Autonomous model-based experimental design for rapid reaction development

文献情報

出版日 2022-08-02

DOI 10.1039/D2RE00208F

インパクトファクター 4.239

著者

Sebastian Knoll, Martin Horn

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要旨

Currently, the development of flow processes is seen as a resource intensive and specialized activity, when compared to batch processes. We describe an optimization workflow, based on newly-developed open-source software (Optipus). This procedure facilitates the automation of flow optimization experiments, collects and utilizes data in real time, and is able to autonomously perform real-time model fitting and evaluation. We highlight the application of the software to optimize a four-dimensional nucleophilic aromatic substitution and a six-dimensional photochemical benzylic bromination. Overall, the utilization of Optipus will enable early generation and use of predictive models for the identification of the sensitivity of product quality to critical parameter changes, significantly reducing development time and risks.

掲載誌

Reaction Chemistry & Engineering

CiteScore: 0

自己引用率: 8.8%

年間論文数: 284

Reaction Chemistry & Engineering is an interdisciplinary journal reporting cutting-edge research focused on enhancing the understanding and efficiency of reactions. Reaction engineering leverages the interface where fundamental molecular chemistry meets chemical engineering and technology. Challenges in chemistry can be overcome by the application of new technologies, while engineers may find improved solutions for process development from the latest developments in reaction chemistry. Reaction Chemistry & Engineering is a unique forum for researchers whose interests span the broad areas of chemical engineering and chemical sciences to come together in solving problems of importance to wider society. All papers should be written to be approachable by readers across the engineering and chemical sciences. Papers that consider multiple scales, from the laboratory up to and including plant scale, are particularly encouraged.

Autonomous model-based experimental design for rapid reaction development

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