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cond-mat.mtrl-sci2024★ 1 cited
Machine Learned Potential for High-Throughput Phonon Calculations of Metal-Organic Frameworks
Alin Marin Elena, Prathami Divakar Kamath, Théo Jaffrelot Inizan +3
Metal-organic frameworks (MOFs) are highly porous and versatile materials studied extensively for applications such as carbon capture and water harvesting. However, computing phono…
cond-mat.mtrl-sci2024
Modelling Silica using MACE-MP-0 Machine Learnt Interatomic Potentials
Jamal Abdul Nasir, Jingcheng Guan, Woongkyu Jee +4
Silica polymorphs and zeolites are fundamental to a wide range of industrial applications owing to their diverse structural characteristics, thermodynamic and mechanical stability…