All Articles

Chemical similarity description of liquid kinetics across composition space in magnesium alloys

Smart design tungsten-weighted refractory high entropy alloys (WW-RHEAs) under dynamic loading

Explainable deep learning elucidates orbital–spin synergy in multi-field-responsive Pt-BiFeO₃ for efficient photocatalytic H₂ production

Data-efficient adaptation of DPA-4 force fields to DFT+U energetics: a case study in NiO

Computational screening of reconfigurable van der Waals ferroelectric semiconductor heterojunctions for all-in-one optoelectronic devices

A knowledge-distilled artificial neural network constitutive model for finite element simulation of hot-deformed β-C titanium alloy

Integrating physical metallurgy principles and machine learning for predicting continuous cooling phase transformations in steel

Reaction-anchored generative informatics for million-scale CO₂ catalyst screening via multi-adsorbate constraints

Multi-activity derivative automated labeling and margin-sampling active learning for efficient determination of phase boundaries

Prediction of electron localization functions from superposed atomic densities for accelerated superhydride discovery

Physics-informed machine learning framework integrating solid solution strengthening theory for accelerated hardness prediction in high-entropy alloys

Commentary on ten selected 2025 papers in AI for Materials Science

Data-driven design of high-abundance rare earth permanent magnets for low-carbon and resource-efficient production

A federated learning–driven data fusion strategy for the hardenability prediction of gear steel

Correction: Machine learning and shap-based prediction of multifactor thermal-oxidative aging behavior in glass fiber reinforced polyamide6

LLM-driven materials knowledge extraction: multimodal parsing, ontology, and agentic systems

Machine-learning-enabled composition–process co-design of heat-resistant cast aluminum alloys with superior elevated-temperature strength

PhyMLP: an automated strategy for machine-learning potential construction via data fusion and adaptive point-sampling