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Metals 2016, 6(6), 129; doi:10.3390/met6060129

Models to Predict the Viscosity of Metal Injection Molding Feedstock Materials as Function of Their Formulation

1
Chair of Polymer Processing, Montanuniversitaet Leoben, Otto Gloeckel-Strasse 2, 8700 Leoben, Austria
2
Center for Experimental Mechanics, University of Ljubljana, Pot za Brdom 104, 1125 Ljubljana, Slovenia
3
Polymer Competence Center Leoben GmbH, Roseggerstrasse 12, 8700 Leoben, Austria
4
Industrial Liaison Department, Montanuniversitaet Leoben, Peter-Tunner-Strasse 27, 8700 Leoben, Austria
*
Author to whom correspondence should be addressed.
Academic Editor: Hugo F. Lopez
Received: 30 March 2016 / Revised: 19 May 2016 / Accepted: 23 May 2016 / Published: 28 May 2016
(This article belongs to the Special Issue Metal Injection Moulding)
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Abstract

The viscosity of feedstock materials is directly related to its processability during injection molding; therefore, being able to predict the viscosity of feedstock materials based on the individual properties of their components can greatly facilitate the formulation of these materials to tailor properties to improve their processability. Many empirical and semi-empirical models are available in the literature that can be used to predict the viscosity of polymeric blends and concentrated suspensions as a function of their formulation; these models can partly be used also for metal injection molding binders and feedstock materials. Among all available models, we made a narrow selection and used only simple models that do not require knowledge of molecular weight or density and have parameters with physical background. In this paper, we investigated the applicability of several of these models for two types of feedstock materials each one with different binder composition and powder loading. For each material, an optimal model was found, but each model was different; therefore, there is not a universal model that fits both materials investigated, which puts under question the underlying physical meaning of these models. View Full-Text
Keywords: feedstock; metal injection molding; models; polypropylene; polyoxymethylene; polymer blends; powder content; rheology; stainless steel; viscosity feedstock; metal injection molding; models; polypropylene; polyoxymethylene; polymer blends; powder content; rheology; stainless steel; viscosity
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Gonzalez-Gutierrez, J.; Duretek, I.; Kukla, C.; Poljšak, A.; Bek, M.; Emri, I.; Holzer, C. Models to Predict the Viscosity of Metal Injection Molding Feedstock Materials as Function of Their Formulation. Metals 2016, 6, 129.

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