The Master Sinter Curve and Its Application to Binder Jetting Additive Manufacturing

2020 ◽  
Vol 142 (10) ◽  
Author(s):  
Evan Wheat ◽  
Gitanjali Shanbhag ◽  
Mihaela Vlasea

Abstract The master sinter curve (MSC) is an empirical model used to predict the density of a part after being sintered. The model is typically applied to components that undergo isotropic shrinkage. Parts manufactured using binder jetting additive manufacturing (BJAM) are known to have nonuniform powder systems and high levels of anisotropy. This work explores the application of the master sinter curve to components made by BJAM. Cylindrical samples were manufactured with the long axis parallel (vertical), perpendicular (horizontal), and 45 deg to the printing direction. A bimodal blend of titanium powder (0–45  µm and 106–150 µm) was used to make samples with consistent green densities (ranging from 47.2% to 52.3%) between the different orientations. Samples were then sintered at heating rates of 1, 3, and 5 °C/min to a maximum of 1400 °C. After sintering, the samples showed significant variation between the different orientations, with vertical samples on average 7.6 ± 2.98% and 4.7 ± 1.20% denser than the horizontal and the 45 deg samples, respectively. The calculated apparent activation energies for sintering were within the same range for all orientations, 200–260 kJ/mol for vertical and 45 deg, and 140–260 kJ/mol for horizontal samples. Validation sinter runs showed that the density prediction errors of the master sinter curves were between 0.9% and 4.3%. This work shows that the master sinter curve can be applied to predict the sintered density of components manufactured by binder jetting additive manufacturing.

Author(s):  
Wenchao Du ◽  
Xiaorui Ren ◽  
Yexiao Chen ◽  
Chao Ma ◽  
Miladin Radovic ◽  
...  

Binder jetting additive manufacturing is a promising technology for fabricating ceramic parts with complex or customized geometries. However, this process is limited by the relatively low density of the fabricated parts even after sintering. This paper reports a study on effects of mixing powders with graded particle sizes on the powder bed packing density and consequently the sintered density. For the first time, a linear packing model, which can predict the packing density of mixed powders, has been used to guide the selection of particle sizes and fractions of constituent powders. A selection process was constructed to obtain the maximum mixed packing density. In the part of model validation, three types of alumina powders with average sizes of 2 μm, 10 μm, and 70 μm, respectively, were mixed in optimum volumetric fractions that could lead to the maximum packing density based on model predictions. Powder bed packing density was measured on binary mixtures, ternary mixture, and each constituent powders. Furthermore, disk-shaped samples were made, using binder jetting additive manufacturing, from each constituent and mixed powder. Results show that binary and ternary mixtures have higher powder bed packing densities and sintered densities than the corresponding constituent powders. The disks made from the ternary mixture achieved the highest sintered density of 65.5%.


Author(s):  
Yun Bai ◽  
Grady Wagner ◽  
Christopher B. Williams

The binder jetting additive manufacturing (AM) process provides an economical and scalable means of fabricating complex parts from a wide variety of materials. While it is often used to fabricate metal parts, it is typically challenging to fabricate full density parts without large degree of sintering shrinkage. This can be attributed to the inherently low green density and the constraint on powder particle size imposed by challenges in recoating fine powders. To address this issue, the authors explored the use of bimodal powder mixtures in the context of binder jetting of copper. A variety of bimodal powder mixtures of various particle diameters and mixing ratios were printed and sintered to study the impact of bimodal mixtures on the parts' density and shrinkage. It was discovered that, compared to parts printed with monosized fine powders, the use of bimodal powder mixtures improves the powder's packing density (8.2%) and flowability (10.5%), and increases the sintered density (4.0%) while also reducing the sintering shrinkage (6.4%).


2021 ◽  
Author(s):  
SOYEON PARK ◽  
KUN (KELVIN) FU

Polymer nanocomposites have advantages in mechanical, electrical, and optical properties compared to individual components. These unique properties of the nanocomposites have attracted attention in many applications, including electronics, robotics, biomedical fields, automotive industries. To achieve their high performance, it is crucial to control the orientation of nanomaterials within the polymer matrix. For example, the electric conductivity will be maximized in the ordered direction of conductive nanomaterials such as graphene and carbon nanotubes (CNTs). Conventional fabrication methods are commonly used to obtain polymer nanocomposites with the controlled alignment of nanomaterials using electric or magnetic fields, fluid flow, and shear forces. Such approaches may be complex in preparing a manufacturing system, have low fabrication rate, and even limited structure scalability and complexity required for customized functional products. Recently, additive manufacturing (AM), also called 3D printing, has been developed as a major fabrication technology for nanocomposites with aligned reinforcements. AM has the ability to control the orientation of nanoparticles and offers a great way to produce the composites with cost-efficiency, high productivity, scalability, and design flexibility. Herein, we propose a manufacturing process using AM for the architected structure of polymer nanocomposites with oriented nanomaterials using a polylactic acid polymer as the matrix and graphite and CNTs as fillers. AM can achieve the aligned orientation of the nanofillers along the printing direction. Thus, it enables the fabrication of multifunctional nanocomposites with complex shapes and higher precision, from micron to macro scale. This method will offer great opportunities in the advanced applications that require complex multiscale structures such as energy storage devices (e.g., batteries and supercapacitors) and structural electronic devices (e.g., circuits and sensors).


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