Jens Markert

Model-Based Optimal Design of Experiments for Determining Reaction Network Structures

A new approach for optimal experimental design has been developed to support the work of chemists and process engineers in determining reaction kinetics of complex reaction networks. The methodology is applied on sub-networks of the hydroformylation process of 1-dodecene with a Biphephos-modified rhodium catalyst in a DMF-decane thermomorphic solvent system (TMS). The isomerization and hydrogenation sub-networks are systematically analyzed with respect to parameter estimability. They are determined in a sequential approach using model-based optimal experimental design via perturbations with respect to temperature and synthesis gas pressure, and subsequently used to build up the reaction network. The focus of this contribution is the parameter estimation procedure at the very early investigation stage where model uncertainties are high. Sensitivities of sensitive parameters are increased while others are suppressed, which are carried over from the estimated sub-networks or structurally more difficult to determine. This subsequently leads to more reliable parameter estimations.