Rheological cure characterization of a polyfunctional epoxy acrylic resin

Cañamero-Martínez, Pedro; Fuente, José Luis de la

doi:10.1016/j.reactfunctpolym.2010.07.010

Cited by 44 publications

(18 citation statements)

References 36 publications

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“…The dynamic viscosity (h), storage modulus (G') and loss modulus (G'') as a function of temperature were recorded for analysis. As shown in Fig Figure 5 b, the gelation occurred at lower temperatures for the TEIA/D230 and TEIA/MHHPA systems compared with the DGEBA/D230 and DGEBA/MHHPA systems, indicated by the intersection of G' and G'' curves; [32] consequently, the whole curing process for the TEIA system could be completed at a lower process temperature or in a shorter time relative to the DGEBA systems. Based on the above results, it can be concluded that TEIA with low viscosity has better processability and is convenient for the end use.…”

Section: Viscosity and Processabilitymentioning

confidence: 88%

Synthesis and Properties of a Bio‐Based Epoxy Resin with High Epoxy Value and Low Viscosity

et al. 2013

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A bio-based epoxy resin (denoted TEIA) with high epoxy value (1.16) and low viscosity (0.92 Pa s, 258C) was synthesized from itaconic acid and its chemical structure was confirmed by 1H NMR and 13C NMR spectroscopy. Its curing reaction with poly(propylene glycol) bis(2-aminopropyl ether) (D230) and methyl hexahydrophthalic anhydride (MHHPA) was investigated. For comparison, the commonly used diglycidyl ether of bisphenol A (DGEBA) was also cured with the same curing agents. The results demonstrated that TEIA showed higher curing reactivity towards D230/MHHPA and lower viscosity compared with DGEBA, resulting in the better processability. Owing to its high epoxy value and unique structure, comparable or better glass transition temperature as well as mechanical properties could be obtained for the TEIA-based network relative to the DGEBA-based network. The results indicated that itaconic acid is a promising renewable feedstock for the synthesis of bio-based epoxy resin with high performance.

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Section: Viscosity and Processabilitymentioning

confidence: 88%

Synthesis and Properties of a Bio‐Based Epoxy Resin with High Epoxy Value and Low Viscosity

et al. 2013

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“…Among the possible binders, thermoset resins present a singularity: their viscosity is time dependent [69,70]. These kinds of polymers present an initial low viscosity that grows exponentially with time.…”

Section: Effect Of Variable Viscosity: Curing Polymeric Resinsmentioning

confidence: 99%

“…Where η 0 is the initial viscosity and k n is a strongly temperature-dependent rheological kinetic constant [70]. Starting from the reduced Navier-Stokes equation:…”

Section: Effect Of Variable Viscosity: Curing Polymeric Resinsmentioning

confidence: 99%

Wetting and Navier-Stokes Equation — The Manufacture of Composite Materials

Caccia¹,

Camarano²,

Sergi³

et al. 2015

Wetting and Wettability

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It is well known that there are several processes to manufacture composite materials, a large part of which consist in the infiltration of a liquid (matrix) through a porous medium (reinforcement). To perform these processes, both thermodynamics (wetting) and kinetics (Navier-Stokes) must be considered if a good quality composite material is sought. Although wetting and the laws that govern it have been well known for over 200 years, dating back to the original works of Young and Laplace, this is not the case with the Navier-Stokes equation, which remains so far unsolved. Although the Navier-Stokes equation, which describes the motion of a fluid, has been solved for many particular cases, such as the motion of a fluid through a pipe, which has resulted in the well-known Poiseuille equation, or the motion of a fluid through a porous media, described by the Darcy's law (empirical law obtained by Darcy), its general solution remains one of the greatest challenges of mathematicians today. Therefore, the objective of this chapter is to present the resolution of the Navier-Stokes equation with the laws of wetting for different cases of interest in the manufacture of composite materials.

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“…The corresponding values of the viscosities are then determined through (10) (Table VII). When the encapsulant material's viscosity is nominal-the-best, (11) shows the signal-to-noise (SN) ratio used to determine the desired parameter combination to achieve a robust process. Results are shown in Table VII.…”

Section: B Computer-aided Robust Parametric Designmentioning

confidence: 99%

“…Li et al [10] presented a conceptual approach to integrate the design and control methodology for complex processes with specific application in an epoxydispensing control system. Martinez et al [11] recorded the evolution of viscoelastic properties at different temperatures and proposed a kinetic model for the cross-linking reaction. An empirical model was used to predict the change in viscosity of this system with time until gelation is reached.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Parametric Design for a Robust LED Encapsulation Process

Huang

2012

IEEE Trans. Compon., Packag. Manufact. Technol.

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Light-emitting diodes (LEDs) have been adopted in a wide variety of lighting situations. As lighting technology evolves, illumination devices are moving toward miniaturization and high-power applications. Packaging of illumination devices is essential to providing a path for heat dispersion. A full understanding of the viscosity change of the encapsulation material is critical to ensure manufacturability and improved process yield. The typical viscosity model is the initial viscosity plus the change in viscosity over time at a given temperature. The change in viscosity is a function of the reaction rate and the pro-exponential factor. This paper includes the pro-exponential factor in the regression model to improve the prediction accuracy. Through experimental data, the material's viscosity is determined as a function of process temperature, the ratio of the curing agent, and the curing time. A computer-aided parametric design is used to assess the effect of the variation of individual factors on the quality function and proposes a robust LED encapsulation process. An artificial neural network that considers interactions between parameters and establishes fitness functions is used to further enhance the accuracy of predictions and determine the optimal process solution through an iterative training algorithm. The optimal process scenario suggested by this research is a 10% curing agent preheated at 333°K for 40 min. This robust process can improve the signal-to-noise ratios by approximately 43%.Index Terms-Artificial neural network, computer-aided parametric design, light-emitting diode (LED) encapsulation, viscosity model.

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Rheological cure characterization of a polyfunctional epoxy acrylic resin

Cited by 44 publications

References 36 publications

Synthesis and Properties of a Bio‐Based Epoxy Resin with High Epoxy Value and Low Viscosity

Synthesis and Properties of a Bio‐Based Epoxy Resin with High Epoxy Value and Low Viscosity

Wetting and Navier-Stokes Equation — The Manufacture of Composite Materials

Intelligent Parametric Design for a Robust LED Encapsulation Process

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