3 papers
cond-mat.mtrl-sci2026
Accelerated Discovery of Materials with Extreme Work Functions through Uncertainty-Aware Multi-Fidelity Screening
Jun Meng, Ryan Jacobs, Rehan Kapadia +1
Work function plays a pivotal role in technologies ranging from energy conversion and electronics to catalysis. In this work, we integrated machine learning (ML) with multi-fidelit…
cond-mat.mtrl-sci2025
Understanding and Design of Interstitial Oxygen Conductors
Jun Meng
Highly efficient oxygen active materials that react with, absorb, and transport oxygen is essential for fuel cells, electrolyzers and related applications. While vacancy mediated o…
cond-mat.mtrl-sci2025
A practical guide to machine learning interatomic potentials -- Status and future
Ryan Jacobs, Dane Morgan, Siamak Attarian +27
The rapid development and large body of literature on machine learning interatomic potentials (MLIPs) can make it difficult to know how to proceed for researchers who are not exper…