A robotic platform for rapid optimization and scale up of photocatalytic transformations

Objectif

In the ERC Consolidator Grant FlowHAT, we developed RoboChem, a fully autonomous robotic platform capable of optimizing photocatalytic reactions with minimal human intervention. Despite its success, several key challenges emerged that limit its full potential, including overlooked reaction parameters in literature, the absence of a seamless workflow between high-throughput experimentation (HTE) and autonomous optimization, and inherent biases in published reaction datasets.

The ERC Proof of Concept (PoC) RoboChem project aims to address these limitations by integrating RoboChem with HTE technology, creating a hybrid workflow that enhances efficiency, reproducibility, and scalability in reaction optimization. HTE will provide rapid, broad screening of reaction parameters, systematically identifying key factors affecting yield and selectivity. RoboChem will then refine these parameters, delivering precise optimization while reducing material waste and development time from months to days. This dual approach mirrors traditional chemical discovery but significantly accelerates the process, ensuring robustness in both academic and industrial settings.

By integrating HTE-driven screening with AI-powered robotic optimization, this project will establish a data-driven reaction optimization framework that improves predictive modeling and enhances experimental reproducibility. Through validation in industrially relevant contexts, we seek to demonstrate RoboChem’s transformative potential and pave the way for a spin-off company dedicated to advancing automation in synthetic chemistry.