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Revealing Fast Ionic Conduction in Solid Electrolytes through Machine Learning Accelerated Raman Calculations
Manuel Grumet, Takeru Miyagawa, Olivier Pittet +4
Fast ionic conduction is a defining property of solid electrolytes for all-solid-state batteries. Previous studies have suggested that liquid-like cation motion associated with fas…
Predicting the Thermal Behavior of Semiconductor Defects with Equivariant Neural Networks
Xiangzhou Zhu, Patrick Rinke, David A. Egger
The presence of defects strongly influences semiconductor behavior. However, predicting the electronic properties of defective materials at finite temperatures remains computationa…
Machine Learning Accelerates Raman Computations from Molecular Dynamics for Materials Science
David A. Egger, Manuel Grumet, Tomáš Bučko
Raman spectroscopy is a powerful experimental technique for characterizing molecules and materials that is used in many laboratories. First-principles theoretical calculations of R…
Machine-Learning Force Fields Reveal Shallow Electronic States on Dynamic Halide Perovskite Surfaces
Frederico P. Delgado, Frederico Simões, Leeor Kronik +2
The spectacular performance of halide perovskites in optoelectronic devices is rooted in their tolerance to defects. Previous studies showed that defects in these materials generat…