Hydrodynamic dispersion within porous biofilms

Y. Davit, H. Byrne, J. Osborne, J. Pitt-Francis, D. Gavaghan, and M. Quintard
Phys. Rev. E 87, 012718 – Published 23 January 2013

Abstract

Many microorganisms live within surface-associated consortia, termed biofilms, that can form intricate porous structures interspersed with a network of fluid channels. In such systems, transport phenomena, including flow and advection, regulate various aspects of cell behavior by controlling nutrient supply, evacuation of waste products, and permeation of antimicrobial agents. This study presents multiscale analysis of solute transport in these porous biofilms. We start our analysis with a channel-scale description of mass transport and use the method of volume averaging to derive a set of homogenized equations at the biofilm-scale in the case where the width of the channels is significantly smaller than the thickness of the biofilm. We show that solute transport may be described via two coupled partial differential equations or telegrapher's equations for the averaged concentrations. These models are particularly relevant for chemicals, such as some antimicrobial agents, that penetrate cell clusters very slowly. In most cases, especially for nutrients, solute penetration is faster, and transport can be described via an advection-dispersion equation. In this simpler case, the effective diffusion is characterized by a second-order tensor whose components depend on (1) the topology of the channels' network; (2) the solute's diffusion coefficients in the fluid and the cell clusters; (3) hydrodynamic dispersion effects; and (4) an additional dispersion term intrinsic to the two-phase configuration. Although solute transport in biofilms is commonly thought to be diffusion dominated, this analysis shows that hydrodynamic dispersion effects may significantly contribute to transport.

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  • Received 9 January 2012

DOI:https://doi.org/10.1103/PhysRevE.87.012718

©2013 American Physical Society

Authors & Affiliations

Y. Davit1,2,3, H. Byrne1,4, J. Osborne4, J. Pitt-Francis4, D. Gavaghan4, and M. Quintard2,3

  • 1Mathematical Institute, University of Oxford, 24-29 St Giles', Oxford OX1 3LB, United Kingdom
  • 2Université de Toulouse; INPT, UPS; Institut de Mécanique des Fluides de Toulouse (IMFT), Allée Camille Soula, F-31400 Toulouse, France
  • 3CNRS IMFT, F-31400 Toulouse, France
  • 4Department of Computer Science, Oxford University, Wolfson Building, Parks Road, Oxford OX1 3QD, United Kingdom

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Vol. 87, Iss. 1 — January 2013

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