Optimization of a boron nitride nanotubes nanofluid-cooled microchannel heat sink at different concentrations

The microchannel heat sink (MCHS) has become the most relevant micro-heat exchanger for a small area in need of an effective high removal system. However, dissipation from microchips where MCHS is utilized—the microprocessor and microcontroller—is getting higher with sizes smaller. A more coolant needed to address increasing load microchip nanofluid, nanosized particles dispersed base fluid, among those explored. This paper reports new potential use non-metallic boron nitride nanotube (BNN), that capable improving overall performance rectangular MCHS. heuristic method, multi-objective genetic algorithm (MOGA), employed simultaneously minimize thermal resistance pressured drop nanotubes (BNN) nanofluid-cooled obtain optimized dimensions at various mass concentrations. method achieving conflicting objectives, minimization pressure drop; increase former decreases latter vice versa. In addition, experimental thermophysical properties BNN nanofluid are used provide reliability optimization outcomes identifying best concentration cooling 50 °C. results showed as decreases, decreases. For concentrations 0.001, 0.003, 0.005, 0.01 0.03% lowest, 0.0711 K/W mass.%. 0.0115 W. lowered by 5.34% compared water same operating conditions. These indicate great electronics Optimization MOGA provides fast analysis into potentials any coolants applications shown here, being provided experimentally obtained properties.