Accelerating battery materials discovery with an agentic AI for automated XPS analysis integrating physical constraints and chemometrics
Zhenzhen Yang, Gabriel M. Veith, Seoung‐Bum Son et al.
2026 · Energy and AI
The chemical heterogeneity of interfaces, such as the solid-electrolyte interphase (SEI), is a critical factor governing battery performance and degradation, yet its characterization remains a major bottleneck for materials discovery. While X-ray Photoelectron Spectroscopy (XPS) is essential for probing surface chemistry, conventional manual analysis is slow, subjective, and severely limits the pace of research by contributing to a reproducibility crisis. To overcome this barrier, we introduce a novel, open-source agentic AI framework that transforms XPS analysis from a laborious task into an…
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