An Integrated Microreactor System for Self-Optimization of a Heck Reaction: From Micro- to Mesoscale Flow Systems
An Integrated Microreactor System for Self-Optimization of a Heck Reaction: From Micro- to Mesoscale Flow Systems
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DOI：
10.1002/anie.201002590
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发表时间：
2010-01-01
影响因子：
16.6
通讯作者：
Jensen, Klavs F.
中科院分区：
文献类型：
--
作者：
McMullen, Jonathan P.;Stone, Matthew T.;Jensen, Klavs F.
与传统的间歇合成相比，连续流动过程提供了几个优点，包括易于放大[1，2]，以及能够在极端压力和温度下安全地运行反应。[3-6]微反应器尤其被证明具有优越的热和质传递速率，[7-9]提供对反应条件的精确控制。[10]这些特性使微反应器成为快速反应、高放热反应、爆炸反应、[13]和涉及含能中间体的反应。[14]微反应器的小体积容量还允许在日益复杂的分子目标上高效地开发更复杂的连续流动反应，因为它们极大地减少了优化反应条件所需的材料的数量。然而，微反应器流动系统所需的特殊设备也增加了并行筛选反应条件的难度，这通常是批量进行的。因此，在一系列连续的实验中开发有效的策略来优化反应条件对微反应器特别有价值。为此，我们开发了一种自我优化的微反系统，它使用以前的反应数据来有效地选择未来的实验。这种方法允许同时优化多个参数。已经开发了几个自动化微反应堆系统，能够采样一系列预定的反应条件。这些系统通常采用单变量方法，每次只调整一个变量。[21]这种穷举搜索本身效率低下，因为它们可能收集远离所需最大值的数据点的很大百分比。还开发了一种基于实验方法设计的更复杂的自动化微反系统。虽然该系统非常适合于响应面建模，但就优化所需的反应数量而言，该方法的效率较低。[22]将反馈整合到反应优化中可以通过引导系统远离较低产率的反应条件来显著提高整个过程的速度和效率。此外，在微反应器中获得的反应优化结果通常不受质量或热传递效应的限制。因此，通过将观察到的化学知识与已建立的化学工程反应器设计方法相结合，可以更容易地从最佳实验室条件转移到更大规模的反应器。[24-26]在这里，我们描述了一个采用由内尔德-米德单纯形法指导的“黑箱”优化技术的自优化微反应器系统。该系统被证明通过调节烯烃当量和停留时间来最大化Heck反应的产率。在微型反应器中获得优化条件后，在中尺度流动反应器中将反应放大50倍。在中尺度反应器中考察了反应条件，发现与在微反应器中观察到的产率很好地一致。然后允许最佳停留时间和烯烃当量在中尺度反应器中运行22个反应器体积(约2h)，提纯后得到的分离产率与在线高效液相分析结果一致。我们选择研究4-氯三氟苯(1)和2，3-二氢呋喃(2；方案1)的Heck反应，因为所需的产物3很容易与第二个等量的芳基氯反应。因此，反应的产率高度依赖于…的数量。
Continuous flow processes offer several advantages over traditional batch synthesis including ease of scale up [1, 2] and the ability to run reactions safely at extreme pressures and temperatures.[3–6] Microreactors in particular have been shown to have superior heat and mass transfer rates,[7–9] providing precise control of reaction conditions.[10] These attributes make microreactors ideal for fast reactions,[11] highly exothermic reactions,[12] explosive reactions,[13] and reactions that involve energetic intermediates.[14] The small volume capacity of microreactors has also allowed the efficient development of more sophisticated continuous flow reactions on increasingly complex molecular targets since they greatly reduce the quantities of materials needed to optimize reaction conditions.[8, 15–20] However, the specialized equipment required for microreactor flow systems also increases the difficulty of screening reaction conditions in parallel as is commonly performed in batch. Thus, developing efficient strategies to optimize reaction conditions in a series of consecutive experiments is particularly valuable for microreactors. Towards this end we have developed a self-optimizing microreactor system that uses previous reaction data to efficiently select future experiments. This approach allows numerous parameters to be optimized simultaneously. Several automated microreactors systems have been developed that are capable of sampling a series of predetermined reaction conditions. These systems often employ a univariable approach in which only a single variable is adjusted at a time.[21] Such exhaustive searches are inherently inefficient since they are likely to gather a significant percentage of data points that are far away from the desired maximum. A more sophisticated automated microreactor system based on Design of Experiment methods has also been developed. Although this system is ideally suited for response surface modeling, the approach is less efficient in terms of the number of reactions required for an optimization.[22] Integrating feedback into the reaction optimization could significantly increase the speed and efficiency of the overall process by directing the system away from lower yielding reaction conditions.[23] Furthermore, reaction optimization results obtained in a microreactor are typically not limited by mass or heat transfer effects. Consequently, moving from optimal laboratory conditions to larger scale reactors can be more easily achieved by integrating the observed chemical understanding with established chemical engineering reactor design methods.[24–26]Herein we describe a self-optimizing microreactor system that employs a “black-box” optimization technique directed by the Nelder–Mead Simplex Method.[27] The system was shown to maximize the yield of a Heck reaction by adjusting the equivalents of the alkene and the residence time. Upon obtaining optimized conditions in a microreactor, the reaction was scaled-up 50-fold in a mesoscale flow reactor. Reaction conditions were surveyed in the mesoscale reactor and found to be in good agreement with the yields observed in the microreactor. The optimal residence time and equivalents of alkene were then allowed to run in the mesoscale reactor for 22 reactor volumes (ca. 2h) and upon purification the resulting isolated yield was found to be in good agreement with the online HPLC analysis. We chose to examine the Heck reaction of 4-chlorobenzotrifluoride (1) and 2, 3-dihydrofuran (2; Scheme 1) since the desired product 3 readily reacts with a second equivalent of the aryl chloride.[28] Thus, the yield of the reaction is highly dependent upon the number of …