11 citations · 14 across the 5 of their papers we have counts for
9 papers
Predicting Interface Structure using the Minima Hopping Method with a Machine Learning Interatomic Potential
Chang-Ti Chou, Menghang Wang, Chao Yang +4
Predicting atomic-scale interfacial structures remains a central challenge in materials science due to their structural complexity and the difficulty of direct comparison between c…
Quantum theory of nonlinear phononics
Francesco Libbi, Boris Kozinsky
The recent capability to use THz pulses to control the nuclear quantum degrees of freedom in crystals has opened promising avenues for the advanced manipulation of material propert…
Equivalence of charged and neutral density functional formulations for correcting the many-body self-interaction of polarons
Stefano Falletta, Jennifer Coulter, Joel B. Varley +4
The electron self-interaction problem in density functional theory affects the accurate modeling of polarons, particularly their localization and formation energy. Charged and neut…
Multiscale light-matter dynamics in quantum materials: from electrons to topological superlattices
Taufeq Mohammed Razakh, Thomas Linker, Ye Luo +12
Light-matter dynamics in topological quantum materials enables ultralow-power, ultrafast devices. A challenge is simulating multiple field and particle equations for light, electro…
Coupled reaction and diffusion governing interface evolution in solid-state batteries
Jingxuan Ding, Laura Zichi, Matteo Carli +4
Understanding and controlling the atomistic-level reactions governing the formation of the solid-electrolyte interphase (SEI) is crucial for the viability of next-generation solid…
High-performance training and inference for deep equivariant interatomic potentials
Chuin Wei Tan, Marc L. Descoteaux, Mit Kotak +11
Machine learning interatomic potentials, particularly those based on deep equivariant neural networks, have demonstrated state-of-the-art accuracy and computational efficiency in a…