Stars
Agentic AI for Science (AAI4Science) Hackathon 2025
AtomBench: A Benchmark for Generative Atomic Structure Models using GPT, Diffusion, and Flow Architectures https://arxiv.org/abs/2510.16165
SlaKoNet: A Unified Slater-Koster Tight-Binding Framework Using Neural Network Infrastructure for the Periodic Table
Evaluation of universal machine learning force-fields https://doi.org/10.1021/acsmaterialslett.5c00093
https://doi.org/10.1016/j.jcat.2025.116171
https://atomgptlab.github.io/jarvis_leaderboard/
A Google-Colab Notebook Collection for Materials Design: https://jarvis.nist.gov/
JARVIS-Tools: an open-source software package for data-driven atomistic materials design. Publications: https://scholar.google.com/citations?user=3w6ej94AAAAJ
Generative Pretrained Transformer Models for Materials Design https://www.youtube.com/@dr_k_choudhary
ChatGPT Material Explorer 1.0 Example Prompts
BenchQC: A Benchmarking Toolkit for Quantum Computation
Evaluation of universal machine learning force-fields https://doi.org/10.1021/acsmaterialslett.5c00093
SLMat: ServerLess Materials Design Toolkit, Preprint: https://doi.org/10.26434/chemrxiv-2024-fqq27
Fine-tuning & Reinforcement Learning for LLMs. 🦥 Train OpenAI gpt-oss, DeepSeek-R1, Qwen3, Gemma 3, TTS 2x faster with 70% less VRAM.
Repository for links to software packages and databases used in deep-learning applications for materials science
This repository is no longer maintained. For the latest updates and continued development, please visit: https://github.com/atomgptlab/jarvis-tools-notebooks
TB3Py: Two- and three-body tight-binding calculations for materials
Project to setup and analyze interface calculations using density functional theory.