Apparent Anomalous Temperature Dependence of Self-Diffusion Studied by Pulsed-Field Gradient Nuclear Magnetic Resonance and Thermodynamic Modeling - Institut Charles Gerhardt - Institut de Chimie Moléculaire et des Matériaux de Montpellier Accéder directement au contenu
Article Dans Une Revue Journal of Physical Chemistry Letters Année : 2024

Apparent Anomalous Temperature Dependence of Self-Diffusion Studied by Pulsed-Field Gradient Nuclear Magnetic Resonance and Thermodynamic Modeling

Résumé

The self-diffusivity of cyclohexane and n-octane adsorbed in hierarchical zeolite monoliths has been investigated by using PFG-NMR. In these samples, the intrinsic FAU-X zeolite microporosity combines with a complex macroporous network composed of aggregated zeolite nanocrystals. As temperature is increased, cyclohexane self-diffusivity apparently decreases, reaches a minimum, and then starts increasing upon further increasing the temperature. Such striking, i.e., non-Arrhenius, temperature dependence is not observed for n-octane in the same samples and for cyclohexane adsorbed in purely microporous FAU-X. Through thermodynamic modeling, we show that this anomalous behavior can be rationalized by considering the evolution in the adsorbate populations when changing the temperature. In more detail, we show that the slow and fast diffusing species present in the microporosity and secondary porosity arising from the packing of zeolite nanocrystals vary significantly with a strong impact on the effective diffusivity. Applying the temperature evolution of their relative fractions to a simple two-phase diffusion model helps obtain insights into the physicochemical factors responsible for the complex behavior of effective self-diffusivity in hierarchical zeolites.
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Dates et versions

hal-04557296 , version 1 (24-04-2024)

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Sujeet Dutta, Andrei Nossov, Anne Galarneau, Youcef Didi, Bilel Said, et al.. Apparent Anomalous Temperature Dependence of Self-Diffusion Studied by Pulsed-Field Gradient Nuclear Magnetic Resonance and Thermodynamic Modeling. Journal of Physical Chemistry Letters, 2024, 15 (12), pp.3276-3284. ⟨10.1021/acs.jpclett.3c03468⟩. ⟨hal-04557296⟩
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