Adsorption energetics of hydrocarbons on silicalite

A Tian−Calvet type calorimeter is applied to the simultaneous determination of adsorption isotherms and heats of adsorption. This is the first of a series of studies of the effect of adsorbate size and polarity on the energetics of adsorption in zeolites. The adsorbate gases used in this study are quadrupolar (N2 and CO2) and nonpolar (Ar, O2, CH4, C2H6, and SF6). The heats of adsorption of both polar and nonpolar gases are either constant or increase with coverage, so silicalite may be classified as a relatively homogeneous adsorbent compared to X type zeolite. Reversibility was established by comparing adsorption and desorption isotherms. Reproducibility was studied by comparing runs for different samples of the same adsorbent. The average experimental error in loading is ±0.6%. The error in the isosteric heat of adsorption is ±2% for heats larger than 20 kJ/mol and ±5% for heats smaller than 20 kJ/mol.

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“…Our result for the increase in isosteric heat for the addition of a methyl group of 10.2 kJ/mol agrees well with figures of 10.0−10.4 kJ/mol. ,, …”

Section: Resultssupporting

confidence: 89%

Calorimetric Heats of Adsorption and Adsorption Isotherms. 1. O₂, N₂, Ar, CO₂, CH₄, C₂H₆, and SF₆ on Silicalite

et al. 1996

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“…The aforementioned Figures 7 and 8 show results and comparisons from the current GCMC simulation effort and ANN predictive modeling procedure with experimental and simulation results found in the literature. The simulated isotherms are in a good agreement with the existing experimental [ 34–38 ] and simulation works. [ 30–33 ] The increase of the fugacity from the lowest values (10 −7 bar) to the highest (30 bar) drives the sorption of increasing hydrocarbon amounts in the silicalite porous structure.…”

Section: Simulation Resultssupporting

confidence: 82%

“…The constructed ANNs individually use as training data sets sorption and diffusion data sets (hydrocarbon, number of atoms, temperature, fugacity, sorbed amount, loading, and self‐diffusivity) from previous simulation [ 15,30–33 ] and experimental studies [ 34–38 ] found in the literature along with the results obtained from the present GCMC and MD simulations of the pure alkanes and alkenes. Thus, it was possible to have rich data information from different sources combining experimental measurements and simulation results making the ANN predictions more accurate.…”

Section: Molecular Modeling and Simulationsmentioning

confidence: 99%

Modeling Sorption and Diffusion of Alkanes, Alkenes, and their Mixtures in Silicalite: From MD and GCMC Molecular Simulations to Artificial Neural Networks

Gurras

Gergidis

2021

Advcd Theory and Sims

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Molecular dynamics (MD) in canonical (NVT) statistical ensemble and grand canonical‐Monte Carlo (GCMC) simulations along with artificial neural network (ANN) techniques are used for the study of diffusion and sorption characteristics of small alkanes, alkenes, and their mixtures in silicalite. In particular, sorption isotherms and self‐diffusion coefficients of alkanes (ethane to hexane), alkenes (ethene to hexene), and the respective alkane–alkene mixtures (consisting of the same number of carbon atoms) in silicalite are studied. The findings are directly compared with recent magic‐angle spinning pulsed field‐gradient nuclear magnetic resonance experimental diffusivity measurements and are in close agreement. Furthermore, new results are provided for the alkane–alkene systems. The sorption data from GCMC simulations, the self‐diffusivity calculations from the MD simulations along with available experimental data are used for the development of ANN predictive modeling procedures in order to give generic sorption and diffusion predictions for pure alkanes, alkenes in different input values of fugacity, temperature, and sorbate loadings at the minimum computational resources and time. Finally, structural characteristics for pure alkane, alkenes, and alkane–alkene mixtures when confined in the silicalite framework are computed revealing sorption domains and siting preferences.

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“…6 to 10. The adsorption isotherm of pentane at 300 K is compared with experimental results of Sun et al 46 and with UA simulation results of Vlugt et al 17 Experimental data of Dubinin et al 47 and Rakhmatkariev et al 48 are not shown. They report significantly lower maximum loadings values.…”

Section: Iv1 Adsorption Isothermsmentioning

confidence: 99%

Development of a transferable guest–host force field for adsorption of hydrocarbons in zeolites : I. Reinvestigation of alkane adsorption in silicalite by grand canonical Monte Carlo simulation

Pascual

Ungerer

Tavitian

et al. 2003

Phys. Chem. Chem. Phys.

105

167

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Adsorption energetics of hydrocarbons on silicalite

Cited by 12 publications

References 2 publications

Calorimetric Heats of Adsorption and Adsorption Isotherms. 1. O₂, N₂, Ar, CO₂, CH₄, C₂H₆, and SF₆ on Silicalite

Calorimetric Heats of Adsorption and Adsorption Isotherms. 1. O₂, N₂, Ar, CO₂, CH₄, C₂H₆, and SF₆ on Silicalite

Modeling Sorption and Diffusion of Alkanes, Alkenes, and their Mixtures in Silicalite: From MD and GCMC Molecular Simulations to Artificial Neural Networks

Development of a transferable guest–host force field for adsorption of hydrocarbons in zeolites : I. Reinvestigation of alkane adsorption in silicalite by grand canonical Monte Carlo simulation

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Adsorption energetics of hydrocarbons on silicalite

Cited by 12 publications

References 2 publications

Calorimetric Heats of Adsorption and Adsorption Isotherms. 1. O2, N2, Ar, CO2, CH4, C2H6, and SF6 on Silicalite

Calorimetric Heats of Adsorption and Adsorption Isotherms. 1. O2, N2, Ar, CO2, CH4, C2H6, and SF6 on Silicalite

Modeling Sorption and Diffusion of Alkanes, Alkenes, and their Mixtures in Silicalite: From MD and GCMC Molecular Simulations to Artificial Neural Networks

Development of a transferable guest–host force field for adsorption of hydrocarbons in zeolites : I. Reinvestigation of alkane adsorption in silicalite by grand canonical Monte Carlo simulation

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Calorimetric Heats of Adsorption and Adsorption Isotherms. 1. O₂, N₂, Ar, CO₂, CH₄, C₂H₆, and SF₆ on Silicalite

Calorimetric Heats of Adsorption and Adsorption Isotherms. 1. O₂, N₂, Ar, CO₂, CH₄, C₂H₆, and SF₆ on Silicalite