All Articles

Catalyst-state-aware AI agents for trajectory design in reconstructing 2D electrocatalysts

When code does not run: reproducibility challenges in materials machine learning benchmarks

Generative AI for atomistic nanomaterial reconstruction: from static structures to conditioned ensembles

Computational materials agents: from task demonstrations to executable scientific workflows

AI agents accelerate catalyst discovery for ultrafast water purification

Computational Nutrition 2.0: an algorithmic frontier for AI agents

AI agents for MOFs and COFs discovery

Development of AI-eChemist Laboratory

Battery material databases in the age of AI agents

Decoding MOF structures from powder diffraction with generative AI

MatterChat: how a structure-aware multimodal LLM bridges atomic structures and scientific reasoning in materials science

From execution loop to reasoning loop in autonomous materials research

From unstructured to structured: opportunities, risks and engineering practices for LLM-based data extraction in chemistry and materials

A closed-loop universal catalyst design workflow ready for AI agents

An energy-efficient scheduling approach for wind-solar-hydrogen systems based on distributed reinforcement learning

AI agents as co-designers of catalysts: a paradigm shift for designing Cu-based single-atom alloy catalysts in CO₂ electroreduction

DigMethpy: an AI-empowered digital catalysis platform for methane pyrolysis molten catalyst design

On-premise AI agents: a future foundation for education, academia, and industry