5 papers
Human and LLM Collaboration for Accelerated Materials Synthesis and Discovery
Gregory Bassen, Wyatt Bunstine, Sarah Okandey +7
Although Large Language Models (LLM) and Artificial Intelligence (AI) tools have enabled a rapid increase in the generation rate of predicted materials, the rate of new materials d…
Coupling Language Models with Physics-based Simulation for Synthesis of Inorganic Materials
Edward W. Staley, Tom Arbaugh, Michael Pekala +6
Modern generative machine learning (ML) models can propose novel inorganic crystalline materials with targeted properties; however, synthesis planning of these materials remains di…
Can Coding Agents Reproduce Findings in Computational Materials Science?
Ziyang Huang, Yi Cao, Ali K. Shargh +15
Large language models are increasingly deployed as autonomous coding agents and have achieved remarkably strong performance on software engineering benchmarks. However, it is uncle…
Real-space orbital tiling approach for the design of novel superconductors
Gregory Bassen, Wyatt Bunstine, Rebecca Han +3
Despite substantial advances in the field, we still lack a predictive framework capable of guiding the discovery of new families of superconductors. While momentum-space approaches…
Hydroflux-Controlled Growth of Magnetic K-Cu-Te-O(H) Phases
Allana G. Iwanicki, Brandon Wilfong, Eli Zoghlin +3
Innovative synthetic approaches can yield new phases containing novel structural and magnetic motifs. In this work, we show the synthesis and magnetic characterization of three new…