<ul data-eligibleForWebStory="true"><li>Chemical process optimization is essential for efficiency and economic performance.</li><li>A multi-agent framework using large language models (LLMs) autonomously infers operating constraints from minimal process descriptions.</li><li>The framework, named AutoGen, demonstrated competitive performance with conventional optimization methods while achieving better computational efficiency.</li><li>The approach shows potential for scenarios where operational constraints are poorly defined, particularly for emerging processes and retrofit applications.</li></ul>

LLM-guided Chemical Process Optimization with a Multi-Agent Approach

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