8 citations · 8 across the 3 of their papers we have counts for
7 papers
Thermal Transport in SiC with Intrinsic Defects and Mg Transmutation Products
Chen Shen, Yang Su, Maciej P. Polak +5
Silicon carbide is a leading candidate material for advanced nuclear energy systems, but irradiation-induced defects and transmutation products can severely degrade its thermal con…
Improving Combined Detection and Classification of TEM Defects via Mask-Conditioned Latent Diffusion Augmentation
Ni Li, Nuohao Liu, Ryan Jacobs +5
Analyzing microstructural defects in transmission electron microscopy (TEM) images, particularly in irradiated metal alloys, is often limited by the availability of high-quality, l…
Regression with Large Language Models for Materials and Molecular Property Prediction
Ryan Jacobs, Maciej P. Polak, Lane E. Schultz +3
We demonstrate the ability of large language models (LLMs) to perform material and molecular property regression tasks, a significant deviation from the conventional LLM use case.…
Leveraging Vision Capabilities of Multimodal LLMs for Automated Data Extraction from Plots
Maciej P. Polak, Dane Morgan
Automated data extraction from research texts has been steadily improving, with the emergence of large language models (LLMs) accelerating progress even further. Extracting data fr…
Mechanical Properties of the Meninges: Large Language Model Assisted Systematic Review of over 25,000 Studies
Brandon P. Chelstrom, Maciej P. Polak, Dane Morgan +1
Accurate constitutive models and corresponding mechanical property values for the meninges are important for predicting mechanical damage to brain tissue due to traumatic brain inj…
Beyond designer's knowledge: Generating materials design hypotheses via large language models
Quanliang Liu, Maciej P. Polak, So Yeon Kim +5
Materials design often relies on human-generated hypotheses, a process inherently limited by cognitive constraints such as knowledge gaps and limited ability to integrate and extra…