Artificial Neural Networks for Accurate Prediction of Physical Properties of Aqueous Quaternary Systems of Carbon Dioxide (CO2)-Loaded 4-(Diethylamino)-2-butanol and Methyldiethanolamine Blended with Monoethanolamine-Reference-Cited by-同舟云学术

Artificial Neural Networks for Accurate Prediction of Physical Properties of Aqueous Quaternary Systems of Carbon Dioxide (CO2)-Loaded 4-(Diethylamino)-2-butanol and Methyldiethanolamine Blended with Monoethanolamine

Published:2016-10-26 Issue:44 Volume:55 Page:11614-11621
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Pouryousefi Fatemeh¹,Idem Raphael¹,Supap Teeradet¹,Tontiwachwuthikul Paitoon¹

Affiliation:

1. Clean Energy Technologies Research Institute (CETRI), University of Regina, Regina, SK S4S 0A2, Canada

Funder

Canada Foundation for Innovation

Faculty of Graduate Studies and Research, University of Regina

Natural Sciences and Engineering Research Council of Canada

Clean Energy Technologies Research Institute, University of Regina

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.iecr.6b03018

Reference21 articles.

1. Rate-Based Process Modeling Study of CO2 Capture with Aqueous Monoethanolamine Solution

2. Separation of CO2 and SO2 from flue gas streams by liquid membranes

3. Density and Viscosity of Monoethanolamine + Water + Carbon Dioxide from (25 to 80) °C

4. Experiment and model for the viscosity of carbonated MDEA–MEA aqueous solutions

5. New Analytical Technique for Carbon Dioxide Absorption Solvents

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