Prediction of the chemical and thermal shrinkage in a thermoset polymer

نویسندگان

  • Oleksandr G. Kravchenko
  • Chunyu Li
  • Alejandro Strachan
  • Sergii G. Kravchenko
چکیده

Multi-scale model for response of the bi-material “thermostat,” consisting of a single unidirectional lamina of carbon/epoxy and an uncured layer of neat diglycidyl ether of bisphenol F (DGEBF) with curing agent, diethyltoluenediamine (DETDA), is developed in order to measure thermal strains during a prescribed, but arbitrary thermal history. Molecular modeling simulations provided the elastic modulus, coefficient of thermal expansion, glass transition temperature of DGEBF/DETDA as a function of degree of cure. Cure kinetic properties were determined with differential scanning calorimeter measurements. The model allowed separation of strains due to cure shrinkage and thermal expansion. Combining the molecular modeling predictions, cure kinetic measurements and “thermostat” deflection measurements, complete polymer shrinkage phenomenon is determined over a prescribed thermal cycle. Furthermore, this work can provide a vehicle to develop cure cycles wherein the difference between instantaneous glass transition temperature and specimen temperature is controlled to provide optimum cure cycles for minimum cure shrinkage.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Investigation of the ultrasonic welding strength in glass fiber reinforced thermoset polymers with surface preparation method using laser beam

In this research, tensile strength of ultrasonic welded parts made of thermoset polymer-reinforced glass fiber with surface preparation has been investiagted. In order to elevate the adhesion of two surfaces laser grooving method has been applied. Two type of thermoplastic materials including Plymethyl methacrylate (PMMA) and polypropylene (PP) have been used as interlayers. Influences of main ...

متن کامل

Investigation of the ultrasonic welding strength in glass fiber reinforced thermoset polymers with surface preparation method using laser beam

In this research, tensile strength of ultrasonic welded parts made of thermoset polymer-reinforced glass fiber with surface preparation has been investiagted. In order to elevate the adhesion of two surfaces laser grooving method has been applied. Two type of thermoplastic materials including Plymethyl methacrylate (PMMA) and polypropylene (PP) have been used as interlayers. Influences of main ...

متن کامل

Reactive Secondary Sequence Oxidative Pathology Polymer Model and Antioxidant Tests

AIMS To provide common Organic Chemistry/Polymer Science thermoset free-radical crosslinking Sciences for Medical understanding and also present research findings for several common vitamins/antioxidants with a new class of drugs known as free-radical inhibitors. STUDY DESIGN Peroxide/Fenton transition-metal redox couples that generate free radicals were combined with unsaturated lipid oils t...

متن کامل

Prediction of the Effect of Polymer Membrane Composition in a Dry Air Humidification Process via Neural Network Modeling

Utilization of membrane humidifiers is one of the methods commonly used to humidify reactant gases in polymer electrolyte membrane fuel cells (PEMFC). In this study, polymeric porous membranes with different compositions were prepared to be used in a membrane humidifier module and were employed in a humidification test. Three different neural network models were developed to investigate several...

متن کامل

Thermal conductivity of Water-based nanofluids: Prediction and comparison of models using machine learning

Statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. This paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. The thermal conductivity of nanofluids increases with the volume fraction and temperature. Machine learni...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014