Toward dynamic crystal structure prediction: integrating thermodynamic and kinetic modeling

2026/01/01 by Prem K. Reddy, Anish V. Dighe, Rajan R. Bhawnani +1 · 1 voice
Chemistry · Materials Science · #Crystallization and Solubility Studies #Crystallography and molecular interactions #Machine Learning in Materials Science

paper · pdf · doi:10.1039/d5ce00977d

openalex publication_date 2026/01/01 · openalex created_date 2026/02/07 · openalex updated_date 2026/07/21

Abstract

This article reviews the transition from static crystal structure prediction (CSP) to dynamic multiscale frameworks that delineate self-assembly, nucleation, and growth. A unified strategy for the prediction of polymorphs and morphology is outlined.

Citations

• TURBOMOLE: Modular program suite for ab initio quantum-chemical and condensed-matter simulations
• Software update: The ORCA program system—Version 5.0

Discussions

• An #OpenAccess Highlight article by Meenesh R. Singh & co. featured on the issue 11 cover 👇 "Toward dynamic crystal structure prediction: integrating thermodynamic and kinetic modeling" 🔗 doi.org/ [bsky, 1 points, 0 comments]

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