Chemical experiments conducted in laboratories have become faster and more reproducible with the advancement of automation and robotic systems. Although self-driving laboratory (SDL) systems, in particular, have the potential to accelerate experimental processes, they are not widely adopted due to high costs, complex infrastructure requirements, and limited accessibility. This limitation creates a disparity in scientific research between institutions with and without access to resources. Consequently, making autonomous systems accessible to a broader community of researchers is considered a critical need.
In this study conducted by Timothy Noël and his research team, the goal was to develop RoboChem-Flex, a low-cost and accessible autonomous laboratory system. Because existing systems remain limited in use due to their high cost and the need for multidisciplinary expertise, bridging this gap formed the core starting point of the study. Within this scope, the RoboChem-Flex platform was developed to investigate whether complex chemical processes could be optimized even with limited resources by utilizing open-source software and cost-effective hardware components.
The platform combines low-cost hardware components with open-source software. For the hardware, the Arduino Uno was selected as the programmable microcontroller. On the software side, an open-source package called OmniPlatypus (open-source device control software), which requires minimal coding and features a “plug-and-play” architecture, was used. Bayesian optimization algorithms were utilized to optimize the experimental processes. The system was designed to operate both fully autonomously and with human intervention. The performance of the developed platform was tested through six different case studies involving photocatalysis (accelerating reactions with light energy), biocatalysis (using biological enzymes), and thermal reactions.
The study demonstrates that the RoboChem-Flex platform can optimize complex chemical processes within a low-cost system. In photocatalytic reactions, the RoboChem-Flex platform achieved a reaction time of 2 minutes and a yield of 71%. Compared to previous studies in the literature, these values offer both higher yield and shorter reaction times. Additionally, the system achieves high selectivity and yield values even with limited datasets. The findings suggest that when using a “human-in-the-loop” configuration, the platform can be set up at a low cost of approximately $5,000, thereby increasing accessibility in scientific research. It is anticipated that this approach could enable more research groups to benefit from automation technologies in the future.
Translated by: Hazel BİRGÜL
Editor: Elinsu AK
Reference: Pilon, S., Savino, E., Bayley, O. M., Vanzella, M., Claros, M., Siasiaridis, P., Liu, J., Lukas, F., Damian, M., Tseliou, V., Intini, N., Slattery, A., SanJosé-Orduna, J., den Hartog, T., Peters, R. A. H., Gargano, A. F. G., Mutti, F. G., & Noël, T. (2026). A flexible and affordable self-driving laboratory for automated reaction optimization. Nature Synthesis. https://doi.org/10.1038/s44160-026-01053-0
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