110th Anniversary: Surrogate Models Based on Artificial Neural Networks To Simulate and Optimize Pressure Swing Adsorption Cycles for CO2 Capture-Reference-Cited by-同舟云学术

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110th Anniversary: Surrogate Models Based on Artificial Neural Networks To Simulate and Optimize Pressure Swing Adsorption Cycles for CO2 Capture

Published:2019-09-05 Issue:39 Volume:58 Page:18241-18252
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Leperi Karson T.¹,Yancy-Caballero Daison¹,Snurr Randall Q.¹^ORCID,You Fengqi²^ORCID

Affiliation:

1. Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States

2. Robert Frederick Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York 14853, United States

Funder

National Science Foundation

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.9b02383

Reference48 articles.

1. Introduction to Carbon Capture and Sequestration

2. Carbon Capture

3. He, X.; Nieto, D. R.; Lindbråthen, A.; Hägg, M.B. In Process Systems and Materials for CO2 Capture; John Wiley & Sons, Ltd, 2017; pp 249–281.

4. A Technical, Economic, and Environmental Assessment of Amine-Based CO2 Capture Technology for Power Plant Greenhouse Gas Control

5. Comparative analysis of CO2 separation from flue gas by membrane gas absorption technology and chemical absorption technology in China

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