# Isayev Lab at CMU We develop machine learning methods for chemistry and materials science at [Carnegie Mellon University](https://www.cmu.edu/). Our research spans neural network potentials, molecular generation, and AI-driven discovery of molecules and materials. **PI:** [Olexandr Isayev](https://scholar.google.com/citations?user=GnATMRoAAAAJ) ## AIMNet2 Models AIMNet2 is our neural network interatomic potential for fast, accurate molecular simulations. It predicts energies, forces, charges, and Hessians at near-DFT accuracy, orders of magnitude faster. | Model | Description | Elements | |-------|-------------|----------| | [aimnet2-wb97m-d3](https://huggingface.co/isayevlab/aimnet2-wb97m-d3) | General purpose (wB97M-D3) | 14: H,B,C,N,O,F,Si,P,S,Cl,As,Se,Br,I | | [aimnet2-2025](https://huggingface.co/isayevlab/aimnet2-2025) | Improved intermolecular (B97-3c) | 14: H,B,C,N,O,F,Si,P,S,Cl,As,Se,Br,I | | [aimnet2-nse](https://huggingface.co/isayevlab/aimnet2-nse) | Open-shell / radicals (wB97M) | 14: H,B,C,N,O,F,Si,P,S,Cl,As,Se,Br,I | | [aimnet2-pd](https://huggingface.co/isayevlab/aimnet2-pd) | Palladium chemistry (wB97M-D3) | 14: H,B,C,N,O,F,Si,P,S,Cl,Se,Br,Pd,I | All models include 4 ensemble members in safetensors format for uncertainty estimation. ## Quick Start ```bash pip install "aimnet[hf]" ``` ```python from aimnet.calculators import AIMNet2Calculator calc = AIMNet2Calculator("isayevlab/aimnet2-wb97m-d3") results = calc( {"coord": coords, "numbers": atomic_numbers, "charge": 0.0}, forces=True, ) ``` ## Links - [GitHub](https://github.com/isayevlab) | [Lab Website](https://isayevlab.org/) | [AIMNet2 Paper](https://doi.org/10.1039/D4SC08572H) ## Citation ```bibtex @article{anstine2025aimnet2, title={AIMNet2: A Neural Network Potential to Meet your Neutral, Charged, Organic, and Elemental-Organic Needs}, author={Anstine, Dylan and Zubatyuk, Roman and Isayev, Olexandr}, journal={Chemical Science}, year={2025}, publisher={Royal Society of Chemistry}, doi={10.1039/D4SC08572H} } ```