54 citations · 86 across the 4 of their papers we have counts for
4 papers
EPW-VASP interface for first-principles calculations of electron-phonon interactions
Danylo Radevych, Aidan Thorn, Manuel Engel +5
We present an interface between the Vienna \textit{Ab initio} Simulation Package (VASP) and the EPW software for calculating materials properties governed by electron-phonon (e-ph)…
Machine learning search for stable binary Sn alloys with Na, Ca, Cu, Pd, and Ag
Aidan Thorn, Daviti Gochitashvili, Saba Kharabadze +1
We present our findings of a large-scale screening for new synthesizable materials in five M-Sn binaries, M = Na, Ca, Cu, Pd, and Ag. The focus on these systems was motivated by th…
Prediction of stable Li-Sn compounds: boosting ab initio searches with neural network potentials
Saba Kharabadze, Aidan Thorn, Ekaterina A. Koulakova +1
The Li-Sn binary system has been the focus of extensive research because it features Li-rich alloys with potential applications as battery anodes. Our present re-examination of the…
MAISE: Construction of neural network interatomic models and evolutionary structure optimization
Samad Hajinazar, Aidan Thorn, Ernesto D. Sandoval +2
Module for ab initio structure evolution (MAISE) is an open-source package for materials modeling and prediction. The code's main feature is an automated generation of neural netwo…