Hierarchical Bayesian estimation for adsorption isotherm parameter determination

Shih, Chunkai; Park, Jongwoo; Sholl, David S.; Realff, Matthew J.; Yajima, Tomoyuki; Kawajiri, Yoshiaki

doi:10.1016/j.ces.2019.115435

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DOE OSTI · 1799844

Hierarchical Bayesian estimation for adsorption isotherm parameter determination

Shih, Chunkai·Park, Jongwoo·Sholl, David S.·Realff, Matthew J.·Yajima, Tomoyuki·Kawajiri, Yoshiaki

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Abstract

Estimation of isotherm model parameters from experimental data is necessary in adsorption process modeling. To facilitate isotherm modeling, databases that store experimental data exist. Nevertheless, data inconsistency among different researchers must be resolved to find a single set of isotherm parameters from multiple data sets. Herein, we propose a hierarchical Bayesian estimation method to quantify the discrepancy by a multiplicative factor while simultaneously obtaining the probability distributions of a single set of isotherm parameters. This approach also allows us to identify outliers, which are data sets that are not in agreement with other sets. The proposed approach is demonstrated for the case of CO 2 adsorption in the metal-organic framework UiO-66.

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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY adsorption isotherm hierarchical Bayesian estimation isotherm model parameters probability distributions statistical analysis

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Shih, Chunkai, Park, Jongwoo, Sholl, David S., Realff, Matthew J., Yajima, Tomoyuki, Kawajiri, Yoshiaki. 2019-12-12. Hierarchical Bayesian estimation for adsorption isotherm parameter determination. https://doi.org/10.1016/j.ces.2019.115435

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