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Abstract
In the post-processing of large maritime components, a considerable amount of waste in the form of milling and grinding chips is produced. At the same time, additive manufacturing technologies have shown great potential in producing high-volume parts for maritime applications, allowing novel design approaches and short lead times. In this context, this study presents a sustainable approach to recycle and use aluminium bronze waste material, generated during post-processing of large cast ship propellers, as feedstock for laser-powder directed energy deposition. The recycling technology used to produce powder batches is inductive re-melting in combination with ultrasonic atomization. The derived metal powders are characterized using digital image analysis, powder flowability tests, scanning electron microscopy as well as energy dispersive X-ray spectroscopy. Compared to conventional metal powders produced by gas atomization, the recycled material shows excellent sphericity and a powder size distribution with a higher content of finer and coarser particles. Metallographic sections of deposited additively produced specimens show an increased hardness and reduced ductility, but also competitive densities and higher yield and ultimate tensile strength compared to cast material. The process chain shows high potential for the maritime sector to enable circular and sustainable manufacturing.
AbstractRed mud is the waste of bauxite refinement into alumina, the feedstock for aluminium production1. With about 180 million tonnes produced per year1, red mud has amassed to one of the largest environmentally hazardous waste products, with the staggering amount of 4 billion tonnes accumulated on a global scale1. Here we present how this red mud can be turned into valuable and sustainable feedstock for ironmaking using fossil-free hydrogen-plasma-based reduction, thus mitigating a part of the steel-related carbon dioxide emissions by making it available for the production of several hundred million tonnes of green steel. The process proceeds through rapid liquid-state reduction, chemical partitioning, as well as density-driven and viscosity-driven separation between metal and oxides. We show the underlying chemical reactions, pH-neutralization processes and phase transformations during this surprisingly simple and fast reduction method. The approach establishes a sustainable toxic-waste treatment from aluminium production through using red mud as feedstock to mitigate greenhouse gas emissions from steelmaking.
Efficient density evolution during sintering of the as-printed component is vital to reach full densification and required properties of binder jet (BJT) components. However, due to the high porosity and brittle nature of the green compact, analysis of the microstructure development during sintering is very difficult, resulting in lack of understanding of the densification process. Density development from green state (57 ± 1.6 %) up to full density (99 ± 0.3 %) was characterized by high-resolution synchrotron X-Ray computed tomography (SXCT) on BJT 316L samples from ex-situ interrupted sintering tests. Periodicity of density fluctuations along the building direction was revealed for the first time and was related to the layer thickness of ~ 42 μm during printing that decreased down to ~ 33 μm during sintering. Sintering simulations, utilizing a continuum sintering model developed for BJT, allowed to replicate the density evolution during sintering with a mean error of 2 % and its fluctuation evolution from green (1.66 %) to sintered (0.56 %) state. Additionally, simulation of extreme particle size segregation (1 μm to 130 μm) suggested that non-optimized printing could lead to undesirable density fluctuation amplitude rapid increase (~10 %) during sintering. This might trigger the nucleation of defects (e.g., layer delamination, cracking, or excessive residual porosity) during the sintering process.
AbstractAir‐coupled ultrasonic testing (ACU) is a pioneering technique in non‐destructive testing (NDT). While contact testing and fluid immersion testing are standard methods in many applications, the adoption of ACU is progressing slowly, especially in the low ultrasonic frequency range. A main reason for this development is the difficulty of generating high amplitude ultrasonic bursts with equipment that is robust enough to be applied outside a laboratory environment. This paper presents the fluidic ultrasonic transducer as a solution to this challenge. This novel aeroacoustic source uses the flow instability of a sonic jet in a bistable fluidic switch to generate ultrasonic bursts up to 60 kHz with a mean peak pressure of 320 Pa. The robust design allows operation in adverse environments, independent of the operating fluid. Non‐contact through‐transmission experiments are conducted on four materials and compared with the results of conventional transducers. For the first time, it is shown that the novel fluidic ultrasonic transducer provides a suitable acoustic signal for NDT tasks and has potential of furthering the implementation of ACU in industrial applications.This article is protected by copyright. All rights reserved
In ultrasonic testing, material and structural properties of a specimen can be derived from the time-of-flight (ToF). Using signal features, such as the first peak or envelope maximum, to calculate the ToF is error-prone in multipath arrangements or dispersive and attenuating materials, which is not the case for the signal onset. Borrowing from seismology, researchers used the Akaike information criterion (AIC) picker to automatically determine onset times. The most commonly used formulation, Maeda's AIC picker, is reassessed and found to be based on inappropriate assumptions for signals often used in ultrasonic testing and dependent on arbitrary parameters. Consequently, an onset picker for ultrasonic through-transmission measurements is proposed, based on a spectral entropy criterion (SEC) to model the signal using the AIC framework. This SEC picker takes into account the spectral properties of the ultrasonic signal and is virtually free of arbitrary parameters. Synthetic and experimental data are used to compare the performance of SEC and AIC pickers. It is shown that the accuracy of onset picking is improved for densely sampled data.
AbstractThe high-temperature corrosion behaviors of the equimolar CrCoNi medium-entropy alloy and CrMnFeCoNi high-entropy alloy were studied in a gas atmosphere consisting of a volumetric mixture of 10% H2O, 2% O2, 0.5% SO2, and 87.5% Ar at 800 °C for up to 96 h. Both alloys were initially single-phase fcc with a mean grain size of ~ 50 μm and a homogeneous chemical composition. The oxide layer thickness of CrMnFeCoNi increased linearly with exposure time while it remained constant at ~ 1 μm for CrCoNi. A Cr2O3 layer and minor amounts of (Co,Ni)Cr2O4 developed on the latter while three oxide layers were detected on the former, i.e., a thin and continuous chromium rich oxide layer at the oxide/alloy interface, a dense (Mn,Cr)3O4 layer in the center and a thick and porous layer of Mn3O4 and MnSO4 at the gas/oxide interface. Additionally, a few metal sulfides were observed in the CrMnFeCoNi matrix. These results were found to be in reasonable agreement with thermodynamic calculations.
Noble metal-free nanoparticles (NPs) based on multi-principal element alloys (MPEAs) were synthesized using a one-step pulsed laser ablation in liquids (PLALs) method for the electrochemical reduction of CO2. Laser ablation was performed in pure water or poly-(diallyldimethylammonium chloride) (PDADMAC)-containing an aqueous solution of Al8Cr17Co17Cu8Fe17Ni33 MPEA targets. Transmission electron microscopy (TEM) measurements combined with energy dispersive X-ray (EDX) mapping were used to characterize the structure and composition of the laser-generated MPEA nanoparticles (MPEA-NPs). These results confirmed the presence of a characteristic elemental distribution of a core-shell phase structure as the predominant NP species. The electrocatalytic performance of the laser-generated MPEA-NPs was characterized by linear sweep voltammetry (LSV) demonstrating an enhanced electrocatalytic CO2 activity for PDADMAC-stabilized NPs. The findings of these investigations indicate that MPEAs have great potential to replace conventional, expensive noble metal electrocatalysts.
The production of plastics is rising since they have been invented. Micro, submicro- and nanoplastics are produced intentionally or generated by environmental processes, and constitute ubiquitous contaminants which are ingested orally by consumers. Reported health concerns include intestinal translocation, inflammatory response, oxidative stress and cytotoxicity. Every digestive milieu in the gastrointestinal tract does have an influence on the properties of particles and can cause changes in their effect on biological systems. In this study, we subjected plastic particles of different materials (polylactic acid, polymethylmethacrylate, melamine formaldehyde) and sizes (micro- to nano-range) to a complex artificial digestion model consisting of three intestinal fluid simulants (saliva, gastric and intestinal juice). We monitored the impact of the digestion process on the particles by performing Dynamic Light Scattering, Scanning Electron Microscopy and Asymmetric Flow Field-Flow Fractionation. An in vitro model of the intestinal epithelial barrier was used to monitor cellular effects and translocation behavior of (un)digested particles. In conclusion, artificial digestion decreased cellular interaction and slightly increased transport of all particles across the intestinal barrier. The interaction with organic matter resulted in clear differences in the agglomeration behavior. Moreover, we provide evidence for polymer-, size- and surface-dependent cellular effects of the test particles.
Iron oxide of various structures is frequently used as food colorant (E 172). The spectrum of colors ranges from yellow over orange, red, and brown to black, depending on the chemical structure of the material. E 172 is mostly sold as solid powder. Recent studies have demonstrated the presence of nanoscaled particles in E 172 samples, often to a very high extent. This makes it necessary to investigate the fate of these particles after oral uptake. In this study, 7 differently structured commercially available E 172 food colorants (2 x Yellow FeO(OH), 2 x Red Fe2O3, 1 x Orange Fe2O3 + FeO(OH) and 2 x Black Fe3O4) were investigated for particle dissolution, ion release, cellular uptake, crossing of the intestinal barrier and toxicological impact on intestinal cells. Dissolution was analyzed in water, cell culture medium and artificial digestion fluids. Small-angle X-ray scattering (SAXS) was employed for determination of the specific surface area of the colorants in the digestion fluids. Cellular uptake, transport and toxicological effects were studied using human differentiated Caco-2 cells as an in vitro model of the intestinal barrier. For all materials, a strong interaction with the intestinal cells was observed, albeit there was only a limited dissolution, and no toxic in vitro effects on human cells were recorded.
AbstractHigh-strength aluminum alloys used in aerospace and automotive applications obtain their strength through precipitation hardening. Achieving the desired mechanical properties requires precise control over the nanometer-sized precipitates. However, the microstructure of these alloys changes over time due to aging, leading to a deterioration in strength. Typically, the size, number, and distribution of precipitates for a quantitative assessment of microstructural changes are determined by manual analysis, which is subjective and time-consuming. In our work, we introduce a progressive and automatable approach that enables a more efficient, objective, and reproducible analysis of precipitates. The method involves several sequential steps using an image repository containing dark-field transmission electron microscopy (DF-TEM) images depicting various aging states of an aluminum alloy. During the process, precipitation contours are generated and quantitatively evaluated, and the results are comprehensibly transferred into semantic data structures. The use and deployment of Jupyter Notebooks, along with the beneficial implementation of Semantic Web technologies, significantly enhances the reproducibility and comparability of the findings. This work serves as an exemplar of FAIR image and research data management.