Machine Learned Potential for High-Throughput Phonon Calculations of Metal–-Organic Frameworks

Prathami Divakar Kamath, Alin Marin Elena, Theo Jaffrelot inizan, Andrew Scott Rosen, Federica Zanca, Kristin Persson

Keywords: Machine Learning Potentials, Metal--organic Frameworks, phonons, high-throughput screening

TL;DR: This paper presents MACE-MP-MOF0, a machine-learned potential that enables efficient and accurate predictions of phonon properties in MOFs, accelerating materials discovery and design

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Submission Number: 66