experts to ensure the quality, originality and novelty of the work published.

Learn more about the benefits of publishing in a special issue: https://www.elsevier.com/authors/submit-your-paper/special-issues

About the journal (from its website)

The journal will broadly cover all areas of chemistry where artificial intelligence (AI) and machine learning approaches are used. While studies in more traditional sub-disciplines of chemist will certainly be considered, we would welcome and encourage submissions of work that could potentially stimulate interdisciplinary interests involving AI. All submissions must provide a significant contribution to our understanding of contemporary and future AI theory, AI methods, and/or AI applications in chemistry, medicine, biology, and materials science. Studies conducted at all spatial and temporal scales will be considered.

We will be open to submissions on all relevant topics and but particularly interested in the following areas of research:

Quantum chemical methods combining artificial intelligence (AI) and big data techniques; AI oriented calculations and data system; Construction of AI models; AI assisted materials design; AI assisted structure-activity relationship; Machine learning protocols and application in chemistry; Multi-scale modelling method development; Intelligent spectrum analysis based on AI; Application of AI in complex chemical systems; Application of AI in organic chemistry; Application of AI in drug discovery; Application of AI in identification of sprout compounds and targets; Development of AI software and hardware; Research on the integrating experimental and theory; AI-based spectroscopic analysis and monitoring. The forms of articles to be accepted include reviews, research articles, correspondence letters, news items, etc.