3 papers
cond-mat.mtrl-sci2026
Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design
Aravindan Kamatchi Sundaram, Mohit Chakraborty, Sai Mani Kumar Devathi +2
The design of sustainable materials requires access to materials performance and sustainability data from literature corpus in an organized, structured and automated manner. Natura…
cond-mat.mtrl-sci2025
Physically Interpretable Interatomic Potentials via Symbolic Regression and Reinforcement Learning
Bilvin Varughese, Troy D. Loeffler, Suvo Banik +9
The development of next-generation molecular simulation models requires moving beyond pre-defined functional forms toward machine learning (ML) techniques that directly capture mul…
cs.LG2025
Enhancing Experimental Efficiency in Materials Design: A Comparative Study of Taguchi and Machine Learning Methods
Shyam Prabhu, P Akshay Kumar, Antov Selwinston +3
Materials design problems often require optimizing multiple variables, rendering full factorial exploration impractical. Design of experiment (DOE) methods, such as Taguchi techniq…