Bubble absorption enhancement in water-based nanofluids using nickel oxide nanoparticles in the presence of surfactant

Subject Areas :

Danial  Jafari Farsaani ¹ (Department of Chemical Engineering, Shahreza Branch, Islamic Azad University, Shahreza, Iran,)
Elham  Ameri ² (Department of Chemical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran.)

Received: 2022-04-03 Accepted : 2022-10-09 Published : 2023-05-22

Keywords: Nanofluid, Nickel oxide nanoparticles, Ceramic, gas absorption, corrolation,

Abstract :

To solve the problems caused by the use of chemical solvents such as amine solutions and caustic solution, a single bubble adsorption tower was used to investigate the effect of water-based nanofluids with nickel oxide nanoparticles on the CO2 adsorption process. CO2 was introduced as single bubbles from the end of a column, and the mass transfer coefficients and adsorption rates were investigated. The results showed that nickel oxide nanoparticles are hydrophobic and the addition of surfactant to nanofluid increases the surface electric charge of nickel oxide nanoparticles and increases the surface polarity for gas absorption. In this way, carbon dioxide gas is absorbed on the surface of nanoparticles due to its very polar nature, and this phenomenon increased the amount of gas absorption in the nanofluid by 270% compared to the base fluid.The maximum mass transfer flux for adsorption of CO2 with nanofluids containing nickle oxide nanoparticles was observed in the weight fraction of nanoparticles of 0.1%. To investigate the effect of important parameters on the mass transfer process in a single bubble tower, the parameters of nanoparticle weight fraction, gas injection nozzle diameter, with different levels were investigated. Finally, an experimental relationship was presented to estimate the mass transfer coefficient of CO2 gas, which is a function of the flow regime and microscopic structure of nanoparticles. The results showed that the amount of computational error for the proposed model is less than 20% and this model can estimate the laboratory results with a suitable approximation.

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