Lowering thermal reduction temperatures in two-step thermochemical water splitting

This thesis aims to make a contribution towards improving the operational conditions of two-step solar thermochemical technologies. One of the most important challenges affecting efficiency and cost is the high thermal reduction temperature required in these processes (in excess of 1400 °C), which affects the redox materials performance (high temperatures contribute to sintering and deactivation); the reactor operation (high temperatures implies larger reradiation losses); and the rest of the system (significant heat recovery as well as high temperature heat exchangers are required). In this context, this thesis proposes and develops two strategies for lowering the thermal reduction temperature. The first approach is to modify the thermodynamics of the STCH reactions, to lower reaction temperatures by substituting thermal energy with electricity. This process is referred to as a thermo-electrochemical cycle and helps to lower the thermal reduction temperature without decreasing the water to hydrogen conversion. The second approach is searching for novel materials using machine learning techniques in order to explore larger compositional combinations which could not be undertaken by experimental or computational chemistry methods. The exploration of materials leads to discovery of novel compositions with targeted thermodynamic properties, allowing for lower thermal reduction requirements while maintaining high water to hydrogen conversion yields. Contributions of both strategies are presented in this thesis, demonstrated theoretical and experimentally.