Two-Dimensional Flow Boiling Characteristics With Wettability Surface In Microgap Heat Sink And Heat Transfer Prediction Using Artificial Neural Network

As technology becomes increasingly miniaturized, thermal management becomes challenging to keep devices away from overheating due to extremely localized heat dissipation. Two-phase cooling or flow boiling in microspaces utilizes the highly efficient thermal energy transport of phase change from liquid to vapor. However, the excessive consumption of liquid-phase by highly localized heat source causes the two-phase flow maldistribution, leading to a significantly reduced heat transfer coefficient, high-pressure loss, and limited flow rate. In this study, flow boiling in a two-dimensional (2D) microgap heat sink with a hydrophilic coating is investigated with bubble morphology, heat transfer, and pressure drop for conventional (nonhydrophilic) and hydrophilic heat sinks. The experiments are carried out on a stainless steel (SS) plate, having a microgap depth of 170 mu m using de-ionized (DI) water at room temperature. Two different hydrophilic surfaces (partial and full channel shape) are fabricated on the heated surface to compare the thermal performance with the conventional surface. Vapor films and slugs are flushed quickly on the hydrophilic surfaces, resulting in heat transfer enhancement on the hydrophilic heat sink compared to the conventional heat sink. The channel hydrophilic heat sink shows better cooling performance and pressure stability as it provides a smooth route for the incoming water to cool the hot spot. Moreover, the artificial neural network (ANN) prediction of heat transfer coefficient shows a good agreement with the experimental results as data fit within +/- 5% average error.