4.6 Article

Predicting Effective Conductivities Based on Geometric Microstructure Characteristics

期刊

AICHE JOURNAL
卷 62, 期 5, 页码 1834-1843

出版社

WILEY
DOI: 10.1002/aic.15160

关键词

effective conductivity; predictive analytics; porous media; constrictivity; geometric tortuosity; geodesic tortuosity; stochastic microstructure modeling

资金

  1. SNSF [407040_154047, 407040_153790, 200021_135270]
  2. SWISS CTI grant [16851.1 PFNM-NM]
  3. Swiss National Science Foundation (SNF) [200021_135270, 407040_154047, 407040_153790] Funding Source: Swiss National Science Foundation (SNF)

向作者/读者索取更多资源

Empirical relationships between effective conductivities in porous and composite materials and their geometric characteristics such as volume fraction epsilon, tortuosity tau and constrictivity beta are established. For this purpose, 43 virtually generated 3D microstructures with varying geometric characteristics are considered. Effective conductivities sigma(eff) are determined by numerical transport simulations. Using error-minimization the following relationships have been established: sigma(eff)=sigma(0) epsilon(1.15)beta(0.37)/tau(4.39)(geod) and sigma(eff)=sigma(0) epsilon beta(0.36)/tau(5.17)(geod) (simplified formula) with intrinsic conductivity sigma(0), geodesic tortuosity sigma(geod) and relative prediction errors of 19% and 18%, respectively. We critically analyze the methodologies used to determine tortuosity and constrictivity. Comparing geometric tortuosity and geodesic tortuosity, our results indicate that geometric tortuosity has a tendency to overestimate the windedness of transport paths. Analyzing various definitions of constrictivity, we find that the established definition describes the effect of bottlenecks well. In summary, the established relationships are important for a purposeful optimization of materials with specific transport properties, such as porous electrodes in fuel cells and batteries. (C) 2016 American Institute of Chemical Engineers

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