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Electron Beam Powder Bed Fusion-manufactured (E-PBF) porous components with narrow pores or channels and rough walls or struts can be filled with trapped powder after the manufacturing process. Adequate powder removal procedures are required, especially for high-density porous structures. In the present research, sheetbased porous structures with different thicknesses based on triply periodic minimal surfaces fabricated by EPBF were subjected to different post-processing methods, including a traditional powder recovery system for EPBF, chemical etching and ultrasound vibration-assisted powder removal. Wall thickness, internal defects, microstructure and morphology features, powder distribution inside the specimens, mechanical properties and deformation modes were investigated. A powder recovery system could not remove all residual powder from dense structures. In turn, chemical etching was effective for surface morphology changes and subsurface layers elimination but not for powder removal, as it affected the wall thickness, considerably influencing the mechanical properties of the whole structure. The ultrasound vibration method was quite effective for the removal of residual powder from sheet-based TMPS structures and without a severe degradation of mechanical properties. 10.1016/j.msea.2022.144479 Ultrasound vibration also caused grain refinement.
The greatest challenge when using deep convolutional neural networks (DCNNs) for automatic segmentation of microstructural X-ray computed tomography (XCT) data is the acquisition of sufficient and relevant data to train the working network. Traditionally, these have been attained by manually annotating a few slices for 2D DCNNs. However, complex multiphase microstructures would presumably be better segmented with 3D networks. However, manual segmentation labeling for 3D problems is prohibitive. In this work, we introduce a method for generating synthetic XCT data for a challenging six-phase Al–Si alloy composite reinforced with ceramic fibers and particles. Moreover, we propose certain data augmentations (brightness, contrast, noise, and blur), a special in-house designed deep convolutional neural network (Triple UNet), and a multi-view forwarding strategy to promote generalized learning from synthetic data and therefore achieve successful segmentations. We obtain an overall Dice score of 0.77. Lastly, we prove the detrimental effects of artifacts in the XCT data on achieving accurate segmentations when synthetic data are employed for training the DCNNs. The methods presented in this work are applicable to other materials and imaging techniques as well. Successful segmentation coupled with neural networks trained with synthetic data will accelerate scientific output.
The stress–strain behavior of ceramics, such as aluminum titanate, has certain features that are unusual for brittle materials—in particular, a substantial nonlinearity under uniaxial tension, and load–unload hysteresis caused by the sharp increase of the incremental stiffness at the beginning of unloading. These features are observed experimentally and are attributed to microcracking. Here we compare different degrees of stress–strain nonlinearity of aluminum titanate materials and quantitatively model them. We use advanced mechanical testing to observe the mechanical response at room and high temperature; electron microscopy, and X-ray refraction radiography to observe the microstructural changes. Experiments show that two types of microcracks can be distinguished: (i) microcracks induced by cooling from the sintering temperature (due to heterogeneity and anisotropy of thermal expansion), with typical sizes of the order of grain size, and (ii) much larger microcracks generated by the mechanical loading. The two microcrack types produce different effects on the stress–strain curves. Such microcracks and the features of the stress–strain behavior depend on the density of the cooling-induced microcracks and on the distribution of grain sizes. They are modeled analytically and numerically.
Higher energy density materials are being pushed by the research community to make lithium ion batteries a better competitor of chemical fossil fuels for transport applications. This increases potential risk of lithium ion batteries and therefore safety investigations are highly important for application purposes. Operando Computer Tomography provides a non-destructive investigation method of different abuse mechanisms.
Application of X-ray computed tomography (XCT) for studying lithium-ion batteries has gained interest among the research community especially in the past decade [1]. This technique is widely used for ex-situ samples to measure porosity and tortuosity [2], particle size and volume distribution [3] in the graphite anode as well as different cathode materials such as LiCoOx and NiMnCoOx. [4]. In situ measurements of commercial batteries are also often carried out to detect defects induced in a cell by a safety abuse test or manufacturing process [5]. Operando CT of large cells (for example 18650 form factor) is conducted at synchrotron facilities with high flux of high energy photons, however at a cost of details due to the large field of view [6].
Methodik
Thanks to their high brilliance, synchrotron beam facilitates us to do a full Computed Tomography in a short time. This enables us to measure batteries while being cycled with a reasonable time resolution to record morphological changes. In this poster we illustrate how one can utilize this ability to investigate abuse mechanisms on an actual commercially available lithium ion battery as well as a home made micro cell.
Ergebnisse
In this work, lab-based and synchrotron X-ray computed tomography is applied to commercial Li-ion batteries. It is shown how to find most suitable imaging settings to study available lithium-ion batteries on different size scales, from cell level to particle level. We also demonstrate how to optimize contrast as well as both temporal and spatial resolutions to study in-situ and operando processes in a commercial battery using attenuation and phase contrast SXCT. Manufacturing defects and inconsistencies on cell level as well as the electrode and microstructure on material level are shown in our study. Moreover, some abuse conditions are imaged in operando in a commercially available li-ion battery.
Diskussion
This work has demonstrated various imaging settings using lab and synchrotron based X-ray computed tomography to study in-situ as well as under operando condition, some abuse mechanisms in commercial lithium-ion batteries from cell level to electrode and particle level.
Inconel 718 (IN718) is a traditional age-hardenable nickel-based alloy that has been increasingly processed by additive manufacturing (AM) in recent years. In the as-solidified condition, IN718 exhibits chemical segregation and the undesired Laves phase, requiring a solution annealing (SA) prior to aging. The material produced by AM does not respond to the established thermal routines in the same way as conventionally produced IN718, and there is still no consensus on which routine yields optimal results. This work aims to provide a fundamental understanding of the heat treatment (HT) response by continuously monitoring the microstructural evolution during SA via time-resolved synchrotron x-ray diffraction, complemented by ex-situ scanning electron microscopy (SEM). The samples were produced by laser powder bed fusion to a geometry of 10x20x90 mm³, from which Ø1x5 mm³ cylindric specimens were extracted. Two different scanning strategies – incremental 67° rotations, Rot, and alternating 0°/67° tracks, Alt – were used, leading to two different as-built conditions. 1-hour SAs were carried out in the beamline ID22 of the ESRF at 50 KeV. Two SA temperatures, SA1 = 1020 °C, and SA2 = 1080 °C were tested for each scanning strategy. Data were processed using the software PDIndexer. In the as-built state, all samples showed typical subgrain columnar cell structures with predominant Nb/Mo segregation and Laves phase at the cell walls, as seen by SEM. The Alt scan induced higher intensity on the Laves peaks than the Rot scan, suggesting a greater content of Laves. Chemical homogenization in the SA was largely achieved during the heating ramp (Fig. 1). SA2 eliminated the Laves peaks just before reaching 1080 °C, and mitigated differences between Rot and Alt samples. On the other hand, SA1 induced the precipitation of the generally detrimental δ phase, also observed by SEM. Furthermore, the Rot scan showed higher δ peak intensities than the Alt scan, indicating a higher content of δ in the latter. No signs of recrystallization were observed in any of the investigated SAs.
The overview of the activity of Federal Institute for Material Research and Testing (BAM, Belin, Germany) in the field of additively manufacturing material characterization will be presented. The research of our group is focused on the 3D imaging of AM materials by means of X-ray Computed Tomography at the lab and at synchrotron, and the residual stress characterization by diffraction (nondestructive technique). Also, two successful research project in collaboration with CAM2, Sweden are presented.
Li dendrites penetration through solid electrolytes (SEs) challenges the development of solid-state Li batteries (SSLBs). To date, significant efforts are devoted to understand the mechanistic dynamics of Li dendrites nucleation, growth, and propagation in SEs, and various strategies that aim to alleviate and even inhibit Li dendrite formation have been proposed. Nevertheless, most of these conventional strategies require either additional material processing steps or new materials/layers that eventually increase battery cost and complexity. In contrast, using external fields, such as mechanical force, temperature physical field, electric field, pulse current, and even magnetic field to regulate Li dendrites penetration through SEs, seems to be one of the most cost-effective strategies. This review focuses on the current research progress of utilizing external physical fields in regulating Li dendrites growth in SSLBs. For this purpose, the mechanical properties of Li and SEs, as well as the experimental results that visually track Li penetration dynamics, are reviewed. Finally, the review ends with remaining open questions in future studies of Li dendrites growth and penetration in SEs. It is hoped this review can shed some light on understanding the complex Li dendrite issues in SSLBs and potentially guide their rational design for further development.
Structural alloys are largely employed in key industrial sectors and their demand is predicted to rise rapidly for the next decades. Most of these materials require a large amount of energy for extraction and manufacturing, which causes the emission of greenhouse gases and other pollutants. Therefore, strategies for improving the sustainability of structural metallic alloys are urgently needed.
Additive Manufacturing (AM), in particular Laser Powder Bed Fusion (PBF-LB/M), aims to be a sustainable manufacturing process, as it allows the build-up of complex geometry in near net-shape from 3D models, while minimizing material waste and the energy required for the process and post-process treatments.
Nevertheless, the application of additively manufactured parts in structural safety-relevant applications is still hindered by the poor fatigue performance. The cause of this has been mainly attributed to the presence of manufacturing defects and surface roughness. Therefore, a huge effort has been made to optimize the process parameters and to introduce post-process treatments to minimize the defect content. However, material flaws cannot be fully eliminated, but these can be considered in a damage tolerance framework for the prediction of the fatigue performance of additively manufactured metallic materials, which is essential for part design and qualification.
This work aims at presenting different modelling strategies for the prediction of the fatigue limit of AM metals. Simple empirical models and more complex models based on fatigue short crack propagation are proposed. The investigated material is an AlSi10Mg alloy fabricated by PBF-LB/M and subjected to two different low-temperature heat-treatments (265°C for 1 h and 300°C for 2h). The results show that the models can provide good approximation of the fatigue limits and help in the interpretation of the scatter of fatigue data.
This paper presents an automatic damage imaging technique by employing a signal processing approach based on applying hierarchically clustered filters across different domains. The technique involves time-frequency-wavenumber filter banks which are applied sequentially to ultrasonic guided wave (UGW) data. The study is conducted for a single lap joint composite specimen with a special focus on small voids which were formed due to manual adhesive component mixing. UGW data are acquired with a 3D Scanning Laser Doppler Vibrometer (LDV) over the scan area of the bonded plate. UGWs are excited at the central frequency of 100 kHz by a single piezoelectric transducer mounted on the surface of the single plate. Within each domain of time, frequency, and wavenumber, four filters are designed which results in 64 distinct filtered wavefields. From each filtered wavefield, an image is obtained by using root-mean-square (RMS) calculation of the signals. The obtained results are then combined to create a final, improved-resolution image of the scan area. The final image is compared to the image obtained through RMS calculation of full wavefield with interpolation through Delaunay triangulation and the image obtained by X-ray radiography. The results show that the smallest void that could be detected has a diameter of 2.14 mm.
Al-Si alloys produced by Laser Powder Bed Fusion (PBFLB) allow the fabrication of lightweight free-shape components. Due to the extremely heterogeneous cooling and heating, PBF-LB induces high magnitude residual stress (RS) and a fine Si microstructure. As the RS can be deleterious to the fatigue resistance of engineering components, great efforts are focused on understanding their evolution in as-built state (AB) and after post-process heat treatments (HT). RS in single edge notch bending (SENB) subjected to different HT are investigated (HT1: 1h at 265°C and HT2: 2h at 300°C).