From the 1 of 75 linked papers with an AI index.
3 citations · 6 across the 21 of their papers we have counts for
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Catalyst-Agent: Autonomous heterogeneous catalyst screening with an LLM Agent
Achuth Chandrasekhar, Janghoon Ock, Amir Barati Farimani
The paper presents Catalyst-Agent, an LLM-powered autonomous system that integrates database search, slab construction, MLIP-based adsorption energy calculations, and feedback-driv…
PolyJarvis: An LLM-Orchestrated Agent for Automated All-Atom Molecular Dynamics of Amorphous Homopolymers
Alexander Zhao, Achuth Chandrasekhar, Amir Barati Farimani
All-atom molecular dynamics (MD) simulations can predict polymer properties from molecular structure, yet their execution requires specialized expertise in force field selection, s…
Pepti-Agent: An AI Agent for Peptide Design and Optimization
Houxu Chen, Achuth Chandrasekhar, Amir Barati Farimani
Therapeutic peptides occupy a valuable design space between small molecules and biologics, but their development requires satisfying several competing constraints at once: solubili…
Material Database Agent: A Multimodal Agentic Framework for Scientific Literature Mining
Achuth Chandrasekhar, Omid Barati Farimani, Radheesh Sharma Meda +1
Materials science workflows rely on structured and unstructured data from the vast body of available scientific literature. However, most of the experimental details remain buried…
Polymer-Agent: Large Language Model Agent for Polymer Design
Vani Nigam, Achuth Chandrasekhar, Amir Barati Farimani
On-demand Polymer discovery is essential for various industries, ranging from biomedical to reinforcement materials. Experiments with polymers have a long trial-and-error process,…
Text to Band Gap: Pre-trained Language Models as Encoders for Semiconductor Band Gap Prediction
Ying-Ting Yeh, Janghoon Ock, Achuth Chandrasekhar +2
We investigate transformer-based language models, including RoBERTa, T5, Llama-3, and MatSciBERT, for predicting the band gaps of semiconductor materials directly from textual desc…