Research Digest — 2026-07-25¶
Grain Boundaries & Dendrite Growth in Solid Electrolytes¶
1. Li-P-S Electrolyte Materials as a Benchmark for Machine Learning Interatomic Potentials¶
Source: Journal of Chemical Theory and Computation (acs.jctc.5c02006) · 📅 2026-06-15 · ↗ Open paper
Fragapane et al. establish Li-P-S (LPS) glassy electrolytes as a benchmark system for evaluating MLIP performance. They systematically compare different MLIP architectures on sulfide electrolytes, assessing accuracy in predicting structural, dynamical, and transport properties against AIMD reference data.
Relevance to DENG.Group
Highly relevant to Yanhao Deng's work on ML potentials for sulfide-type electrolytes. The benchmark dataset and evaluation framework could serve as a validation standard for the group's MLIP models. Li-P-S is a well-studied system that connects to Cheng Peng's grain boundary simulations in sulfide electrolytes.