MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
MatClaw: an open materials-science agent that turns natural-language tasks into reproducible simulation workflows.
The papers and code related to deep generative models for material discovery.
Awesome list about AI4Polymer
MatAgent: A generative framework for interpretable and targeted inorganic materials design using diffusion-based generation, property prediction, and LLM-driven reasoning.
A comprehensive database collection for AI4Polymer
A curated list of AI agents and related resources for materials science research and applications
Rapid materials discovery in the terminal
Machine Learning For Characterization and Processing Lecture
An atomic structure editing agent that translates intuitive natural language prompts into crystal structure modifications.
AI4C-ML is a machine learning intergration for catalyst discovery, enabling atom generation, data-driven prediction of catalytic performance through descriptor engineering, model optimization, and scalable screening workflows.
A lightweight agent-callable workflow prototype for AI4Materials simulation analysis.
Materials Genomics Lecture
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