A new micromechanics model and effective elastic modulus of nanotube reinforced composites

Pan, Jing; Bian, Lichun; Zhao, Huichuan; Zhao, Yang

doi:10.1016/j.commatsci.2015.11.009

Cited by 46 publications

(15 citation statements)

References 33 publications

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“…These parameters are usually evaluated based on the experimental observation of micrographs. According to the previous studies on the elastic modulus of CNT-reinforced polymer composites, when the values of A / L and n are 0.5 and 2, respectively, very good agreement has been resulted between the theoretical predictions and experimental measurements (Dastgerdi et al, 2013; Pan et al, 2016; Yanase et al, 2013; Yang et al, 2012). Therefore, the values of waviness factor, number of waves, density, length and diameter of CNFs, and interfacial thermal resistance are considered to be A / L = 0.5, n = 2, ρ CNF = 1.7 g/cm 3 , L CNF = 5 µm, d CNF = 100 nm and R k = 8.3 × 10 −8 m 2 K/W, respectively.…”

Section: Resultssupporting

confidence: 63%

Effect of microstructural features on the thermal conducting behavior of carbon nanofiber–reinforced styrene-based shape memory polymer composites

Liu

Jiang

2020

Journal of Intelligent Material Systems and Structures

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This article presents a novel hierarchical micromechanics approach to carefully investigate the thermal conductivities of styrene-based shape memory polymer composites containing carbon nanofibers. The research is mainly focused on the simulation of carbon nanofiber/shape memory polymer interfacial thermal resistance and carbon nanofiber agglomeration as two critical microstructural features of carbon nanofiber–shape memory polymer composite materials. The computed results are compared with the available experimental measurements. It is found that both of those microstructural factors along with carbon nanofiber non-straight shape significantly affecting the thermal conducting behavior must be incorporated in the analysis to have a more realistic prediction. The thermal conductivity of carbon nanofiber–reinforced shape memory polymer composites reduces significantly due to the effects of carbon nanofiber/shape memory polymer interfacial resistance and carbon nanofiber agglomeration and waviness. It is suggested to uniformly disperse carbon nanofibers into the shape memory polymers and reduce interfacial resistance for improving the carbon nanofiber–styrene composite thermal properties. In addition, the present study reveals that the effective thermal conductivities of the shape memory polymer composites reinforced by aligned carbon nanofibers are greatly enhanced over those of the shape memory polymer composites containing randomly dispersed carbon nanofibers. The effects of percentage, waviness parameters, degree of agglomeration, material properties, length and diameter of carbon nanofibers as well as interfacial thermal resistance value on the thermal behavior of carbon nanofiber–reinforced styrene-based shape memory polymer composites are investigated.

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Section: Resultssupporting

confidence: 63%

Effect of microstructural features on the thermal conducting behavior of carbon nanofiber–reinforced styrene-based shape memory polymer composites

Liu

Jiang

2020

Journal of Intelligent Material Systems and Structures

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“…The effective modulus of the composites can be obtained by various methods, such as sparse method, Mori–Tanaka method, self-consistent method, differential method, Reuss–Voigt model, generalized self-consistent method, and so on. 6 –9 Wu et al 10 considered the cement paste is a three-dimensional microscopic model, and the cement slurry modulus values, the mineral composition of the various materials, and the content of cement paste must be constants to calculate the elastic modulus using this model. Ren et al 11 studied that based on the Reuss–Voigt model, the elastic modulus model of the random short fiber composite was established, and the elastic modulus, Poisson’s ratio, and size of each constituent material must be known to predict the elastic modulus of specimen.…”

Section: Introductionmentioning

confidence: 99%

The compressive behavior of cement mortar with the addition of nano metakaolin

Guo

Fan

Haiyang

2018

Nanomaterials and Nanotechnology

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Elastic modulus is an important mechanical index for the cement-based materials, which has a significant effect on the static and dynamic response of the concrete structure. To investigate the compressive behavior of nano metakaolin cement mortar, the effects of dispersion conditions, water to binder ratios, and mineral admixtures on the compressive strength of nano metakaolin cement mortar were examined. The elastic modulus of nano metakaolin cement mortar under different water to binder ratios and mineral admixtures was obtained. Based on the theory of micromechanics of composite materials, a theoretical model was deduced to calculate elastic modulus of nano metakaolin cement mortar. Based on the experimental results, an influence coefficient was introduced into simplified model to estimate the elastic modulus of nano metakaolin cement mortar. The results demonstrate that the application of ultrasonic dispersion and long-duration dispersion time (no more than 15 min) can effectively improve the compressive strength of nano metakaolin cement mortar. Compressive strength of nano metakaolin cement mortar mixed with ground granulated blast furnace slag, fly ash, and attapulgite clay is 33.38%, 17.65%, and 6.45% higher than that of the ordinary mortar, respectively. Compared with the experimental results, the calculated error of theoretical model is no more than 5%, while the calculated error of the simplified model is no more than 10%.

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“…The Mori-Tanaka method considers the interaction among fillers. The strain localization tensor of a two-phase composite is written as bold-italicBfalse¯MT=γ0bold∶[(1−vf)bold-italicI+vfγ0]−1 [27,31] with γ0=[bold-italicI+Esbold∶Cm−1bold∶(Cf−Cm)]−1, where Es is the Eshelby’s tensor associated with filler shapes, which has the explicit formula only for the regular filler shape [41]. γ0 is determined by the properties of components and the way of combination.…”

Section: Discussion Of the Combined Self-consistent Methodsmentioning

confidence: 99%

A Combined Self-Consistent Method to Estimate the Effective Properties of Polypropylene/Calcium Carbonate Composites

Xiong

Liu

et al. 2018

Polymers

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Abstract:In this work, trying to avoid difficulty of application due to the irregular filler shapes in experiments, self-consistent and differential self-consistent methods were combined to obtain a decoupled equation. The combined method suggests a tenor γ independent of filler-contents being an important connection between high and low filler-contents. On one hand, the constant parameter can be calculated by Eshelby's inclusion theory or the Mori-Tanaka method to predict effective properties of composites coinciding with its hypothesis. On the other hand, the parameter can be calculated with several experimental results to estimate the effective properties of prepared composites of other different contents. In addition, an evaluation index σ f of the interactional strength between matrix and fillers is proposed based on experiments. In experiments, a hyper-dispersant was synthesized to prepare polypropylene/calcium carbonate (PP/CaCO 3 ) composites up to 70 wt % of filler-content with dispersion, whose dosage was only 5 wt % of the CaCO 3 contents. Based on several verifications, it is hoped that the combined self-consistent method is valid for other two-phase composites in experiments with the same application progress as in this work.

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A new micromechanics model and effective elastic modulus of nanotube reinforced composites

Cited by 46 publications

References 33 publications

Effect of microstructural features on the thermal conducting behavior of carbon nanofiber–reinforced styrene-based shape memory polymer composites

Effect of microstructural features on the thermal conducting behavior of carbon nanofiber–reinforced styrene-based shape memory polymer composites

The compressive behavior of cement mortar with the addition of nano metakaolin

A Combined Self-Consistent Method to Estimate the Effective Properties of Polypropylene/Calcium Carbonate Composites

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