Design of physical models of reaction kinetics using meta-modelling by taking the example of electrooxidation of methanol in alkaline media

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The quantitative determination of physical models of kinetics of complex (electro-)chemical reactions is essential for a deeper understanding of the processes that occur during reaction and, thus, also for knowledge-driven improvements of the kinetics. For electrochemical reactions, the challenges lie in qualitative and quantitative identification of processes, their interactions and especially their dependency on electric current and potential. In this project, a new approach for quantitative physical modelling of reaction kinetics is developed and it is applied to methanol oxidation in alkaline direct methanol fuel cells (ADMFCs).Due to the high energy density of methanol, ADMFCs are a highly attractive power supply for portable and mobile applications. Utilisation of an alkaline electrolyte allows usage of non-precious, i.e. inexpensive, metals like nickel as catalyst. ADMFCs using alkaline membrane electrolyte are not yet well investigated and their power is presently significantly lower than that of acidic methanol fuel cells. Slow kinetics of alkaline methanol oxidation is considered as one possible reason for the low performance. Due to the complex interaction of multiphase mass transport, ion transport, sorption processes and various reaction steps, analysis and identification of the kinetics of this reaction is a complex challenge, especially when porous technical electrodes are employed.Within the scope of this project, micro and macro kinetics as well as rate determining steps of alkaline methanol oxidation will be identified by suitable combination of physical model approaches and meta modelling. This is realised by combining knowledge about the single processes in the form of mathematical equations with a database of possible physical model approaches to describe further processes and dependencies on parameters. The crucial step is to further combine these physical equations with meta modelling to extract correct dependencies from experimental results. The method will be first applied to a simpler system without influence of mass transport processes to determine micro kinetics. This will be realised in experiments by using a rotating ring disc electrode (RRDE) dipped into an alkaline methanol solution. In a second step, macro kinetics will be examined at a porous, technical anode of a fuel cell. The measurement data that is required for model identification is generated by experimental examinations at both, RRDE level and cell level. The empirical equations of the meta model will finally be replaced stepwise by physical equations until a completely physical model is formed that describes the reaction processes at an anode of an ADMFC. Analysing this model will provide a deeper understanding of the reaction processes.