3 papers
cond-mat.mtrl-sci2026
Building informative materials datasets beyond targeted objectives
Rafael Espinosa Castañeda, Ashley Dale, Hongchen Wang +6
Materials science data collection can be expensive, making the reuse and long-term utility of datasets critical important for future discovery campaigns. In practice, researchers p…
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…
cs.LG2025
Training-Free Active Learning Framework in Materials Science with Large Language Models
Hongchen Wang, Rafael Espinosa Castañeda, Jay R. Werber +3
Active learning (AL) accelerates scientific discovery by prioritizing the most informative experiments, but traditional machine learning (ML) models used in AL suffer from cold-sta…