Accurate prediction of materials phase diagrams from first principles remains a central challenge in computational materials science. Machine-learning interatomic potentials can provide near-DFT ...
Active learning encompasses a suite of iterative sampling methodologies that seek to maximise predictive performance while minimising the burden of manual annotation. By identifying and labelling only ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results