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Batch Adsorber Analogue Model for Rapid Screening of Large Adsorbent Databases for Post - Combustion CO2 Capture

  • Author / Creator
    Subramanian Balashankar, Vishal
  • A simplified proxy model based on a well-mixed batch adsorber for vacuum swing adsorption (VSA) based carbon dioxide 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 carbon dioxide purity and recovery that meet current US Department of Energy (US-DOE) for post-combustion carbon dioxide capture and to calculate the corresponding parasitic energy is developed. The model, which can be evaluated within a few seconds, showed a classification Matthews Correlation Coefficient (MCC) of 0.77 compared to 0.39, the best offered by any traditional metric. The model was 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 carbon dioxide capture applications. More than hundred thousand adsorbents from carbon capture materials database (CCMDB) are then screened for the high performing adsorbents using BAAM. The effects of key adsorbent characteristics on the process performance are also studied. A detailed model optimization is then conducted to validate the BAAM's predictions. The characteristics of an ideal adsorbent are then found by a parametric study using the non-linearity plot (NLP).

  • Subjects / Keywords
  • Graduation date
    Spring 2019
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/r3-k10c-3581
  • License
    Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.