Models to Predict the Viscosity of Metal Injection Molding Feedstock Materials as Function of Their Formulation
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 pr...
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| Format: | Article |
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MDPI AG
2016-05-01
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| Series: | Metals |
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| Online Access: | http://www.mdpi.com/2075-4701/6/6/129 |
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| author | Joamin Gonzalez-Gutierrez Ivica Duretek Christian Kukla Andreja Poljšak Marko Bek Igor Emri Clemens Holzer |
| author_facet | Joamin Gonzalez-Gutierrez Ivica Duretek Christian Kukla Andreja Poljšak Marko Bek Igor Emri Clemens Holzer |
| author_sort | Joamin Gonzalez-Gutierrez |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-13T01:45:31Z |
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| institution | Directory Open Access Journal |
| issn | 2075-4701 |
| language | English |
| last_indexed | 2024-12-13T01:45:31Z |
| publishDate | 2016-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Metals |
| spelling | doaj.art-c8e7d6ee1c0c4b1aa953dea18c11f5672022-12-22T00:03:39ZengMDPI AGMetals2075-47012016-05-016612910.3390/met6060129met6060129Models to Predict the Viscosity of Metal Injection Molding Feedstock Materials as Function of Their FormulationJoamin Gonzalez-Gutierrez0Ivica Duretek1Christian Kukla2Andreja Poljšak3Marko Bek4Igor Emri5Clemens Holzer6Chair of Polymer Processing, Montanuniversitaet Leoben, Otto Gloeckel-Strasse 2, 8700 Leoben, AustriaChair of Polymer Processing, Montanuniversitaet Leoben, Otto Gloeckel-Strasse 2, 8700 Leoben, AustriaIndustrial Liaison Department, Montanuniversitaet Leoben, Peter-Tunner-Strasse 27, 8700 Leoben, AustriaCenter for Experimental Mechanics, University of Ljubljana, Pot za Brdom 104, 1125 Ljubljana, SloveniaCenter for Experimental Mechanics, University of Ljubljana, Pot za Brdom 104, 1125 Ljubljana, SloveniaCenter for Experimental Mechanics, University of Ljubljana, Pot za Brdom 104, 1125 Ljubljana, SloveniaChair of Polymer Processing, Montanuniversitaet Leoben, Otto Gloeckel-Strasse 2, 8700 Leoben, AustriaThe 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.http://www.mdpi.com/2075-4701/6/6/129feedstockmetal injection moldingmodelspolypropylenepolyoxymethylenepolymer blendspowder contentrheologystainless steelviscosity |
| spellingShingle | Joamin Gonzalez-Gutierrez Ivica Duretek Christian Kukla Andreja Poljšak Marko Bek Igor Emri Clemens Holzer Models to Predict the Viscosity of Metal Injection Molding Feedstock Materials as Function of Their Formulation Metals feedstock metal injection molding models polypropylene polyoxymethylene polymer blends powder content rheology stainless steel viscosity |
| title | Models to Predict the Viscosity of Metal Injection Molding Feedstock Materials as Function of Their Formulation |
| title_full | Models to Predict the Viscosity of Metal Injection Molding Feedstock Materials as Function of Their Formulation |
| title_fullStr | Models to Predict the Viscosity of Metal Injection Molding Feedstock Materials as Function of Their Formulation |
| title_full_unstemmed | Models to Predict the Viscosity of Metal Injection Molding Feedstock Materials as Function of Their Formulation |
| title_short | Models to Predict the Viscosity of Metal Injection Molding Feedstock Materials as Function of Their Formulation |
| title_sort | models to predict the viscosity of metal injection molding feedstock materials as function of their formulation |
| topic | feedstock metal injection molding models polypropylene polyoxymethylene polymer blends powder content rheology stainless steel viscosity |
| url | http://www.mdpi.com/2075-4701/6/6/129 |
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