Using light to drive a chemical transformation introduces challenges for ensuring the robust transferability of photochemical reactions across different platforms and scales. We demonstrate a modeling tool to predict the performance of a photochemical reaction as a function of the reactor geometry, concentration of the photoactive species, irradiance of the light source, and residence time. High-throughput experimentation is utilized to optimize reaction conditions and to determine kinetic parameters and quantum yield. Optical characterization of the photoactive reaction species and the reactor is performed to determine the photon absorption rate. The experimental data is combined with computational modeling to predict photochemical conversion for different vial or flow reactors across multiple scales for a [2 + 2] photocycloaddition reaction and a photoredox-mediated decarboxylative intramolecular arene alkylation reaction. The method developed in this work facilitates the transferability of the photochemical processes between different photoreactors without the need for an intensive experimental optimization for each and enables a robust and efficient scale-up.

中文翻译：

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高通量实验与计算建模相结合，预测光化学转化在不同平台上放大的性能

使用光驱动化学转化为确保光化学反应在不同平台和规模上的稳健转移能力提出了挑战。我们展示了一种建模工具来预测光化学反应的性能，该性能取决于反应堆几何形状，光活性物质的浓度，光源的辐照度和停留时间。高通量实验可用于优化反应条件并确定动力学参数和量子产率。进行光活性反应物质和反应器的光学表征以确定光子吸收速率。实验数据与计算模型相结合，以预测[2 + 2]光环加成反应和光氧化还原介导的脱羧分子内芳烃烷基化反应在多个规模上的不同样品瓶或流动反应器的光化学转化。在这项工作中开发的方法有利于光化学过程在不同光反应器之间的转移，而无需为每个光反应器进行深入的实验优化，并实现了稳健而有效的放大。