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Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

TOOL · arXiv cs.CL English(EN) · 2w

Catalyst-Agent: Autonomous heterogeneous catalyst screening with an LLM Agent

Researchers have developed Catalyst-Agent, an AI system designed to autonomously screen for novel catalysts. This LLM-powered agent utilizes material databases and computational models to suggest structural modifications and calculate adsorption energies. Tested on key reactions like ORR, NRR, and CO2RR, Catalyst-Agent demonstrated a success rate of 33-41% and converged on successful materials within 1-4 trials on average, showcasing the potential of AI agents in accelerating scientific discovery. AI

IMPACT Accelerates scientific discovery by automating complex material screening processes.
RESEARCH · arXiv cs.CL English(EN) · 1mo · [2 sources]

Material Database Agent: A Multimodal Agentic Framework for Scientific Literature Mining

Researchers have developed the Material Database Agent (MDA), a multimodal agentic framework designed to automate the extraction of information from scientific literature for materials science databases. This system processes PDF articles, converting them into structured data by analyzing text, tables, and figures. MDA utilizes multiple sub-agents to compile this information into a unified database, aiming to overcome the manual and time-consuming nature of current data construction methods. AI

IMPACT Automates the creation of scientific databases, potentially accelerating materials science research and discovery.