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Computational Investigation of Correlations in Adsorbate Entropy for Pure-silica Zeolite Adsorbents

Published

Author(s)

Christopher Rzepa, Daniel Siderius, Harold Hatch, Vincent K. Shen, Rangarajan Srinivas, Jeetain Mittal

Abstract

Vast numbers of unstudied hypothetical porous frameworks continue to spark interest in optimizing adsorption and catalytic processes Evaluating the use of such materials depends on the accessibility of thermodynamic metrics such as the free energy which, in turn, depend on satisfactory estimation or calculation of the adsorption entropy, which often remains elusive. Previous works using experimental data have demonstrated relationships between the entropy and system descriptors, allowing for sensible predictions based on more-easily obtained physical parameters. However, the resultant conclusions were based on experimental data for industrially relevant alkanes, leaving open the question of the general applicability of such relationships. In this paper, we evaluate correlations between gas-phase and adsorbed-phase entropies for a much larger and more chemically diverse set of adsorbate molecules by using force fields and statistical mechanical expressions to calculate those entropies. In total, we perform calculations for 37 molecules across 10 chemical categories available in the TraPPE force field set, as adsorbed in five siliceous zeolites. Our results show that linear correlations between the gas- and adsorbed-phase entropies persist for the much larger set of adsorbate molecules studied here, proving a much broader applicability and justifying the use of simple correlations for many adsorbates and, presumably, adsorbent materials.
Citation
Journal of Physical Chemistry C
Volume
124
Issue
30

Keywords

adsorption, entropy, molecular simulation, thermodynamics

Citation

Rzepa, C. , Siderius, D. , Hatch, H. , Shen, V. , Srinivas, R. and Mittal, J. (2020), Computational Investigation of Correlations in Adsorbate Entropy for Pure-silica Zeolite Adsorbents, Journal of Physical Chemistry C, [online], https://doi.org/10.1021/acs.jpcc.0c02671, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=930106 (Accessed October 4, 2024)

Issues

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Created June 29, 2020, Updated October 12, 2021