Description

Electrochemical processes are at the heart of a multitude of industrial activities like electrowinning and electrorefining of metals, electrosynthesis, plating, electro-chemical forming and machining, etching, polishing, anodizing, protection against corrosion, batteries and fuel cells, waste water treatment. In order to remain competitive in those sectors, product innovation is essential. Hence, there is a continuous search for novel products and more advanced technologies. On the other side, efforts are concentrated on the optimization of existing processes to meet the ever higher quality requirements together with an improved efficiency and reduced production and ecological costs.

Whether it is for the design of a new electrochemical reactor, or the optimization of an existing electrochemical process, a mechanistic comprehension of the electrochemical and physical processes is essential. Many research activities are devoted to this topic in the electrochemical society. Yet a frequently encountered problem is the fact that for one specific reaction different models and parameter values are proposed, depending on the experimental technique used and the modeling assumptions made.

The aim of this project is to develop an innovative methodology to come to a quantitative, accurate and statistically founded modeling of electrochemical reactions. The project will result in a curve-fitting tool for the regression of electrochemical reaction models from experimental data.

The curve-fitting tool will rely on the following basic features: (1) a spectrum of experimental techniques, (2) an error-analysis of the experimental data, (3) a mechanistic reaction model, (4) a complete physical model, (5) powerful curve-fitting algorithms. The modeled data will be provided by a numerical software package specially designed to model electrochemical data.

This methodology will allow to: (1) put forward a model for the studied reaction that complies with experimental data originating from a variety of experimental techniques and conditions, (2) quantify the percentage that this model explains the experiments, (3) quantify the model parameters in a reliable way, (4) determine the accuracy of the model parameters.

The innovation of this project lies in the integration of all these aspects in one integrated software tool.

It is expected that the results of this project will be a most valuable tool for advanced electrochemical process design and improvement.
AcronymGOA57
StatusFinished
Effective start/end date1/01/0831/12/12

    Flemish discipline codes

  • Chemical sciences

    Research areas

  • electrochemical engineering, experimental and modeling, quantification

ID: 3245822