11 citations · 19 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…
Known Unknowns: Out-of-Distribution Property Prediction in Materials and Molecules
Nofit Segal, Aviv Netanyahu, Kevin P. Greenman +2
Discovery of high-performance materials and molecules requires identifying extremes with property values that fall outside the known distribution. Therefore, the ability to extrapo…
Symmetry-Constrained Generation of Diverse Low-Bandgap Molecules with Monte Carlo Tree Search
Akshay Subramanian, James Damewood, Juno Nam +3
Organic optoelectronic materials are a promising avenue for next-generation electronic devices due to their solution processability, mechanical flexibility, and tunable electronic…
Automated patent extraction powers generative modeling in focused chemical spaces
Akshay Subramanian, Kevin P. Greenman, Alexis Gervaix +2
Deep generative models have emerged as an exciting avenue for inverse molecular design, with progress coming from the interplay between training algorithms and molecular representa…
Lattice-Constant and Band-Gap Tuning in Wurtzite and Zincblende BInGaN Alloys
Kevin P. Greenman, Logan Williams, Emmanouil Kioupakis
InGaN light-emitting diodes (LEDs) are more efficient and cost effective than incandescent and fluorescent lighting, but lattice mismatch limits the thickness of InGaN layers that…