Do adsorbent screening metrics predict process performance? A process optimisation based study for post-combustion capture of CO2

Autores
Rajagopalan, Ashwin Kumar; Avila, Adolfo María; Rajendran, Arvind
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Recent interest in carbon dioxide capture has led to development of hundreds of adsorbents. The selection of the adsorbents and analyzing their performance for a given process is a challenging task. Usually, the expected performances of these adsorbents are evaluated by inspecting the isotherms and using simple adsorbent screening metrics (selectivities, working capacities, figures of merit, etc.). In this work, a process-optimization based approach to screen adsorbents for post-combustion CO2 capture for vacuum swing adsorption (VSA) is presented. Four different adsorbents (Mg-MOF-74, UTSA-16, Zeolite 13X and activated carbon) were chosen as test materials and were subjected to process-optimization studies on a 4-step PSA cycle with light product pressurization (LPP). Two kinds of process optimization studies were performed. The first to maximize purity and recovery and the second to minimize energy consumption and maximize productivity subject to purity/recovery constraints. This study highlights that most commonly used adsorbent metrics do not necessarily rank the performance of the materials at a process scale. It is also shown that the process performance was more sensitive to the affinity of N2 than that of CO2.
Fil: Rajagopalan, Ashwin Kumar. University of Alberta; Canadá
Fil: Avila, Adolfo María. University of Alberta; Canadá. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Rajendran, Arvind. University of Alberta; Canadá
Materia
Co2 Capture
Adsorption
Screening
Optimization
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/43192

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spelling Do adsorbent screening metrics predict process performance? A process optimisation based study for post-combustion capture of CO2Rajagopalan, Ashwin KumarAvila, Adolfo MaríaRajendran, ArvindCo2 CaptureAdsorptionScreeningOptimizationhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2Recent interest in carbon dioxide capture has led to development of hundreds of adsorbents. The selection of the adsorbents and analyzing their performance for a given process is a challenging task. Usually, the expected performances of these adsorbents are evaluated by inspecting the isotherms and using simple adsorbent screening metrics (selectivities, working capacities, figures of merit, etc.). In this work, a process-optimization based approach to screen adsorbents for post-combustion CO2 capture for vacuum swing adsorption (VSA) is presented. Four different adsorbents (Mg-MOF-74, UTSA-16, Zeolite 13X and activated carbon) were chosen as test materials and were subjected to process-optimization studies on a 4-step PSA cycle with light product pressurization (LPP). Two kinds of process optimization studies were performed. The first to maximize purity and recovery and the second to minimize energy consumption and maximize productivity subject to purity/recovery constraints. This study highlights that most commonly used adsorbent metrics do not necessarily rank the performance of the materials at a process scale. It is also shown that the process performance was more sensitive to the affinity of N2 than that of CO2.Fil: Rajagopalan, Ashwin Kumar. University of Alberta; CanadáFil: Avila, Adolfo María. University of Alberta; Canadá. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Rajendran, Arvind. University of Alberta; CanadáElsevier2015-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/43192Rajagopalan, Ashwin Kumar; Avila, Adolfo María; Rajendran, Arvind; Do adsorbent screening metrics predict process performance? A process optimisation based study for post-combustion capture of CO2; Elsevier; International Journal of Greenhouse Gas Control; 46; 11-2015; 76-851750-5836CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.ijggc.2015.12.033info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S175058361530181Xinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:54:17Zoai:ri.conicet.gov.ar:11336/43192instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:54:17.375CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Do adsorbent screening metrics predict process performance? A process optimisation based study for post-combustion capture of CO2
title Do adsorbent screening metrics predict process performance? A process optimisation based study for post-combustion capture of CO2
spellingShingle Do adsorbent screening metrics predict process performance? A process optimisation based study for post-combustion capture of CO2
Rajagopalan, Ashwin Kumar
Co2 Capture
Adsorption
Screening
Optimization
title_short Do adsorbent screening metrics predict process performance? A process optimisation based study for post-combustion capture of CO2
title_full Do adsorbent screening metrics predict process performance? A process optimisation based study for post-combustion capture of CO2
title_fullStr Do adsorbent screening metrics predict process performance? A process optimisation based study for post-combustion capture of CO2
title_full_unstemmed Do adsorbent screening metrics predict process performance? A process optimisation based study for post-combustion capture of CO2
title_sort Do adsorbent screening metrics predict process performance? A process optimisation based study for post-combustion capture of CO2
dc.creator.none.fl_str_mv Rajagopalan, Ashwin Kumar
Avila, Adolfo María
Rajendran, Arvind
author Rajagopalan, Ashwin Kumar
author_facet Rajagopalan, Ashwin Kumar
Avila, Adolfo María
Rajendran, Arvind
author_role author
author2 Avila, Adolfo María
Rajendran, Arvind
author2_role author
author
dc.subject.none.fl_str_mv Co2 Capture
Adsorption
Screening
Optimization
topic Co2 Capture
Adsorption
Screening
Optimization
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Recent interest in carbon dioxide capture has led to development of hundreds of adsorbents. The selection of the adsorbents and analyzing their performance for a given process is a challenging task. Usually, the expected performances of these adsorbents are evaluated by inspecting the isotherms and using simple adsorbent screening metrics (selectivities, working capacities, figures of merit, etc.). In this work, a process-optimization based approach to screen adsorbents for post-combustion CO2 capture for vacuum swing adsorption (VSA) is presented. Four different adsorbents (Mg-MOF-74, UTSA-16, Zeolite 13X and activated carbon) were chosen as test materials and were subjected to process-optimization studies on a 4-step PSA cycle with light product pressurization (LPP). Two kinds of process optimization studies were performed. The first to maximize purity and recovery and the second to minimize energy consumption and maximize productivity subject to purity/recovery constraints. This study highlights that most commonly used adsorbent metrics do not necessarily rank the performance of the materials at a process scale. It is also shown that the process performance was more sensitive to the affinity of N2 than that of CO2.
Fil: Rajagopalan, Ashwin Kumar. University of Alberta; Canadá
Fil: Avila, Adolfo María. University of Alberta; Canadá. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Rajendran, Arvind. University of Alberta; Canadá
description Recent interest in carbon dioxide capture has led to development of hundreds of adsorbents. The selection of the adsorbents and analyzing their performance for a given process is a challenging task. Usually, the expected performances of these adsorbents are evaluated by inspecting the isotherms and using simple adsorbent screening metrics (selectivities, working capacities, figures of merit, etc.). In this work, a process-optimization based approach to screen adsorbents for post-combustion CO2 capture for vacuum swing adsorption (VSA) is presented. Four different adsorbents (Mg-MOF-74, UTSA-16, Zeolite 13X and activated carbon) were chosen as test materials and were subjected to process-optimization studies on a 4-step PSA cycle with light product pressurization (LPP). Two kinds of process optimization studies were performed. The first to maximize purity and recovery and the second to minimize energy consumption and maximize productivity subject to purity/recovery constraints. This study highlights that most commonly used adsorbent metrics do not necessarily rank the performance of the materials at a process scale. It is also shown that the process performance was more sensitive to the affinity of N2 than that of CO2.
publishDate 2015
dc.date.none.fl_str_mv 2015-11
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/43192
Rajagopalan, Ashwin Kumar; Avila, Adolfo María; Rajendran, Arvind; Do adsorbent screening metrics predict process performance? A process optimisation based study for post-combustion capture of CO2; Elsevier; International Journal of Greenhouse Gas Control; 46; 11-2015; 76-85
1750-5836
CONICET Digital
CONICET
url http://hdl.handle.net/11336/43192
identifier_str_mv Rajagopalan, Ashwin Kumar; Avila, Adolfo María; Rajendran, Arvind; Do adsorbent screening metrics predict process performance? A process optimisation based study for post-combustion capture of CO2; Elsevier; International Journal of Greenhouse Gas Control; 46; 11-2015; 76-85
1750-5836
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ijggc.2015.12.033
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S175058361530181X
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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