Computational design of biopolymer aerogels and predictive modelling of their nanostructure and mechanical behaviour
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 netw...
Main Authors: | , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2021-05-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-021-89634-1 |
id |
doaj-2274f0e386de419987d2c9510bacb93e |
---|---|
record_format |
Article |
spelling |
doaj-2274f0e386de419987d2c9510bacb93e2021-05-16T11:23:37ZengNature Publishing GroupScientific Reports2045-23222021-05-0111111010.1038/s41598-021-89634-1Computational design of biopolymer aerogels and predictive modelling of their nanostructure and mechanical behaviourRajesh Chandrasekaran0Markus Hillgärtner1Kathirvel Ganesan2Barbara Milow3Mikhail Itskov4Ameya Rege5Department of Continuum Mechanics, RWTH Aachen UniversityDepartment of Continuum Mechanics, RWTH Aachen UniversityDepartment of Aerogels and Aerogel Composites, Institute of Materials Research, German Aerospace CenterDepartment of Aerogels and Aerogel Composites, Institute of Materials Research, German Aerospace CenterDepartment of Continuum Mechanics, RWTH Aachen UniversityDepartment of Aerogels and Aerogel Composites, Institute of Materials Research, German Aerospace CenterAbstract 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.https://doi.org/10.1038/s41598-021-89634-1 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Rajesh Chandrasekaran Markus Hillgärtner Kathirvel Ganesan Barbara Milow Mikhail Itskov Ameya Rege |
spellingShingle |
Rajesh Chandrasekaran Markus Hillgärtner Kathirvel Ganesan Barbara Milow Mikhail Itskov Ameya Rege Computational design of biopolymer aerogels and predictive modelling of their nanostructure and mechanical behaviour Scientific Reports |
author_facet |
Rajesh Chandrasekaran Markus Hillgärtner Kathirvel Ganesan Barbara Milow Mikhail Itskov Ameya Rege |
author_sort |
Rajesh Chandrasekaran |
title |
Computational design of biopolymer aerogels and predictive modelling of their nanostructure and mechanical behaviour |
title_short |
Computational design of biopolymer aerogels and predictive modelling of their nanostructure and mechanical behaviour |
title_full |
Computational design of biopolymer aerogels and predictive modelling of their nanostructure and mechanical behaviour |
title_fullStr |
Computational design of biopolymer aerogels and predictive modelling of their nanostructure and mechanical behaviour |
title_full_unstemmed |
Computational design of biopolymer aerogels and predictive modelling of their nanostructure and mechanical behaviour |
title_sort |
computational design of biopolymer aerogels and predictive modelling of their nanostructure and mechanical behaviour |
publisher |
Nature Publishing Group |
series |
Scientific Reports |
issn |
2045-2322 |
publishDate |
2021-05-01 |
description |
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. |
url |
https://doi.org/10.1038/s41598-021-89634-1 |
work_keys_str_mv |
AT rajeshchandrasekaran computationaldesignofbiopolymeraerogelsandpredictivemodellingoftheirnanostructureandmechanicalbehaviour AT markushillgartner computationaldesignofbiopolymeraerogelsandpredictivemodellingoftheirnanostructureandmechanicalbehaviour AT kathirvelganesan computationaldesignofbiopolymeraerogelsandpredictivemodellingoftheirnanostructureandmechanicalbehaviour AT barbaramilow computationaldesignofbiopolymeraerogelsandpredictivemodellingoftheirnanostructureandmechanicalbehaviour AT mikhailitskov computationaldesignofbiopolymeraerogelsandpredictivemodellingoftheirnanostructureandmechanicalbehaviour AT ameyarege computationaldesignofbiopolymeraerogelsandpredictivemodellingoftheirnanostructureandmechanicalbehaviour |
_version_ |
1721439454271373312 |