38 citations · 45 across the 5 of their papers we have counts for
5 papers
Preference Learning from Physics-Based Feedback: Tuning Language Models to Design BCC/B2 Superalloys
Satanu Ghosh, Collin Holgate, Neal R. Brodnik +4
We apply preference learning to the task of language model-guided design of novel structural alloys. In contrast to prior work that focuses on generating stable inorganic crystals,…
Toward Reliable Ad-hoc Scientific Information Extraction: A Case Study on Two Materials Datasets
Satanu Ghosh, Neal R. Brodnik, Carolina Frey +4
We explore the ability of GPT-4 to perform ad-hoc schema based information extraction from scientific literature. We assess specifically whether it can, with a basic prompting appr…
Q-RBSA: High-Resolution 3D EBSD Map Generation Using An Efficient Quaternion Transformer Network
Devendra K. Jangid, Neal R. Brodnik, McLean P. Echlin +3
Gathering 3D material microstructural information is time-consuming, expensive, and energy-intensive. Acquisition of 3D data has been accelerated by developments in serial sectioni…
Fracture Diodes: Directional asymmetry of fracture toughness
N. R. Brodnik, S. Brach, C. M. Long +4
Toughness describes the ability of a material to resist fracture or crack propagation. It is demonstrated here that fracture toughness of a material can be asymmetric, i.e., the re…
3DMaterialGAN: Learning 3D Shape Representation from Latent Space for Materials Science Applications
Devendra K. Jangid, Neal R. Brodnik, Amil Khan +4
In the field of computer vision, unsupervised learning for 2D object generation has advanced rapidly in the past few years. However, 3D object generation has not garnered the same…