University of Oulu

Phys.Chem.Chem.Phys.,2019, 21, 24373, https://doi.org/10.1039/C9CP04379A

NMR relaxation and modelling study of the dynamics of SF6 and Xe in porous organic cages

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Author: Håkansson, Pär1; Javed, Muhammad Asadullah1; Komulainen, Sanna1;
Organizations: 1NMR Research Unit, University of Oulu, P. O. Box 3000, 90014 Oulu, Finland
2Department of Chemistry and Centre for Materials Discovery, University of Liverpool, Crown Street, Liverpool L69 7ZD, UK
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 2.8 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2019112243721
Language: English
Published: Royal Society of Chemistry, 2019
Publish Date: 2019-11-22
Description:

Abstract

The porous solid formed from organic CC3 cage molecules has exceptional performance for rare gas separation. NMR spectroscopy provides a way to reveal the dynamical details by using experimental relaxation and diffusion measurements. Here, we investigated T₁ and T₂ relaxation as well as diffusion of ¹²⁹Xe and SF₆ gases in the CC3-R molecular crystal at various temperatures and magnetic field strengths. Advanced relaxation modelling made it possible to extract various important dynamical parameters for gases in CC3-R, such as exchange rates, activation energies and mobility rates of xenon, occupancies of the cavities, rotational correlational times, effective relaxation rates, and diffusion coefficients of SF₆.

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Series: PCCP. Physical chemistry chemical physics
ISSN: 1463-9076
ISSN-E: 1463-9084
ISSN-L: 1463-9076
Volume: 21
Issue: 44
Pages: 24373 - 24382
DOI: 10.1039/C9CP04379A
OADOI: https://oadoi.org/10.1039/C9CP04379A
Type of Publication: A1 Journal article – refereed
Field of Science: 114 Physical sciences
116 Chemical sciences
Subjects:
Funding: This work was supported by innovation programme under the Marie Sklodowska-Curie grant no. 703446, the Kvantum institute (University of Oulu) and the CA15209 COST Action (EURELAX). The financial support of the European Research Council (ERC) under Horizon 2020 (H2020/2018–2022/ERC grant agreement no. 772110), Academy of Finland (grants #289649, 285666, 294027 and 319216) are also acknowledged. We thank the Engineering and Physical Sciences Research Council (EPSRC) for financial support under Grant EP/N004884/1. The computational resources were provided by the CSC – IT Center for Science, Finland and the Finnish Grid and Cloud Infrastructure (FGCI) (urn:nbn:fi:research-infras-2016072533).
Academy of Finland Grant Number: 289649
285666
294027
319216
Detailed Information: 289649 (Academy of Finland Funding decision)
285666 (Academy of Finland Funding decision)
294027 (Academy of Finland Funding decision)
319216 (Academy of Finland Funding decision)
Copyright information: © 2019 The Authors. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.
  https://creativecommons.org/licenses/by/3.0/