Your Location:
Home >
Browse articles >
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

    • Chinese Journal of Chemical Engineering   Vol. 27, Issue 8, Pages: 1904-1911(2019)
    • Published:2019

    Scan QR Code

  • 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:

  •  
  •  
icon
The trial reading is over, you can activate your VIP account to continue reading.
Deactivate >
icon
The trial reading is over. You can log in to your account, go to the personal center, purchase VIP membership, and read the full text.
Already a VIP member?
Log in >

0

Views

226

Downloads

0

CSCD

Alert me when the article has been cited
Submit
Tools
Download
Export Citation
Share
Add to favorites
Add to my album

Related Articles

A new method to forecast multi-time scale load of natural gas based on augmentation data-machine learning model
Research on composite scale inhibitors for inhibiting calcium carbonate scaling in high temperature geothermal fluid
Improved neural network automation design method for energy saving and carbon emission reduction of petrochemical production processes
State surveillance and fault diagnosis of distillation columns using residual network-based passive acoustic monitoring
Prediction of ionic liquid toxicity by interpretable machine learning

Related Author

Denglong Ma
Ruitao Wu
Zekang Li
Kang Cen
Jianmin Gao
Zaoxiao Zhang
Li Shuai
Ma Yongli

Related Institution

School of Mechanical Engineering, Xi’an Jiaotong University
School of Civil Engineering and Architecture, Southwest Petroleum University
State Key Laboratory for Manufacturing System Engineering, Xi’an Jiaotong University
School of Chemical Engineering and Technology, Xi’an Jiaotong University
School of Chemical Engineering and Technology, Tianjin University
0