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Material defects in fiber reinforced polymers such as delaminations can rapidly degrade the material properties or can lead to the failure of a component. Pulse thermography (PT) has proven to be a valuable tool to identify and quantify such defects in opaque materials. However, quantification of delaminations within semitransparent materials is extremely challenging. We present an approach to quantify delaminations within materials being semitransparent within the wavelength ranges of the optical excitation sources as well as of the infrared (IR) camera. PT experimental data of a glass fiber reinforced polymer with a real delamination within the material were reconstructed by one dimensional (1D) mathematical models. These models describe the heat diffusion within the material and consider semitransparency to the excitation source as well to the IR camera, thermal losses at the samples surfaces and a thermal contact resistance between the two layers describing the delamination. By fitting the models to the PT data, we were able to determine the depth of the delamination very accurately. Additionally, we analyzed synthetic PT data from a 2D simulation with our 1D-models to show how the thermal contact resistance is influenced by lateral heat flow within the material.
This paper reports results from in situ electrochemical X-ray absorption near-edge spectroscopy (XANES) studies of the corrosion processes on model thin iron films in the presence of iron reducing bacteria Shewanella putrefaciens. Here we investigate the electrochemical activity of two cultures grown in the presence and absence of Fe(III) citrate in the culture medium. The XANES spectra and the OCP data of the Fe sample incubated with the culture grown in absence of Fe(III) did not show any significant changes during twenty hours of monitoring. In the case of the culture grown in Fe(III) containing medium, an accelerated dissolution of the iron film was observed together with the formation of a mixed Fe(II)-Fe(III) hydroxide surface layer. The open circuit potential (OCP) steadily approached the free corrosion potential of iron in neutral chloride containing electrolytes, indicating a continuous dissolution process without passivation.
Ultrashort pulse laser processing of materials allows for precise machining with high accuracy. By increasing the repetition rate to several 100 kHz, laser machining becomes quick and cost-effective. Ultrafast laser processing at high repetition rates and peak intensities above 10^13 W/cm^2 can cause a potential hazard by generation of unwanted x-ray radiation. Therefore, radiation protection must be considered. For 925 fs pulse duration at a center wavelength of 1030 nm, the x-ray emission in air at a repetition rate of 400 kHz was investigated up to a
peak intensity of 2.6 × 10^14 W/cm^2. Based on the presented measurements, the properties of potential shielding materials will be discussed. By extending our previous works, a scaling of the x-ray radiation emission to higher peak intensities up to 10^15 W/cm^2 is described, and emitted x-ray doses are predicted.
In this contribution, chemical, structural, and mechanical alterations in various types of femtosecond laser-generated surface structures, i.e., laser-induced periodic surface structures (LIPSS, ripples), Grooves, and Spikes on titanium alloy, are characterized by various surface analytical techniques, including X-ray diffraction and glow-discharge optical emission spectroscopy. The formation of oxide layers of the different laser-based structures inherently influences the friction and wear performance as demonstrated in oil-lubricated reciprocating sliding tribological tests (RSTTs) along with subsequent elemental mapping by energy-dispersive X-ray analysis. It is revealed that the fs-laser scan processing (790 nm, 30 fs, 1 kHz) of near-wavelength-sized LIPSS leads to the formation of a graded oxide layer extending a few hundreds of nanometers into depth, consisting mainly of amorphous oxides. Other superficial fs-laser-generated structures such as periodic Grooves and irregular Spikes produced at higher fluences and effective number of pulses per unit area present even thicker graded oxide layers that are also suitable for friction reduction and wear resistance. Ultimately, these femtosecond laser-induced nanostructured surface layers efficiently prevent a direct metal-to-metal contact in the RSTT and may act as an anchor layer for specific wear-reducing additives contained in the used engine oil.
The mixture of ammonium nitrate (AN) prills and fuel oil (FO), usually referred to as ANFO, is extensively used in the mining industry as a bulk explosive. One of the major performance predictors of ANFO mixtures is the fuel oil retention, which is itself governed by the complex pore structure of the AN prills. In this study, we present how X-ray computed tomography (XCT), and the associated advanced data processing workflow, can be used to fully characterise the structure and morphology of AN prills. We show that structural parameters such as volume fraction of the different phases and morphological parameters such as specific surface area and shape factor can be reliably extracted from the XCT data, and that there is a good agreement with the measured oil retention values. Importantly, oil retention measurements (qualifying the efficiency of ANFO as explosives) correlate well with the specific surface area determined by XCT. XCT can therefore be employed non-destructively; it can accurately evaluate and characterise porosity in ammonium nitrate prills, and even predict their efficiency.
Hydrocarbons fuel our economy. Furthermore, intermediate goods and consumer products are often hydrocarbon-based. Beside all the progress they made possible, hydrogen-containing substances can have severe detrimental effects on materials exposed to them. Hydrogen-assisted failure of iron alloys has been recognised more than a century ago. The present study aims to providing further insight into the degradation of the austenitic stainless steel AISI 304L (EN 1.4307) exposed to hydrogen. To this end, samples were electrochemically charged with the hydrogen isotope deuterium (2H, D) and analysed by scanning electron microscopy (SEM), electron back-scatter diffraction (EBSD) and time-of-flight secondary ion mass spectrometry (ToF-SIMS). It was found that deuterium caused a phase transformation from the original γ austenite into ε- and α’-martensite. Despite their low solubility for hydrogen, viz. deuterium, the newly formed phases showed high deuterium concentration which was attributed to the increased density of traps. Information about the behaviour of deuterium in the material subjected to external mechanical load was gathered. A four-point-bending device was developed for this purpose. This allowed to analyse in-situ pre-charged samples in the ToF-SIMS during the application of external mechanical load. The results indicate a movement of deuterium towards the regions of highest stress.
Accelerator magnets that can reach magnetic fields well beyond the Nb-Ti performance limits are presently being built and developed, using Nb3Sn superconductors. This technology requires reaction heat treatment (RHT) of the magnet coils, during which Nb3Sn is formed from its ductile precursor materials (a “wind and react” approach). The Nb3Sn microstructure and microchemistry are strongly influenced by the conductor fabrication route, and by the Phase changes during RHT. By combining in situ differential scanning calorimetry, high Energy synchrotron x-ray diffraction, and micro-tomography experiments, we have acquired a unique data set that describes in great detail the phase and microstructure changes that take place during the processing of restacked rod process (RRP), powder-in-tube (PIT), and internal tin (IT) Nb3Sn wires. At temperatures below 450 ° the phase evolutions in the three wire types are similar, with respectively solid state interdiffusion of Cu and Sn, Cu6Sn5 formation, and Cu6Sn5 peritectic transformation. Distinct differences in phase evolutions in the wires are found when temperatures exceed 450 °C. The volume changes of the conductor during RHT are a difficulty in the production of Nb3Sn accelerator magnets. We compare the wire diameter changes measured in situ by dilatometry with the phase and void volume evolution of the three types of Nb3Sn wire. Unlike the Nb3Sn wire length changes, the wire diameter evolution is characteristic for each Nb3Sn wire type. The strongest volume increase, of about 5%, is observed in the RRP wire, where the main diameter increase occurs above 600 °C upon Nb3Sn formation.
We describe and demonstrate a novel experimental approach to measure broadband, amplitude- and phase-resolved scattering spectra of single nanoparticles with 10-nm spatial resolution. Nanofocusing of Surface plasmon polaritons (SPPs) propagating along the shaft of a conical gold taper is used to create a spatially isolated, spectrally broad nanoscale light source at ist very apex. The interference between these incident SPPs and SPPs that are backpropagating from the apex leads to the formation of an inherently phase-stable interferogram, which we detect in the far field by partially scattering SPPs off a small protrusion on the taper shaft. We show that these interferograms allow the reconstruction of both the amplitude and phase of the local optical near fields around individual nanoparticles optically coupled to the taper apex. We extract local light scattering spectra of particles and quantify line broadenings and spectral shifts induced by tip-sample coupling. Our experimental findings are supported by corresponding finite-difference time-domain and coupled dipole simulations and Show that, in the limit of weak tip-sample coupling, the measurements directly probe the projected local density of optical states of the plasmonic system. The combination of a highly stable inline interferometer with the inherent optical background suppression through nanofocusing makes it a promising tool for the locally resolved study of the spectral and temporal optical response of coupled hybrid nanosystems.
Separation technology as a sub-discipline of thermal process engineering is one of the most critical steps in the production of chemicals, essential for the quality of intermediate and end products.
The discipline comprises the construction of facilities that convert raw materials into value-added products along the value chain. Conversions typically take place in repeated reaction and separation steps—either in batch or continuous processes. The end products are the result of several production and separation steps that are not only sequentially linked, but also include the treatment of unused raw materials, by-products and wastes. Production processes in the process industry are particularly susceptible to fluctuations in raw materials and other influences affecting product quality. This is a challenge, despite increasing fluctuations, to deliver targeted quality and simultaneously meet the increasing dynamics of the market, at least for high value fine chemicals. In order to survive successfully in a changed environment, chemical companies must tread new paths. This includes the potential of digital technologies. The full integration and intelligent networking of systems and processes is progressing hesitantly. This contribution aims to encourage a more holistic approach to the digitalization in thermal process engineering by introduction of integrated and networked systems and processes.
Municipal solid waste incineration (MSWI) is one of the leading technologies for municipal solid waste (MSW) treatment in Europe. Incineration bottom ash (IBA) is the main solid residue from MSWI, and its annual European production is about 20 million tons. The composition of IBA depends on the composition of the incinerated waste; therefore, it may contain significant amounts of ferrous and non-ferrous (NFe) metals as well as glass that can be recovered. Technologies for NFe metals recovery have emerged in IBA treatment since the 1990s and became common practice in many developed countries. Although the principles and used apparatus are nearly the same in all treatment trains, the differences in technological approaches to recovery of valuable components from IBA – with a special focus on NFe metals recovery – are summarized in this paper.
The analysis of pollen chemical composition is important to many fields, including agriculture, plant physiology, ecology, allergology, and climate studies. Here, the potential of a combination of different spectroscopic and spectrometric methods regarding the characterization of small biochemical differences between pollen samples was evaluated using multivariate statistical approaches. Pollen samples, collected from three populations of the grass Poa alpina, were analyzed using Fourier-transform infrared (FTIR) spectroscopy, Raman spectroscopy, surface enhanced Raman scattering (SERS), and matrix assisted laser desorption/ionization mass spectrometry (MALDI-TOF MS). The variation in the sample set can be described in a hierarchical framework comprising three populations of the same grass species and four different growth conditions of the parent plants for each of the populations. Therefore, the data set can work here as a model system to evaluate the classification and characterization ability of the different spectroscopic and spectrometric methods. ANOVA Simultaneous Component Analysis (ASCA) was applied to achieve a separation of different sources of variance in the complex sample set. Since the chosen methods and sample preparations probe different parts and/or molecular constituents of the pollen grains, complementary information about the chemical composition of the pollen can be obtained. By using consensus principal component analysis (CPCA), data from the different methods are linked together. This enables an investigation of the underlying global information, since complementary chemical data are combined. The molecular information from four spectroscopies was combined with phenotypical information gathered from the parent plants, thereby helping to potentially link pollen chemistry to other biotic and abiotic parameters.
Mechanical flexibility in single crystals of covalently bound materials is a fascinating and poorly understood phenomenon. We present here the first example of a plastically flexible one-dimensional (1D) coordination polymer. The compound [Zn(m-Cl)2(3,5-dichloropyridine)2]n is flexible over two crystallographic faces. Remarkably, the single crystal remains intact when bent to 1808. A combination of microscopy, diffraction, and spectroscopic studies have been used to probe the structural response of the crystal lattice to mechanical bending. Deformation of the covalent polymer chains does not appear to be responsible for the observed macroscopic bending. Instead, our results suggest that mechanical bending occurs by displacement of the coordination polymer chains. Based on experimental and theoretical evidence, we propose a new model for mechanical flexibility in 1D coordination polymers. Moreover, our calculations propose a cause of the different mechanical properties of this compound and a structurally similar elastic material
Spatial heterodyne spectroscopy (SHS) is a novel spectral analysis technique that is being applied for Raman spectroscopy of minerals. This paper presents the theoretical basis of SHS and its application for Raman measurements of calcite, quartz and forsterite in marble, copper ore and nickel ore, respectively. The SHS measurements are done using a broadband (518–686 nm) and resolving power R ≈ 3000 instrument. The spectra obtained using SHS are compared to those obtained by benchtop and modular dispersive spectrometers. It is found that SHRS performance in terms of resolution is comparable to that of the benchtop spectrometer and better than the modular dispersive spectrometer, while the sensitivity of SHRS is worse than that of a benchtop spectrometer, but better than that of a modular dispersive spectrometer. When considered that SHS components are small and can be packaged into a handheld device, there is interest in developing an SHS-based Instrument for mobile Raman spectroscopy. This paper evaluates the possibility of such an application.
The quantitative analysis of microstructural features is a key to understanding the micromechanical behavior of metal matrix composites (MMCs), which is a premise for their use in practice. Herein, a 3D microstructural characterization of a five-phase MMC is performed by synchrotron X-ray computed tomography (SXCT). A workflow for advanced deep learning-based segmentation of all individual phases in SXCT data is shown using a fully convolutional neural network with U-net architecture. High segmentation accuracy is achieved with a small amount of training data. This enables extracting unprecedently precise microstructural parameters (e.g., volume fractions and particle shapes) to be input, e.g., in micromechanical models.
Numerous new tin catalysts that enable the synthesis of cyclic polylactides with broad variation in their molecular mass were recently developed. The abundance of cyclics in matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectra is, however, frequently reported to greatly exceed that of linears. Thus, the MALDI ionization behavior of various end-capped linear poly(L-lactide)s and one cyclic poly(L-lactide) was investigated and compared.
Neat compounds and various blends of cyclic and linear species were prepared and studied under identical conditions with regard to sample preparation and instrumental condition, except for the laser power. For this purpose, two different MALDI-TOF mass spectrometers were applied.
Our results reveal that cyclics indeed show a slightly better ionization in MALDI, although their ionization as a neat compound seems to be less effective than that of linear polylactides. The ionization of most linear polylactides investigated does not depend on the end group structure. However, linear polylactides containing 12-bromododecyl end groups reveal an unexpected saturation effect that is not caused by fragmentation of the polymer or the end group, or by electronic saturation of the detector digitizer. Furthermore, polylactides with a 2-bromoethyl end group did not show such a saturation effect.
An overestimation of cyclic species in MALDI-TOF mass spectra of poly(L-lactide)s must be considered, but the commonly assumed peak suppression of linear polymers in mixtures of both structures can be excluded.
Many standardised durability testing methods have been developed for Portland cement-based concretes, but require validation to determine whether they are also applicable to alkali-activated materials. To address this question, RILEM TC 247-DTA ‘Durability Testing of Alkali-Activated Materials’ carried out round robin testing of carbonation and chloride penetration test methods, applied to five different alkali-activated concretes based on fly ash, blast furnace slag or metakaolin. The methods appeared overall to demonstrate an intrinsic precision comparable to their precision when applied to conventional concretes. The ranking of test outcomes for pairs of concretes of similar binder chemistry was satisfactory, but rankings were not always reliable when comparing alkali-activated concretes based on different precursors. Accelerated carbonation testing gave similar results for fly ash-based and blast furnace slag-based alkali-activated concretes, whereas natural carbonation testing did not. Carbonation of concrete specimens was observed to have occurred already during curing, which has implications for extrapolation of carbonation testing results to longer service life periods. Accelerated chloride penetration testing according to NT BUILD 443 ranked the tested concretes consistently, while this was not the case for the rapid chloride migration test. Both of these chloride penetration testing methods exhibited comparatively low precision when applied to blast furnace slag-based concretes which are more resistant to chloride ingress than the other materials tested.
The suitability of common analytical methods for the determination of active substances from wood preservatives in aged wood samples was investigated during an interlaboratory study. Permethrin, propiconazole and tebuconazole were quantified in 1.5 and 8 year-old wood samples by gas chromatography and liquid chromatography. Generally, the applied Methods yielded reliable results for these samples. However, wood components can coelute with propiconazole and tebuconazole during liquid chromatography. Optimization of separation might be required if UV detection is applied.
Current and future requirements to industrial analytical infrastructure—part 2: smart sensors
(2020)
Complex processes meet and need Industry 4.0 capabilities. Shorter product cycles, flexible production needs, and direct assessment of product quality attributes and raw material attributes call for an increased need of new process analytical technologies (PAT) concepts. While individual PAT tools may be available since decades, we need holistic concepts to fulfill above industrial needs. In this series of two contributions, we want to present a combined view on the future of PAT (process analytical technology), which is projected in smart labs (Part 1) and smart sensors (Part 2). Part 2 of this feature article series describes the future functionality as well as the ingredients of a smart sensor aiming to eventually fuel full PAT functionality. The smart sensor consists of (i) chemical and process information in the physical twin by smart field devices, by measuring multiple components, and is fully connected in the IIoT 4.0 environment. In addition, (ii) it includes process intelligence in the digital twin, as to being able to generate knowledge from multi-sensor and multi-dimensional data. The cyber-physical system (CPS) combines both elements mentioned above and allows the smart sensor to be self-calibrating and self-optimizing. It maintains its operation autonomously. Furthermore, it allows—as central PAT enabler—a flexible but also target-oriented predictive control strategy and efficient process development and can compensate variations of the process and raw material attributes. Future cyber-physical production systems—like smart sensors—consist of the fusion of two main pillars, the physical and the digital twins. We discuss the individual elements of both pillars, such as connectivity, and chemical analytics on the one hand as well as hybrid models and knowledge workflows on the other. Finally, we discuss its integration needs in a CPS in order to allow is versatile deployment in efficient process development and advanced optimum predictive process control.
The competitiveness of the chemical and pharmaceutical industry is based on ensuring the required product quality while making optimum use of plants, raw materials, and energy. In this context, effective process control using reliable chemical process analytics secures global competitiveness. The setup of those control strategies often originate in process development but need to be transferable along the whole product life cycle. In this series of two contributions, we want to present a combined view on the future of PAT (process analytical technology), which is projected in smart labs (part 1) and smart sensors (part 2). In laboratories and pilot plants, offline chemical analytical methods are frequently used, where inline methods are also used in production. Here, a transferability from process development to the process in operation would be desirable. This can be obtained by establishing PAT methods for production already during process development or scale-up. However, the current PAT (Bakeev 2005, Org Process Res 19:3–62; Simon et al. 2015, Org Process Res Dev 19:3–62) must become more flexible and smarter. This can be achieved by introducing digitalization-based knowledge management, so that knowledge from product development enables and accelerates the integration of PAT. Conversely, knowledge from the production process will also contribute to product and process development. This contribution describes the future role of the laboratory and develops requirements therefrom. In part 2, we examine the future functionality as well as the ingredients of a smart sensor aiming to eventually fuel full PAT functionality—also within process development or scale-up facilities (Eifert et al. 2020, Anal Bioanal Chem).
By adding hyaluronic acid (HA) to dioctyl sodium sulfosuccinate (AOT)‐stabilized gold nanotriangles (AuNTs) with an average thickness of 7.5±1 nm and an edge length of about 175±17 nm, the AOT bilayer is replaced by a polymeric HA‐layer leading to biocompatible nanoplatelets. The subsequent reduction process of tetrachloroauric acid in the HA‐shell surrounding the AuNTs leads to the formation of spherical gold nanoparticles on the platelet surface. With increasing tetrachloroauric acid concentration, the decoration with gold nanoparticles can be tuned. SAXS measurements reveal an increase of the platelet thickness up to around 14.5 nm, twice the initial value of bare AuNTs. HRTEM micrographs show welding phenomena between densely packed particles on the platelet surface, leading to a crumble formation while preserving the original crystal structure. Crumbles crystallized on top of the platelets enhance the Raman signal by a factor of around 20, and intensify the plasmon‐driven dimerization of 4‐nitrothiophenol (4‐NTP) to 4,4′‐dimercaptoazobenzene in a yield of up to 50 %. The resulting crumbled nanotriangles, with a biopolymer shell and the absorption maximum in the second window for in vivo imaging, are promising candidates for biomedical sensing.
We present here our methodological approach applied to the study of Egyptian inks in Late Antiquity. It is based on an interdisciplinary strategy, bringing together a variety of disciplines from humanities and natural sciences, and it aims at systematically collecting a statistically relevant amount of data regarding the composition of the inks. The application of a wellestablished, non-invasive protocol that includes near-infrared imaging and X-ray fluorescence spectroscopy for in situ measurements enables the identification and characterisation of inks dating from the end of Late Antiquity onwards. However, sometimes this method limits our understanding when characterising more ancient inks. Trying to overcome these limitations, the potential of a new device for the characterisation of organic compounds is here explored by conducting preliminary tests on mock samples.
In this work, we present the results from 77 codicological units that include some of the earliest manuscripts of our corpus that presently lists 159 units.
Imperceptible magnetic sensor matrix system integrated with organic driver and amplifier circuits
(2020)
Artificial electronic skins (e-skins) comprise an integrated matrix of flexible devices arranged on a soft, reconfigurable surface. These sensors must perceive physical interaction spaces between external objects and robots or humans. Among various types of sensors, flexible magnetic sensors and the matrix configuration are preferable for such position sensing. However, sensor matrices must efficiently map the magnetic field with real-time encoding of the positions and motions of magnetic objects. This paper reports an ultrathin magnetic sensor matrix system comprising a 2 × 4 array of magnetoresistance sensors, a bootstrap organic shift register driving the sensor matrix, and organic signal amplifiers integrated within a single imperceptible platform. The system demonstrates high magnetic sensitivity owing to the use of organic amplifiers. Moreover, the shift register enabled real-time mapping of 2D magnetic field distribution.
The DNA in living cells can be effectively damaged by high-energy radiation, which can lead to cell death. Through the ionization of water molecules, highly reactive secondary species such as low-energy electrons (LEEs) with the most probable energy around 10 eV are generated, which are able to induce DNA strand breaks via dissociative electron attachment. Absolute DNA strand break cross sections of specific DNA sequences can be efficiently determined using DNA origami nanostructures as platforms exposing the target sequences towards LEEs. In this paper, we systematically study the effect of the oligonucleotide length on the strand break cross section at various irradiation energies. The present work focuses on poly-adenine sequences (d(A4), d(A8), d(A12), d(A16), and d(A20)) irradiated with 5.0, 7.0, 8.4, and 10 eV electrons. Independent of the DNA length, the strand break cross section shows a maximum around 7.0 eV electron energy for all investigated oligonucleotides confirming that strand breakage occurs through the initial formation of negative ion resonances. When going from d(A4) to d(A16), the strand break cross section increases with oligonucleotide length, but only at 7.0 and 8.4 eV, i.e., close to the maximum of the negative ion resonance, the increase in the strand break cross section with the length is similar to the increase of an estimated geometrical cross section. For d(A20), a markedly lower DNA strand break cross section is observed for all electron energies, which is tentatively ascribed to a conformational change of the dA20 sequence. The results indicate that, although there is a general length dependence of strand break cross sections, individual nucleotides do not contribute independently of the absolute strand break cross section of the whole DNA strand. The absolute quantification of sequence specific strand breaks will help develop a more accurate molecular level understanding of radiation induced DNA damage, which can then be used for optimized risk estimates in cancer radiation therapy.
The primary screening of hybridoma cells is a time-critical and laborious step during the development of monoclonal antibodies. Often, critical errors occur in this phase, which supports the notion that the generation of monoclonal antibodies with hybridoma technology is difficult to control and hence, a risky venture. We think that it is crucial to improve the screening process to eliminate most of the critical deficits of the conventional approach. With this new microarray-based procedure, several advances could be achieved: Selectivity for excellent binders, high-throughput, reproducible signals, avoidance of misleading avidity (multivalency) effects, and performance of simultaneous competition experiments. The latter can also be used to select clones of desired cross-reactivity properties. In this paper, a model system with two excellent clones against carbamazepine, two weak clones, and blank supernatant containing fetal bovine serum was designed to examine the effectiveness of the new system. The excellent clones could be detected largely independent of the immunoglobulin G (IgG) concentration, which is usually unknown during the clone screening since the determination and subsequent adjustment of the antibody concentration are not feasible in most cases. Furthermore, in this approach, the enrichment, isolation, and purification of IgG for characterization is not necessary. Raw cell culture supernatant can be used directly, even when fetal calf serum (FCS) or other complex media is used. In addition, an improved method for the oriented antibody-immobilization on epoxy-silanized slides is presented. Based on the results of this model system with simulated hybridoma supernatants, we conclude that this approach should be preferable to most other protocols leading to many false positives, causing expensive and lengthy elimination steps to weed out the poor clones.
A strain-based automated operational modal analysis algorithm is proposed to track the long-term dynamic behavior of a horizontal wind turbine under operational conditions.
This algorithm is firstly validated by a scaled wind turbine model, and then it is applied to the dynamic strain responses recorded from a 5 MW wind turbine system. We observed variations in the fundamental frequency and 1f, 3f excitation frequencies due to the mass imbalance of the blades and aerodynamic excitation by the tower dam or tower wake. Inspection of the Campbell diagram revealed that the adverse resonance phenomenon and Sommerfeld effect causing excessive vibrations of the wind tower.
Tempo-spectral multiplexing in flow cytometry with lifetime detection using QD-encoded polymer beads
(2020)
Semiconductor quantum dots (QDs) embedded into polymer microbeads are known to be very attractive emitters for spectral multiplexing and colour encoding. Their luminescence lifetimes or decay kinetics have been, however, rarely exploited as encoding parameter, although they cover time ranges which are not easily accessible with other luminophores. We demonstrate here the potential of QDs made from II/VI semiconductors with luminescence lifetimes of several 10 ns to expand the lifetime range of organic encoding luminophores in multiplexing applications using time-resolved flow cytometry (LT-FCM). For this purpose, two different types of QD-loaded beads were prepared and characterized by photoluminescence measurements on the ensemble level and by single-particle confocal laser scanning microscopy. Subsequently, these lifetime-encoded microbeads were combined with dye-encoded microparticles in systematic studies to demonstrate the potential of these QDs to increase the number of lifetime codes for lifetime multiplexing and combined multiplexing in the time and colour domain (tempo-spectral multiplexing). These studies were done with a recently developed novel luminescence lifetime flow cytometer (LT-FCM setup) operating in the time-domain, that presents an alternative to reports on phase-sensitive lifetime detection in flow cytometry.
Laser powder bed fusion (L-PBF) is the most prominent additive manufacturing (AM) technology for metal part production. Among the high number of factors influencing part quality and mechanical properties, the inter layer time (ILT) between iterative melting of volume elements in subsequent layers is almost completely unappreciated in the relevant literature on L-PBF. This study investigates the effect of ILT with respect to build height and under distinct levels of volumetric energy density (VED) using the example of 316L stainless steel. In-situ thermography is used to gather information on cooling conditions during the process, which is followed by an extensive metallographic analysis. Significant effects of ILT and build height on heat accumulation, sub-grain sizes, melt pool geometries and hardness are presented. Furthermore, the rise of defect densities can be attributed to a mutual interplay of build height and ILT. Hence, ILT has been identified as a crucial factor for L-PBF of real part components especially for those with small cross sections.
This paper demonstrates that the instrumented indentation test (IIT), together with a trained artificial neural network (ANN), has the capability to characterize the mechanical properties of the local parts of a welded steel structure such as a weld nugget or heat affected zone.
Aside from force-indentation depth curves generated from the IIT, the profile of the indented surface deformed after the indentation test also has a strong correlation with the materials’ plastic behavior. The profile of the indented surface was used as the training dataset to design an ANN to determine the material parameters of the welded zones. The deformation of the indented surface in three dimensions shown in images were analyzed with the computer vision algorithms and the obtained data were employed to train the ANN for the characterization of the mechanical properties. Moreover, this method was applied to the images taken with a simple light microscope from the surface of a specimen. Therefore, it is possible to quantify the mechanical properties of the automotive steels with the four independent methods: (1) force-indentation depth curve; (2) profile of the indented surface; (3) analyzing of the 3D-measurement image; and (4) evaluation of the images taken by a simple light microscope. The results show that there is a very good Agreement between the material parameters obtained from the trained ANN and the experimental uniaxial tensile test. The results present that the mechanical properties of an unknown steel can be determined by only analyzing the images taken from its surface after pushing a simple indenter into its surface.
Ethylene propylene diene monomer (EPDM) Rubbers with the flame retardants tris(2-ethylhexyl)phosphate, ammonium polyphosphate, polyaniline, and aluminum trihydroxide were prepared and analyzed in this study. The homogenous dispersion of the fillers in the rubber matrix was confirmed by scanning electron microscope. To investigate the interplay of the different flame retardants, the flame retardants were varied systematically. The comprehensive study sought combinations of flame retardants that allow high loadings of flame retardants without deterioration of the physical and mechanical properties of the EPDM rubber. The eight EPDM rubbers were investigated via thermogravimetric analysis and pyrolysis gas chromatography coupled with a mass spectrometer (Py GC/MS) to investigate the potential synergistic effects. In the Py-GC/MS experiments, 27 pyrolysis products were identified. Furthermore, UL 94, limiting oxygen index, FMVSS 302, glow wire tests, and cone calorimeter tests were carried out. In the cone calorimeter test the EPDM rubbers R-1AP and R-1/2P achieved an increase in residue at flameout of 76% and a reduction in total heat evolved of about 35%. Furthermore, the compounds R-1AP and R-1/2P achieved a reduction in MARHE to about 150 kW m−1, a reduction of over 50% compared to the unprotected rubber R.
Distributed acoustic sensing (DAS) over tens of kilometers of fiber optic cables is well-suited for monitoring extended railway infrastructures. As DAS produces large, noisy datasets, it is important to optimize algorithms for precise tracking of train position, speed, and the number of train cars, The purpose of this study is to compare different data analysis strategies and the resulting parameter uncertainties. We present data of an ICE 4 train of the Deutsche Bahn AG, which was recorded with a commercial DAS system. We localize the train signal in the data either along the temporal or spatial direction, and a similar velocity standard deviation of less than 5 km/h for a train moving at 160 km/h is found for both analysis methods, The data can be further enhanced by peak finding as well as faster and more flexible neural network algorithms. Then, individual noise peaks due to bogie clusters become visible and individual train cars can be counted. From the time between bogie signals, the velocity can also be determined with a lower standard deviation of 0.8 km/h, The analysis methods presented here will help to establish routines for near real-time Train tracking and train integrity analysis.
Effects of laser-induced periodic surface structures on the superconducting properties of Niobium
(2020)
It is well known that the use of ultrashort (fs) pulsed lasers can induce the generation of (quasi-) periodic nanostructures (LIPSS, ripples) on the surface of many materials. Such nanostructures have also been observed in sample’s surfaces irradiated with UV lasers with a pulse duration of 300 ps. In this work, we compare the characteristics of these nanostructures on 1-mm and on 25-μm thick niobium sheets induced by 30 fs n-IR and 300 ps UV pulsed lasers. In addition to conventional continuous or burst mode processing configurations, two-dimensional laser beam and line scanning modes have been investigated in this work. The latter allows the processing of large areas with a more uniform distribution of nanostructures at the surface. The influence of the generated nanostructures on the superconducting properties of niobium has also been explored. For this aim, magnetic hysteresis loops have been measured at different cryogenic temperatures to analyse how these laser treatments affect the flux pinning behaviour and, in consequence, the superconductor’s critical current values. It was observed that laser treatments are able to modify the superconducting properties of niobium samples.
Laser-induced periodic surface structures (LIPSS) are often present when processing solid targets with linearly polarized ultrashort laser pulses. The different irradiation parameters to produce them on metals, semiconductors and dielectrics have been studied extensively, identifying suitable regimes to tailor its properties for applications in the fields of optics, medicine, fluidics and tribology, to name a few. One important parameter widely present when exposing the samples to the high intensities provided by these laser pulses in air environment, that generally is not considered, is the formation of a superficial laser-induced oxide layer. In this paper, we fabricate LIPSS on a layer of the oxidation prone hard-coating material chromium nitride in order to investigate the impact of the laser-induced oxide layer on its formation. A variety of complementary surface analytic techniques were employed, revealing morphological, chemical and structural characteristics of well-known high-spatial frequency LIPSS (HSFL) together with a new type of low-spatial frequency LIPSS (LSFL) with an anomalous orientation parallel to the laser polarization. Based on this input, we performed finite-difference time-domain calculations considering a layered system resembling the geometry of the HSFL along with the presence of a laser-induced oxide layer. The simulations support a scenario that the new type of LSFL is formed at the interface between the laser-induced oxide layer and the non-altered material underneath. These findings suggest that LSFL structures parallel to the polarization can be easily induced in materials that are prone to oxidation.
Among additive manufacturing (AM) technologies, the laser powder bed fusion (L-PBF) is one of the most important technologies to produce metallic components. The layer-wise build-up of components and the complex process conditions increase the probability of the occurrence of defects. However, due to the iterative nature of its manufacturing process and in contrast to conventional manufacturing technologies such as casting, L-PBF offers unique opportunities for in-situ monitoring. In this study, two cameras were successfully tested simultaneously as a machine manufacturer independent process monitoring setup: a high-frequency infrared camera and a camera for long time exposure, working in the visible and infrared spectrum and equipped with a near infrared filter. An AISI 316L stainless steel specimen with integrated artificial defects has been monitored during the build. The acquired camera data was compared to data obtained by computed tomography. A promising and easy to use examination method for data analysis was developed and correlations between measured signals and defects were identified. Moreover, sources of possible data misinterpretation were specified. Lastly, attempts for automatic data analysis by data Integration are presented.
This article deals with the relevance and practical feasibility of micromechanical simulations for their application to general geomechanical problems involving fluid-saturated granular assemblies, whether frictional or cohesive. A set of conceptual and numerical tools is here presented, advocating for a parallel computation using graphical processing units (GPUs) to treat large numbers of degrees of freedom with conventional Desktop computers. The fluid phase is here simulated with a particle-resolved approach in the frame of the Lattice Botzmann Method (LBM) while the granular solid phase is modelled as a collection of discrete particles from a Molecular Dynamics DEM perspective. The range of possible material behaviours for the solid granular phase is intended here to cover a broad spectrum from purely frictional to viscous cohesive materials with either brittle or transient debonding features. Specific details of the implementation and some validation cases are put forward.
Finally, some exemplary applications in the fields of soil erosion and geotechnical profile installation are provided along with a discussion on the parallel performance of the presented models. The results show that a micromechanical approach can be feasible and useful in practice, providing meaningful insights into complex engineering problems like the erosion kinetics of a soil under an impinging jet or the penetration resistance of a deep foundation in a layered soil profile.
Increasing traffic volume on the one hand and ageing infrastructure on the other hand have created many new challenges for maintenance and structural health monitoring of roads and bridges. In the past, many bridges and road structures have been neglected, often resulting in traffic congestion, road closure, and increased repair costs.
This research is concerned with the development of a system to improve the challenge of maintenance and early detection of damage, particularly moisture penetration and corrosion of steel reinforced concrete components. The objective is to develop a method that will also work after 30 years and longer. Many new IoT solutions are equipped with internal energy storage elements (accumulators or batteries) which are inappropriate here, since most relevant signs of concrete degradation occur after decades, where the functioning of such elements are more than questionable. The presented technology approach uses radio-frequency identification (RFID) and enables connectivity to sensors. It offers the advantage of an passive, completely independent energy supply without any energy storage components.
Since the system should be permanently embedded in concrete, it is crucial to develop a long-term stable device which is adapted to the environmental influences of the structure, e.g., long-term resistance in very alkaline environment of pH 13. In numerous experiments, the robustness of the system was tested and evaluated. Various tests with encapsulations to protect the electronics were performed, and for long-term validation different concrete specimens were instrumented with RFID-sensor-systems. Their operating time is now around two years and investigations for signs of fatigue and damage to the encapsulation and the electronics are ongoing.
The Lycurgus cup is an ancient glass artefact that shows dichroism as it looks green when a white light is reflected on it and a red colouring appears when a white light is transmitted through it. This peculiar dichroic effect is due to silver and gold nanoparticles present in the glass. In this research we show the synthesis of dichroic silver nanoparticles and their embedding in a 3D printable nanocomposite. The addition of gold nanoparticles to the silver nanoparticle composite, gave a 3D printable nanocomposite with the same dichroism effect of the Lycurgus cup.
Almost 500 municipal solid waste incineration plants in the EU, Norway and Switzerland generate about 17.6 Mt/a of incinerator bottom ash (IBA). IBA contains minerals and metals. Metals are mostly separated and sold to the scrap market and minerals are either disposed of in landfills or utilised in the construction sector. Since there is no uniform regulation for IBA utilisation at EU level, countries developed own rules with varying requirements for utilisation. As a result from a cooperation network between European experts an up-to-date overview of documents regulating IBA utilisation is presented. Furthermore, this work highlights the different requirements that have to be considered. Overall, 51 different parameters for the total content and 36 different parameters for the emission by leaching are defined. An analysis of the defined parameter reveals that leaching parameters are significantly more to be considered compared to total content parameters. In order to assess the leaching behaviour nine different leaching tests, including batch tests, up-flow percolation tests and one diffusion test (monolithic materials) are in place.
A further discussion of leaching parameters showed that certain countries took over limit values initially defined for landfills for inert waste and adopted them for IBA utilisation. The overall utilisation rate of IBA in construction works is approximately 54 wt%. It is revealed that the rate of utilisation does not necessarily depend on how well regulated IBA utilisation is, but rather seems to be a result of political commitment for IBA recycling and economically interesting circumstances.
Machine learning based multi-sensor fusion for the nondestructive testing of corrosion in concrete
(2020)
Half-cell potential mapping (HP) is the most popular non-destructive testing method (NDT) for locating corrosion damage in concrete. It is generally accepted that HP is susceptible to environmental factors caused by salt-related deterioration, such as different moisture and chloride gradients. Additional NDT methods are able to identify distinctive areas but are not yet used to estimate more accurate test results. We present a Supervised Machine Learning (SML) based approach to data fusion of seven different signal features to obtain higher quality information. SMLs are methods that explore (or learn) relationships between different (sensor) data from predefined data labels. To obtain a representative, labelled data set we conducted a comprehensive experiment simulating the deterioration cycle of a chloride exposed device in the laboratory. Our data set consists of 18 measurement campaigns, each containing HP, Ground Penetrating- Radar, Microwave Moisture and Wenner resistivity data. We compare the performance of different ML approaches. Many outperform the best single method, HP. We describe the intrinsic challenges posed by a data-driven approach in NDT and show how future work can help overcome them.
The ISO 16000 standard series provide guidelines for emission measurements of volatile organic compounds (VOCs) from building materials. However, polymer-based consumer products such as toys may also release harmful substances into indoor air. In such cases, the existing standard procedures are unsuitable for official control laboratories due to high costs for large emission testing chambers. This paper aims at developing and comparing alternative and more competitive methods for the emission testing of consumer products. The influence of the emission chamber size was investigated as smaller chambers are more suited to the common size of consumer products and may help to reduce the costs of testing. Comparison of the performance of a 203 l emission test chamber with two smaller chambers with the capacity of 24 l and 44 ml, respectively, was carried out by using a polyurethane reference material spiked with 14 VOCs during the course of 28 days. The area-specific emission rates obtained in the small chambers were always similar to those of the 203 l reference chamber after a few hours. This implies that smaller chambers can provide at least useful numbers on the extent of polymer-based consumer product emissions into indoor air, thereby supporting meaningful exposure assessments.