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在连续流中自主优化纳米颗粒催化还原反应。

Autonomous optimisation of a nanoparticle catalysed reduction reaction in continuous flow.

机构信息

Institute for Process Research and Development, School of Chemistry, University of Leeds, Leeds, LS2 9JT, UK.

出版信息

Chem Commun (Camb). 2021 May 18;57(40):4926-4929. doi: 10.1039/d1cc00859e.

Abstract

An automated continuous flow reactor system equipped with inline analysis, was developed and applied in the self-optimisation of a nanoparticle catalysed reaction. The system was used to optimise the experimental conditions of a gold nanoparticle catalysed 4-nitrophenol reduction reaction, towards maximum conversion in under 2.5 hours. The data obtained from this optimisation was then used to generate a kinetic model, allowing us to predict the outcome of the reaction under different conditions. By combining continuous flow nanoparticle synthesis with this approach, the development timeline for these emerging catalysts could be significantly accelerated.

摘要

我们开发了一种配备在线分析功能的自动化连续流反应器系统,并将其应用于纳米粒子催化反应的自动优化中。该系统用于优化金纳米粒子催化 4-硝基苯酚还原反应的实验条件,以在 2.5 小时内实现最大转化率。然后,我们使用从该优化中获得的数据生成了一个动力学模型,使我们能够预测不同条件下反应的结果。通过将连续流纳米粒子合成与这种方法相结合,可以显著加速这些新兴催化剂的开发时间表。

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