Investigation and optimization of ultrasound-assisted process of carbon dioxide absorption into amine-based nanofluids

Abstract

In this study, the effect of the simultaneous application of the nanofluids and ultrasound waves on the carbon dioxide (CO2) absorption process has been investigated in a batch system. For this purpose, the methyl diethanolamine (MDEA)-based nanofluids containing zinc oxide (ZnO) nanoparticles were prepared through a two-step procedure and used as the liquid absorbents. The absorption experiments were carried out using the pressure drop method in an isothermal reactor equipped with a high-frequency (1.7 MHz) ultrasound transducer. The effects of various factors, including the temperature, initial pressure, MDEA concentration, nanoparticle concentration, and ultrasonic power upon the absorption process, were investigated using the design-of-experiments (DOE) method. At first, a parameter screening was applied to determine the significant factors affecting the process. After removing the insignificant parameters, the process optimization was performed using the response surface method (RSM). The results indicated that the employment of high-frequency ultrasound waves had a great effect on improving the CO2 absorption rate. By using a small amount of ultrasonic power (3.9 W), the absorption rate was increased by 632%. The results of the screening revealed that among the mentioned input factors, the effects of the ultrasound power, MDEA concentration, and initial pressure on the process were significant, and the effects of the other factors were insignificant. Based upon the results, among the input factors, the ultrasonic power had the greatest impact on the CO2 absorption rate. The results also revealed that the utilization of ZnO nanoparticles in the ultrasound-assisted process of CO2 absorption, could lead to a slight reduction in the absorption rate, resulting from attenuation of the ultrasonic wave propagation in the liquid due to the presence of nanoparticles. The results of RSM optimization demonstrated that the best model to describe the process behavior was the quadratic model. A polynomial relation was also presented in terms of the factors affecting the process. Additionally, the optimal values of the input factors were determined to attain the maximum absorption rate by using RSM optimization.