Modeling and Optimizing N/O-Enriched Bio-Derived Adsorbents for CO<sub>2</sub> Capture: Machine Learning and DFT Calculation Approaches-Reference-Cited by-同舟云学术

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Modeling and Optimizing N/O-Enriched Bio-Derived Adsorbents for CO₂ Capture: Machine Learning and DFT Calculation Approaches

Published:2022-07-14 Issue:30 Volume:61 Page:10670-10688
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Rahimi Mohammad¹^ORCID,Abbaspour-Fard Mohammad Hossein¹,Rohani Abbas¹,Yuksel Orhan Ozge²^ORCID,Li Xiang³

Affiliation:

1. Department of Biosystems Engineering, Ferdowsi University of Mashhad, Mashhad 9177948974, Iran

2. Department of Chemical Engineering, Hacettepe University, Ankara 06800, Turkey

3. Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System, Xi’an Jiaotong University, Xi’an 710049, China

Funder

Ferdowsi University of Mashhad

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.2c01887

Reference113 articles.

1. The swing adsorption reactor cluster (SARC) for post combustion CO2 capture: Experimental proof-of-principle

2. Sustainable gasification biochar as a high efficiency adsorbent for CO2 capture: A facile method to designer biochar fabrication

3. Carbon dioxide capture in biochar produced from pine sawdust and paper mill sludge: Effect of porous structure and surface chemistry

4. Stability of amine-functionalized CO2 adsorbents: a multifaceted puzzle

5. Biomass-derived activated carbon with simultaneously enhanced CO2 uptake for both pre and post combustion capture applications

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