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20242026
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cond-mat.mtrl-sci2026

Vibrational, structural, and chemical fingerprints of ion diffusion in crystalline solids

Gavin Winter, Juno Nam, Rafael Gómez-Bombarelli

Predicting mobile-ion self-diffusivity from molecular dynamics (MD) simulations is essential for identifying promising solid-state electrolytes, but directly simulating ion d…

cond-mat.mtrl-sci2026

From Knowledge to Action: Outcomes of the 2025 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

Aritra Roy, Kevin Shen, Andrew MacBride +350

Large language models (LLMs) are rapidly changing how researchers in materials science and chemistry discover, organize, and act on scientific knowledge. This paper analyzes a broa…

cond-mat.mtrl-sci2026

Universal Framework for Decomposing Ionic Transport into Interpretable Mechanisms

KyuJung Jun, Pablo A. Leon, Jurğis Ruža +2

Understanding mechanisms of ion transport in bulk materials is central to designing next-generation ion conductors for energy storage devices, yet studies employing all-atom molecu…

cond-mat.mtrl-sci2025

Flow Matching for Accelerated Simulation of Atomic Transport in Crystalline Materials

Juno Nam, Sulin Liu, Gavin Winter +3

Atomic transport underpins the performance of materials in technologies such as energy storage and electronics, yet its simulation remains computationally demanding. In particular,…

cond-mat.mtrl-sci2024

Interpolation and differentiation of alchemical degrees of freedom in machine learning interatomic potentials

Juno Nam, Jiayu Peng, Rafael Gómez-Bombarelli

Machine learning interatomic potentials (MLIPs) have become a workhorse of modern atomistic simulations, and recently published universal MLIPs, pre-trained on large datasets, have…