Rapid, automated determination of reaction models and kinetic parameters

We herein report a novel kinetic modelling methodology whereby identification of the correct reaction model and parameters is conducted by an autonomous framework combined with transient flow measurements to enable comprehensive process understanding minimal user input. An automated chemistry platform was employed initially conduct linear flow-ramp experiments rapidly map profile three processes using data. Following experimental data acquisition, computational approach utilised discriminate between all possible models as well identify for each process. Species that are known participate in (starting materials, intermediates, products) inputted prior ramp experiments, then candidates compiled into library based on their potential occur after mass balance assessment. Parallel optimisation evaluates algorithmically altering allow convergence simulated curve provided. Statistical analysis determines most likely simplicity agreement This gaining full understanding, small number data-rich conducted, kinetics evaluated autonomously, shows significant improvements current industrial techniques terms labour, time overall cost. The described can be from any set code open-source.