Preparation and characterisation of physicochemical properties of aluminium oxide (Al2O3) – water nanofluids using two step methods

• Main Author: Nur Atikah , Ali
• Format: Undergraduates Project Papers
• Language: English
• Published: 2010
• Subjects: TP Chemical technology
• Online Access: http://umpir.ump.edu.my/id/eprint/5268/1/CD5481.pdf; http://umpir.ump.edu.my/id/eprint/5268/

Nanofluids is a kind of new engineering material which consisting of solid nanoparticles with size typically of 1-100nm by dispersing it into based fluids.This research presents the preparation of Aluminium Oxide(Al2O) nanofluids by using two-step methods.This nanofluids was prepared by dispersing Al32O nanoparticles(<50nm)in distilled water based fluids with the addition of calculated amount of Sodium Dodecylbenzene Sulphonate(SDBS)as a surfactant and absence of SDBS surfactant.The nanofluids were sonicated with ultrasonic vibrator at power of 700 Watt and frequency of 40k Hz for 15 minutes.It was tested that with the presence of surfactant in the nanofluids,the nanofluids was stable for 2 weeks.Absence of surfactant cause the small amount of particle aggregates had settled out of suspension after 1 day.Stabilization of the Al2O33 nanofluids with and without surfactant can be obtained with Transmission Electron Microscopy(TEM).Distilled water based fluids display Newtonian behavior but it transform to non-Newtonian fluid with the addition of Al2O3 nanoparticles.Viscosity of the Al2O nanofluids was measured both as a function of Al2O3 3 nanoparticles volume fraction and temperature between 30oC and 60oC using Brookfield DV- II Pro Viscometer and results showed that no anomolous effects of viscosity with increasing of temperatures.The range of the viscosity from 30oC and 60oC is between 4.05 cP to 2.55 cP and viscosity of nanofluids increase with the Al2O nanoparticles volume concentration.The result then was compared with the previous researcher’s experimental data.Thermal conductivity of the Al2O3 3 nanofluids water based was predicted using regression equation then compared it with previous experimental data.