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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/43192
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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 |
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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 |
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reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
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Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
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dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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13.13397 |