2 papers
cond-mat.mtrl-sci2025
Active Î-learning with universal potentials for global structure optimization
Joe Pitfield, Mads-Peter Verner Christiansen, Bjørk Hammer
Universal machine learning interatomic potentials (uMLIPs) have recently been formulated and shown to generalize well. When applied out-of-sample, further data collection for impro…
cond-mat.mtrl-sci2025
RAFFLE: Active learning accelerated interface structure prediction
Ned Thaddeus Taylor, Joe Pitfield, Francis Huw Davies +1
Interfaces between materials play a crucial role in the performance of most devices. However, predicting the structure of a material interface is computationally demanding due to t…