Targeting high symmetry in structure predictions by biasing the potential energy surface
Ground-state structures found in nature are, in many cases, of high symmetry. But structure
prediction methods typically render only a small fraction of high-symmetry structures …
prediction methods typically render only a small fraction of high-symmetry structures …
Feature engineering descriptors, transforms, and machine learning for grain boundaries and variable-sized atom clusters
Obtaining microscopic structure-property relationships for grain boundaries is challenging
due to their complex atomic structures. Recent efforts use machine learning to derive these …
due to their complex atomic structures. Recent efforts use machine learning to derive these …
Efficient selection of linearly independent atomic features for accurate machine learning potentials
Machine learning potentials are promising in atomistic simulations due to their comparable
accuracy to first-principles theory but much lower computational cost. However, the …
accuracy to first-principles theory but much lower computational cost. However, the …
Exploring exohedral functionalization of fullerene with automation and Neural Network Potential
M Liu, Y Han, Y Cheng, X Zhao, H Zheng - Carbon, 2023 - Elsevier
Exohedral functionalized fullerenes have shown superior physicochemical properties over
pristine carbon cages. The functional groups could significantly improve solubility, electron …
pristine carbon cages. The functional groups could significantly improve solubility, electron …
Describe, Transform, Machine Learning: Feature Engineering for Grain Boundaries and Other Variable-Sized Atom Clusters
Obtaining microscopic structure-property relationships for grain boundaries are challenging
because of the complex atomic structures that underlie their behavior. This has led to recent …
because of the complex atomic structures that underlie their behavior. This has led to recent …
[HTML][HTML] Computational materials discovery
J Roberts, E Zurek - The Journal of Chemical Physics, 2022 - pubs.aip.org
Tremendous advances in first-principles program packages, spectacular speed-ups in
computer hardware coupled with significant algorithmic developments in crystal structure …
computer hardware coupled with significant algorithmic developments in crystal structure …