Abstract:

Traditional manual procedures in the realm of chemical synthesis are often inefficient and exhibit several drawbacks including excessive energy consumption and substantial waste generation. The increasing adoption of automation technology within this field allows machines to perform time-consuming and repetitive tasks, thereby providing scientists with greater opportunities to focus on high-value activities. The advancement of intelligent algorithms is streamlining this process, and when combined with real-time reaction analysis and automation, it is generating unparalleled opportunities for chemical synthesis. A thorough understanding of flow and reaction processes through the automated optimization of continuous synthesis technology positions it as a cutting-edge application method across various domains. This paper aimed to investigate the effects and optimization strategies associated with the automated optimization of continuous synthesis technology in areas such as biopharmaceuticals, material synthesis, organic chemistry and reaction kinetics. The findings presented herein suggested that the automated optimization of continuous synthesis technology possesseed significant application potential within chemical synthesis. Furthermore, future research endeavors could explore additional applications and optimization strategies for automation technology across other fields.

Key words: automatic optimization, artificial intelligence, machine learning, continuous flow, flow chemistry

摘要：

传统手动程序在化学合成领域效率不足，且存在能耗大、废物产生多等多方面缺点。自动化技术在化学合成领域的应用日益广泛，将耗时和重复的任务交给机器来完成，为科学家们提供了更多专注于高价值活动的机会。智能算法的发展进一步推动这一进程，其与实时反应分析和自动化相结合，为化学合成带来了前所未有的机遇。自动优化连续合成技术对流动和反应过程的准确把握，使其成为应用在各个领域的一种前沿手段。本文探讨了自动优化连续合成技术在生物制药、材料合成、有机化工、反应动力学等领域的应用效果及优化策略，表明自动优化连续合成技术在化学合成领域具有广阔的应用前景，未来研究可进一步探索自动化技术在更多领域的应用及优化策略。

关键词: 自动优化, 人工智能, 机器学习, 连续流, 流动化学