Molecular analysis and design using generative artificial intelligence <i>via</i> multi-agent modeling
Isabella Stewart, Markus J. Buehler
Abstract
their molecular structure, charge distribution, and other features. We validate that as predicted, increased dipole moment and polarizability is indeed achieved in the designed molecules. We anticipate an increasing integration of these techniques into the molecular engineering workflow, ultimately enabling the development of innovative solutions to address a wide range of societal challenges. We conclude with a critical discussion of challenges and opportunities of the use of multi-agent generative AI for molecular engineering, analysis and design.
Topics & Concepts
Generative grammarComputer scienceGemmaArtificial intelligenceTest (biology)EcologyBiologyBotanyMachine Learning in Materials ScienceComputational Drug Discovery MethodsProtein Structure and Dynamics