Abstract
Sinusoidal variations of operative parameters in flow chemistry allows the fast exploration of chemical design spaces through inline measurements of an objective function.
Highlights
Development of new syntheses and performance enhancement of existing processes continue to be challenges for production of both fine-chemicals and commodities
One way to reduce the number of experiments required to find an optimal condition is the use of design of experiment (DoE) methods,[1,2] which provide reaction conditions aimed at describing the variations of some objective function with respect to the optimization parameters while using a small number of experiments
For various sets of kinetic/process parameters, a dynamic experiment was simulated to obtain the objective function value over time and 50 random times were selected for comparison with the corresponding steady-state values of the objective function by computing the difference Δ of such values
Summary
Development of new syntheses and performance enhancement of existing processes continue to be challenges for production of both fine-chemicals and commodities. One way to reduce the number of experiments required to find an optimal condition is the use of design of experiment (DoE) methods,[1,2] which provide reaction conditions aimed at describing the variations of some objective function with respect to the optimization parameters while using a small number of experiments These approaches employ a simple model, the response surface, to represent the objective function (e.g., yield) by parameters that link the objective function to the optimization variables (e.g., reaction temperature, contact time, and reagent concentration).[3,4] these methods rely on the response surface providing a good approximation the actual system
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