Empirical principles, and structure-property relations derived from chemical intuition, have driven for centuries the design of materials and molecules with desirable properties, and the identification of viable synthetic pathways. In recent years, thanks to the compilation of curated experimental and computational databases of compounds and reactions, and to the general advances in the application of machine-learning techniques to all fields of science, the design of molecules and materials has been increasingly led by data-driven approaches.
This special issue welcomes manuscripts that report novel methods and breakthrough applications to design chemical compounds and materials with improved properties, and synthetic routes to obtain them, by screening existing databases, by actively exploring chemical space, and by combining computational approaches with automated chemistry. Applications include, but are not limited to, discovery, computational or experimental characterization of catalysts and materials for energy storage and production as well as novel synthetic routes for molecules and materials.
Topics covered include, but are not limited to:
- Computational or experimental characterization of catalysts and materials for energy storage and production
- Novel synthetic routes for molecules and materials
Daniel H. Ess, Brigham Young University
Kim E. Jelfs, Imperial College
Heather J. Kulik, MIT
Michele Ceriotti, École Polytechnique Fédérale de Lausanne
Angelos Michaelides, University of Cambridge
David Manolopoulos, University of Oxford
Todd Martinez, Stanford University
David Sherrill, Georgia Institute of Technology
Please note that papers will be published as normal when they are ready in a regular issue of the journal and will populate on a virtual collection page within a few days of publication. Inclusion in the collection will not cause delay in publication.
How to submit:
- Please submit through the online submission system.
- Under manuscript type → select Article or Communication, as appropriate.
- Under manuscript information → Title/Abstract → select “Invited Submission: No”.
- Under manuscript information → Manuscript classification → select Special Topic: “Chemical Design by Artificial Intelligence”