Cure kinetics and viscosity modelling of a high-performance epoxy resin film

Garschke, Claudia; Parlevliet, Patricia; Weimer, Christian; Fox, Bronwyn

doi:10.1016/j.polymertesting.2012.09.011

Cited by 100 publications

(80 citation statements)

References 19 publications

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“…Monitoring curing processes of certain resin/curing agent system is important to optimize the product performance and choose appropriate curing condition. Different technologies including differential scanning calorimetry (DSC), dielectric analysis (DEA), Raman spectroscopy and thermogravimetric analysis (TGA) have been utilized to characterize the curing processes and the curing degree [10][11][12]. DSC analysis, based on the enthalpy released during polymerization reactions of a sample, has been extensively used to monitor the curing processes of http://dx.doi.org/10.1016/j.sna.2016.08.028 0924-4247/© 2016 Elsevier B.V. All rights reserved.…”

Section: Introductionmentioning

confidence: 99%

Electrochemical impedance spectroscopy (EIS): An efficiency method to monitor resin curing processes

Han

Wang

Zhang

et al. 2016

Sensors and Actuators A: Physical

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Section: Introductionmentioning

confidence: 99%

Electrochemical impedance spectroscopy (EIS): An efficiency method to monitor resin curing processes

Han

Wang

Zhang

et al. 2016

Sensors and Actuators A: Physical

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“…Rheological modeling to describe the viscosity behavior of resin has been investigated in recent years . Viscosity (

η

) is a function of pressure ( P ), temperature ( T ), time ( t ), shear rate (

\overset{γ}{true}

), and filler properties ( F ), as shown in eq.…”

Section: Theorymentioning

confidence: 99%

A method based on the time–temperature superposition principle to predict pressurization time in compression molding

Zhang

Zhao

Zhang

2018

J of Applied Polymer Sci

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The quality of epoxy composites reinforced by glass fibers and manufactured by compression molding is affected by the pressurization time. Traditional methods, including differential scanning calorimetry and dynamic thermomechanical analysis, cannot be reliably used to predict pressurization time in the scenario of continuous production and inconstant circumstances seen in industry. In this paper, the rheological behaviors of epoxy under constant temperature were investigated and analyzed to verify if the time–temperature superposition (TTS) principle, which defines the relation between time and temperature in the deformation and relaxation response of a viscoelastic material, could be suitably applied to describe them. The results show that the TTS principle could indeed be used to predict resin viscosity by the horizontal shift factor. A new method based on the TTS principle and written into a program to forecast pressurization time in compression molding is proposed. The uniform surface color and the qualified thickness of the composite components using the program indicate that the program works well and that this method is feasible for predicting pressurization time during compression molding. The results of tensile and short‐beam shear strength tests show that pressurization time affects the mechanical properties of the final product. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018, 135, 45308.

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“…Based on the Castro–Macosko model, the temperature‐dependent viscosity evolution could be predicted by a dynamic rheological analysis. The physical resin parameters ( E η and

η_{\infty}

) could be estimated following Arrhenius relationship for viscosity model at zero cure:

normall normaln η_{0} (|, α = 0) = normall normaln η_{\infty} + \frac{E_{η}}{R T}

…”

Section: Theoriotical Backgroundmentioning

confidence: 99%

“…Therefore, phenomenological models are much simpler to develop and mostly could also accurately describe and predict the kinetic behavior, which is the reason why it is more preferable in the practice. Several studies are conducted on curing kinetics and rheological modeling and of epoxy resin systems, among which mostly phenomenological models are preferred due to its simplicity to develop and nevertheless good ability to describe the curing/rheological behavior . The modeling of the curing and rheological behavior by the phenomenological models is based on selection of representing reaction models, estimation of start parameters and evaluation of final model parameters.…”

Section: Introductionmentioning

confidence: 99%

Influence of model parameter estimation methods and regression algorithms on curing kinetics and rheological modelling

Abliz

Artys

Ziegmann

2017

J of Applied Polymer Sci

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The accuracy of the phenomenological curing and rheological models are strongly related to the estimated start parameters and selected regression algorithms. Considering the versatile methods for model start parameter estimation (model‐free vs. model‐fitting, dynamic vs. isothermal) and regression analysis algorithm (linear vs. nonlinear, single‐target vs. multi‐target), this paper investigates the theoretical basis and influence of these aspects on the model development process and model quality. The curing kinetics is modelled by model‐free and model‐fitting start parameters and different regression algorithms, followed by cross model validation at the final. The results showed that the different parameter estimation methods and evaluation algorithms have a remarkable influence on the final model parameters and its quality. The study shows the correlation between the different aspects and provides a basis for better selection of model parameter evaluation methods and regression algorithms for model development with improved quality and accuracy. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017, 134, 45137.

show abstract

Cure kinetics and viscosity modelling of a high-performance epoxy resin film

Cited by 100 publications

References 19 publications

Electrochemical impedance spectroscopy (EIS): An efficiency method to monitor resin curing processes

Electrochemical impedance spectroscopy (EIS): An efficiency method to monitor resin curing processes

A method based on the time–temperature superposition principle to predict pressurization time in compression molding

Influence of model parameter estimation methods and regression algorithms on curing kinetics and rheological modelling

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