526 citations
- Chinese Academy of SciencesCN36 papers
- Aalto UniversityFI34 papers
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36 papers · 1 filter
Benchmarking Chemically Scalable Machine-Learning Interatomic Potentials for Large-Scale Simulations of Multicomponent Alloys
Fei Shuang, Penghua Ying, Kai Liu +5
Machine learning interatomic potentials (MLIPs) with broad chemical flexibility are essential for atomistic simulations of compositionally complex alloys, but their deployment in l…
Anisotropic and isotropic elasticity and thermal transport in monolayer C networks from machine-learning molecular dynamics
Qing Li, Haikuan Dong, Penghua Ying +1
Two-dimensional fullerene networks have recently attracted increasing interest due to their diverse bonding topologies and mechanically robust architectures. In this work, we devel…
Interface phonon modes governing the ideal limit of thermal transport across diamond/cubic boron nitride interfaces
Xiaonan Wang, Xin Wu, Penghua Ying +2
Understanding the ideal limit of interfacial thermal conductance (ITC) across semiconductor heterointerfaces is crucial for optimizing heat dissipation in practical applications. B…
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…
Advances in modeling complex materials: The rise of neuroevolution potentials
Penghua Ying, Cheng Qian, Rui Zhao +4
Interatomic potentials are essential for driving molecular dynamics (MD) simulations, directly impacting the reliability of predictions regarding the physical and chemical properti…
Insight into the effect of force error on the thermal conductivity from machine-learned potentials
Wenjiang Zhou, Nianjie Liang, Xiguang Wu +3
Machine-learned potentials (MLPs) have been extensively used to obtain the lattice thermal conductivity via atomistic simulations. However, the impact of force errors in various ML…