203 citations · 380 across the 22 of their papers we have counts for
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Dislocation-loop formation is a first-order phase transition
Xiaoya Chang, Arsalan Hashemi, Nima Ghafari Cherati +3
Dislocation loops are the elementary product of radiation damage in crystals, limiting reactor-component lifetimes, power-electronics reliability and the coherence of solid-state q…
Nine-element machine-learned interatomic potentials for multiphase refractory alloys
Jesper Byggmästar, Tiago Lopes, Zheyong Fan +1
New refractory alloys are being continuously designed and characterised for applications requiring good high-temperature mechanical properties and stability. Computational design f…
Stabilisation of hBN/SiC Heterostructures with Vacancies and Transition-Metal Atoms
Arsalan Hashemi, Nima Ghafari Cherati, Sadegh Ghaderzadeh +3
When two-dimensional atomic layers of different materials are brought into close proximity to form van der Waals (vdW) heterostructures, interactions between adjacent layers signif…
NEP89: Universal neuroevolution potential for inorganic and organic materials across 89 elements
Ting Liang, Ke Xu, Eric Lindgren +16
While machine-learned interatomic potentials offer near-quantum-mechanical accuracy for atomistic simulations, many are material-specific or computationally intensive, limiting the…
Boron Isotope Effects on Raman Scattering in Bulk BN, BP, and BAs: A Density-Functional Theory Study
Nima Ghafari Cherati, I. Abdolhosseini Sarsari, Arsalan Hashemi +1
For many materials, Raman spectra are intricately structured and provide valuable information about compositional stoichiometry and crystal quality. Here we use density-functional…
Density dependence of thermal conductivity in nanoporous and amorphous carbon with machine-learned molecular dynamics
Yanzhou Wang, Zheyong Fan, Ping Qian +2
Disordered forms of carbon are an important class of materials for applications such as thermal management. However, a comprehensive theoretical understanding of the structural dep…
General-purpose machine-learned potential for 16 elemental metals and their alloys
Keke Song, Rui Zhao, Jiahui Liu +25
Machine-learned potentials (MLPs) have exhibited remarkable accuracy, yet the lack of general-purpose MLPs for a broad spectrum of elements and their alloys limits their applicabil…