Process Optimization of the Morphological Properties of Epoxy Resin Molding Compounds Using Response Surface Design

Author:

Vogelwaid Julian12ORCID,Bayer Martin1ORCID,Walz Michael1ORCID,Kutuzova Larysa3ORCID,Kandelbauer Andreas34ORCID,Jacob Timo2ORCID

Affiliation:

1. Mobility Electronics, Engineering Technology Polymer & Packaging, Robert Bosch GmbH, 72770 Reutlingen, Germany

2. Fakultät für Naturwissenschaften, Institut für Elektrochemie, Universität Ulm, 89081 Ulm, Germany

3. Fakultät für Life Sciences, Reutlingen University, 72762 Reutlingen, Germany

4. Department of Material Sciences and Process Engineering, Institute of Wood Technology and Renewable Materials, University of Natural Resources and Life Sciences, 1180 Vienna, Austria

Abstract

An epoxy compound’s polymer structure can be characterized by the glass transition temperature (Tg) which is often seen as the primary morphological characteristic. Determining the Tg after manufacturing thermoset-molded parts is an important objective in material characterization. To characterize quantitatively the dependence of Tg on the degree of cure, the DiBenedetto equation is usually used. Monitoring polymer network formation during molding processes is therefore one of the most challenging tasks in polymer processing and can be achieved using dielectric analysis (DEA). In this study, the morphological properties of an epoxy resin-based molding compounds (EMC) were optimized for the molding process using response surface analysis. Processing parameters such as curing temperature, curing time, and injection rate were investigated according to a DoE strategy and analyzed as the main factors affecting Tg as well as the degree of cure. A new method to measure the Tg at a certain degree of cure was developed based on warpage analysis. The degree of cure was determined inline via dielectric analysis (DEA) and offline using differential scanning calorimetry (DSC). The results were used as the response in the DoE models. The use of the DiBenedetto equation to refine the response characteristics for a wide range of process parameters has significantly improved the quality of response surface models based on the DoE approach.

Publisher

MDPI AG

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