AIMNetCentral: Fast Machine-Learned Potentials for Molecular Dynamics
Introducing AIMNetCentral, our streamlined Python package for deploying AIMNet2 neural network potentials in molecular dynamics simulations with ASE and PySisyphus integration.
News
Updates from our research group including new publications, software releases, and lab news.
AQuaRef: Machine Learning Accelerated Quantum Refinement of Protein Structures
Our collaborative work on AQuaRef is now published in Nature Communications. This AI-enabled quantum refinement method leverages AIMNet2 to achieve unprecedented accuracy in protein structure determination from cryo-EM and X-ray crystallography data.
AIMNet2: A Neural Network Potential for Neutral, Charged, and Element-Organic Molecules
Our AIMNet2 paper is now published in Chemical Science, introducing a transferable neural network potential trained on 20 million DFT calculations that covers 14 chemical elements.
Welcome to the Isayev Lab News
Introducing our new lab news section where we share research updates, publication announcements, software releases, and developments from our group at Carnegie Mellon University.
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