A low-cost, modular self-driving laboratory platform (RoboChem-Flex) is designed to democratize autonomous chemical experimentation. This platform combines customizable hardware with Python-based cont...

Recent years have witnessed growing interest in integrating enabling technologies into synthetic organic chemistry to address long-standing challenges in reproducibility, sustainability, and scalability. This perspective showcases how modern tools, ranging from continuous-flow reactors and electrochemical cells to photochemical technologies, biocatalysis, mechanochemistry, and self-driving laboratories, are reshaping the way chemists design, perform, and optimize reactions. Through selected case studies, we highlight how these technologies not only solve specific reactivity and process issues but also open new avenues for reactivity discovery and chemical innovation. Rather than viewing technology as a complication, we advocate for its adoption as a natural extension of synthetic creativity, capable of enhancing safety, reducing waste, and expanding accessible chemical space. Our aim is to inspire broader implementation and interdisciplinary training to equip the next generation of chemists with the tools to rethink how synthesis is performed in the 21st century.

Self-driving laboratories (SDLs) have the potential to revolutionize chemical discovery and optimization, yet their widespread adoption remains limited by high costs, complex infrastructure, and limited accessibility. Here, we introduce RoboChem-Flex, a low-cost, modular self-driving laboratory platform designed to democratize autonomous chemical experimentation. The system combines customizable, in-house-built hardware with a flexible Python-based software framework that integrates real-time device control and advanced Bayesian optimization strategies, including multi-objective and transfer learning workflows. RoboChem-Flex supports both fully autonomous closed-loop operation and human-in-the-loop configurations, enabling seamless integration with shared analytical equipment and minimizing entry barriers. We validate the versatility of the platform across six diverse case studies, including photocatalysis, biocatalysis, thermal cross-couplings, and enantioselective catalysis, spanning both single and multi-objective optimizations. Through these campaigns, we demonstrate RoboChem-Flex’s ability to navigate large, complex chemical spaces, autonomously identify scalable high-performance reaction conditions, and flexibly adapt to a variety of analytical setups. By providing an affordable, scalable, and open platform, RoboChem-Flex offers a tangible step toward making SDLs accessible to resource-limited laboratories, fostering broader participation in automated chemical research.

Prof. Timothy Noel of the University of Amsterdam’s Van ‘t Hoff Institute for Molecular Sciences has been awarded a Vici grant by the Dutch research council NWO. Worth 1.5 million euros, the Vici is o...

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Photochemical transformations have garnered renewed interest over the past decade for their ability to enable unique reactions under mild conditions. However, scaling up such processes, particularly in multiphase systems (e.g., gas–liquid), remains challenging. Previously, we demonstrated the potential of the photochemical rotor-stator spinning disc reactor (pRS-SDR) for scaling the photooxidation of α-terpinene to ascaridole, though the system was limited by the light source, resulting in suboptimal operation in a photon-limited regime. In this work, we unlock the full potential of the pRS-SDR by integrating a high-powered light source (up to 652 W optical output) specifically designed for the reactor. The results show that the high gas–liquid mass transfer rates achievable in the pRS-SDR allow for significant productivity improvements under high irradiance (16.3 kg day–1 at 92% α-terpinene conversion and 2.52 W cm–2 in a 27 mL irradiated volume), representing an order of magnitude increase compared to our previous study. However, the photooxidation of β-citronellol exhibited notable limitations, highlighting the importance of selecting appropriate model reactions when evaluating intensified photochemical reactors.

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