Prediction and Optimization of Copper Inverse Opal Wick for Enhanced Capillary-Fed Evaporative Cooling

Capillary-fed thin-film evaporation is a promising route for passive thermal management, enabling high performance cooling devices like heat pipes and vapor chambers. The wick design is crucial, and high performance is defined by sustaining large heat fluxes at low overall thermal resistance. Previous modeling efforts on evaporator wicks have predominantly focused on silicon pillar arrays, which provide limited guidance for microporous wicks. Microporous wicks have been widely used in passive thermal management owing to its capability dissipating high heat flux by increasing the effective evaporation area and sustaining the liquid supply. In this work, we take copper inverse opal (CIO) as a representative microporous wick and develop a predictive numerical pore-scale evaporation model together with an optimization framework. The model captures pore scale complexity by computing local contact angles from surface normals to set a dry-out criterion and by evaluating thermal resistance with a spherical cap based interfacial area model. We then couple the model with a multi-objective genetic algorithm to optimize axially graded CIO wicks at a fixed overall thickness, where the pore geometry is varied section by section along the flow direction, to increase the critical heat flux (CHF) while lowering the overall thermal resistance. For designs with fixed thickness, pore-size graded CIO wicks outperform uniform-pore designs, achieving up to a 33.8% increase in CHF and a 62% reduction in thermal resistance. This framework can be extended to different microporous wicks and offers guidelines for capillary fed evaporative cooling systems.