化工学报 ›› 2024, Vol. 75 ›› Issue (11): 4120-4140.DOI: 10.11949/0438-1157.20240836

• 综述与专论 • 上一篇    下一篇

自动化与智能化在流动化学中的应用

阮见(), 李双, 温正慧()   

  1. 甬江实验室流动与智能化合成组,浙江 宁波 315202
  • 收稿日期:2024-07-24 修回日期:2024-08-29 出版日期:2024-11-25 发布日期:2024-12-26
  • 通讯作者: 温正慧
  • 作者简介:阮见(1997—),男,硕士,初级工程师,jian-ruan@ylab.ac.cn
  • 基金资助:
    甬江实验室科研项目(B400QASE00)

Application of automation and artificial intelligence in flow chemistry

Jian RUAN(), Shuang LI, Zhenghui WEN()   

  1. Flow and Intelligent Synthesis Research Group, Yongjiang Laboratory, Ningbo 315202, Zhejiang, China
  • Received:2024-07-24 Revised:2024-08-29 Online:2024-11-25 Published:2024-12-26
  • Contact: Zhenghui WEN

摘要:

流动化学作为化学合成的重要前沿技术,具有高效、安全可控、环保等特点,广泛应用于药物合成、精细化工和材料科学等多个领域。近年来,随着自动化与人工智能技术的发展,流动化学逐渐实现了全流程自动化和智能化的系统转型。自动化流动化学系统通过集成自动化设备与控制系统,实时监督与调控反应条件,尽可能减少人为操作带来的误差,从而提高实验稳定性和可重复性。人工智能算法的引入使系统能够处理大量文献及实验数据,探索高维化学空间,缩短实验周期,提升反应效率和发现新反应。初步总结了智能化流动化学系统的发展现状,介绍了自动化流动化学系统的构建与应用,同时探讨基于人工智能的智能化发展路径,包括机器学习算法和大语言模型的应用等。基于实例分析现阶段的研究成果,展示了智能化流动化学系统在化学合成中的巨大潜力与应用前景。

关键词: 流动化学, 自动化, 智能化, 高通量筛选, 机器学习

Abstract:

Flow chemistry, as an important frontier technology in chemical synthesis, has the characteristics of high efficiency, safety, controllability, and environmental protection. It is widely used in drug synthesis, fine chemicals, and materials science. Recent advances in automation and artificial intelligence (AI) have enabled flow chemistry to achieve full-process automation and intelligence. Automated systems integrate equipment and control systems to monitor and regulate reaction conditions in real-time, minimizing human error and enhancing stability and reproducibility. AI algorithms allow these systems to handle large data volumes, navigate high-dimensional chemical space, shorten experimental cycles, and improve efficiency and yield. This paper summarizes the development of intelligent flow chemistry systems, discusses the construction and application of the automated systems, and explores AI-based advancements, including machine learning algorithms and large language models. Case studies highlight the significant potential and application prospects of intelligent flow chemistry systems in chemical synthesis.

Key words: flow chemistry, automation, artificial intelligence, high-throughput screening, machine learning

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