2 citations · 2 across the 1 of their papers we have counts for
3 papers
Machine-Learned Interatomic Potential for Predictive Simulation of MoS2 Epitaxy
Emir Bilgili, Nicholas Taormina, Richard Hennig +2
A machine-learned interatomic potential (MLIP) for multilayer MoS2 was developed using the ultra-fast force field (UF3) framework. The UF3 MLIP reproduces key properties in strong…
Effect of Misfit and Threading Dislocations on Surface Energies of PbTe-PbSe Interfaces
Emir Bilgili, Nicholas Taormina, Yang Li +3
This work quantifies the effect of misfit and threading dislocations on the surface energies of PbTe-PbSe interfaces, with the defect structures of the interfaces being obtained fr…
Machine-learning interatomic potential for AlN for epitaxial simulation
Nicholas Taormina, Emir Bilgili, Jason Gibson +3
A machine learned interatomic potential for AlN was developed using the ultra-fast force field (UF3) methodology. A strong agreement with density functional theory calculations in…