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An autonomous flow microreactor platform was developed that was able to conduct reaction experiments and measure the outlet reactant and product concentrations using HPLC without user supervision. The platform performed unmanned kinetic experiments with the aim of precisely estimating the parameters of a kinetic model for the esterification between benzoic acid and ethanol catalysed by sulfuric acid. The capabilities of the autonomous platform were demonstrated on three different experimental scenarios: 1) performing steady-state experiments, where the experimental reaction conditions were pre-defined by the user; 2) performing steady-state experiments, where the conditions were optimised online by Model-Based Design of Experiments (MBDoE) algorithms, with the aim of improving parameter precision; 3) executing transient experiments, where the conditions were pre-selected by the user. For the steady-state experiments, the platform automatically performed online parameter estimation and MBDoE with a pre-selected kinetic model. It was demonstrated that a campaign of steady-state experiments designed using online MBDoE algorithms led to more precise parameter estimates than a campaign of experiments designed by the traditional factorial design. Transient experiments were shown to expedite kinetic parameter estimation and use less reagents than campaigns of steady-state experiments, as it was no longer necessary to wait for the system to reach steady-state. In general, the transient experiments offered less precise parameter estimates than the steady-state campaigns, however the experiments could be completed in just 2 h instead of the 8 h required for a campaign of steady-state experiments.

An autonomous microreactor platform for the rapid identification of kinetic models