Call For Papers: Integrating Machine Learning in Modeling Catalysis at the Nanoscale

The integration of machine learning into computational and experimental materials science offers great potential to solve materials design issues related to global challenges. Energy conversion with nanocatalysts holds a particular challenge due to the complex structure of the materials, requiring multiple computational methodologies that can grasp the architectural complexity.

This Special Issue from ACS Materials Au will showcase the variety of computational materials science methods, including machine learning, that are applied to catalysis using nanomaterials for energy conversion.

Topics include, but are not limited to:

• Machine learning method development for catalyst design or characterization
• Prediction or rationalization of catalytic properties of nanomaterials by machine learning
• Machine learning aided experimental measurements or theoretical calculations of catalytic efficiency for energy conversion using nanomaterials
• Needs, challenges, and opportunities in predicting catalytic performance through machine learning

Submit your manuscript by October 31, 2025.

Organizing Editors

Prof. Stephanie Brock, Deputy Editor, ACS Materials Au
Wayne State University, United States

Prof. Maytal Caspary Toroker, Guest Editor
Technion-Israel Institute of Technology, Israel

Prof. Ricardo Grau-Crespo, Guest Editor
University of Reading, United Kingdom

Prof. Ana Belén Muñoz García, Guest Editor
University of Naples Federico II, Italy

Submission Information

We welcome submissions for this Special Issue through October 31, 2025. For more information on submission requirements, please visit the journal’s Author Guidelines page.

Accepted manuscripts for consideration in this Special Issue will include research articles, perspectives, and reviews, and tutorials. Papers accepted for publication for this Special Issue will be available ASAP (as soon as publishable) online. After all submissions have been published, they will then be compiled online on a dedicated landing page to form the Special Issue. Manuscripts submitted for consideration will undergo the full rigorous peer review process expected from ACS journals.

ACS Materials Au is a fully open access journal; thus, your paper will be available to anyone, at anytime, anywhere in the world. Please visit our Open Science Resource Center for more information on pricing, institutional agreements, and more.

How to Submit

• Log in to the ACS Publishing Center.
• Select the "Journals" tab.
• Choose ACS Materials Au.
• Click "Submit."
• Select your manuscript type, and, under "Special Issue Selection," choose “Integrating Machine Learning in Modeling Catalysis at the Nanoscale."

If you have any general questions regarding submission to this Special Issue, please contact Prof. Stephanie Brock (brock-office@materialsau.acs.org).