化工学报 ›› 2024, Vol. 75 ›› Issue (11): 4120-4140.DOI: 10.11949/0438-1157.20240836
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:
Jian RUAN(), Shuang LI, Zhenghui WEN()
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。
中图分类号:
阮见, 李双, 温正慧. 自动化与智能化在流动化学中的应用[J]. 化工学报, 2024, 75(11): 4120-4140.
Jian RUAN, Shuang LI, Zhenghui WEN. Application of automation and artificial intelligence in flow chemistry[J]. CIESC Journal, 2024, 75(11): 4120-4140.
图3 自动化平台的用户界面:(a)基于LabView的SPS-flow合成平台用户界面[31];(b)基于LabView和MATLAB的高通量电化学微流控平台用户界面[32];(c)基于Python的RoboChem平台用户界面[35];(d)基于Python的NIMS-OS平台用户界面[37]
Fig.3 The user interface of the automated platform. (a) LabView-based SPS-flow synthesis platform user interface[31]; (b) LabView and MATLAB-based High-throughput electrochemical microfluidic platform user interface[32]; (c) Python-based RoboChem platform user interface[35]; (d) Python-based NIMS-OS platform user interface[37]
图5 不同反应平台使用的反应器:(a)光催化反应器[40];(b)电催化反应器[58]
Fig.5 Reactors for different reaction platforms: (a) Photocatalytic reactor[40]; (b) Electrocatalytic reactor[58]
仪器类型 | 连接方式 | 优点 | 缺点 | 响应时间 |
---|---|---|---|---|
红外光谱(IR) | in-line | 快速数据获取 非破坏性检测 能分析气体、液体和固体样品 | 提供的结构信息有限 对高温、高压的适应性较差 | 2 s~2 min |
紫外/可见吸收光谱 (UV-vis) | in-line | 高灵敏度 能快速进行定性和定量分析 | 对光敏感试剂可能产生影响 提供的结构信息较少 | 2~30 s |
核磁共振波谱(NMR) | in-line on-line | 非破坏性检测 提供详细的结构信息 能检测反应中的瞬态中间体 分析速度快 | 设备成本高 | 1 min~2 h |
高效液相色谱(HPLC) | at-line | 提供深入的样品分析 适用于复杂混合物 高灵敏度 | 需要标定过程 需要样品前处理 分析时间相对较长 | 5~ 30 min |
气相色谱(GC) | at-line | 高分辨率 快速分析 | 需要标定过程 仅限于挥发性和热稳定性化合物 需要样品前处理 | 5~30 min |
质谱(MS) | at-line | 高灵敏度 分析速度快 适用范围广 能提供详细的结构信息 | 设备成本高 破坏性检测 | 1 s~2 min |
拉曼光谱(Raman) | in-line | 非破坏性检测 分析速度快 适用于含水体系 | 灵敏度低 提供的结构化信息少 | 1~30 s |
表1 常见在线分析设备的连接方式及优劣势对比[68]
Table 1 Comparison of common online analysis device connection mode and advantages/disadvantages[68]
仪器类型 | 连接方式 | 优点 | 缺点 | 响应时间 |
---|---|---|---|---|
红外光谱(IR) | in-line | 快速数据获取 非破坏性检测 能分析气体、液体和固体样品 | 提供的结构信息有限 对高温、高压的适应性较差 | 2 s~2 min |
紫外/可见吸收光谱 (UV-vis) | in-line | 高灵敏度 能快速进行定性和定量分析 | 对光敏感试剂可能产生影响 提供的结构信息较少 | 2~30 s |
核磁共振波谱(NMR) | in-line on-line | 非破坏性检测 提供详细的结构信息 能检测反应中的瞬态中间体 分析速度快 | 设备成本高 | 1 min~2 h |
高效液相色谱(HPLC) | at-line | 提供深入的样品分析 适用于复杂混合物 高灵敏度 | 需要标定过程 需要样品前处理 分析时间相对较长 | 5~ 30 min |
气相色谱(GC) | at-line | 高分辨率 快速分析 | 需要标定过程 仅限于挥发性和热稳定性化合物 需要样品前处理 | 5~30 min |
质谱(MS) | at-line | 高灵敏度 分析速度快 适用范围广 能提供详细的结构信息 | 设备成本高 破坏性检测 | 1 s~2 min |
拉曼光谱(Raman) | in-line | 非破坏性检测 分析速度快 适用于含水体系 | 灵敏度低 提供的结构化信息少 | 1~30 s |
图6 自动化在线分离研究:(a)自动化在线纳滤分离回收均相催化剂[69];(b)自动化连续结晶[74];(c)自动化在线快速柱层析分离[77]
Fig.6 Summary of automated inline separation: (a) automated inline nanofiltration to recycle homogeneous catalyst[69]; (b) automated continuous crystallization[74]; (c) automated inline flash chromatography[77]
图7 常规连续流自动化系统:(a)连续流微反应器自动化平台[78];(b)全自动纳摩尔级连续流反应筛选和微摩尔级合成平台[62](1 bar=0.1 MPa)
Fig.7 Continuous flow automated system: (a) continuous flow microreactor automation platform[78]; (b) the platform for automated nanomolescale reaction screening and micromole-scale synthesis in flow[62]
图9 自动化连续流电化学平台:(a)多功能微流控高通量电化学合成平台[32];(b)基于弹状流的自动化电化学流动平台[80]
Fig.9 Automated continuous-flow electrochemical platform: (a) multifunctional microfluidic platform for high-throughput experimentation of electrochemistry[32]; (b) automated slug-based electrochemical flow platform[80]
图10 自动化连续多肽合成系统:(a)自动化流动合成蛋白质[81];(b)自动化固相合成PMOs[82]
Fig.10 Automated flow peptide synthesis experimental platform: (a) automated flow synthesis of proteins[81]; (b) automated solid-phase synthesis of PMOs[82]
图11 面向连续多步合成的自动化系统:(a)基于流路切换阀的自动化连续流系统AutoSyn[70];(b)径向合成平台[83];(c)自动化连续流固相合成平台[31]
Fig.11 Automated systems for multistep synthesis: (a) automated switching-valve-based continuous-flow system, AutoSyn[70]; (b) radial synthesis platform[83]; (c) automated continuous-flow solid phase synthesis platform[31]
图12 基于DoE优化策略的流动合成过程:(a)合成1,2,4-𫫇二唑和1,2,4-三唑的小分子化合物库[88];(b)高温高压条件下合成稠合嘧啶酮和喹诺酮衍生物[90]
Fig.12 DoE method used to optimize flow synthesis process. (a) Synthesis of 1,2,4-oxadiazole and 1,2,4-triazole small molecule compound libraries[88]; (b) Synthesis of the fused pyrimidinone and quinolone derivatives under high temperature and pressure[90]
图15 基于随机森林算法和多臂老虎机算法优化的C—N交叉偶联反应研究[33,97]
Fig.15 The C—N cross-coupling reaction study based on random forest algorithm and multi-armed bandit algorithm[33,97]
图16 基于贝叶斯优化的智能化合成系统:(a)模块化机器人流动合成平台[100];(b)闭环、多目标优化的连续流光催化系统RoboChem[35];(c)多任务贝叶斯优化合成平台[102] (1 psi=6895 Pa)
Fig.16 Bayesian optimization-based intelligent synthetic system. (a) Modular robot flow synthesis platform[100]; (b) RoboChem, a closed-loop, multi-objective optimization platform for photocatalysis system[35]; (c) Multi-task Bayesian optimization synthesis platform[102]
图18 用于复杂分子设计和合成的计算机辅助正向合成平台Allchemy[103]
Fig.18 Allchemy: a computational platform for forward synthesis in complex molecule design and synthesis[103]
图20 自动化实验平台在云端实验室领域的初步应用:(a)跨国界云端实验室系统[111];(b)云端平台协调多实验室发现并优化有机激光发射器[34]
Fig.20 The preliminary applications of automated experiment platform in cloud laboratory field: (a) cross-border cloud laboratory systems[111]; (b) the cloud platform coordinates multi-laboratory discovery and optimization of organic laser emitters[34]
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