14 citations · 15 across the 2 of their papers we have counts for
2 papers
cond-mat.mtrl-sci2026★ 1 cited
Deciphering borophene growth pathways with data-driven simulations
Colin Bousige, Jean Furstoss, Julien Lam +1
Deterministic synthesis of borophene remains challenging because many polymorphs compete during nucleation and growth. Here we combine a reactive machine-learned interatomic potent…
cond-mat.mtrl-sci2023★ 14 cited
Neural network approach for a rapid prediction of metal-supported borophene properties
Pierre Mignon, Abdul-Rahman Allouche, Neil Richard Innis +1
We develop a high-dimensional neural network potential (NNP) to describe the structural and energetic properties of borophene deposited on silver. This NNP has the accuracy of DFT…