一个基于LLM的智能代理及其在使兰酸盐化工艺更绿色的应用
Qinglin Wang1,2, Yu Wang1,2, Xingchu Gong1,2,3
1Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Pharmaceuticals (Basel, Switzerland)
|February 27, 2026
概括
与微流体技术集成的大型语言模型 (LLM) 创建了SapoMind,这是一种用于可持续的兰诺林酒精生产的智能代理. 这种绿色化学方法大大减少了废物和能源消耗.
科学领域:
- 绿色化学 绿色化学
- 化学工程是化学工程的重要组成部分.
- 人工智能的人工智能
背景情况:
- 传统的批量肥化用于兰诺林酒精是能源密集型的,并产生大量的废物.
- 目前的方法与绿色化学原则相冲突,原因是效率低下和对环境的影响.
研究的目的:
- 开发一种有效和可持续的化工艺,用于兰诺林酒精.
- 通过将大型语言模型 (LLM) 与微流体技术集成来解决批处理的局限性.
主要方法:
- 一个基于LLM的智能代理SapoMind (版本1.0) 是使用LLM和连续流微反应器开发的.
- SapoMind 启用了自动参数推,实验设计和执行以优化流程.
- 监督的微调提高了系统在优化肥的性能.
主要成果:
- 在70°C和9分钟的停留时间达到最佳的连续流动肥化,符合欧洲药典标准.
- 与批量方法相比,优化过程减少了53%的碳排放量和37%的固体废物.
- 绿色评分从82升至93分,这表明可持续性有所提高.
结论:
- 通过LLM驱动的智能代理可以有效地优化绿色化学过程.
- SapoMind证明了兰诺林酒精生产具有显著的环境和运营优势.
- 这种方法代表了人工智能和微流体的新整合,用于可持续的化学制造.
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