Multiscale water transport in hydrogel-based bionic leaf coolers

Photovoltaic cells (PVCs) form a crucial part of the EU net-zero ambition, with a targeted capacity of 600 GW by 2030. However, high operating temperatures severely limit PVCs' electrical efficiency. An emerging solution is to use the hydrogel-based bionic leaf cooler (HBLC). The HBLC mimics the structure of plant leaves using fibre bundles and hydrogel particles, to achieve pump-free water transport and efficient evaporative cooling, boosting PVCs' electrical efficiency by 10+%. Despite its massive potential, HBLC development is hindered by our limited understanding of its multiscale water transport mechanisms and the lack of high-fidelity simulation tools. This project will integrate multidisciplinary expertise of the fellow and host to address the challenges with three objectives: (1) develop a high-fidelity multiscale computational model for water transport in HBLC, incorporating the coupled flow, heat transfer, and evaporation, and resolving the distinct length scales; (2) uncover the fundamental mechanisms that the flow, heat transfer, and evaporation interact to achieve self-adaptive high-rate evaporative cooling, and elucidate the dependence of the HBLC cooling performance on system parameters, e.g., the geometries and materials properties of the fibre bundles and hydrogel particles; (3) develop a machine-learning-assisted optimization tool to identify optimum HBLC designs. The project will lead to a step change in high-fidelity modelling and scientific understanding of the multiscale water transport in HBLCs. These could lead to a paradigm shift from trial-and-error experiment-based to high-fidelity simulation-based design of high-performance, low-cost, eco-friendly HBLCs for PVCs. With the developed optimization tool, the project target is a >16% relative increase in PVC efficiency through HBLC cooling, which can generate >100 TWh of electricity and reduce >21 million tons of CO2 emissions annually by 2030, contributing to the EU's net-zero ambition.