Machine-Learned Potentials for Accelerated CCSD(T)-level Evaluations: Applications to OH(H2O)n
An end-to-end machine learning workflow for the development of potential energy surfaces at the DLPNO-CCSD(T)/aug-cc-pVTZ level is described and applied to hydroxide-water complexes with two to five water molecules. This workflow utilizes a two-part machine learning process, achieving both accuracy and efficiency by co...