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cond-mat.mtrl-sci2026

Hierarchical high-throughput screening of alkaline-stable lithium-ion conductors combining machine learning and first-principles calculations

Zhuohan Li, KyuJung Jun, Bowen Deng +1

Solid-state batteries require lithium-ion conductors that combine high ionic conductivity with stability under harsh electrochemical and chemical conditions. Here, we investigate t…

cond-mat.mtrl-sci2026

Mechanisms of alkali ionic transport in amorphous oxyhalides solid state conductors

Luca Binci, KyuJung Jun, Bowen Deng +1

Amorphous oxyhalides have attracted significant attention due to their relatively high ionic conductivity (1 mS cm), excellent chemical stability, mechanical softness, an…

cond-mat.mtrl-sci2025

Modeling phase transformations in Mn-rich disordered rocksalt cathodes with machine learning interatomic potentials

Peichen Zhong, Bowen Deng, Shashwat Anand +2

Mn-rich disordered rocksalt (DRX) cathode materials exhibit a phase transformation from a disordered to a partially disordered spinel-like structure (-phase) during electrochem…

cond-mat.mtrl-sci2025

Crystal structure prediction with host-guided inpainting generation and foundation potentials

Peichen Zhong, Xinzhe Dai, Bowen Deng +2

Unconditional crystal structure generation with diffusion models faces challenges in identifying symmetric crystals as the unit cell size increases. We present the Crystal Host-Gui…

cond-mat.mtrl-sci2025

Cross-functional transferability in universal machine learning interatomic potentials

Xu Huang, Bowen Deng, Peichen Zhong +3

The rapid development of universal machine learning interatomic potentials (uMLIPs) has demonstrated the possibility for generalizable learning of the universal potential energy su…

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…