Reaction Kinetics using a Chemputable Framework for Data Collection and Analysis

Abstract: 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.

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch

References and Relationships

• Bibliographic citation: Reaction Kinetics using a Chemputable Framework for Data Collection and Analysis ; day:24 ; month:01 ; year:2024 ; extent:9 ; Angewandte Chemie ; (24.01.2024) (gesamt 9)

Contributors, Places and Time

• Creator: Matysiak, Bartosz M. ; Thomas, Dean ; Cronin, Leroy

Further information

• DOI: 10.1002/ange.202315207
• URN: urn:nbn:de:101:1-2024012514100541174923
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 15.08.2025, 7:32 AM CEST