2021 Research Using Robo-Met's Materials Analysis

July 22, 2021

Robo-Met Product Icon Check out some of this year's first half's new insights uncovered through Robo-Met.3D®'s automated serial sectioning, and tap or click on the title to read more. Contact us to learn more about how you can use Robo-Met to get the material insights you need today.


Read also: Robo-Met Publications in 2020 | 2019 | 2018 | 2017


Effect of thermo-mechanical treatment and strontium addition on workability and mechanical properties of AlSiCu casting alloy

skim2021rmimageIn this study, the potential application of Al-Si-Cu aluminum alloy (ALDC12), which is widely used in the high-pressure die-casting (HPDC) process, for fabricating a wrought product was evaluated. The effects of thermo-mechanical treatment and Sr addition on the microstructure, workability, and mechanical properties of the ALDC12 alloy were investigated in detail. The introduction of thermo-mechanical treatment significantly reduced the interconnectivity of the brittle eutectic Si phase formed during solidification and average grain size. Therefore, the uniformly distributed spherical Si particles and fine grain size considerably improved both the strength and ductility of the ALDC12 alloy. Furthermore, the addition of Sr effectively modified the eutectic Si phase in the casting process, which significantly reduced the occurrence of edge cracks in the subsequent rolling step and further improved the mechanical properties of the final sheets. Consequently, through microstructural control of the ALDC12 aluminum alloy by the thermo-mechanical treatment and Sr addition, it was possible to obtain suitable workability and significantly improved mechanical properties compared with those of cast products.
 
Citation: Lee, Y. S., Jung, J. K., Kim, S. B., Kim, S. H., Lim, C. Y., Kim, H. W., ... & Hyun, S. K. (2021). Effect of thermo-mechanical treatment and strontium addition on workability and mechanical properties of AlSiCu casting alloy. Materials Characterization, 111256.
 

Flaw Identification in Additively Manufactured Parts Using X-ray Computed Tomography and Destructive Serial Sectioning

In additive manufacturing (AM), internal flaws that form during processing can have a detrimental impact on the resultingXCTROBOMET fatigue behavior of the component. Nondestructive x-ray computed tomography (XCT) has been routinely used to inspect AM components. This technique, however, is limited by what is resolvable as well as the automated procedures available to analyze the data. In this study, we compared XCT scans and automated flaw recognition analysis of the corresponding data to results obtained from an automated mechanical polishing-based serial sectioning system. Although internal porosity and surface roughness were easily observed by serial sectioning with bright-field optical microscopy, the same level of information could not be obtained from the XCT data. For the acquisition parameters used, XCT had only a 15.7% detection rate compared to that of serial sectioning. The results point to the need to recognize the limitations of XCT and for supplementary XCT scan quality metrics in addition to the voxel size.

Citation: Snow, Z., Keist, J., Jones, G., Reed, R., Reutzel, E., and Sundar V  (2021). Flaw Identification in Additively Manufactured Parts Using X-ray Computed Tomography and Destructive Serial Sectioning. Journal of Materials Engineering and Performance, 1-7.

Read the full article here. 

The contribution of aluminides to strength of Al–Mg2Si–Cu–Ni alloys at room and elevated temperatures.

The effect of the Ni/Cu-rich aluminides on the strength of Al–15%Mg2Si–Cu–Ni alloys at room and elevated temperatures was analyzed and revealed. The contribution of aluminides to alloys' strength is promoted with the temperature increasing from 25 °C to 350 °C. Both Mg2Si and aluminides strengthen Al matrix and carry the load at room temperature (25 °C). The thermal stable and interconnected aluminides play the leading role in load-carrying and load-transfer capacity at high temperature (350 °C), resulting in the pronounced contribution to alloys' strength. At 450 °C, aluminides lose load-bearing capacity and have no effect on the increase of alloys’ strength.
 
Citation: Sun, Y., Li, C., Liu, Y., Ding, R., Liu, X., Kim, S. H., & Yu, L. (2021). The contribution of aluminides to strength of Al–Mg2Si–Cu–Ni alloys at room and elevated temperatures. Materials Science and Engineering: A, 817, 141381.

Identification and Quantification of 3D Fiber Clusters in Fiber-Reinforced Composite Materials

Microscale computed tomography scans of fiber-reinforced composites reveal that fibers are most often not strictly parallel to each other but exhibit varying degrees of misalignment and entanglement. One characteristic of this entanglement is the degree to which fibers stay together as clusters. In this study, a method for identifying and isolating fiber clusters was established, and scans of two different composite microstructures were analyzed. To identify clusters, fiber center points of the first cross-section were triangulated, and the variation of the perimeter and area of triangles along the fiber direction was used to identify fiber triads which stay together. A filtering process eliminated fiber triads not part of a larger cluster. Geometric properties of the clusters such as cluster orientation, radius of gyration, cluster density, and volume fraction were calculated and compared. The metrics revealed fundamental differences between the two samples, suggesting that clusters have origins in manufacturing.

Citation: Schey, M. J., Beke, T., Appel, L., Zabler, S., Shah, S., Hu, J., ... & Stapleton, S. (2021). Identification and Quantification of 3D Fiber Clusters in Fiber-Reinforced Composite Materials. JOM, 1-14.

AFRL Additive Manufacturing Modeling Series: Challenge 2, Microscale Process-to-Structure Data Description

The Air Force Research Laboratory Additive Manufacturing Modeling Series was executed to create calibration and validation data sets relevant to models of laser powder bed fusion-processed metallic materials. This article describes the data generated for the 2nd of 4 challenge questions which was specifically focused on microscale process-to-structure modeling needs. This work describes the experimental methods, and the resulting characterization data collected from a series of single-track and multi-track deposits built with an EOS M280 from the nickel-based alloy IN625. In general, track dimensions followed common scaling behaviors as a function of processing parameters in quasi-steady-state regions, but significant systematic track geometry variations were quantified in transient regions with more dynamic energy input processes.

 

Citation: Schwalbach, E. J., Chapman, M. G., & Groeber, M. A. (2021). AFRL Additive Manufacturing Modeling Series: Challenge 2, Microscale Process-to-Structure Data Description. Integrating Materials and Manufacturing Innovation, 1-19.

AFRL additive manufacturing modeling series: challenge 4, 3D reconstruction of an IN625 high-energy diffraction microscopy sample using multi-modal serial sectioning.

High-energy diffraction microscopy (HEDM) in-situ mechanical testing experiments offer unique insight into the evolving deformation state within polycrystalline materials. These experiments rely on a sophisticated analysis of the diffraction data to instantiate a 3D reconstruction of grains and other microstructural features associated with the test volume. For microstructures of engineering alloys that are highly twinned and contain numerous features around the estimated spatial resolution of HEDM reconstructions, the accuracy of the reconstructed microstructure is not known. In this study, we address this uncertainty by characterizing the same HEDM sample volume using destructive serial sectioning (SS) that has higher spatial resolution.
HEDMFig4_HTML
 
The SS experiment was performed on an Inconel 625 alloy sample that had undergone HEDM in-situ mechanical testing to a small amount of plastic strain (~ 0.7%), which was part of the Air Force Research Laboratory Additive Manufacturing (AM) Modeling Series. A custom-built automated multi-modal SS system was used to characterize the entire test volume, with a spatial resolution of approximately 1 µm. Epi-illumination optical microscopy images, backscattered electron images, and electron backscattered diffraction maps were collected on every section. All three data modes were utilized and custom data fusion protocols were developed for 3D reconstruction of the test volume. The grain data were homogenized and downsampled to 2 µm as input for Challenge 4 of the AM Modeling Series, which is available at the Materials Data Facility repository.
 
Citation: Chapman, M. G., Shah, M. N., Donegan, S. P., Scott, J. M., Shade, P. A., Menasche, D., & Uchic, M. D. (2021). AFRL additive manufacturing modeling series: challenge 4, 3D reconstruction of an IN625 high-energy diffraction microscopy sample using multi-modal serial sectioning. Integrating Materials and Manufacturing Innovation, 1-13.
 
 

Read also:Robo-Met Publications in 2020 | 2019 | 2018 | 2017


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