13 citations · 20 across the 5 of their papers we have counts for
5 papers
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…
A quantized anomalous Hall effect above 4.2 K in stacked topological insulator/magnet bilayers
Rakshit Jain, Matthew Roddy, Vishakha Gupta +9
Quantized anomalous Hall effects (QAHEs) occur in remarkable electronic states which possess not only quantized Hall signals but in some cases regions of dissipationless electron t…
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Yoel Zimmermann, Adib Bazgir, Zartashia Afzal +141
Here, we present the outcomes from the second Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry, which engaged participants across global hyb…
Sampling Latent Material-Property Information From LLM-Derived Embedding Representations
Luke P. J. Gilligan, Matteo Cobelli, Hasan M. Sayeed +2
Vector embeddings derived from large language models (LLMs) show promise in capturing latent information from the literature. Interestingly, these can be integrated into material e…
Data-Driven Materials Discovery and Synthesis using Machine Learning Methods
Sterling G. Baird, Marianne Liu, Hasan M. Sayeed +1
Experimentally [1-38] and computationally [39-50] validated machine learning (ML) articles are sorted based on the size of the training data: 1-100, 101-10000, and 10000+ in a comp…