3 papers
cond-mat.mtrl-sci2026
Predicting Novel Stable Materials for Experimental Synthesis
Yuqi An, Sihong Zhu, Joseph Montoya +2
Machine-learning-accelerated materials discovery has yielded large numbers of computationally stable compounds, yet many remain experimentally unrealized, underscoring a persistent…
physics.chem-ph2023
GMP-Featurizer: A parallelized Python package for efficiently computing the Gaussian Multipole features of atomic systems
Xiangyun Lei, Joseph Montoya
GMP-Featurizer is a lightweight, accurate, efficient, and scalable software package for calculating the Gaussian Multipole (GMP) features \cite{GMP} for a variety of atomic systems…
cond-mat.mtrl-sci2020
Machine learning with persistent homology and chemical word embeddings improves prediction accuracy and interpretability in metal-organic frameworks
Aditi S. Krishnapriyan, Joseph Montoya, Maciej Haranczyk +2
Machine learning has emerged as a powerful approach in materials discovery. Its major challenge is selecting features that create interpretable representations of materials, useful…