collaborators

5 papers

cond-mat.mtrl-sci2026

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…

cs.AI2026

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…

cond-mat.supr-con2025

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…

cond-mat.mtrl-sci2025

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…

cond-mat.supr-con2025

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…