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- W2017175265 abstract "Abstract CO2 emission from burning fossil fuels has been identified as the major contributor to the increase in atmospheric CO2 levels that can potentially lead to global climate changes. Among main methods that are being developed for CO2 capture and separation, carbon dioxide adsorption is of great interest due to its low energy consumption, low equipment cost and easiness for application. In this work, a new simple-to-use correlation, which is easier than current available models involving a large number of parameters, requiring more complicated and longer computations, is presented to predict accurately the carbon dioxide adsorption isotherms for a molecular sieve as a function of temperature and carbon dioxide partial pressure. This correlation predicts the carbon dioxide adsorption isotherms for carbon dioxide partial pressures and temperatures up to 120 kPa and 470 K respectively. The promising method to develop correlation for accurate prediction of carbon dioxide adsorption isotherms could be extended for CO2 capture and separation for the wide range of adsorbents including various molecular sieves just by readjusting the tuned coefficients. The average absolute deviation between reported data and the proposed correlation is around 4%. Simple-to-use approach can be of immense practical value for the Engineers and Scientists to have a quick check on adsorption capacities of a given adsorbent at various temperatures and pressures without performing any experimental measurements. In particular, personnel dealing with regulatory bodies of greenhouse gas abatement, process industries would find the proposed approach to be user friendly involving no complex expressions with transparent calculations." @default.
- W2017175265 created "2016-06-24" @default.
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- W2017175265 date "2009-08-04" @default.
- W2017175265 modified "2023-09-26" @default.
- W2017175265 title "Rapid Prediction of Carbon Dioxide Adsorption Isotherms for Molecular Sieves Using Simple Correlation" @default.
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- W2017175265 doi "https://doi.org/10.2118/122882-ms" @default.
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