An alternative method for parameter identification from temperature programmed reduction (TPR) data

The experimental method of temperature programmed reduction (TPR) for the investigation of gas–solid reactions is well established and widely used since the 1970s. With regard to the temporal and financial effort for TPR measurements, the quantitative model-based analysis of the data is not adequately developed. The TPR data analysis is comprised of two aspects: a discrete model identification and a continuous parameter optimisation. In this contribution, a general model for TPR experiments is introduced and a strategy for the model identification is proposed. This results in a large number of continuous optimisation problems which can be solved very efficiently by a proposed optimisation algorithm that is especially tailored for the problem at hand. The applicability of the method is demonstrated using TPR measurements of iron oxide in hydrogen gas.