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Experimental Study on the Throttling Effect of SC-CO2 Containing Ethanol System Flowing Through the Coaxial Annular Nozzle and the Prediction Based on Artificial Neural Network

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Abstract

Supercritical fluid process has been used in several industrial fields as a novel technique to produce nanoparticles. Throttling effect may occur when supercritical CO2 and ethanol passes through a coaxial annular nozzle together in supercritical antisolvent, exerting considerable negative effects on particle size and morphology, thus, it is imperative to study the throttling effect. A new experimental system was developed to study the effects of inlet temperature, inlet pressure and ethanol content on the throttling effect of supercritical CO2 system using a 100 μm diameter coaxial annular nozzle in this paper. Supercritical CO2 and desired amount of ethanol were mixed in the coaxial annular nozzle and the temperature and pressure at the inlet and outlet of the nozzle were recorded by the data acquisition system. The results show that high inlet temperature and ethanol content can acquire higher throttling temperature while high inlet pressure enhances the throttling effect, obtaining a lower throttling temperature. The initial density and phase state were confirmed to be the key factors to affect the throttling effect. In order to accurately predict the throttling effect, a back-propagation neural network model with the Correlation Coefficient of 0.99 531 and the Mean Retive Error ranging from 1.0841 % to 1.3209 % was proposed based on the experimental data, which demonstrated that it can be used as a powerful tool to predict the throttling effect of supercritical CO2 containing ethanol system.

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Acknowledgments

The work reported here was supported by National Natural Science Foundation of China (Project No. 21676162) and Science and Technology Development Plan Project of Shandong Province (2014GSF117026). The authors thankfully acknowledge all these supports.

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Authors and Affiliations

  1. College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao, 266061, China

    Zhuo Zhang, Qingling Li & Dedong Hu

  2. Center for New Drug Pharmacological Research of Lunan Pharmaceutical Group, State Key Laboratory, Generic Manufacture Technology of Chinese Traditional Medicine, Linyi, 273400, China

    Guimin Zhang, Guizhou Hao, Weiqiang Wang & Rongkai Cao

  3. School of Mechanical Engineering, Shandong University, Jinan, 250061, China

    Fayu Sun

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  1. Zhuo Zhang
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  2. Guimin Zhang
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  3. Guizhou Hao
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Correspondence to Dedong Hu.

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Zhang, Z., Zhang, G., Hao, G. et al. Experimental Study on the Throttling Effect of SC-CO2 Containing Ethanol System Flowing Through the Coaxial Annular Nozzle and the Prediction Based on Artificial Neural Network. Int J Thermophys 42, 149 (2021). https://doi.org/10.1007/s10765-021-02896-9

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  • DOI: https://doi.org/10.1007/s10765-021-02896-9

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