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生物聚合物气凝胶的计算设计及纳米结构和力学行为的预测建模。

Computational design of biopolymer aerogels and predictive modelling of their nanostructure and mechanical behaviour.

机构信息

Department of Continuum Mechanics, RWTH Aachen University, Eilfschornsteinstr. 18, 52062, Aachen, Germany.

Department of Aerogels and Aerogel Composites, Institute of Materials Research, German Aerospace Center, Linder Höhe, 51147, Cologne, Germany.

出版信息

Sci Rep. 2021 May 13;11(1):10198. doi: 10.1038/s41598-021-89634-1.

Abstract

To address the challenge of reconstructing or designing the three-dimensional microstructure of nanoporous materials, we develop a computational approach by combining the random closed packing of polydisperse spheres together with the Laguerre-Voronoi tessellation. Open-porous cellular network structures that adhere to the real pore-size distributions of the nanoporous materials are generated. As an example, κ-carrageenan aerogels are considered. The mechanical structure-property relationships are further explored by means of finite elements. Here we show that one can predict the macroscopic stress-strain curve of the bulk porous material if only the pore-size distributions, solid fractions, and Young's modulus of the pore-wall fibres are known a priori. The objective of such reconstruction and predictive modelling is to reverse engineer the parameters of their synthesis process for tailored applications. Structural and mechanical property predictions of the proposed modelling approach are shown to be in good agreement with the available experimental data. The presented approach is free of parameter-fitting and is capable of generating dispersed Voronoi structures.

摘要

为了解决重建或设计纳米多孔材料的三维微观结构的挑战,我们开发了一种计算方法,将多分散球体的随机密堆积与拉盖尔-沃罗诺伊细分相结合。生成了符合纳米多孔材料真实孔径分布的多孔蜂窝状网络结构。以 κ-卡拉胶气凝胶为例。通过有限元法进一步探讨了力学结构-性能关系。这里我们表明,如果仅预先知道孔径分布、固体分数和孔壁纤维的杨氏模量,则可以预测大块多孔材料的宏观应力-应变曲线。这种重建和预测建模的目的是为了针对特定应用对其合成工艺参数进行反向工程。所提出的建模方法的结构和机械性能预测与现有实验数据吻合较好。所提出的方法无需参数拟合,并且能够生成离散的 Voronoi 结构。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/30bc/8119483/1bac9b27fd39/41598_2021_89634_Fig1_HTML.jpg

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