371 citations · 601 across the 20 of their papers we have counts for
4 papers · 1 filter
Can Coding Agents Reproduce Findings in Computational Materials Science?
Ziyang Huang, Yi Cao, Ali K. Shargh +15
Large language models are increasingly deployed as autonomous coding agents and have achieved remarkably strong performance on software engineering benchmarks. However, it is uncle…
Uncertainty-aware phase fraction prediction and active-learning-guided out-of-domain discovery of refractory multi-principal element alloys
A. K. Shargh, C. D. Stiles, J. A. El-Awady
Refractory multi-principal element alloys (RMPEAs) represent a novel class of alloys characterized by an extensive compositional design space and the potential for exceptional mech…
From Papers to Property Tables: A Priority-Based LLM Workflow for Materials Data Extraction
Koushik Rameshbabu, Jing Luo, Ali Shargh +2
Scientific data are widely dispersed across research articles and are often reported inconsistently across text, tables, and figures, making manual data extraction and aggregation…
AIMD-L: An automated laboratory for high-throughput characterization of structural materials for extreme environments
Todd C. Hufnagel, Pranav Addepalli, Anuruddha Bhattacharjee +14
Rapid developments in artificial intelligence and machine learning as applied to materials science are creating an urgent need for experimental data, which can be provided by high-…