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Pore Size Gradient Effect in Monolithic Silica Mesopore Networks Revealed by In-Situ SAXS Physisorption.
Kube, Sebastian A; Turke, Kevin; Ellinghaus, Rüdiger; Wallacher, Dirk; Thommes, Matthias; Smarsly, Bernd M.
Afiliação
  • Kube SA; Department of Mechanical Engineering and Materials Science, Yale University, 15 Prospect Street, New Haven, Connecticut 06511, United States.
  • Wallacher D; Helmholtz Center Berlin for Materials and Energy, Hahn-Meitner-Platz 1, 14109 Berlin, Germany.
  • Thommes M; Institute of Separation Science and Technology, Department of Chemical and Bioengineering, University of Erlangen-Nuremberg, Egerlandstrasse 3, 91058 Erlangen, Germany.
Langmuir ; 36(40): 11996-12009, 2020 Oct 13.
Article em En | MEDLINE | ID: mdl-32936653
ABSTRACT
In disordered mesopore networks, the size distribution and connection between adjacent pores control desorption. How network characteristics can be extracted from corresponding physisorption isotherms is still a matter of research. To elucidate this, we study krypton physisorption (117.8 K) in the mesopore networks of "Nakanishi"-type monolithic silica. Combining physisorption in scanning acquisition mode with synchrotron-based in-situ SAXS provides complementary information on pore-filling states. These data reveal a mean pore size gradient in which pores grow smaller towards the material's network center. This structural motif cannot be derived through conventional isotherm analysis, but it is clearly exposed through scanning desorption curves which do not quite converge but merge individually with the main desorption isotherm before the lower hysteresis closing point. Hence, our findings provide the basis to build advanced models for analyzing scanning isotherms and extracting network characteristics through new descriptors, such as pore size and connectivity distributions as a function of the distance from the network center.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article