Experimental studies and artificial neural network modeling of surface tension of aqueous sodium L-prolinate solutions and piperazine blends

Muhammad Shuaib Shaikh; A. M. Shariff; M. A. Bustam; Sahil Garg; Khadija Qureshi; Pervez Hameed Shaikh; Inamullah Bhatti

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Experimental studies and artificial neural network modeling of surface tension of aqueous sodium L-prolinate solutions and piperazine blends

Chemical Engineering Thermodynamics | Updated：2026-01-06

- Experimental studies and artificial neural network modeling of surface tension of aqueous sodium L-prolinate solutions and piperazine blends
- Experimental studies and artificial neural network modeling of surface tension of aqueous sodium L-prolinate solutions and piperazine blends
- 中国化学工程学报（英文版） 2019年27卷第8期页码：1904-1911
- Affiliations：
  
  1. Department of Chemical Engineering, Mehran University of Engineering & Technology Jamshoro, Sindh,Pakistan,76062
  2. Research Centre(CO2RES), Universiti Teknologi PETRONAS, Bandar Seri Iskandar,Perak,Malaysia,32610
  3. School of Chemical Engineering, The University of Queensland, St Lucia,Australia,4072
  4. Office of Research Innovation and Commercialization(ORIC), Mehran University of Engineering & Technology Jamshoro, Sindh,Pakistan,76062
- Author bio：
- Funds：
- DOI：
  中图分类号：
- 纸质出版：2019
- Accepted：
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Muhammad Shuaib Shaikh, A. M. Shariff, M. A. Bustam, 等. Experimental studies and artificial neural network modeling of surface tension of aqueous sodium L-prolinate solutions and piperazine blends[J]. 中国化学工程学报（英文版）, 2019,27(8):1904-1911.

Muhammad Shuaib Shaikh, A. M. Shariff, M. A. Bustam, Sahil Garg, Khadija Qureshi, Pervez Hameed Shaikh, Inamullah Bhatti. Experimental studies and artificial neural network modeling of surface tension of aqueous sodium L-prolinate solutions and piperazine blends[J]. Chinese Journal of Chemical Engineering, 2019, 27(8): 1904-1911.
Muhammad Shuaib Shaikh, A. M. Shariff, M. A. Bustam, 等. Experimental studies and artificial neural network modeling of surface tension of aqueous sodium L-prolinate solutions and piperazine blends[J]. 中国化学工程学报（英文版）, 2019,27(8):1904-1911. DOI：

Muhammad Shuaib Shaikh, A. M. Shariff, M. A. Bustam, Sahil Garg, Khadija Qureshi, Pervez Hameed Shaikh, Inamullah Bhatti. Experimental studies and artificial neural network modeling of surface tension of aqueous sodium L-prolinate solutions and piperazine blends[J]. Chinese Journal of Chemical Engineering, 2019, 27(8): 1904-1911. DOI：

摘要

Abstract

The surface tension study is very crucial for the design of CO

gas absorption contacting equipment. The significance of the surface tension has been increasing due to its consideration in various technological fields. This property influences the mass transfer and hydrodynamics of gas absorption systems

mainly multiphase systems

in which the interface between gas and liquid exists. Therefore

in this study

surface tension of aqueous solutions of sodium L-prolinate (SP) and piperazine (PZ) blends were measured at ten different temperatures from (298.15 to 343.15) K. The SP mass fractions were 0.10

0.20

and 0.30; while the mass fractions of PZ were 0.02 and 0.05. The experimental results showed that the surface tension increase with increasing the mass fractions of SP and PZ in aqueous blends

and decrease linearly with rising temperature. The experimental data of surface tension were correlated by two empirical correlations as a function of temperature and mass fractions for estimating the predicted data using the optimized correlation coefficients. Moreover

the modeling of surface tension data was carried out using Artificial Neu

ral Network (ANN) approach. The results obtianed from ANN modeling were compared with applied empirical correlation. It was found that the ANN approach outperformed the empirical correlation used in this study. Besides

a quantitative analysis of variation (ANOVA) was performed in order to determine the significance of data. The surface tension of aqueous SP and SP + PZ was also compared with various conventional solvents.

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