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Stochastic 3D Models for the Micro-structure of Advanced Functional Materials

机译:用于高级功能材料微结构的随机3D模型

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Optimization of functional materials is a challenging task. Thereby, stochastic morphology models can provide helpful methods. Three classes of stochastic models are presented describing different micro-structures of functional materials by means of methods from stochastic geometry, graph theory and time series analysis. The structures of these materials strongly differ from each other, where we consider organic solar cells being an anisotropic composite of two materials, non-woven gas-diffusion layers in proton exchange membrane fuel cells consisting of a system of curved carbon fibers, and graphite electrodes in Li-ion batteries which are built up by an isotropic two-phase system (i.e., consisting of a pore and a solid phase). The goal is to give an overview how the stochastic modeling of functional materials can be organized and to provide an outlook how these models can be used for material optimization with respect to functionality.
机译:功能材料的优化是一个具有挑战性的任务。 因此,随机形态模型可以提供有用的方法。 提出了三类随机模型,其通过来自随机几何形状,图论和时间序列分析的方法描述了功能材料的不同微结构。 这些材料的结构彼此相差,在那里考虑有机太阳能电池是两种材料的各向异性复合材料,在质子交换膜燃料电池中由弯曲碳纤维和石墨电极组成的质子交换膜燃料电池中的非织造气体扩散层 在锂离子电池中,由各向同性的两相系统(即由孔和固相组成)。 目标是概述如何组织功能材料的随机建模,并提供了如何将这些模型用于相对于功能的材料优化的Outlook。

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