Thermal performances of hybrid nanofluids as coolant in computers using design of experiment method

Abstract

According to Gordon Moore's 1965 law, the number of transistors in a dense integrated circuit (IC) doubles approximately every two years, and this correlates with the amount of heat generated by the transistors. Due to the high demand for a better cooling system, one of the solutions to increase the cooling performance of the liquid cooling system is the use of nanofluid or hybrid nanofluid as a coolant in the liquid cooling system. The term "hybrid nanofluid" refers to a fluid containing multiple nanoparticles dispersed in a base fluid. It has excellent thermal properties which can help improve the performance of a conventional coolant. Based on the literature review, a good hybrid nanofluid requires good stability for a period of time and an optimized mixing ratio to ensure a high synergetic effect. However, there were very few studies on the impact of surfactants on thermal conductivity, and the optimization of hybrid nanofluid was limited to the One Factor at a Time method (OFAT). Therefore, this study endeavours to evaluate the stability of the hybrid nanofluid effect on thermal conductivity, to analyse the best mixing ratio of hybrid nanofluid based on thermal conductivity and viscosity using Design of Experiment (DOE), and to analyse the heat transfer performance of hybrid nanofluid in a liquid cooling system for CPU. This study was divided into three experimental works to achieve the aforementioned objectives. Titanium Dioxide (TiO2) and Graphene nanoplatelet (GNP) were mixed in distilled water using Hexadecyltrimethylammonium bromide (CTAB) as surfactant and ultrasonic vibration to increase the dispersion. The DOE analysis was conducted using Design Expert 11, which gives a more comprehensive analysis than OFAT because statistical analysis considers all possible mixing ratios within the range. Then, the best parameter of the hybrid nanofluid was used to prepare as a coolant in the liquid cooling system for the CPU for heat transfer performance analysis. The overall results showed that the prepared hybrid nanofluid was stable for 30 minutes for thermal conductivity and viscosity analysis with a ratio of 1:10 to 3:10 of surfactant to the mass of TiO2. Furthermore, the higher concentration of surfactant, the lower the thermal conductivity reading. Thus, the surfactant ratio of 1:10 is the best surfactant for hybrid nanofluid. For the mixing ratio analysis, three concentrations were used: 0.1vol%, 0.3vol%, and 0.5vol% respectively with mixing ratio and temperature as the factors while thermal conductivity and viscosity as responses. The results revealed the best parameters were 0.3vol% and 1:4 mixing ratio of TiO2-GNP. Subsequently, the best mixing ratio of hybrid nanofluid was used in the liquid cooling system for the CPU. The thermal resistance results showed that the prepared hybrid nanofluid was 2.7% lower than distilled water and the lowest than any other prepared nanofluids in the previous study. In conclusion, this study presents a better insight into the effect of surfactants on thermal conductivity, proposes a method to comprehensively investigate the mixing ratio of hybrid nanofluid as well as the heat transfer enhancement of hybrid nanofluid compared to the conventional coolant.