Special Issue

DFT and Machine Learning Applications in Chemistry and Materials Science for Sustainable Energy Research

Submission Deadline: April 15, 2026 (Open) Submit Now

Guest Editor

Rajesh Kumar Raju, PhD

Research Officer –Scientist in AI Material Discover, Theory and Simulation, National Research Council Canada, Clean Energy Innovation (CEI) Research Centre, Mississauga, Ontario, Canada

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Research Interests: Computational chemistry; density functional theory; catalysis; biochemistry; AI/ML material and molecular discovery; energy; CO_₂ capture and conversion; electroreduction; batteries

About This Topic

Density Functional Theory (DFT) remains a foundational tool in computational chemistry and materials science, enabling accurate quantum-level insights into the electronic structure and properties of molecules and materials. With the growing demand for sustainable energy solutions, integrating DFT with emerging machine learning (ML) and artificial intelligence (AI) methods has created new opportunities for accelerating the discovery and design of materials for energy-related applications. This special issue aims to highlight recent progress at the intersection of DFT, ML, and molecular modeling, with a particular focus on applications in catalysis, CO_₂ capture and electroreduction, battery materials, and molecular-level insights into clean energy technologies. However, the scope is not limited to these areas—we welcome a broad range of contributions involving advanced computational methodologies and data-driven approaches that support innovation in chemistry, materials science, and sustainability.

Keywords

Density functional theory (DFT); machine learning (ML); artificial intelligence (AI); sustainable energy; CO_₂ capture and conversion; electrocatalysis; battery materials; molecular simulation; catalyst design; computational chemistry; materials discovery; green chemistry

Manuscript Submission Information

Manuscripts should be submitted through the LIDSEN Submission System. Detailed information on manuscript preparation and submission is available in the Instructions for Authors. All submitted articles will be thoroughly refereed through a single-blind peer-review process and will be processed following the Editorial Process and Quality Control policy. Upon acceptance, the article will be immediately published in a regular issue of the journal and will be listed together on the special issue website, with a label that the article belongs to the Special Issue. LIDSEN distributes articles under the Creative Commons Attribution (CC BY 4.0) License in an open-access model. The authors own the copyright to the article, and the article can be free to access, distribute, and reuse provided that the original work is correctly cited.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). Research articles and review articles are highly invited. Authors are encouraged to send the tentative title and abstract of the planned paper to the Editorial Office (rpse@lidsen.com) for record. If you have any questions, please do not hesitate to contact the Editorial Office.

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