“Batch” Kinetics in Flow with Online IR Analysis and Continuous Control**

Current methods for generating kinetic data can be categorized as either sampling steady-state conditions in flow or generating timeseries data in batch.[1] The latter method has proven particularly useful in identifying complex kinetic mechanisms.[2] Unfortunately, both of these techniques have significant limitations. While continuous flow experiments, especially in microreactors, have advantages over batch in terms of mixing times,[3,4] temperature control,[5,6] materials savings,[7] and the ability to perform sequential experiments without intermediate cleaning steps, batch experiments are seen as better suited to generating kinetic data due to the ability to collect data from many time points in a single experiment.[2] However, with continuous online measurement, flow experiments can generate such time-series data by continuously varying flow rate in a low-dispersion reactor.[8] This analysis is possible because, under ideal conditions, a batch reactor and a plug-flow reactor have the same kinetics design equation; i.e., they will have the exact same conversion as a function of conditions and time for any reaction, as time in the batch reactor corresponds to residence time in the plug flow reactor.[1] These reactors are typically treated differently only due to deviations from ideality, such as concentration or temperature gradients from imperfect mixing. A recent contribution by Mozharov et al. presented a method to take advantage of the ideality of microreactors to derive time-series data via flow manipulation.[9] In their method, a Knoevenagel condensation in a microreactor was allowed to come to steady state at a low flow rate. A step change in flow rate then rapidly flushed the contents of the reactor. As this reactor volume exited, an inline Raman probe measured the product concentration. While this enabled generation of a conversion curve in agreement with steadystate experiments, the exact reaction times during this flow-rate step change could not be known because the step change was not actually instantaneous, requiring graphical and empirical estimation of reaction times. As stated in Mozharov et al., “The step increase in flow rate is never perfect. The system always needs some time to speed up to the higher flow rate... The exact function F(τ) during this transitional period is uncertain.”[9] This non-ideality is due to effects such as non-rigidity of tubing walls and the syringe plunger, preventing an immediate change in the pressure profile throughout the system. The method developed here involves allowing a microreactor system to come to steady state at short residence time, which significantly reduces the initial waiting period before flow manipulation can begin. Uncertainty in accurate determination of residence time is avoided through a controlled ramp rather than a step change in flow rate. This enables the rate of the change in residence time to be set, allowing control over the trade-off between more experimental data and experiment duration. This work focuses on describing this new methodology and is intended to be broadly applicable to a wide range of chemistries for which time-series data are desired. Ideally, this method could be applied with inline analysis to any chemistry capable of being quenched chemically, thermally, or otherwise. However, an integrated online sensor at the end of the reaction zone would allow this method to be expanded even further. As such, ATR-FTIR, UV/Vis, flow NMR, Raman, fluorescence spectrometry, and more are amenable to this technique. The efficacy of this new technique was demonstrated using a Paal-Knorr reaction of 2,5-hexanedione (1) and ethanolamine (2) in dimethyl sulfoxide (DMSO) (Schemes 1 and 2)[10,11] in an automated flow platform (Figure S1),[12,13] which used an inline Mettler Toledo ReactIR ATR-FTIR flow cell[14] to continuously monitor the effluent from a silicon microreactor.