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  <controlfield tag="008">260224s2009    xxu                      </controlfield>
  <datafield tag="245" ind1="0" ind2="0">
    <subfield code="a">Correlation for the effective gas diffusion coefficient in carbon paper diffusion media</subfield>
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  <datafield tag="260" ind1=" " ind2=" ">
    <subfield code="a"></subfield>
    <subfield code="b"></subfield>
    <subfield code="c">nov./dic. 2009</subfield>
  </datafield>
  <datafield tag="270" ind1=" " ind2=" ">
    <subfield code="a">09/06/2010 ; 09/06/2010</subfield>
  </datafield>
  <datafield tag="300" ind1=" " ind2=" ">
    <subfield code="a">9 p. ; 6070-6078</subfield>
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    <subfield code="a">Transcripci&#xF3;n del resumen del autor. The understanding of mass transport limitations in polymer electrolyte membrane (PEM) fuel cells is crucial in the research and progress of this technology. The structure of the components, specifically the as diffusion layer (GDL), of PEM fuel cells, is complex. Thus, for the purpose of simulating mass transport in the GDL, the effect of the structure on the diffusion coefficient is taken into account by introducing an effective diffusion coefficient. The effective diffusion coefficient of a gas is lower than its corresponding bulk diffusion coefficient due to the presence of a solid matrix in the porous materials. Currently, the Bruggeman approximation is the most widely used correlation for estimating the effective diffusion coefficient in the GDL. Other semiempirical models are also available. However, these correlations overestimate the effective diffusion coefficient due to the assumptions on which they are based. In this study, correlations for the through-plane and in-plane diffusibility in the GDL are developed based on a three-dimensional (3D) simulation of gas diffusion in the GDL. The 3D structure of the TORAY carbon paper with no binding material is reconstructed using stochastic models and used as the modeling domain. The numerical results are shown to have a good agreement with experimental data of diffusibility in both directions. Correlations for two different porosity ranges are given.</subfield>
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    <subfield code="a">6</subfield>
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  <datafield tag="773" ind1="0" ind2=" ">
    <subfield code="t">Energy &amp; fuels</subfield>
    <subfield code="g">23</subfield>
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    <subfield code="c">ARTICULO</subfield>
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    <subfield code="a">Zamel, Nada</subfield>
    <subfield code="9">42417</subfield>
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  <datafield tag="100" ind1="1" ind2=" ">
    <subfield code="a">Li, Xiaohong</subfield>
    <subfield code="9">42418</subfield>
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  <datafield tag="100" ind1="1" ind2=" ">
    <subfield code="a">Shen, Jun</subfield>
    <subfield code="9">42419</subfield>
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    <subfield code="c">170854</subfield>
    <subfield code="d">170854</subfield>
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    <subfield code="a">BAAB</subfield>
    <subfield code="b">BAAB</subfield>
    <subfield code="d">2026-03-05</subfield>
    <subfield code="j">200045708</subfield>
    <subfield code="l">0</subfield>
    <subfield code="p">200045708</subfield>
    <subfield code="r">2026-03-05 15:13:12</subfield>
    <subfield code="w">2026-03-05</subfield>
    <subfield code="y">ARTICULO</subfield>
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