Exploring celecoxib polymorph landscape using AIMNet2 machine learning interatomic potential
Year: 2026
Type: article
Abstract: of the most stable known polymorph. Hybrid-DFT calculations yield a similar low-energy landscape in which multiple polymorphs remain thermodynamically competitive. Finite-temperature analyses further expose the limits of static-lattice models for ultra-soft crystals such as form I. Beyond celecoxib, the framework supplies physically motivated targets for experimental polymorph screening and a transferable strategy for crystal-structure prediction across flexible drug molecules.
Source: Chemical Science
DOI: 10.1039/d5sc09784c
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: diamond
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