most citedUncertainty Quantification and Propagation in Atomistic Machine Learning

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physics.chem-ph2026

Agentic AI for Density-Functional Development: Revisiting r2SCAN

Santosh Adhikari, Kelsey A. Parker, Etinosa Osaro +2

We demonstrate physics-constrained agentic development of a meta-generalized gradient approximation (meta-GGA) functional using a large language model (LLM) to assist the search an…

physics.chem-ph2026

MLIPilot: LLM-Driven Auto-Research for Machine-Learned Interatomic Potentials

Etinosa Osaro, Santosh Adhikari, Stamatia Zavitsanou +2

Constructing production-quality machine-learned interatomic potentials (MLIPs) requires balancing accuracy, dynamical stability, and computational throughput under constraints that…