Adaptive mixed variable Bayesian self-optimisation of catalytic reactions

文献情報

出版日 2023-10-17

DOI 10.1039/D3RE00476G

インパクトファクター 4.239

著者

Naser Aldulaijan, Joe A. Marsden, Jamie A. Manson, Adam D. Clayton

原文を見る

要旨

Catalytic reactions play a central role in many industrial processes, owing to their ability to enhance efficiency and sustainability. However, complex interactions between the categorical and continuous variables leads to non-smooth response surfaces, which traditional optimisation methods struggle to navigate. Herein, we report the development and benchmarking of a new adaptive latent Bayesian optimiser (ALaBO) algorithm for mixed variable chemical reactions. ALaBO was found to outperform other open-source Bayesian optimisation toolboxes, when applied to a series of test problems based on simulated kinetic data of catalytic reactions. Furthermore, through integration of ALaBO with a continuous flow reactor, we achieved the rapid self-optimisation of an exemplar Suzuki–Miyaura cross-coupling reaction involving six distinct ligands, identifying a 93% yield within a budget of just 25 experiments.

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.

Adaptive mixed variable Bayesian self-optimisation of catalytic reactions

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