Accurate Lattice Free Energies of Packing Polymorphs from Probabilistic Generative Models.

ABSTRACT: Finite-temperature lattice free energy differences between polymorphs of molecular crystals are fundamental to understanding and predicting the relative stability relationships underpinning polymorphism, yet are computationally expensive to obtain. Here, we implement and critically assess machine-learning-enabled targeted free energy calculations derived from flow-based generative models to compute the free energy difference between two ice crystal polymorphs (Ice XI and Ic), modeled with a fully flexible empirical classical force field. We demonstrate that even when remapping from an analytical reference distribution, such methods enable a cost-effective and accurate calculation of free energy differences between disconnected metastable ensembles when trained on locally ergodic data sampl

SUBMITTER: Olehnovics E 

PROVIDER: S-EPMC11912200 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature