Computationally Accelerated Discovery and Experimental Demonstration of High-Performance Materials for Advanced Solar Thermochemical Hydrogen Production
Recipient University of Colorado Boulder/UCB (PI: Charles Musgrave)
Subs University of Colorado Boulder/UCB (PI: Aaron Holder and PI: Alan Weimer)
Water Splitting Technology STCH
Abstract The University of Colorado Boulder (CU) is leading this collaborative computational and experimental project to develop new materials for solar thermochemical water splitting (STWS) for renewable hydrogen production. Professor Charles Musgrave is the Primary Investigator (PI), and will team with Profs. Alan Weimer (co-PI) and Aaron Holder (CU) and leverage state-of-the-art expertise and capabilities at Sandia National Laboratories, Idaho National Laboratory, and the National Renewable Energy Laboratory to design and test novel materials for STWS. The project, called “Computationally Accelerated Discovery and Experimental Demonstration of High-Performance Materials for Advanced Solar Thermochemical Hydrogen Production” focuses on computationally accelerated discovery and design and experimental demonstration of metal oxide materials to mediate the efficient conversion of solar energy and water into hydrogen.
Two-step STWS provides a promising route for efficient conversion of solar energy to fuels because it utilizes the entire solar spectrum and minimizes the number of conversion steps to produce H2 from H2O and sunlight. However, to commercialize STWS, significant technical challenges related to the discovery of effective water splitting materials and the development of efficient systems to utilize these materials remain. Despite the examination of a relatively large number of redox materials, an optimal material to drive this process has yet to be developed. This project will accelerate the RD&D of new, durable materials for solar thermochemical water splitting through a computationally accelerated and experimentally validated materials-by-design approach using advanced machine-learned models to optimize material thermodynamic and kinetic properties for STWS that meet or exceed DOE targets for economic (less than $2/kg H2) and efficient (greater than 20% solar to hydrogen conversion efficiency) H2 production.
This project will focus on the discovery, design and demonstration of mixed metal oxides for STWS, with a predominant emphasis on perovskite and spinel metal oxides, which meet or exceed DOE targets. Materials will be computationally screened and experimentally validated for high hydrogen productivity, fast reduction and oxidation kinetics, low thermal reduction temperatures, and long term stability and reactivity using coupled quantum mechanical modeling and machine-learned models where machine learned models of the formation energy of materials enable the high-throughput initial screening of large numbers of candidate materials. These models are essential for overcoming the limitations of high throughput computational evaluation of processes that occur at elevated temperatures because the use of the correct high temperature structure is essential to obtaining accurate data for screening important thermodynamic and kinetic properties of metal oxides. The redox stability of metal oxides that split water via an oxygen vacancy mediated mechanism will be evaluated, and the materials’ thermodynamic and kinetic properties will be tuned through topological (structure and coordination) and compositional (doping) control. In order to validate models and demonstrate the performance of predicted materials, experimental testing will be conducted on promising active materials to measure H2 production, equilibrium oxygen vacancy concentration, and intrinsic material kinetics. Experimental work will be carried out in conjunction with Prof. Alan Weimer at CU as well as through collaborations with Sandia and Idaho National Laboratories.