More precise model used for prediction of nanocomposites behavior

TEHRAN, Oct. 17 (MNA) – Iranian researchers from Amirkabir University of Technology presented a numerical model to predict the behavior of polymeric composites more precisely in the presence of nanoparticles, INIC reports.

Polymers reinforced with nanoparticles have attracted the attention of many researchers in recent years; therefore, correct prediction of elasticity modules of the polymer reinforced with nanoparticles is very important because it decreases the number of required tests, and as a result, reduces the laboratorial costs.

Results of the research have applications in materials engineering, mechanical engineering and aerospace to decrease laboratorial costs.

According to Iran Nanotechnology Initiative Council (INIC), the difference between the results obtained from the model and experimental data is less than that of the previous models.

According to the researchers, debonding between the reinforcing phase and the polymeric bed is not very important in composites without the presence of nanoparticles, and the assumption of ideal contact is mostly correct. It has always been assumed in the previous theoretical models presented in the past that there is an ideal contact between the reinforcing agent at nanometric scale and the bed matrix. However, this assumption is not necessarily correct in nanocomposites, to the extent that significant difference is usually observed between the numerical data and experimental data, especially in high weight percentages of nanoparticles.

The model presented in this research can determine numerical module of nanocomposites with low error percent compared with experimental data. Based on the results, the error in modules obtained from laboratorial results and the numerical determine module decreases from 27% to 7% due to the calculation of rebonding. Therefore, the need for laboratorial tests is minimized by using the new method.

Results of the research have been published in Composites Science and Technology, vol. 117, issue 1, 2015, pp. 379-385.



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