Project Details
Description
Fixed price - The application of reliable ab initio methods to complex problems, like solvent effects, solid-liquid and gas-liquid interfaces, and catalysis, requires the development of novel, highly scalable electronic structure (ES), non-equilibrium statistical mechanics and machine learning (ML) software. The proposed research will develop such software, through a collaboration of experts in ES theory, non-equilibrium statistical mechanics, and computer science/applied math, and apply these new implementations to important problems including heterogeneous catalysis and polymer upcycling. This entire group has a strong history of collaboration for many years, including a current Computational Chemical Sciences (CCS) grant.
Status | Finished |
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Effective start/end date | 9/01/23 → 30/09/24 |
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