Accelerating mechanistic understanding in chemical synthesis: Design of Experiment, kinetic analysis and systems modelling

该项目完全符合EPSRC的职权范围，与研究领域：催化，合成有机化学，化学反应动力学和机制以及制造技术和机器人技术保持一致。后一个区域设置为“增长”。我们的项目将采用高度仪器化的机器人平台，辅以丰富的反应数据分析。一旦生成了几个反应数据集，我们将研究机器学习算法来预测新系统中的反应结果(例如：底物、条件、催化剂变化)。该项目有可能属于人工智能技术，EPSRC已经指出这是一个重要的领域。Fairlambgroup目前的资助由EPSRC（EP/S009965/1）支持，使用自动化和收集丰富的机械数据。

The project fits squarely into EPSRC remit, aligning with the research areas: Catalysis, Syntheticorganic chemistry, Chemical reaction dynamics and mechanisms and Manufacturing technologiesand Robotics. The latter area is set as "Grow". Our project will employ a highly instrumented roboticplatform, complemented by rich reaction data analysis. Once several reaction datasets have beengenerated we will examine machine learning algorithms to predict reaction outcomes in new systems(e.g. substrates, conditions, catalyst changes). The project has the potential to fall into ArtificialIntelligence Technologies, which EPSRC has indicated as an area of importance. The Fairlambgroup's current grant, using automation and gathering rich mechanistic data, is supported by EPSRC(EP/S009965/1)