Hostname: page-component-586b7cd67f-dsjbd Total loading time: 0 Render date: 2024-11-26T06:21:41.537Z Has data issue: false hasContentIssue false
  • English
  • Français

Mass Transport/Diffusion and Surface Reaction Process with Lattice Boltzmann

Published online by Cambridge University Press:  20 August 2015

Giuseppe De Prisco  and
Xiaowen Shan
Giuseppe De Prisco*
Affiliation:
Exa Corporation, 55 Network Drive, Burlington, Massachusetts 01773, USA Ingrain Inc, 3733 Westheimer Road, Houston, Texas 77027, USA
Xiaowen Shan*
Affiliation:
Exa Corporation, 55 Network Drive, Burlington, Massachusetts 01773, USA
*
Corresponding author.Email:[email protected]
Email:[email protected]
Get access

Abstract

Multi-component flow with chemical reactions is a common problem in different industrial applications: the mixing chamber of a reaction injection molding (RIM) machine; the dynamics of diesel soot particles interacting with a porous-ceramic particulate filter; reactive transport in porous media; bio-chemical processes involving enzyme-catalyzed kinetics. In all these cases, mass diffusion/convection and wall or volume chemical interactions among components play an important role. In the present paper we underline the importance of diffusion/convection/reaction mechanisms in bio-chemical processes using the Lattice Boltzmann (LB) technique. The bio-application where we studied diffusion/convection/reaction mechanisms is the quorum-sensing pathway for the bio-synthesis of the AI-2, a molecule that allows the bacteria to launch a coordinated attack on a host immune system (see [9,10] for more details of the bio-application). The overall goal is to create a micro-device to screen potential drugs that inhibit AI-2 bio-synthesis. The Michaelis-Menten saturation kinetic model is implemented at the reactive surface and the results are shown in terms of two dimensionless numbers: Damkohler (Da) and Peclet (Pe) number. For high Pe number a small conversion of reactants into products is obtained at the reactive surface, but the overall flux of products is high; moreover, a fast saturation of the conversion of reactants to products is obtained for high Da numbers. The trade-off for setting the Pe and Da numbers depends on the specific application and the technologies used in the micro-device (e.g., sensitivity of the detector, cost of reactants).

Keywords

76P0576R0576R5074F2592C4505.10.-a05.20.Dd47.11.Qr47.63.mfLattice Boltzmannmulti-componentdiffusion-reaction
Type
Research Article
Information
Communications in Computational Physics , Volume 9 , Issue 5 , May 2011 , pp. 1362 - 1374
Copyright
Copyright © Global Science Press Limited 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

[1]Chen, S. and Doolen, G., Lattice Boltzmann method for fluid flows, Ann. Rev. Fluid. Mech., 30 (1998), 329–364.Google Scholar
[2]Gervais, T. and Jensen, K. F., Mass transport and surface reactions in microfluidic systems, Chem. Eng. Sci., 61(4) (2006), 1102–1121.Google Scholar
[3]Guo, Z., Zheng, C. and Shi, B., Discrete lattice effects on the forcing term in the lattice Boltz-mann method, Phys. Rev. E., 65 (2002), 046308.CrossRefGoogle ScholarPubMed
[4]Hu, G., Gao, Y. and Li, D., Modeling micropatterned antigen-antibody binding kinetics in a microfluidic chip, Biosens. Bioelectron., 22(7) (2007), 1403–1409.Google Scholar
[5]Kang, Q., Lichtner, P. C. and Zhang, D., Lattice Boltzmann pore-scale model for multicompo-nent reactive transport in porous media, J. Geophys. Res., 111 (2006), B05203.Google Scholar
[6]Kang, Q., Lichtner, P. C. and Zhang, D., An improved lattice Boltzmann model for multicom-ponent reactive transport in porous media at the pore scale, Water. Resour. Res., 43 (2007), W12S14.CrossRefGoogle Scholar
[7]Kang, Q., Zhang, D. and Chen, S., Simulation of dissolution and precipitationinporous media, J. Geophys. Res., 108(B10) (2003), 2505–2513.Google Scholar
[8]Kang, Q., Zhang, D., Chen, S. and He, X., Lattice Boltzmann simulation of chemical dissolution in porous media, Phys. Rev. E., 65 (2002), 036318.Google Scholar
[9]Lewandowski, A. T., Assembly of Quorum Sensing Pathway Enzymes onto Patterned Microfabricated Devices, PhD thesis, University of Maryland, College Park, 2007.Google Scholar
[10]Luo, X. L., Programmable Biomolecule Assembly and Activity in Prepackaged BioMEMS, PhD thesis, University of Maryland, College Park, 2008.Google Scholar
[11]Shan, X. and Chen, H., Lattice Boltzmann model for simulating flows with multiple phases and components, Phys. Rev. E., 47(3) (1993), 1815–1819.Google Scholar
[12]Shan, X. and Chen, H., Simulation of non-ideal gases and liquid-gas phase transitions by lattice Boltzmann equation, Phys. Rev. E., 49(4) (1994), 2941–2948.CrossRefGoogle Scholar
[13]Shan, X. and Doolen, G., Multi-component lattice Boltzmann model with interparticle interaction, J. Stat. Phys., 81 (1995), 379–393.Google Scholar
[14]Shan, X. and Doolen, G., Diffusion in a multi-component lattice Boltzmann equation model, Phys. Rev. E., 54(4) (1996), 3614–3620.Google Scholar
[15]Shan, X. and He, X., Discretizationof the velocity space in solution of the Boltzmann equation, Phys. Rev. Lett., 80 (1998), 65–68.Google Scholar
[16]Shan, X., Yuan, X.-F. and Chen, H., Kinetic theory representation of hydrodynamics: a way beyond the Navier-Stokes equation, J. Fluid. Mech., 550 (2006), 413–441.Google Scholar
[17]Succi, S., The Lattice Boltzmann Equation for Fluid Dynamics and Beyond, Numerical Mathematics and Scientific Computation, Oxford University Press, 2001.Google Scholar
[18]Zimmermann, M., Delamarche, E., Wolf, M. and Hunziker, P., Modeling and optimization of high-sensitivity, low-volume microfluidic-based surface immunoassays, Biomed. Microdevices., 7 (2005), 99–110.Google Scholar