TY - JOUR

T1 - Models to Predict the Viscosity of Metal Injection Molding Feedstock Materials as Function of Their Formulation

AU - Gonzalez-Gutierrez, Joamin

AU - Duretek, Ivica

AU - Kukla, Christian

AU - Poljšak, Andreja

AU - Bek, Marko

AU - Emri, Igor

AU - Holzer, Clemens

PY - 2016/5/28

Y1 - 2016/5/28

N2 - 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.

AB - 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.

KW - feedstock

KW - metal injection molding

KW - models

KW - polypropylene

KW - polyoxymethylene

KW - polymer blends

KW - powder content

KW - rheology

KW - stainless steel

KW - viscosity

UR - http://www.mdpi.com/2075-4701/6/6/129

U2 - 10.3390/met6060129

DO - 10.3390/met6060129

M3 - Article

VL - 6.2016

SP - 129

EP - 146

JO - Metals : open access journal

JF - Metals : open access journal

SN - 2075-4701

IS - 6

M1 - 129

ER -