3 papers
cond-mat.mtrl-sci2025
Interatomic potential development for topological insulator Bi1-xSbx and its dislocation by force-following active learning
Moon-ki Choi, Daniel Palmer, Harley T. Johnson
We introduce a force following active learning algorithm that integrates density functional theory DFT with the Gaussian Approximation Potential GAP framework to develop a robust i…
cond-mat.mtrl-sci2025
Graph Neural Network for Unified Electronic and Interatomic Potentials: Strain-tunable Electronic Structures in 2D Materials
Moon-ki Choi, Daniel Palmer, Harley T. Johnson
We introduce UEIPNet, an equivariant graph neural network designed to predict both interatomic potentials and tight-binding (TB) Hamiltonians for an atomic structure. The UEIPNet i…
cond-mat.mtrl-sci2025
Graphene-hBN interlayer interactions from quantum Monte Carlo
Kittithat Krongchon, Tawfiqur Rakib, Daniel Palmer +3
The interaction between graphene and hexagonal boron nitride (hBN) plays a pivotal role in determining the electronic and structural properties of graphene-based devices. In this w…