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cond-mat.mtrl-sci2026
Democratizing Atomistic Simulation Workflows for the AI Era with the Quantum Accelerator
Andrew S. Rosen, Naisargi Goyal, Brad Ayers +25
We present the Quantum Accelerator (QuAcc), an open-source workflow library for atomistic simulations with an emphasis on quantum-mechanical calculations. QuAcc provides predefined…
cond-mat.mtrl-sci2024★ 3 cited
Machine Learning Materials Properties with Accurate Predictions, Uncertainty Estimates, Domain Guidance, and Persistent Online Accessibility
Ryan Jacobs, Lane E. Schultz, Aristana Scourtas +7
One compelling vision of the future of materials discovery and design involves the use of machine learning (ML) models to predict materials properties and then rapidly find materia…