Analysis of a Batch Adsorber Analogue for Rapid Screening of Adsorbents for Postcombustion CO 2 Capture
A simplified proxy model based on a well-mixed batch adsorber for vacuum swing adsorption (VSA) based CO2 capture from dry post-combustion flue gas is presented. A graphical representation of the model output allows for the rationalization of broad trends of process performance. The results of the s...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2019 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/119059 |
| Acceso en línea: | http://hdl.handle.net/11336/119059 |
| Access Level: | acceso abierto |
| Palabra clave: | Adsorption CO2 capture Adsobent screening PSA https://purl.org/becyt/ford/2.4 https://purl.org/becyt/ford/2 |
| Sumario: | A simplified proxy model based on a well-mixed batch adsorber for vacuum swing adsorption (VSA) based CO2 capture from dry post-combustion flue gas is presented. A graphical representation of the model output allows for the rationalization of broad trends of process performance. The results of the simplified model are compared with a detailed VSA model that takes into account mass and heat transfer, column pressure drop and column switching, in order to understand its potential and limitations. A new classification metric to identify whether an adsorbent can produce CO2 purity and recovery that meet current US Department of Energy (US-DOE) for post-combustion CO2 capture and to calculate the corresponding parasitic energy is developed. The model, which can be evaluated within a few seconds, showed a classification Matthew correlation coefficient of 0.76 compared to 0.39, the best offered by any traditional metric. The model was also able to predict the energy consumption within 15% accuracy of the detailed model for 83% of the adsorbents studied. The developed metric and the correlation are then used to screen NIST/ARPA-E database to identify promising adsorbents for CO2 capture applications. |
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