Design and Optimization of Hierarchically Ordered Porous Structures for Solar Thermochemical Fuel Production Using a Voxel-Based Monte Carlo Ray-Tracing Algorithm

Abstract

Porous structures can be favorably used in solar thermochemical reactors for the volumetric absorption of concentrated solar radiation. In contrast to isotropic porous topologies, hierarchically ordered porous topologies with stepwise optical thickness enable more homogeneous radiative absorption within the entire volume, leading to a higher and more uniform temperature distribution and, consequently, a higher solar fuel yield. However, their design and optimization require fast and accurate numerical tools for solving the radiative exchange at the pore level within their complex architectures. Here, we present a novel voxel-based Monte Carlo ray-tracing algorithm that discretizes the pore-level domain into a 3D binary digital representation of solid/void voxels. These are exposed to stochastic rays undergoing reflection, absorption, and re-emission at the ray-solid intersection found by querying the voxel value along the ray path. Temperature distributions are found at radiative equilibrium. The algorithm’s fast execution allows its use in a gradient-free optimization scheme. Three hierarchically ordered topologies with parametrized shapes (square grids, Voronoi cells, and sphere lattices) exposed to 1000 suns radiative flux are optimized for maximum solar fuel production based on the thermodynamics of a ceria-based thermochemical redox cycle for splitting H₂O and CO₂. The optimized graded-channeled structure with square grids achieves a 4-fold increase in the volume-specific fuel yield compared to the value obtained for an isotropic reticulated porous structure.