Effect of Confinement on Capillary Phase Transition in Granular Aggregates
Name
PhysRevLett.125.255501.pdf
Description
Published version
Size
897.61 KB
Format
Adobe PDF
Checksum (MD5)
70ab86e9d25ffe725d4c9d7ccbf4c59c
Author(s)
Monfared, Siavash
Zhou, Tingtao
Andrade, José E
Ioannidou, Katerina
Radjaï, Farhang
Ulm, Franz-Josef
Pellenq, Roland J-M
Date Issued
December 2020
Journal
Physical Review Letters
Publisher
American Physical Society (APS)
Citation
Siavash Monfared, Tingtao Zhou, José E. Andrade, Katerina Ioannidou, Farhang Radjaï, Franz-Josef Ulm, and Roland J.-M. Pellenq, Effect of Confinement on Capillary Phase Transition in Granular Aggregates, Phys. Rev. Lett. 125, 255501
Version
Final published version
Abstract
© 2020 American Physical Society. Using a 3D mean-field lattice-gas model, we analyze the effect of confinement on the nature of capillary phase transition in granular aggregates with varying disorder and their inverse porous structures obtained by interchanging particles and pores. Surprisingly, the confinement effects are found to be much less pronounced in granular aggregates as opposed to porous structures. We show that this discrepancy can be understood in terms of the surface-surface correlation length with a connected path through the fluid domain, suggesting that this length captures the true degree of confinement. We also find that the liquid-gas phase transition in these porous materials is of second order nature near capillary critical temperature, which is shown to represent a true critical temperature, i.e., independent of the degree of disorder and the nature of the solid matrix, discrete or continuous. The critical exponents estimated here from finite-size scaling analysis suggest that this transition belongs to the 3D random field Ising model universality class as hypothesized by F. Brochard and P.G. de Gennes, with the underlying random fields induced by local disorder in fluid-solid interactions.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
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DOI of Published Version
https://doi.org/10.1103/PHYSREVLETT.125.255501
