From the 1 of 6 linked papers with an AI index.
6 papers
Performance of universal machine learning potentials in global optimization of inorganic crystal structures
Edan T. Marcial, Laxman Chaudhary, Olesya Gorbunova +1
The paper benchmarks twelve pretrained universal machine learning potentials by using them in unconstrained evolutionary searches to predict ground-state inorganic crystal structur…
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)…
Rigid muffin-tin approximation in plane-wave codes for fast modeling of phonon-mediated superconductors
Danylo Radevych, Tatsuya Shishidou, Michael Weinert +3
We present a pseudopotential-based plane-wave implementation of the rigid muffin-tin approximation (RMTA), offering a computationally efficient alternative to its traditional use i…
High- AgBC and CuBC superconductors accessible via topochemical reactions
Daviti Gochitashvili, Charlsey R. Tomassetti, Elena R. Margine +1
Hole-doping of covalent materials has long served as a blueprint for designing conventional high- superconductors, but thermodynamic constraints severely limit the space…
Improving structure search with hyperspatial optimization and TETRIS seeding
Daviti Gochitashvili, Maxwell Meyers, Cindy Wang +1
Advanced structure prediction methods developed over the past decades include an unorthodox strategy of allowing atoms to displace into extra dimensions. A recently implemented glo…
Stability-superconductivity map for compressed Na-intercalated graphite
Shashi B. Mishra, Edan T. Marcial, Suryakanti Debata +2
A recent ab initio investigation of Na-C binary compounds under moderate pressures has uncovered a possible stable NaC superconductor with an estimated critical temperature up…