Large Language Model Assisted Discovery of Optimal Dopants for Enhanced Thermoelectric Performance in CoSb Based Skutterudites
This paper presents a data-driven framework that leverages large language models to extract compositional insights from scientific literature, enabling the accurate prediction and discovery of novel high-performance filler dopants for CoSb-based skutterudites, which are subsequently validated through quantum simulations.