OpenFlowChem – a platform for quick, robust and flexible automation and self-optimisation of flow chemistry

Abstract

Flow chemistry is a time-saver in the laboratory and a cost-saver in industry partly because of automation and autonomous operation. Nevertheless, a batch process is often preferred over a flow counterpart because setting up the autonomous operation may take a lot of time. In this paper, we propose a novel open-access OpenFlowChem platform based on LabVIEW for process automation, control and monitoring. The platform is optimized for quick system setup, reconfiguration and high flexibility. The platform is demonstrated in three examples: autonomous operation with an automatic stepwise program, proportional–integral–derivative (PID) control and self-optimization. In the first example, the system automatically executed a reaction program defined in a spreadsheet file to study the reversibility of a Pd/SiO₂ catalyst poisoning with quinoline in the reaction of alkyne semihydrogenation. The addition of quinoline increased alkene selectivity and reduced the catalyst activity, but the time required to remove the catalyst poison varied by a factor of 10 and depended on the poison concentration. In the second example, a PID controller adjusted the nitrobenzene concentration in a hydrogenation reaction to compensate for catalyst deactivation and a disturbance in process parameters. The PID controller kept constant the hydrogen consumption determined by an inline optical liquid sensor. In the third example, the product yield in alkyne semihydrogenation was self-optimized, adjusting the flow rates of the substrate, the catalyst poison (quinoline) and the solvent in a tube reactor coated with a 5 wt% Pd/SiO₂ catalyst. As a result, the alkene yield reached 96.5%.