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978-3-8439-3980-5, Reihe Verfahrenstechnik
Philipp Haug Experimental and theoretical investigation of gas purity in alkaline water electrolysis
167 Seiten, Dissertation Technische Universität Clausthal (2019), Softcover, A5
Nowadays hydrogen, which is required in huge quantities for many important industrial processes such as ammonia synthesis, is still being produced through inexpensive, but greenhouse gas emitting processes like steam reforming and coal gasification. In the course of the energy turnaround hydrogen is often seen as the fuel of the future. Within the framework of the power-to-gas concept (PtG), particularly water electrolysis is often discussed as the key technology for future synthesis of hydrogen.
Alkaline water electrolysis has been applied in the industry for decades, but no further research activities have been undertaken for quite some time. For realization and improvement of the PtG concept precise knowledge, especially about the dynamic behavior of the electrolysis process, is indispensable. Usually the acceptable part-load operation of an alkaline water electrolyzer is limited to about 10% - 40% of the nominal load. Below this working range the hydrogen quality is significantly reduced through contamination with oxygen, which is also being produced in the process.
In this study, classical mixing of catholyte and anolyte as well as several other electrolyte management concepts are examined with respect to the resulting gas purity. Next to the classical strategy, the complete electrolyte separation or the application of periodic separation-mixing-sequences are conceivable, which promise a reduction of the product gas contamination. In order to investigate these concepts, experiments are carried out in a custom-built laboratory electrolyzer under industrially relevant conditions, which allow an evaluation of the influence of various process parameters and the quantification of the prevailing crossover mechanisms. In addition, a model is being developed that can be used for the support of the experiments and for the optimization of the process.