A complete description of thermodynamic stabilities of molecular crystals

• DOI: 10.1073/pnas.2111769119
• Publication Date: 2022-02-07T21:30:37Z
• Authors: Venkat Kapil; Edgar A. Engel
• Keywords: monte-carlo; ab initio thermodynamics; Condensed Matter - Materials Science; crystallization; Statistical Mechanics (cond-mat.stat-mech); exchange; temperature; Materials Science (cond-mat.mtrl-sci); FOS: Physical sciences; prediction; polymorphs; chemistry; 01 natural sciences; free-energy; polymorphism; pressure; machine learning; Physical Sciences; 0103 physical sciences; succinic acid; statistical mechanics; Condensed Matter - Statistical Mechanics

Predictions of relative stabilities (competing) molecular crystals are great technological relevance, most notably for the pharmaceutical industry. However, they present a long-standing challenge modeling, as often minuscule free energy differences sensitively affected by description electronic structure, statistical mechanics nuclei and cell, thermal expansion. The importance these effects has been individually established, but rigorous calculations general compounds, which simultaneously account all effects,have hitherto not computationally viable. Here we an efficient "end to end" frame-work that seamlessly combines state-of-the art structure calculations, machine-learning potentials, advanced methods calculate ab initio Gibbs energies organic materials. facile generation potentials diverse set polymorphic benzene, glycine, succinic acid, predictions thermodynamic in qualitative quantitative agreement with experiments highlights predictive studies industrially-relevant materials no longer daunting task.