Do adsorbent screening metrics predict process performance? A process optimisation based study for post-combustion capture of CO2
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...
| Autores: | , , |
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| Tipo de documento: | artigo |
| Estado: | Versão publicada |
| Data de publicação: | 2015 |
| País: | Argentina |
| Recursos: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositório: | CONICET Digital (CONICET) |
| Idioma: | inglês |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/43192 |
| Acesso em linha: | http://hdl.handle.net/11336/43192 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Co2 Capture Adsorption Screening Optimization https://purl.org/becyt/ford/2.4 https://purl.org/becyt/ford/2 |
| Resumo: | 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. |
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