Bayesian Symbolic Learning to Build Analytical Correlations from Rigorous Process Simulations: Application to CO<sub>2</sub> Capture Technologies-Reference-Cited by-同舟云学术

Bayesian Symbolic Learning to Build Analytical Correlations from Rigorous Process Simulations: Application to CO₂ Capture Technologies

Published:2022-11-02 Issue:45 Volume:7 Page:41147-41164
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Negri Valentina¹^ORCID,Vázquez Daniel¹^ORCID,Sales-Pardo Marta²,Guimerà Roger²³,Guillén-Gosálbez Gonzalo¹^ORCID

Affiliation:

1. Institute for Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 1, 8093Zürich, Switzerland

2. Department of Chemical Engineering, Universitat Rovira i Virgili, Tarragona43007, Catalonia, Spain

3. ICREA, Barcelona08010, Catalonia, Spain

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.2c04736

Reference105 articles.

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5. CO2 capture from syngas by an adsorption process at a biomass gasification CHP plant: Its comparison with amine-based CO2 capture

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