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

用于增强对过程规模化学反应中混合现象和对象跟踪的理解的计算机视觉方法

• 批准号: 2889116
• 金额: --
• 依托单位: University of Strathclyde
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2889116
• 关键词: Computer; Vision; Methods; Enhanced; Understanding

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.

目标简述：(i) 研究基于成像的混合分析算法作为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对象跟踪成像方法在新型合成中的应用对小规模和大规模亲核芳族取代的非接触式反应监测。该学生奖学金由 CPACT 总共 1 万英镑的现金捐款支持，该支持是在先前的可行性捐款 5,000 英镑之后提供的。并建立实习研究，以验证我们团队的 Kineticolor 技术在 CPACT 成员公司 CatSci 和 Takeda 感兴趣的化学问题上的概念应用，导师的可用资金将用于补充 3 年 EPSRC 学生奖学金。摘要：除了化学改性之外，混合是反应放大过程中需要考虑的最重要的过程控制参数之一，虽然混合分析中已经有多种分析工具，但高时间分辨率的非接触式成像方法仍然存在。基于最近的 CPACT 可行性和实习研究，我们将探索计算机视觉动力学和混合分析在 Takeda 和 CatSci 合作者确定的两种反应类别的过程规模研究中的应用。