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Bibliographic Details
Main Authors:	Liu, Guanghen, Yang, Songge, Zhong, Yu
Format:	Preprint
Published:	2025
Subjects:	Computational Physics Materials Science
Online Access:	https://arxiv.org/abs/2512.23010
Tags:	Add Tag No Tags, Be the first to tag this record!

Universal Machine Learning Kohn-Sham Hamiltonian for Materials
by: Zhong, Yang, et al.
Published: (2024)

A Universal Spin-Orbit-Coupled Hamiltonian Model for Accelerated Quantum Material Discovery
by: Zhong, Yang, et al.
Published: (2025)

Flow Matching for Accelerated Simulation of Atomic Transport in Crystalline Materials
by: Nam, Juno, et al.
Published: (2024)

Universal Numerical Simulation Model for Laser Material Processing
by: Otto, Andreas, et al.
Published: (2025)

A Python-Based Approach to Sputter Deposition Simulations in Combinatorial Materials Science
by: Thelen, Felix, et al.
Published: (2024)

LeapFrog: Getting the Jump on Multi-Scale Materials Simulations Using Machine Learning
by: Pinto, Damien, et al.
Published: (2024)

Ultrafast magnetic moment transfer and bandgap renormalization in monolayer FeCl$_2$
by: Song, Yu-Hui, et al.
Published: (2025)

Integrated Experiment and Simulation Co-Design: A Key Infrastructure for Predictive Mesoscale Materials Modeling
by: Joshi, Shailendra P., et al.
Published: (2025)

Efficient prediction of potential energy surface and physical properties with Kolmogorov-Arnold Networks
by: Wang, Rui, et al.
Published: (2024)

Identifying Direct Bandgap Silicon Structures with High-throughput Search and Machine Learning Methods
by: Wang, Rui, et al.
Published: (2024)

When is the Four-phonon Effect in Half-Heusler Materials more Pronounced?
by: Wu, Yu, et al.
Published: (2024)

Material Hardness Descriptor Derived by Symbolic Regression
by: Tantardini, Christian, et al.
Published: (2023)

Machine learning assisted canonical sampling (MLACS)
by: Castellano, Aloïs, et al.
Published: (2024)

Cooperative Suppression Strategy for Dual Thermal Transport Channels in Crystalline Materials
by: Wu, Yu, et al.
Published: (2025)

Advancing Nonadiabatic Molecular Dynamics Simulations for Solids: Achieving Supreme Accuracy and Efficiency with Machine Learning
by: Zhang, Changwei, et al.
Published: (2024)

UniMatSim: A High-Throughput Materials Simulation Automation Framework Based on Universal Machine Learning Potentials
by: Xiang, Yanjin, et al.
Published: (2026)

Physics-Aware POD-Based Learning for Ab initio QEM-Galerkin Simulations of Periodic Nanostructures
by: Veresko, Martin, et al.
Published: (2025)

Multiscale micromagnetic / atomistic modeling of heat assisted magnetic recording
by: Gija, Mohammed, et al.
Published: (2025)

AI-Guided Quantum Material Simulator for Education. Case Example: The Neuromorphic Materials Calculator 2025
by: Barrionuevo, Santiago D., et al.
Published: (2025)

AI-assisted inverse design of sequence-ordered high intrinsic thermal conductivity polymers
by: Huang, Xiang, et al.
Published: (2024)

A Fully Ab-Initio Spin-Lattice Dynamics Framework for Magnetic Materials
by: Zhang, Xianxi, et al.
Published: (2026)

Toward Greater Autonomy in Materials Discovery Agents: Unifying Planning, Physics, and Scientists
by: Zhou, Lianhao, et al.
Published: (2025)

The 2D Materials Roadmap
by: Ren, Wencai, et al.
Published: (2025)

Self-supervised Representations and Node Embedding Graph Neural Networks for Accurate and Multi-scale Analysis of Materials
by: Kong, Jian-Gang, et al.
Published: (2022)

Tutorial: AI-assisted exploration and active design of polymers with high intrinsic thermal conductivity
by: Huang, Xiang, et al.
Published: (2024)

A Finite Element Method for Simulation of Coupled Dynamics of Dislocations and Fracture
by: Gu, Boyang, et al.
Published: (2025)

ProME: An Integrated Computational Platform for Material Properties at Extremes and Its Application in Multicomponent Alloy Design
by: Gao, Xingyu, et al.
Published: (2025)

A Foundational Potential Energy Surface Dataset for Materials
by: Kaplan, Aaron D., et al.
Published: (2025)

Machine-Learned Atomic Cluster Expansion Potentials for Fast and Quantum-Accurate Thermal Simulations of Wurtzite AlN
by: Yang, Guang, et al.
Published: (2023)

Investigating Material Interface Diffusion Phenomena through Graph Neural Networks in Applied Materials
by: Zhao, Zirui, et al.
Published: (2024)

Computational predictions of hydrogen-assisted fatigue crack growth
by: Cui, C., et al.
Published: (2024)

Deep Potentials for Materials Science
by: Wen, Tongqi, et al.
Published: (2022)

Building a Regional Data-Centric Materials Science Ecosystem for Processing-Rich Materials Innovation in the Great Plains
by: Mei, D. -M., et al.
Published: (2026)

Strain-tunable Dirac semimetal phase transition and emergent superconductivity in a borophane
by: Zhong, Chengyong, et al.
Published: (2024)

Linear Scaling Calculation of Atomic Forces and Energies with Machine Learning Local Density Matrix
by: Xin, Zaizhou, et al.
Published: (2025)

Large Language Models for Material Property Predictions: elastic constant tensor prediction and materials design
by: Liu, Siyu, et al.
Published: (2024)

MatterGPT: A Generative Transformer for Multi-Property Inverse Design of Solid-State Materials
by: Chen, Yan, et al.
Published: (2024)

The Northeast Materials Database for Magnetic Materials
by: Itani, Suman, et al.
Published: (2024)

Ultrafast electrically controlled magnetism in charge-order-induced ferroelectric altermagnet
by: Gu, Yuhao, et al.
Published: (2026)

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