59 citations · 89 across the 4 of their papers we have counts for
5 papers
Reinforcement Learning on the Discrete Composition Channel of a Crystal Generator: Validated Gains and Reward Hacking
Pawan Prakash, Philipp Höllmer, Addis Fuhr +4
Inverse materials design is a long-standing goal of computational materials discovery. Generative models for crystalline materials are typically trained to match the distribution o…
Symmetry-electronic fingerprints reveal competing magnetic phases in two-dimensional materials
Addis Fuhr, Zachary R. Fox, David Parker +1
Two-dimensional magnets offer compelling platforms for spintronics and quantum technologies, yet predicting their magnetic ground states, moments, and anisotropy remains challengin…
Room-Temperature High-Purity Single Photon Emission from Carbon-Doped Boron Nitride Thin Films
Arka Chatterjee, Abhijit Biswas, Addis S. Fuhr +5
Hexagonal boron nitride (hBN) has emerged as an excellent host material for generating room temperature single photons exhibiting high brightness and spin-photon entanglement. Howe…
JARVIS-Leaderboard: A Large Scale Benchmark of Materials Design Methods
Kamal Choudhary, Daniel Wines, Kangming Li +35
Lack of rigorous reproducibility and validation are major hurdles for scientific development across many fields. Materials science in particular encompasses a variety of experiment…
Bridging Theory with Experiment: Digital Twins and Deep Learning Segmentation of Defects in Monolayer MX2 Phases
Addis S. Fuhr, Panchapakesan Ganesh, Rama K. Vasudevan +1
Developing methods to understand and control defect formation in nanomaterials offers a promising route for materials discovery. Monolayer MX2 phases represent a particularly compe…