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Special Topics & Reviews in Porous Media: An International Journal

Publication de 4  numéros par an

ISSN Imprimer: 2151-4798

ISSN En ligne: 2151-562X

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 1.1 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 1.5 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 0.5 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.00018 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.42 SJR: 0.217 SNIP: 0.362 CiteScore™:: 2.3 H-Index: 19

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SIMULATION OF A CHEMICAL VAPOR DEPOSITION: MOBILE AND IMMOBILE ZONES AND HOMOGENEOUS LAYERS

Volume 1, Numéro 2, 2010, pp. 123-143
DOI: 10.1615/SpecialTopicsRevPorousMedia.v1.i2.40
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RÉSUMÉ

This paper describes how we model chemical vapor deposition for metallic bipolar plates and optimization to deposit a homogeneous layer. Constraint on the deposition process are very low pressure (nearly vacuum) and low temperature (∼400 K). These constraints need catalytic process, and our apparatus deals with a plasma source and precursor gases [see Dobkin, M. K. and Zuraw, D. M. (Principles of Chemical Vapor Deposition, 1st ed., Springer, NY, 2003)]. Such a plasma has the advantage of accelerating the vaporization process [see Lieberman, M. A. and Lichtenberg, A. J. (Principle of Plasma Discharges and Materials Processing, 2st ed., Wiley-Interscience, Hoboken, NJ, 2005)], and of bringing the solid materials to a gaseous phase. Nevertheless, there are also some drawbacks, in that retardation and adsorption processes can hinder the direct transport to the target [see Lieberman and Lichtenberg (2005)]. Here, we present a mesoscopic model, which reflects the retardation, transport, and reaction of the gaseous species through homogeneous media in the chamber. The models include immobile gaseous phases, where the transport of the mobile gaseous species is hindered. Furthermore, the models include the conservation of mass and the porous media are in accordance with Darcy's law, which is an assumption for the flow processes of the gaseous phase. The transport through the stationary and ionized plasma field is treated as a diffusion-dominated flow with mobile and immobile zones [see Gobbert, M. K. and Ringhofer, C. A. (SIAM J. Appl. Math., vol. 58, pp. 737-752,1998) and Lieberman and Lichtenberg (2005)], where the metallic deposit and the gas chamber look like porous media [Rouch, H., (Proc. of the COMSOL Users Conf., Paris, pp. 1-7, 2006) and Cao, G. Z., Brinkman, H., Meijerink, J., DeVries, K. J., and Burggraaf A. J. (J. Mater. Chem.), vol. 3, no. 12, pp. 1307-1311, 1993)]. We choose porous ceramic membranes and gas catalysts like argon (Ar), (Cao et al., 1993) and apply our experience in simulating gaseous flow and modeling the penetration of such porous media [see Jin, S. and Wang, X. (J. Comput. Phys., vol. 179, no. 2, pp. 557-577, 2002)]. Numerical methods are developed to solve such multiscale and multiphase models. We have taken into account combined spatial discretization methods, based on finite volume methods and analytical test functions. Although implicit in time, discretized parts are solved with Runge-Kutta methods and iterative solvers coupled with mobile and immobile equation parts. The numerical experiments validate the modified discretization methods respecting their higher order results and their efficiencies. In real-life simulations of physical experiments, we discuss the validation of our model and the assumed deposition rates.

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