Rxn Rover: automation of chemical reactions with user-friendly, modular software,Reaction Chemistry & Engineering

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Rxn Rover: automation of chemical reactions with user-friendly, modular software
Reaction Chemistry & Engineering ( IF 3.4 ) Pub Date : 2021-11-29 , DOI: 10.1039/d1re00265a
Zachery Crandall _{1,

2} , Kevin Basemann _{1,

2} , Long Qi ₁ , Theresa L. Windus _{1,

2}

Affiliation

The automation of chemical reactions in research and development can be an enabling technology to reduce cost and waste generation in light of technology transformation towards renewable feedstocks and energy in chemical industry. Automation of reaction optimization, in particular, would remove the need for expert input by designing algorithms to statistically analyze the reaction and automatically generate suggested results. In addition, automation can save time and resources, and reduce random human error. However, automation software is commonly coupled to a specific laboratory or device setup or not freely available for use. Rxn Rover is an open-source, modular automation platform for reaction discovery and optimization. Primarily targetting smaller research groups, it is designed using interchangeable plugins to be flexible and easy to integrate into a variety of laboratory environments. Using the Rxn Rover plugin architecture, novel optimization algorithms, analysis instrumentation, and reactor components can be used with minimal or no programming experience. The capability of Rxn Rover is demonstrated in the optimization of a reduction reaction of imine to amine, relevant to energy conversion and manufacturing of fine and commodity chemicals. The reaction was optimized separately using optimizer plugins for SQSnobFit, a Python implementation of the SNOBFIT global optimization algorithm, and Deep Reaction Optimizer (DRO), a deep reinforcement learning algorithm designed for reaction optimization. Using plugins designed for pumps, temperature controllers, and an online liquid chromatography system, the flow reaction was able to be controlled by each algorithm to automate reaction optimization for up to three days, at which point the results were gathered. A successful optimization was performed with SQSnobFit, achieving 70% yield and 95% selectivity, while no successful optimizations were achieved with DRO. Regardless of algorithm performance, Rxn Rover was able to successfully automate both multi-day optimization searches.

中文翻译：

Rxn Rover：使用用户友好的模块化软件实现化学反应的自动化

鉴于化学工业向可再生原料和能源的技术转型，研发中化学反应的自动化可以成为降低成本和废物产生的使能技术。特别是反应优化的自动化将通过设计算法来统计分析反应并自动生成建议的结果，从而消除对专家输入的需要。此外，自动化可以节省时间和资源，并减少随机人为错误。然而，自动化软件通常与特定的实验室或设备设置相关联，或者不能免费使用。Rxn Rover 是一个开源的模块化自动化平台，用于反应发现和优化。主要针对较小的研究小组，它使用可互换的插件设计，灵活且易于集成到各种实验室环境中。使用 Rxn Rover 插件架构，只需极少或无需编程经验即可使用新颖的优化算法、分析仪器和反应器组件。Rxn Rover 的能力体现在优化亚胺到胺的还原反应，与能源转换和精细化学品和商品化学品的制造相关。使用 SQSnobFit 的优化器插件（SNOBFIT 全局优化算法的 Python 实现）和深度反应优化器 (DRO)（专为反应优化而设计的深度强化学习算法）分别优化了反应。使用为泵、温度控制器和在线液相色谱系统设计的插件，流动反应能够由每种算法控制，以自动化反应优化长达三天，然后收集结果。使用 SQSnobFit 进行了成功的优化，实现了 70% 的产量和 95% 的选择性，而使用 DRO 没有实现成功的优化。无论算法性能如何，Rxn Rover 都能够成功地自动化这两个多日优化搜索。

更新日期：2021-12-07

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