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Optimum catalyst selection over continuous and discrete process variables with a single droplet microfluidic reaction platform†
Reaction Chemistry & Engineering ( IF 3.9 ) Pub Date : 2018-04-11 00:00:00 , DOI: 10.1039/c8re00032h
Lorenz M. Baumgartner 1, 2, 3, 4 , Connor W. Coley 1, 2, 3, 4 , Brandon J. Reizman 1, 2, 3, 4 , Kevin W. Gao 1, 2, 3, 4, 5 , Klavs F. Jensen 1, 2, 3, 4
Affiliation  

A mixed-integer nonlinear program (MINLP) algorithm to optimize catalyst turnover number (TON) and product yield by simultaneously modulating discrete variables—catalyst types—and continuous variables—temperature, residence time, and catalyst loading—was implemented and validated. Several simulated case studies, with and without random measurement error, demonstrate the algorithm's robustness in finding optimal conditions in the presence of side reactions and other complicating nonlinearities. This algorithm was applied to the real-time optimization of a Suzuki–Miyaura cross-coupling reaction in an automated microfluidic reaction platform comprising a liquid handler, an oscillatory flow reactor, and an online LC/MS. The algorithm, based on a combination of branch and bound and adaptive response surface methods, identified experimental conditions that maximize TON subject to a yield constraint from a pool of eight catalyst candidates in just 60 experiments, considerably fewer than a previous version of the algorithm.

中文翻译:

使用单个液滴微流体反应平台,可在连续和离散过程变量上优化催化剂选择

已实现并验证了一种混合整数非线性程序(MINLP)算法,该算法通过同时调制离散变量(催化剂类型)和连续变量(温度,停留时间和催化剂负载)来优化催化剂周转数(TON)和产品收率。若干模拟案例研究(带有和不带有随机测量误差)证明了算法在存在副反应和其他复杂非线性情况下寻找最佳条件时的鲁棒性。该算法已应用于在包括液体处理机,振荡流反应器和在线LC / MS在内的自动微流控反应平台中,Suzuki-Miyaura交叉偶联反应的实时优化。该算法基于分支定界和自适应响应面方法的组合,
更新日期:2018-04-11
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