Matysiak Bartosz M, Thomas Dean, Cronin Leroy
School of Chemistry, University of Glasgow, Glasgow, G12 8QQ, UK.
Angew Chem Int Ed Engl. 2024 Feb 26;63(9):e202315207. doi: 10.1002/anie.202315207. Epub 2024 Jan 24.
Automated chemistry platforms have been widely explored, but many focus on fixed tasks for chemical synthesis or analysis. However, a typical synthetic chemistry workflow utilizes both, such as kinetic measurements for reaction development and optimization. Due to their repetitive and time-consuming nature, kinetic measurements are often omitted, which limits the mechanistic investigation of reactions. Herein, we present a "Chemputer" platform with on-line analytics (UV/Vis, NMR) which automates routine kinetic measurements. The system's capabilities are showcased by exploring an inverse electron-demand Diels-Alder using initial rate measurements, a metal complexation using variable time normalization analysis (VTNA), and formation of a series of tosylamide derivatives using Hammett analysis. Over 60 individual experiments are presented which required minimal intervention, highlighting the significant time savings of automation. Owing to the modular design of the platform, which facilitates rapid integration of commercial analytical tools, our approach is widely accessible and adjustable to the reaction under investigation. The platform is operated using the chemical programming language, XDL, hence experimental procedures and results are stored in a precise, computer-readable format. We propose that widespread adoption of this reporting protocol in the chemical community could build a database of validated kinetic data beneficial for Machine Learning.
自动化化学平台已得到广泛探索,但许多平台专注于化学合成或分析的固定任务。然而,典型的合成化学工作流程会同时利用这两者,例如用于反应开发和优化的动力学测量。由于其重复性和耗时性,动力学测量常常被省略,这限制了对反应机理的研究。在此,我们展示了一个具有在线分析功能(紫外/可见光谱、核磁共振)的“化学计算机”平台,该平台可自动进行常规动力学测量。通过使用初始速率测量探索逆电子需求狄尔斯-阿尔德反应、使用可变时间归一化分析(VTNA)进行金属络合以及使用哈米特分析形成一系列甲苯磺酰胺衍生物,展示了该系统的功能。本文展示了60多个独立实验,这些实验只需极少干预,凸显了自动化显著节省时间的优势。由于该平台的模块化设计便于快速集成商业分析工具,我们的方法广泛适用且可根据所研究的反应进行调整。该平台使用化学编程语言XDL运行,因此实验步骤和结果以精确的、计算机可读的格式存储。我们建议化学界广泛采用这种报告协议,以建立一个有利于机器学习的经过验证的动力学数据库。