3 papers
cond-mat.mtrl-sci2026
Large language model-enabled automated data extraction for concrete materials informatics
Zhanzhao Li, Kengran Yang, Qiyao He +1
The promise of data-driven materials discovery remains constrained by the scarcity of large, high-quality, and accessible experimental datasets. Here, we introduce a generalizable…
cond-mat.mtrl-sci2026
Reactivity-Informed Machine Learning for Performance Prediction and Design Space Exploration of Alkali-Activated Slag
Qiyao He, Zhanzhao Li, Kai Gong
Establishing quantitative relationships among mix design, raw material properties, curing conditions, and performance remains a long-standing challenge in cementitious materials, 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…