Design of Microelectronic Cooling Systems Using a Thermodynamic Optimization Strategy Based on Cuckoo Search

This paper proposes a conceptual design strategy for an optimal cooling system, typically used in several microelectronic devices. The methodology was implemented using the entropy generation minimization (EGM) criterion, powered by the cuckoo search (CS) algorithm. EGM-CS methodology was addressed to design rectangular microchannel heat sinks, utilizing high thermal conductive graphite as build material and a water-based colloid as coolant. This strategy was implemented under different hydrodynamic conditions, where it showed strong capability to achieve optimal designs with flowing nanofluids in either laminar or turbulent regimes. In addition, two types of nanoparticles were considered, i.e., Al and TiO
₂
, with several values of volume fraction, as a passive mechanism for enhancing overall system performance. It was corroborated that all considered flowing colloids in laminar regime improve the thermal efficiency of the system. Moreover, an additional enhancement of this performance was observed with smaller nanoparticle concentrations (e.g., 0.01 wt/wt%), which also reduces the side effects due to nanoclustering. Furthermore, fluids with titanium dioxide nanoparticles showed slightly better thermal performance enhancement compared to aluminum particles.