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Correlating Synthesis Parameters to Morphological Entities: Predictive Modeling of Biopolymer Aerogels
Citation Link: https://doi.org/10.15480/882.1758
Publikationstyp
Journal Article
Date Issued
2018-09-09
Sprache
English
Author(s)
Institut
TORE-DOI
Journal
Volume
11.2018
Start Page
Articelnr. 1670
Citation
Materials 11 (9): 1670 (2018)
Publisher DOI
Scopus ID
Publisher
Multidisciplinary Digital Publishing Institute
In the past decade, biopolymer aerogels have gained significant research attention due to their typical properties, such as low density and thermal insulation, which are reinforced with excellent biocompatibility, biodegradability, and ease of functionalization. Mechanical properties of these aerogels play an important role in several applications and should be evaluated based on synthesis parameters. To this end, preparation and characterization of polysaccharide-based aerogels, such as pectin, cellulose and k-carrageenan, is first discussed. An interrelationship between their synthesis parameters and morphological entities is established. Such aerogels are usually characterized by a cellular morphology, and under compression undergo large deformations. Therefore, a nonlinear constitutive model is proposed based on large deflections in microcell walls of the aerogel network. Different sizes of the microcells within the network are identified via nitrogen desorption isotherms. Damage is initiated upon pore collapse, which is shown to result from the failure of the microcell wall fibrils. Finally, the model predictions are validated against experimental data of pectin, cellulose, and k-carrageenan aerogels. Given the micromechanical nature of the model, a clear correlation—qualitative and quantitative—between synthesis parameters and the model parameters is also substantiated. The proposed model is shown to be useful in tailoring the mechanical properties of biopolymer aerogels subject to changes in synthesis parameters.
Subjects
aerogel
polysaccharide
pectin
cellulose
k-carrageenan
micromechanical
predictive model
DDC Class
620: Ingenieurwissenschaften
Publication version
publishedVersion
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