npj Computational Materials

High-throughput study of electrical conductivity in ordered metals

2026-10-20

Thalis H. B. da Silva, Hai-Chen Wang, Tiago F. T. Cerqueira, Simone Di Cataldo, Silvana Botti, Miguel A. L. Marques

Surprisingly high redundancy in electronic structure data across materials explained by low intrinsic dimensionality

2026-10-19

Sazzad Hossain, Ponkrshnan Thiagarajan, Shashank Pathrudkar, Stephanie Taylor, Abhijeet Sadashiv Gangan, Amartya S. Banerjee, Susanta Ghosh

Tracking the lithiation state of Li x Si from machine-learned XPS binding energies

2026-10-17

Michael Alejandro Hernandez Bertran, Davide Tisi, Federico Grasselli, Michele Ceriotti, Elisa Molinari, Deborah Prezzi

Synthesizability, hardness, and stacking order in multicomponent transition metal carbides from machine-learned potentials

2026-10-17

Xin Liu, Anirudh Raju Natarajan

Response-function-conditioned inverse design enables disorder as a design dimension in porous materials

2026-10-16

Wei Zhao, Ran Chen, Jiaxiu Zhang, Liangliang Nan, Song Wang, Honghua Chen, Hanyang Yu, Songcan Chen, Mingqiang Wei

Inverse materials design via joint generation of crystal structures and local electronic descriptors

2026-10-15

Ibuki Okuda, Izumi Takahara, Teruyasu Mizoguchi

Quantifying electronic insulation of solid-electrolyte interphases through electrolyte decomposition kinetics

2026-10-14

Yuan Fang, Zhenyu Zhu, Siqi Shi, Yu Gu, Sai Duan, Xin Xu

Structural optimization in TensErLEED using a parameter tree and R -factor gradients

2026-10-14

Alexandra M. Imre, Paul Haidegger, Florian Kraushofer, Ralf Wanzenböck, Tobias Hable, Sarah Tobisch, Marie Kienzer, Florian Buchner, Jesús Carrete, Georg K. H. Madsen, Michael Schmid, Ulrike Diebold, Michele Riva

Microkinetic modeling of acidic corrosion from first principles and machine-learning molecular dynamics

2026-03-30

Ergen Bao, Wenjing Xu, Hui Ma, Yueqi Si, Ijaz Shahid, Yutong Huo, Peitao Liu, Yan Sun, Xing-Qiu Chen

npj Computational Materials, Published online: 30 March 2026; doi:10.1038/s41524-026-02047-4 Microkinetic modeling of acidic corrosion from first principles and machine-learning molecular dynamics

From ultrathin to bulk: decoding thickness-unrestricted ferroelectricity in Y:HfO₂ via first-principles

2026-03-30

Jin Huang, Jiangheng Yang, Shijie Jia, Junhui Wang, Fei Yan, Zhipeng Wang, Hua Chen, Jiajia Liao, Min Liao, Yichun Zhou

npj Computational Materials, Published online: 30 March 2026; doi:10.1038/s41524-026-02046-5 From ultrathin to bulk: decoding thickness-unrestricted ferroelectricity in Y:HfO 2 via first-principles

Prediction of ambient-pressure high-temperature superconductivity in electronically modified transition-metal hydrides

2026-03-28

Haowei Xu, Olivia Schneble, Rafael Jaramillo, Marek Polański, Ju Li

npj Computational Materials, Published online: 28 March 2026; doi:10.1038/s41524-026-02040-x Prediction of ambient-pressure high-temperature superconductivity in electronically modified transition-metal hydrides

A general purposed machine learning interatomic potential for Mg-Al-Si-O system suitable for Earth materials at high pressure and temperature conditions

2026-03-27

Xin Zhong, Yifan Li, Timm John

npj Computational Materials, Published online: 27 March 2026; doi:10.1038/s41524-026-02056-3 A general purposed machine learning interatomic potential for Mg-Al-Si-O system suitable for Earth materials at high pressure and temperature conditions