ArticleJournal of chemical theory and computation2026
Quantum Chemistry-Driven Molecular Inverse Design of Stable Isomers with Data-Free Reinforcement Learning.
Article in Journal of chemical theory and computation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The inverse design (ID) of molecules remains one of the greatest challenges in chemistry. Machine learning and artificial intelligence (AI) methods are increasingly employed to generate candidate molecules with tailored properties but mostly rely on pretraining over large data sets, which introduces bias. Here, we present a data-free generative AI model called PROTEUS that integrates reinforcement learning with on-the-fly quantum mechanical calculations to enable the
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