Cover Image

NEP89: Universal neuroevolution potential for inorganic and organic materials across 89 elements

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liang, Ting, Xu, Ke, Lindgren, Eric, Chen, Zherui, Zhao, Rui, Liu, Jiahui, Berger, Esmée, Tang, Benrui, Zhang, Bohan, Wang, Yanzhou, Song, Keke, Ying, Penghua, Xu, Nan, Dong, Haikuan, Chen, Shunda, Erhart, Paul, Fan, Zheyong, Ala-Nissila, Tapio, Xu, Jianbin
Format:	Preprint
Published:	2025
Subjects:	Materials Science
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

qNEP: A highly efficient neuroevolution potential with dynamic charges for large-scale atomistic simulations
by: Fan, Zheyong, et al.
Published: (2026)

Highly efficient path-integral molecular dynamics simulations with GPUMD using neuroevolution potentials: Case studies on thermal properties of materials
by: Ying, Penghua, et al.
Published: (2024)

Advances in modeling complex materials: The rise of neuroevolution potentials
by: Ying, Penghua, et al.
Published: (2025)

NEP-CG and NEP-AACG: Efficient coarse-grained and multiscale all-atom-coarse-grained neuroevolution potentials
by: Fan, Zheyong, et al.
Published: (2026)

Combining linear-scaling quantum transport and machine-learning molecular dynamics to study thermal and electronic transports in complex materials
by: Fan, Zheyong, et al.
Published: (2023)

Million-atom heat transport simulations of polycrystalline graphene approaching first-principles accuracy enabled by neuroevolution potential on desktop GPUs
by: Zhou, Xiaoye, et al.
Published: (2024)

NEP-MB-pol: A unified machine-learned framework for fast and accurate prediction of water's thermodynamic and transport properties
by: Xu, Ke, et al.
Published: (2024)

Molecular dynamics simulations of heat transport using machine-learned potentials: A mini review and tutorial on GPUMD with neuroevolution potentials
by: Dong, Haikuan, et al.
Published: (2024)

Solute segregation in polycrystalline aluminum from hybrid Monte Carlo and molecular dynamics simulations with a unified neuroevolution potential
by: Song, Keke, et al.
Published: (2024)

Thermal conductivities of monolayer graphene oxide from machine learning molecular dynamics simulations
by: Zhang, Bohan, et al.
Published: (2025)

Density dependence of thermal conductivity in nanoporous and amorphous carbon with machine-learned molecular dynamics
by: Wang, Yanzhou, et al.
Published: (2024)

Nine-element machine-learned interatomic potentials for multiphase refractory alloys
by: Byggmästar, Jesper, et al.
Published: (2026)

General-purpose machine-learned potential for 16 elemental metals and their alloys
by: Song, Keke, et al.
Published: (2023)

Tensorial properties via the neuroevolution potential framework: Fast simulation of infrared and Raman spectra
by: Xu, Nan, et al.
Published: (2023)

Anisotropic and isotropic elasticity and thermal transport in monolayer C$_{24}$ networks from machine-learning molecular dynamics
by: Li, Qing, et al.
Published: (2025)

Optimizing thermoelectric performance of graphene antidot lattices via quantum transport and machine-learning molecular dynamics simulations
by: Xiao, Yang, et al.
Published: (2025)

GPUMDkit: A User-Friendly Toolkit for GPUMD and NEP
by: Yan, Zihan, et al.
Published: (2026)

Interaction-Enabled Hartree Fixed Points in Fermionic Resetting Dynamics
by: Kumar, Jishad, et al.
Published: (2026)

Coherence-Controlled Quantum Zeno Dynamics from Exact Reset Maps
by: Kumar, Jishad, et al.
Published: (2026)

Thermodynamics of Coherence-Selective Quantum Reset Protocols
by: Kumar, Jishad, et al.
Published: (2026)

Density-dependent sodium-storage mechanisms in hard carbon materials
by: Front, Alexis, et al.
Published: (2025)

On-the-fly reparametrization of pairwise dispersion interactions for accurate and efficient molecular dynamics: Phase diagram of white phosphorus
by: Muhli, Heikki, et al.
Published: (2024)

Optimal quantum reservoir learning in proximity to universality
by: Ivaki, Moein N., et al.
Published: (2025)

Atom-wise formulation of the many-body dispersion problem for linear-scaling van der Waals corrections
by: Muhli, Heikki, et al.
Published: (2024)

Quantum reservoir computing on random regular graphs
by: Ivaki, Moein N., et al.
Published: (2024)

GPUMD 4.0: A high‐performance molecular dynamics package for versatile materials simulations with machine‐learned potentials
by: Ke Xu, et al.
Published: (2025)

Stabilisation of hBN/SiC Heterostructures with Vacancies and Transition-Metal Atoms
by: Hashemi, Arsalan, et al.
Published: (2025)

Driven Polymer Translocation through a Nanopore from a Confining Channel
by: Emamyari, Soheila, et al.
Published: (2025)

Adsorption of polyelectrolytes in the presence of varying dielectric discontinuity between solution and substrate
by: Vahid, Hossein, et al.
Published: (2024)

Structurally Triggered Breakdown of the Phonon Gas Model in Crystalline Metal-Organic Frameworks
by: Ying, Penghua, et al.
Published: (2026)

Atomistic understanding of hydrogen bubble-induced embrittlement in tungsten enabled by machine learning molecular dynamics
by: Bao, Yu, et al.
Published: (2025)

Accurate Modeling of Interfacial Thermal Transport in van der Waals Heterostructures via Hybrid Machine Learning and Registry-Dependent Potentials
by: Jiang, Wenwu, et al.
Published: (2025)

Phonon coherence and minimum thermal conductivity in disordered superlattice
by: Wu, Xin, et al.
Published: (2024)

Dynasor 2: From Simulation to Experiment Through Correlation Functions
by: Berger, Esmée, et al.
Published: (2025)

Boron Isotope Effects on Raman Scattering in Bulk BN, BP, and BAs: A Density-Functional Theory Study
by: Cherati, Nima Ghafari, et al.
Published: (2024)

A high-efficiency neuroevolution potential for tobermorite and calcium silicate hydrate systems with ab initio accuracy
by: Xu, Xiao, et al.
Published: (2025)

Thermal Stabilization of Defect Charge States and Finite-Temperature Charge Transition Levels
by: Hainer, Tobias, et al.
Published: (2025)

Interface phonon modes governing the ideal limit of thermal transport across diamond/cubic boron nitride interfaces
by: Wang, Xiaonan, et al.
Published: (2025)

NEPMaker: Active learning of neuroevolution machine learning potential for large cells
by: Wang, Junjie, et al.
Published: (2026)

Predicting neutron experiments from first principles: A workflow powered by machine learning
by: Lindgren, Eric, et al.
Published: (2025)