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ChatMOF: An Autonomous AI System for Predicting and Generating Metal-Organic Frameworks
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ChatMOF is an autonomous Artificial Intelligence (AI) system that is built to predict and generate metal-organic frameworks (MOFs). By leveraging a large-scale language model (GPT-4 and GPT-3.5-turbo), ChatMOF extracts key details from textual inputs and delivers appropriate responses, thus eliminating the necessity for rigid structured queries. The system is comprised of three core components (i.e. an agent, a toolkit, and an evaluator) and it forms a robust pipeline that manages a variety of tasks, including data retrieval, property prediction, and structure generations. The study further explores the merits and constraints of using large language models (LLMs) AI system in material sciences using and showcases its transformative potential for future advancements.
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Toward Greater Autonomy in Materials Discovery Agents: Unifying Planning, Physics, and Scientists
MAPPS combines LLM workflow planning, code generation, and human intuition with machine-learned force fields to discover crystal structures, reporting high stability and novelty rates on MP-20 and Matbench.
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