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Particle-induced transition in foams

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 Added by Olivier Pitois
 Publication date 2013
  fields Physics
and research's language is English




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The macroscopic behaviour of foams is deeply related to rearrangements occurring at the bubble scale, which dynamics depends on the mobility of the interstitial phase. In this paper, we resort to drainage experiments to quantify this mobility in particulate foams, where a particle suspension is confined between foam bubbles. Results show a strong dependence on each investigated parameter, i.e. bubble size, particle size and gas volume fraction for a given particle volume fraction. A combination of these parameters has been identified as the control parameter lambda, which compares the particle size to the size of passage through constrictions within the foam pore space. lambda highlights a sharp transition: for lambda < 1 particles are free to drain with the liquid, which involves the shear of the suspension in foam interstices, for lambda > 1 particles are trapped and the mobility of the interstitial phase is strongly reduced.



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195 - B. Haffner , Y. Khidas , O. Pitois 2014
The drainage of particulate foams is studied under conditions where the particles are not trapped individually by constrictions of the interstitial pore space. The drainage velocity decreases continuously as the particle volume fraction $phi_{p}$ increases. The suspensions jam - and therefore drainage stops - for values $phi_{p}^{*}$ which reveal a strong effect of the particle size. In accounting for the particular geometry of the foam, we show that $phi_{p}^{*}$ accounts for unusual confinement effects when the particles pack into the foam network. We model quantitatively the overall behavior of the suspension - from flow to jamming - by taking into account explicitly the divergence of its effective viscosity at $phi_{p}^{*}$. Beyond the scope of drainage, the reported jamming transition is expected to have a deep significance for all aspects related to particulate foams, from aging to mechanical properties.
132 - K. Zhang , C.-C. Kuo , C. S. OHern 2017
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