Computer Vision Methods for Enhanced Understanding of Mixing Phenomena and Object Tracking in Process-scale Chemical Reactions

目的简而言之：(I)研究基于成像的混合分析算法作为一种非接触式反应监测方法在大规模格氏试剂合成中的应用。(Ii)研究最近开发的混合和目标跟踪成像方法在小规模和大范围亲核芳香族取代的新型非接触式反应监测中的应用。在此之前，CPACT成员公司CatSci和Takeda对我们团队的Kineticolor技术在感兴趣的化学问题上的概念验证应用进行了可行性和实习研究的GB 5k联合贡献。从导师的可用资金中还将提供额外的捐款，以组成为期3年的EPSRC学生包。摘要：在反应放大过程中，除化学修饰外，混合是最重要的过程控制参数之一。虽然几种分析工具在混合分析方面已经成熟，但高时间分辨率的非接触式成像方法仍处于相对初级阶段。在最近CPACT可行性和实习研究的基础上，我们将探索我们的计算机视觉动力学和混合分析在武田和CatSci的合作者确定的两个反应类别的过程规模研究中的应用。

AIMS IN BRIEF: (i) Investigate the application of imaging-based mixing analysis algorithms as a non-contact reaction monitoring approach to Grignard reagent synthesis on scale.(ii) Investigate the use of recently-developed mixing and object tracking imaging methods towards novel non-contact reaction monitoring of nucleophilic aromatic substitutions on across small and large scales.This studentship is supported by a £10k cash contribution from CPACT. The support follows an earlier £5k combined contribution across feasibility and internship studies to establish proof-of-concept applications of our team's Kineticolor technology on chemical problems of interest to CPACT member companies CatSci and Takeda. Additional contributions are being made from the supervisor's available funds to make up the 3-year EPSRC studentship package.ABSTRACT: Outside chemical modification, mixing is one of the most important process control parameters to consider in reaction scale-up. While several analytical tools are well-established in mixing analysis, non-contact imaging approaches of high temporal resolution remain in their relative infancy. Building on recent CPACT feasibility and internship studies, we will explore the applications of our computer vision kinetics and mixing analyses in the process-scale study of two reaction classes identified by collaborators at Takeda and CatSci.