Inferring Effective Interphase Properties in Composites by Inverse Analysis AITranslate
Abstract AITranslate
Composite materials consist of a matrix reinforced by one or more fillers, each having unique material properties. Coated and uncoated fillers possess an interphase region between the matrix and filler with distinct but poorly known physiochemical properties. Determination of the physical properties of this region is essential for the modeling and design of composite materials, especially when considering nanoscale reinforced systems where the interphase may comprise a significant volume fraction of the overall composite. Direct measurements of the interphase properties are challenging, and most experimental methods involve abrasive techniques that alter local mechanical properties or suffer from experimental bias. In this study, a comprehensive framework is proposed to numerically model the interphase effects and infer the key mechanical properties of the interphase region from experimental measurements of the composite elastic modulus, a macroscale property that can be readily measured. This framework is demonstrated for a matrix reinforced by randomly distributed spherical particles using finite element (FE) analysis but is generalizable to any mechanical composite system. Representative volume elements are analyzed under periodic strains, and the resulting stresses are used to determine the effective stiffness (or modulus) of the simulated composite. Gaussian process regression is used to generate computationally efficient surrogate models that approximate the FE model output. The surrogate models are then explored through statistical inverse analysis to infer the interphase thickness and modulus that best match the macroscale experimental data of six different composite systems. The paper presents the obtained results from calibrated FE analysis as an alternative for the mechanical characterization of interphase regions. The calibrated results show good agreement with the experimental measurements of the composite modulus and account for particle size-dependent elastic behavior. Furthermore, the relationship between filler particle size and the interphase thickness and modulus is explored.
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DOI:https://doi.org/10.1021/acsapm.3c00891
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Composite materials consist of a matrix reinforced by one or more fillers, each having unique material properties. Coated and uncoated fillers possess an interphase region between the matrix and filler with distinct but poorly known physiochemical properties. Determination of the physical properties of this region is essential for the modeling and design of composite materials, especially when considering nanoscale reinforced systems where the interphase may comprise a significant volume fraction of the overall composite. Direct measurements of the interphase properties are challenging, and most experimental methods involve abrasive techniques that alter local mechanical properties or suffer from experimental bias. In this study, a comprehensive framework is proposed to numerically model the interphase effects and infer the key mechanical properties of the interphase region from experimental measurements of the composite elastic modulus, a macroscale property that can be readily measured. This framework is demonstrated for a matrix reinforced by randomly distributed spherical particles using finite element (FE) analysis but is generalizable to any mechanical composite system. Representative volume elements are analyzed under periodic strains, and the resulting stresses are used to determine the effective stiffness (or modulus) of the simulated composite. Gaussian process regression is used to generate computationally efficient surrogate models that approximate the FE model output. The surrogate models are then explored through statistical inverse analysis to infer the interphase thickness and modulus that best match the macroscale experimental data of six different composite systems. The paper presents the obtained results from calibrated FE analysis as an alternative for the mechanical characterization of interphase regions. The calibrated results show good agreement with the experimental measurements of the composite modulus and account for particle size-dependent elastic behavior. Furthermore, the relationship between filler particle size and the interphase thickness and modulus is explored.
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| GB/T 7714-2015 | [1] J. Caleb Arp, John Nicholson, Joseph Geddes, et al. ACS Applied Polymer Materials, 2023(5). DOI:10.1021/acsapm.3c00891. |
| MLA | [1] J. Caleb Arp, et al., ACS Applied Polymer Materials, no. 5, 2023, https://doi.org/10.1021/acsapm.3c00891. |
| APA | [1] J. Caleb Arp, John Nicholson, Joseph Geddes, D. Andrew Brown, Sez Atamturktur Russcher, & Christopher L. Kitchens. (2023). ACS Applied Polymer Materials(5). https://doi.org/10.1021/acsapm.3c00891 |
| IEEE | [1] J. Caleb Arp, John Nicholson, Joseph Geddes, D. Andrew Brown, Sez Atamturktur Russcher, and Christopher L. Kitchens, ACS Applied Polymer Materials, no. 5, 2023, doi: 10.1021/acsapm.3c00891. keywords: {effective interphase;finite element modeling;model calibration;Bayesian inference;homogenization;filled polymers;Show More} |
