8 citations · 8 across the 6 of their papers we have counts for
6 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…
A Crystallographic Metric for Continuous Quantification of Unit Cell Deformation
Shannon Bernier, Gregory Bassen, Matthew Brem +3
Describing the deviation of a real structure from a hypothetical higher-symmetry ideal can be a powerful tool to understand and interpret phase transitions. Here we introduce a sim…
The superconducting diode effect in Josephson junctions fabricated from structurally chiral MoAlC
Peter T. Orban, Gregory Bassen, Evan N. Crites +3
The superconducting diode effect occurs in superconducting materials in which both spin and inversion symmetry are broken. The recently observed chirality-induced spin selectivity…
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…
Closed-loop machine learning for discovery of novel superconductors
Elizabeth A. Pogue, Alexander New, Kyle McElroy +15
The discovery of novel materials drives industrial innovation, although the pace of discovery tends to be slow due to the infrequency of "Eureka!" moments. These moments are typica…