Prepreg age monitoring and qualitative prediction of mechanical performance of composite using dielectric state variables

Abstract

The aviation and automobile industries have recently depended on thermoset epoxy-based prepreg as a raw material for manufacturing composites. Since prepregs have a limited out-life (i.e., the maximum storing time allowed at room temperature), they must be stored in refrigerators at low temperatures. If not maintained, they can often adversely affect the desired quality of the final product. Prepregs are often discarded once the prepreg out-life ends, leading to a loss of millions of dollars and a detrimental impact on the environment. Therefore, it is necessary to develop a simple method to monitor prepreg aging/degradation in order to ensure its usability or repurpose prepreg usage. In this study, we used broadband dielectric spectroscopy to monitor the degradation state of the glass fiber/epoxy prepreg sample stored at room temperature, and the data has been used to predict the mechanical performance of the final manufactured composite part. The frequency-based nondestructive dielectric measuring technique was used to calculate the dielectric strength and relaxation time of the prepregs. The dielectric strength decreased and relaxation time increased with aging, allowing the aging progression to be captured. Furthermore, with aging, the real permittivity value changes to a lower value and the relaxation peak in imaginary permittivity with respect to frequency shifts to a lower frequency. The physics behind this dielectric measurement method has been understood in the context of analyzing the prepreg’s cure kinetics parameters, which has been investigated using differential scanning calorimetry. Overall, this simple dielectric-based monitoring technology will provide confidence in the future use of degraded or out-of-life raw material systems for manufacturing.

Fast and accurate prediction of cure quality and mechanical performance in fiber‐reinforced polymer composite using dielectric variables and machine learning

“…Dynamic DSC scans were conducted at 5°C/min heating rates, ranging from 40 to 200°C, to measure the onset and maximum temperature of curing as well as the enthalpy. The DSC results provided the heat flow as a function of temperature and time, allowing for the calculation of the enthalpy by integrating the area under the peak 28 . The total enthalpy, or total heat, of the reaction can be denoted by H T. The conversion rate can be expressed as follows, considering the reaction rate law. …”

“…Here, A is the frequency factor, E is the activation energy, R is the universal gas constant, and n is the order of the reaction. The activation energy for the cure reaction of the prepreg system was determined using the Kissinger and Ozawa equation, followed by a previous study 28 . Here, the activation energy was considered to be c .…”

“…The DSC results provided the heat flow as a function of temperature and time, allowing for the calculation of the enthalpy by integrating the area under the peak. 28 The total enthalpy, or total heat, of the reaction can be denoted by H T. The conversion rate can be expressed as follows, considering the reaction rate law.…”

“…The activation energy for the cure reaction of the prepreg system was determined using the Kissinger and Ozawa equation, followed by a previous study. 28 Here, the activation energy was considered to be c. 86.5 kJ/mol, with ln(A) (pre-exponential factor) measured as c. 22 s À1 , and the reaction order (n) estimated 30 to be 0.92. The graph and calculated results can be found in Appendix A.…”

Effect of temperature aging of thermoset UD prepregs on inter‐ply friction behavior and formability in prepreg compression molding process

“…Consequently, inadequately stored prepregs are often discarded or buried, resulting in substantial economic losses and adverse environmental effects. 6 Examples of influence of temperature aging on thermoset prepreg properties can be found in the literature. Smith et al 7 and Salzmann et al 8 primarily investigated the variation of resin glass transition temperature (T g ) with different aging levels.…”