Process optimization
With the help of our simulation model described in the previous chapter, computational process optimization methods can now be used to mathematically optimize process conditions and find the optimal operating windows for the multi-enzyme cascade reaction sequence implemented in our miniplant. More specifically, the Institute of Process and Plant Engineering at Hamburg University of Technology has developed the multi-objective process optimization tool “Advanced Process Optimizer” (Adv:PO V0.7), which can be coupled with flow sheet simulator tools such as Aspen Custom Modeler® . The Adv:PO makes use of a genetic algorithm and has been successfully applied to various chemical and biotechnological processes. The implementation of this tool, together with our novel mathematical model, allows for in-depth analysis and process improvement of the multi-enzyme cascade reaction sequence to find optimal operating conditions.
During the optimization run, process variables, i.e. the concentrations of each component, are varied between physically defined limits. Such constraints are determined by component solubility and by the capacity of the miniplant. Multi-objective mathematical functions are defined in order to find the optimal solutions for any experimental variable of the cascade reaction. In this paper we focus exemplarily on presenting our results for maximizing CCI space-time yield in steady-state operation, while at the same time minimizing the amount of the costly cofactors NADH and NAD+. Such focus will broaden the single-criterion-approach of increasing product space-time yield by the economic factor of avoiding unnecessary amounts of costly substances. The objective functions f1 and f2 in equation (14) and (15) represent the maximizing of CCI space-time yield and the minimizing of the cofactor input. They are complemented by physical constraints. As shown in equation (16), the concentration for each component must range within physically reasonable values. Moreover, all dimensions, flow rates, temperatures, and kinetic parameters must stay constant throughout the optimization run. Possible trivial solutions of zero are not accepted: a minimum CCI space-time yield of 0.1 mmol/(l∙h) is set as a constraint for valid solutions.