Analytische Chemie
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Paper des Monats
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Shape memory alloy structures for actuator and vibration damper applications may be manufactured using wire arc additive manufacturing (W AAM), which is one of the additive manufacturing technologies. Multilayer deposition causes heat accumulation during W AAM, which rises the preheat temperature of the previously created layer. This leads to process instabilities, which result in deviations from the desired dimensions and mechanical properties changes. During W AAM deposition of the wall structure, a systematic research is carried out by adjusting the interlayer delay from 10 to 30 s. When the delay period is increased from 10 to 30 s, the breadth decreases by 45% and the height increases by 33%. Grain refinement occurs when the interlayer delay duration is increased, resulting in better hardness, phase transformation temperature, compressive strength, and shape recovery behavior. This study shows how the interlayer delay affects the behavior of W AAM-built nickel-titanium alloy (NiTi) structures in a variety of applications.
This paper describes a wireless mobile prototype able to perform optical measurements by means of a miniatur-ized spectrometer for low light analysis, e.g. fluorescent sensors. Evaluations, calculations, calibration management and result display are performed by a computer or a standard tablet. The device was designed primarily to detect traces of oil in drinking or ground water and for the analyses of crude oils. However, it can also address a wide range of fluorescent sensors. The fast and user-friendly inspection of water quality or oil properties, as well as the adaptability and mobility, make the device attractive for a variety of users. Further application areas could be easily imple-mented by adapting the optics and the software (database, data processing and calibration plots, etc.)
We present a workflow for obtaining fully trained artificial neural networks that can perform automatic particle segmentations of agglomerated, non-spherical nanoparticles from scanning electron microscopy images “from scratch”, without the need for large training data sets of manually annotated images. The whole process only requires about 15 minutes of hands-on time by a user and can typically be finished within less than 12 hours when training on a single graphics card (GPU). After training, SEM image analysis can be carried out by the artificial neural network within seconds. This is achieved by using unsupervised learning for most of the training dataset generation, making heavy use of generative adversarial networks and especially unpaired image-to-image translation via cycle-consistent adversarial networks. We compare the segmentation masks obtained with our suggested workflow qualitatively and quantitatively to state-of-the-art methods using various metrics. Finally, we used the segmentation masks for automatically extracting particle size distributions from the SEM images of TiO2 particles, which were in excellent agreement with particle size distributions obtained manually but could be obtained in a fraction of the time.
Inhibition of respiratory viruses is one of the most urgent topics as underlined by different pandemics in the last two decades. This impels the development of new materials for binding and incapacitation of the viruses. In this work, we have demonstrated that an optimal deployment of influenza A virus (IAV) targeting ligand sialic acid (SA) on a flexible 2D platform enables its binding and wrapping around IAV particles. A series of 2D sialylated platforms consisting graphene and polyglycerol are prepared with different degrees of SA functionalization around 10%, 30%, and 90% named as G-PG-SAL, G-PG-SAM, and G-PG-SAH, respectively. The cryo-electron tomography (Cryo-ET) analysis has proved wrapping of IAV particles by G-PG-SAM.
A confocal-based colocalization assay established for these materials has offered the comparison of binding potential of sialylated and non-sialylated nanoplatforms for IAV. With this method, we have estimated the binding potential of the G-PG-SAM and G-PG-SAH sheets for IAV particles around 50 and 20 times higher than the control sheets, respectively, whereas the low functionalized G-PG-SAL have not shown any significant colocalization value.
Moreover, optimized G-PG-SAM exhibits high potency to block IAV from
binding with the MDCK cells.
Additively manufactured (AM) metallic sheet-based Triply Periodic Minimal Surface Structures (TPMSS) meet several requirements in both bio-medical and engineering fields: Tunable mechanical properties, low sensitivity to manufacturing defects, mechanical stability, and high energy absorption. However, they also present some challenges related to quality control, which can prevent their successful application. In fact, the optimization of the AM process is impossible without considering structural characteristics as manufacturing accuracy, internal defects, as well as surface topography and roughness. In this study, the quantitative non-destructive analysis of TPMSS manufactured from Ti-6Al-4V alloy by electron beam melting was performed by means of X-ray computed tomography (XCT). Several advanced image analysis workflows are presented to evaluate the effect of build orientation on wall thicknesses distribution, wall degradation, and surface roughness reduction due to the chemical etching of TPMSS. It is shown that the manufacturing accuracy differs for the structural elements printed parallel and orthogonal to the manufactured layers. Different strategies for chemical etching show different powder removal capabilities and both lead to the loss of material and hence the gradient of the wall thickness. This affects the mechanical performance under compression by reduction of the yield stress. The positive effect of the chemical etching is the reduction of the surface roughness, which can potentially improve the fatigue properties of the components. Finally, XCT was used to correlate the amount of retained powder with the pore size of the functionally graded TPMSS, which can further improve the manufacturing process.
The literature has shown that the application of laminography provides advantages as 3D radiographic imaging with depth information for in house and mobile testing. This permits to distinguish between overlapping indications, measure the extension along radiation direction and classify indications as surface open or subsurface
ones as required in critical engineering assessment. This work provides a comparative study and measurements of the three techniques Digital Radiography (DR) with Digital Detector Arrays (DDA), Coplanar Translational Laminography (CTL) and Computed Tomography (CT), applied for composite pipeline inspection. It is demonstrated that CTL and CT provide advantages for the evaluation of pipe-to-pipe connections and the evaluation of adhesive applications. They show indications of discontinuities with higher contrast sensitivity than radiography.
Beyond it, two specimen, namely Phantom 1 and Phantom 2, were developed and manufactured by additive manufacturing to analyze the preferential detection sensitivity and the direction of features and depth information for laminographic measurements. Another goal was to show the laminographic capabilities to distinguish between overlapping discontinuities. CTL is especially suitable for mobile inspection. Special glass fiber reinforced polymer samples (GRP) were manufactured for further analysis and comparisons between the abovementioned techniques. Finally, Phantoms 1 and 2 show the capability of laminography to detect overlapping indications and also show that discontinuities oriented perpendicular to the scan direction have the highest contrast sensitivity for laminographic measurements.
For the first time, X-ray refraction techniques are proven for the identification of void formation in Ti-6Al-4V parts produced by selective laser melting. The topology and volume fraction of pores are measured in samples produced with different laser energy density. Unique X-ray refraction methods identify different kinds of defects, characteristic to the regions below and above the Optimum laser energy density, namely unprocessed powder (unmolten powder particles, balling effect, and Fusion defects) from empty keyhole pores. Furthermore, it is possible to detect small inhomogeneities (voids or cracks) with sizes below the spatial resolution of optical microscopy and X-ray computed tomography.
Soft x-ray spectromicroscopy techniques have seen great amount of development in the recent years, and with the development of new diffraction limited synchrotron source, many new nanoscale and mesoscale characterization opportunities of applied materials are foreseen. In this perspective, the authors present some examples that illustrate the capabilities of spectromicroscopy techniques, namely, 2D and 3D spatially resolved chemical quantification, surface and bulk sensitive measurements, and polarization dependent measurements as applied to iron oxide nanoparticulate materials of biological, geological, and other origins.
The preparation and characterization of a Titanium dioxide (TiO2) by a simple, cost effective, facile and eco-friendly green synthesis method using Peltophorum pterocarpum plant extract is presented. The green synthesized nanoparticles were characterized using X-ray diffraction (XRD), Raman spectroscopy, High-resolution transmission electron microscopy (HR-TEM) and X-ray absorption near edge spectroscopy (XANES). XRD results show that the prepared TiO2 NPs were significantly crystalline with various percentages of anatase and rutile phases. The nanoparticles were found to have different diameters ranging from 20 to 80 nm. No evidence of any intermediate or different TiO2 phases were found in XANES measurements performed at the Ti K- and L-edge. It is shown that the TiO2 NPs with high uniformity, high surface area and minimum aggregation can be prepared with relative ease and the desired anatase: rutile phase ratio can be obtained by controlling the experimental conditions.
The growing interest in artificial bioorganic Interfaces as a platform for applications in emerging Areas as personalized medicine, clinical diagnostics, biosensing, biofilms, prevention of biofouling, and other fields of bioengineering is the origin of a need for in Detail multitechnique characterizations of such layers and interfaces. The in-depth analysis of biointerfaces is of special interest as the properties of functional bioorganic coatings can be dramatically affected by in-depth variations of composition.
In worst cases, the functionality of a device produced using such coatings can be substantially reduced or even fully lost.