214 citations · 357 across the 5 of their papers we have counts for
5 papers
14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon
Kevin Maik Jablonka, Qianxiang Ai, Alexander Al-Feghali +50
Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To…
FAIR for AI: An interdisciplinary and international community building perspective
E. A. Huerta, Ben Blaiszik, L. Catherine Brinson +21
A foundational set of findable, accessible, interoperable, and reusable (FAIR) principles were proposed in 2016 as prerequisites for proper data management and stewardship, with th…
How to See Hidden Patterns in Metamaterials with Interpretable Machine Learning
Zhi Chen, Alexander Ogren, Chiara Daraio +2
Machine learning models can assist with metamaterials design by approximating computationally expensive simulators or solving inverse design problems. However, past work has usuall…
Rethinking Interphase Representations for Modeling Viscoelastic Properties for Polymer Nanocomposites
Xiaolin Li, Min Zhang, Yixing Wang +4
Numerical modeling of viscoelastic properties is critical to developing the structure-property relationship of polymer nanocomposites. While it is recognized that the altered polym…
Influences of Granular Constraints and Surface Effects on the Heterogeneity of Elastic, Superelastic, and Plastic Responses of Polycrystalline Shape Memory Alloys
Harshad M. Paranjape, Partha P. Paul, Hemant Sharma +5
Deformation heterogeneities within microstructures of polycrystalline shape memory alloys (SMAs) during superelastic stressing are studied using both experiments and simulations. I…