Wissenschaftliche Artikel der BAM
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- Additive Manufacturing (4)
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- 5 Werkstofftechnik (4)
- 6.3 Strukturanalytik (4)
- 9.5 Tribologie und Verschleißschutz (4)
- 4 Material und Umwelt (3)
- 5.4 Multimateriale Fertigungsprozesse (3)
The prediction of the properties of the materials used in the operation of components is of enormous importance, in order to accelerate the development process of new components. To evaluate new materials in terms of their performance (in a component), the development of new innovative methods is necessary. These methods can also be summarized under the term lab-to-field or materials – upscaling, meaning materials being characterised in a laboratory and their properties being upscaled to the component performance by means of e.g. simulation. i-TRIBOMAT is a EU funded project (H2020, GA Nr. 814494) aiming at building an Open Innovation Test Bed for tribological material characterization and offering corresponding services from tribological characterization of new materials to simulation models for predicting the performance of industrial components. By bundling the infrastructure, know-how for characterization and building a digital platform, i-TRIBOMAT becomes the world’s largest open innovation test bed for tribological material characterization.
The paper presents the results of the radiocarbon dating and ink analysis of a leather fragment bearing an important liturgical text in Hebrew from the early centuries of the common era. The work initiated by the scholarly interest in the text stresses the importance of the date and materiality of the manuscripts and closes with an appeal to the curators of manuscript collections.
The ability to track electrode degradation, both spatially and temporally, is fundamental to understand performance loss during operation of lithium batteries. X-ray computed tomography can be used to follow structural and morphological changes in electrodes; however, the direct detection of electrochemical processes related to metallic lithium is difficult due to the low sensitivity to the element. In this work, 4-dimensional neutron computed tomography, which shows high contrast for lithium, is used to directly quantify the lithium diffusion process in spirally wound Li/SOCl2 primary cells. The neutron dataset enables the quantification of the lithium transport from the anode and the accumulation inside the SOCl2 cathode to be locally resolved. Complementarity between the collected neutron and X-ray computed tomographies is shown and by applying both methods in concert we have observed lithium diffusion blocking by the LiCl protection layer and identified all cell components which are difficult to distinguish using one of the methods alone.
In this work, we describe the use of artificial neural networks for the quantification of X-ray fluorescence measurements. The training data were generated using Monte Carlo simulation, which avoided the use of adapted reference materials. The extension of the available data set by means of an ANN to generate additional data was demonstrated. Particular emphasis was put on the comparability of simulated and experimental data and how the influence of deviations can be reduced. The search for the optimal hyperparameter, manual and automatic, is also described. For the presented case, we were able to train a network with a mean absolute error of 0.1 weight percent for the synthetic data and 0.7 weight percent for a set of experimental data obtained with certified reference materials.
Vor dem Hintergrund der einzigartigen Modularität, hohen Empfindlichkeit und Selektivität von Antikörper‐gesteuerten Indikatorfreisetzungssystemen (gAID‐Systemen) wurde hier ein Multiplex‐Assay für drei organische Explosivstoffmoleküle (TATP, TNT, PETN) entwickelt, der es erlaubt, die Analyten gleichzeitig in flüssiger Phase mit einem einzelnen Teststreifen und einem Fluoreszenzlesegerät bzw. Smartphone als Detektor in Konzentrationen bis in den unteren ppb‐Bereich in <5 min nachzuweisen. Alle drei Systeme, darunter die hier neu entwickelten Systeme für TNT und PETN, tolerieren zudem nicht nur gepufferte wässrige Modelllösungen, sondern auch komplexere Matrices. Neben einem konventionellen Teststreifen mit einem Kanal erlaubte uns die Anwendung von Wachsdrucktechnologie das Herstellen von mehrkanaligen Streifen mit vergleichbarer analytischer Leistungsfähigkeit, was das enorme Potenzial der modular aufgebauten, hybriden Biosensormaterialien im Hinblick auf eine für den Endanwender maßgeschneiderte Vor‐Ort‐Analytik unterstreicht.
Methods and materials are presented here, which enable the manufacturing of fine structures using a 3D-printing method known as two-photon polymerization (2PP). As traditional photolithography methods for structuring ceramic slurries do not function with 2PP, due to light scattering on ceramic particles, a novel water-based photoresist with high ceramic loading of extremely well dispersed ceramic nano particles was developed. This photoresist is basically a ceramic slurry containing a photocurable agent and a photoinitiator to be crosslinkable with the 780 nm wavelength femtosecond laser light source of the 2PP machine. It is demonstrated that it is possible to gain a highly transparent and low viscous slurry suitable for 2PP processing. This work shows the development of the slurry, first printing results and the post-printing processes required to form three dimensional ceramic microstructures consisting of alumina toughened zirconia (ATZ).
New possibilities for concrete analysis 4.0 with the Laser-Induced Breakdown Spectroscopy (LIBS)
(2020)
In civil engineering the damage assessment of concrete infrastructures is an important task to monitor and ensure the estimated life-time. The aging of concrete is caused by different damage processes like the chloride induced pitting corrosion of the reinforcement. The penetration depth and the concentration of harmful species are crucial factors in the damage assessment. As a highly cost and time-consuming standard procedure, the analysis of concrete drill cores or drilling by wet-chemistry is widely used. This method provides element concentration to the total mass as aggregates and binder are homogenized. In order to provide a method that is capable to detect the element concentration regarding the cement content only, the laser-induced breakdown spectroscopy (LIBS) will be presented. The LIBS method uses a focused pulsed laser on the sample surface to ablate material. The high-power density and the laser-material interaction causes a laser-induced plasma that emits elemental and molecular line emission due to energy transition of the excited species in the plasma during the cooling phase.
As each element provides element-specific line emission, it is in principle possible to detect any element on the periodic table (spectroscopic fingerprint) with one laser shot. In combination with a translation stage the sample under investigation can be spatially resolved using a scan raster with a resolution up to 100 µm (element mapping). Due to the high spatial resolution, the element distribution and the heterogeneity of the concrete can be evaluated. By using chemometrics the non-relevant aggregates can be excluded from the data set and the element concentration can be quantified and referred to a specific solid phase like the binding matrix (cement) only. In order to analyze transport processes like diffusion and migration the twodimensional element distributions can provide deep insight into the transport through the pore space and local enrichments of elements. As LIBS is a multi-elemental method it is also possible to compare the ingress and transport process of different elements like Cl, Na, K, S, C, and Li simultaneously and evaluate cross-correlations between the different ions. Furthermore, the element mapping allows to visualize the transport along cracks. This work will show the state of the art in terms of hardware and software for an automated LIBS system as well as different application for a concrete analysis 4.0. Focus will be the application of LIBS for a fast concrete analysis.
This paper reports a systematic study into the effect of different biomass-derived precursors on the structure and porosity of carbons prepared via catalytic graphitization. Glucose, starch and cellulose are combined with iron nitrate and heated under a nitrogen atmosphere to produce Fe3C nanoparticles, which catalyze the conversion of amorphous carbon to graphitic nanostructures. The choice of organic precursor provides a means of controlling the catalyst particle size, which has a direct effect on the porosity of the material. Cellulose and glucose produce mesoporous carbons, while starch produces a mixture of micro- and mesopores under the same conditions and proceeds via a much slower graphitization step, generating a mixture of graphitic nanostructures and turbostratic carbon. Porous carbons are critical to energy applications such as batteries and electrocatalytic processes. For These applications, a simple and sustainable route to those carbons is essential. Therefore, the ability to control the precise structure of a biomass-derived carbon simply through the choice of precursor will enable the production of a new generation of energy materials.
Microbial communities in the immediate environment of socialized invertebrates can help to suppress pathogens, in part by synthesizing bioactive natural products. Here we characterized the core microbiomes of three termite species (genus Coptotermes) and their nest material to gain more insight into the diversity of termite-associated bacteria.
Sampling a healthy termite colony over time implicated a consolidated and highly stable microbiome, pointing toward the fact that beneficial bacterial phyla play a major role in termite fitness. In contrast, there was a significant shift in the composition of the core microbiome in one nest during a fungal infection, affecting the abundance of wellcharacterized Streptomyces species (phylum Actinobacteria) as well as less-studied bacterial phyla such as Acidobacteria. High-throughput cultivation in microplates was implemented to isolate and identify these less-studied bacterial phylogenetic group.
Amplicon sequencing confirmed that our method maintained the bacterial diversity of the environmental samples, enabling the isolation of novel Acidobacteriaceae and expanding the list of cultivated species to include two strains that may define new species within the genera Terracidiphilus and Acidobacterium.
Fluorides are well-known as wood preservatives. One of the limitations of fluoride-based wood preservatives is their high leachability. Alternative to current fluoride salts such as NaF used in wood protection are low water-soluble fluorides. However, impregnation of low water-soluble fluorides into wood poses a challenge. To address this challenge, low water-soluble fluorides like calcium fluoride (CaF2) and magnesium fluoride (MgF2) were synthesized as nanoparticles via the fluorolytic sol−gel synthesis and then impregnated into wood specimens. In this study, the toxicity of nano metal fluorides was assessed by termite mortality, mass loss and visual analysis of treated specimens after eight weeks of exposure to termites, Coptotermes formosanus. Nano metal fluorides with sol concentrations of 0.5 M and higher were found to be effective against termites resulting in 100% termite mortality and significantly inhibited termite feeding. Among the formulations tested, the least damage was found for specimens treated with combinations of CaF2 and MgF2 with an average mass loss less than 1% and visual rating of “1”. These results demonstrate the efficacy of low water-soluble nano metal fluorides to protect wood from termite attack.
In this work the flexural rigidity of individual large diameter multi-walled carbon nanotubes (MWCNTs) was investigated. The bending modulus were obtained by detecting the resonance frequencies of mechanically excited cantilevered carbon nanotubes using the so-called dynamic scanning electron microscopy technique, and applying the Euler–Bernoulli beam theory. For the nanotubes studied, we determined a modulus of up to 160 GPa. This agrees with values reported by other authors for MWCNTs produced by catalytic chemical vapor deposition, however, it is 6-8 times smaller than values reported for single and multi-walled carbon nanotubes produced by arc-discharge synthesis. Toxicological studies with carbon nanotubes have been showing that inhaled airborne nanofibers that reach the deep airways of the respiratory system may lead to serious, asbestos-like lung diseases. These studies suggested that their toxicity critically depends on the fiber flexural rigidity, with high rigidity causing cell lesions. To complement the correlation between observed toxicological effects and fiber rigidities, reliable and routinely applicable measurement techniques for the flexural rigidity of nanofibers are required.
The aim of this study is to increase the tribological performance of hot stamping tools by using a laser implantation process. This technique allows the fabrication of separated, elevated and dome-shaped microfeatures on the tool surface in consequence of a localized dispersing of ceramic particles via pulsed laser radiation. Hence, the topography and material properties of the tool are modified, which influences the tribological interactions at the blank-die interface. However, an appropriate selection of ceramic particles is an essential prerequisite, in order to obtain tailored and highly wear resistant surface features. In this regard, different titanium-based hard particles (TiB2 and TiN) were laser-implanted on hot working tool specimens and subsequently tested by means of a modified pin-on-disk test regarding to their wear and friction behavior.
Physical storage of gaseous hydrogen under high-pressure in glassy micro-containers such as spheres and capillaries is a promising concept for enhancing safety and the volumetric capacity of mobile hydrogen storage systems. As very low permeation through the container wall is required for storage of compressed hydrogen, development of glasses of minimal hydrogen permeability is needed. For this purpose, one has to understand better the dependence of hydrogen permeability on glass structure. The paper points out that minimizing the accessible free volume is as one strategy to minimize hydrogen permeability. Based on previously measured and comprehensive literature data, it is shown that permeation is independently controlled by ionic porosity and network modifier content. Thus, ionic porosity in modified and fully polymerized networks can be decreased equally to the lowest hydrogen permeability among the glasses under study. Applying this concept, a drop of up to 30,000 with respect to the permeation of hydrogen molecules through silica glass is attainable.
A simple and fast prediction scheme is presented for train induced ground and building vibrations. Simple models such as (1-dimensional) transfer matrices are used for the vehicle-track-soil interaction and for the building-soil interaction. The wave propagation through layered soils is approximated by a frequency-dependent homogeneous half-space. The prediction is divided into the parts “emission” (excitation by railway traffic), “transmission” (wave propagation through the soil) and “immission” (transfer into a building). The link between the modules is made by the excitation force between emission and transmission, and by the free-field vibration between transmission and immission. All formula for the simple vehicle-track, soil and building models are given in this article. The behaviour of the models is demonstrated by typical examples, that is the mitigation of train vibrations by elastic track elements, the low- and high-frequency cut-offs characteristic for layered soils, and the interacting soil, wall and floor resonances of multi-storey buildings. It is shown that the results of the simple prediction models can well represent the behaviour of the more time-consuming detailed models, the finite-element boundary-element models of the track, the wavenumber integrals for the soil, and the three-dimensional finite-element models of the building. In addition, measurement examples are given for each part of the prediction confirming that the methods provide reasonable results. As the prediction models are fast in calculation, many predictions can be done, for example to assess the environmental effect along a new railway line. The simple models have the additional advantage that the user needs to know only a minimum of parameters. So, the prediction is fast and user-friendly, but also theoretically and experimentally well-founded.
The transport phenomena in the wire feed laser beam welding are investigated numerically. A three-dimensional transient heat transfer and fluid flow model coupled with free surface tracing and element transport is developed. A ray-tracing method with local grid refinement algorithm is used to calculate the multiple reflections and Fresnel absorption on the keyhole wall. The filler material flows backward along the lateral side of the weld pool, and subsequently flows forward along the longitudinal plane. The occurrence of the bulging phenomenon may further prevent the downward transfer of the additional elements to the root of the weld pool.
The study deals with the application of the high-power hybrid-laser arc welding process on up to 15 mm thick pipe segments with the intention to avoid end crater imperfections during closing of the circumferential welds, where the pipes were turned during welding in 1G- and 2Gpositions.
Different techniques such as laser power ramp-down, abrupt switch-off of the laser power and change of the magnification of the laser spot diameter and defocusing of the laser beam relative to the workpiece were tested to remove the laser energy from the process. It could be shown that a high defocusing of the optic system above 40 mm with a resulting beam diameter > 2.9 mm in a short overlap length of approx.
20 mm leads to the formation of a cup-shaped weld seam, which is preferred for avoidance of cracks and pores in the end crater. A laser optics with motor-driven lens system was used for the welding experiments to defocuse the laser beam without changing the position of the arc.
Notch impact toughness of laser beam welded thick sheets of cryogenic nickel alloyed steel X8Ni9
(2020)
The paper deals with the investigations of the impact toughness of laser beam welded 14.5 mm thick sheets made of cryogenic steel X8Ni9 as a function of preheating. This 9% nickel alloyed steel is widely used in the liquefied natural gas (LNG) industry. An application of highly efficient welding processes such as high-power laser beam welding (LBW) in LNG sector requires an understanding of the interactions between the LBW process parameters and weld properties, in particular the impact toughness. The results show that the original fine-grained martensitic microstructure of the base metal (BM) is significantly changed by melting and crystallization during the LBW, what can lead to a decrease in the impact toughness of the weld metal (WM) below the required level. An optimal preheating temperature range leads to the favorable thermal welding cycle and is of remarkable importance for maintaining the notch impact toughness of laser beam welded joints of these thick steel sheets. A parameter window was identified in which V-notch impact toughness comparable to that of the BM at -196 °C was achieved.
Directed energy deposition additive manufactured parts have steep stress gradients and an anisotropic microstructure caused by the rapid thermo-cycles and the layer-upon-layer manufacturing, hence heat treatment can be used to reduce the residual stresses and to restore the microstructure. The numerical simulation is a suitable tool to determine the parameters of the heat treatment process and to reduce the necessary application efforts. The heat treatment simulation calculates the distortion and residual stresses during the process. Validation experiments are necessary to verify the simulation results. This paper presents a 3D coupled thermo-mechanical model of the heat treatment of additive components. A distortion-based validation is conducted to verify the simulation results, using a C-ring shaped specimen geometry. Therefore, the C-ring samples were 3D scanned using a structured light 3D scanner to compare the distortion of the samples with different post-processing histories.
A self-restraint hot cracking test (free edge test) was used in combination with a novel optical measurement technique to determine the critical straining conditions for solidification cracking for the stainless steel grade 1.4828 (AISI 309). The Lucas-Kanade algorithm for the optical flow (OF) calculation was implemented to obtain the full-field displacement and then the full-field strain.
The use of external laser illumination with appropriate filters allows to obtain good image quality with good contrast. The critical straining conditions required for solidification cracking can be obtained by means the proposed technique in the immediate vicinity of the solidification front. A very good repeatability was demonstrated for the used measurement technique. The critical straining conditions for solidification cracking for the tested steel und under this welding conditions has been detected
Recent studies have confirmed the widening of the weld pool interface, known as a bulge effect, during deep penetration high power laser beam welding. The link between such geometric particularities of the weld pool shape and the hot cracking phenomena is significant. The present work seeks to extend the level of understanding by investigating their relationship. A coupled multiphysics, multiscale numerical framework is developed, comprising a series of subsequent analyses. The study examines the influences of the bulge on the three most dominant effects causing hot cracking, namely the thermal cycles, the mechanical loading, and the local microstructure. The bulge in the weld pool shape forms approximately in the middle of the plate, thus correlating with the location of hot cracking. It increases the hot cracking susceptibility by enhancing the three dominant effects. The numerical results are backed up by experimental data.
Material qualification for laser powder bed fusion (L-PBF) processes are often based on results derived from additively manufactured (AM) bulk material or small density cubes, although it is well known that the part geometry has a tremendous influence on the heat flux and, therefore, on the thermal history of an AM component. This study shows experimentally the effect of simple geometrical obstructions to the heat flux on cooling behavior and solidification conditions of 316L stainless steel processed by L-PBF. Additionally, it respects two distinct inter layer times (ILT) as well as the build height of the parts. The cooling behavior of the parts is in-situ traced by infrared (IR) thermography during the built-up. The IR signals reveal significant differences in cooling conditions, which are correlated to differences in melt pool geometries. The acquired data and results can be used for validation of computational models and improvements of quality assurance.
The Tutzing Symposium "100 % digital: survival strategies for the process industry" (see 4.1) in April 2018 was characterized by a great momentum which has been taken up and continued until today. The aim was to implement the ideas from the Tutzing Symposium in a coordinated and targeted manner. For this purpose, development needs as well as the numerous currently planned or already started research and development activities in the context of digitalisation were first compiled and analysed. This resulted in the current research landscape for digitalization in the process industry. It now enables to identify open topics and to translate them into research funding programs as well as to define new projects in the dialogue between users, suppliers and research, which are to be meaningfully interlinked and consolidated with existing projects.
Due to the strong interest in digitalisation, activities are constantly being added, so that this paper can only provide a snapshot of the situation in the period 2019-2020.
Different approaches have been attempted so far to reduce fuel consumption and linked pollutants, including vehicle equipment and design, with rational driving style being recognized as a potential source of fuel savings. However, no specific methodology had been suggested so far to assess fuel economy of driving other than the fuel consumed itself. In this paper, the Standard deviation of driving acceleration has been found to be directly associated to fuel consumption, so that the less dispersion of the driving acceleration, produces the lower fuel consumptions and emissions. Such metric could be thus used to assess driving style.
In spite that transport activities do not represent the biggest contributor of pollutants emissions, their reduction has been a priority as some other externalities are associated to such emissions and to the transport itself. A crucial element to characterize the behavior of the vehicles against the environment are the losses that such vehicles exhibit in a passive way, that is, without any involvement of power conditions. The energy loses due to the rolling, the drag and to the friction in mechanical components, have been assessed so far in terms of the stopping acceleration when the vehicle idles on a ramp. However, such a testing procedure produces some uncertainties due to the dynamic conditions that are considered. To avoid such critical limitations, in this paper a testing procedure and facility are proposed, which are based on static conditions of the vehicle at the initiation and at the ending of the test, which are assumed to provide a better reliability to the testing. Some preliminary theoretical analysis should be made in order to validate the operational principles proposed herein for such testing facility.
Chemical compositions of a weld can be varying locally as a result of the welding process. These local variations can be due to the vaporization of individual alloying elements. In this work, tungsten inert gas (TIG) bead-on-plate stainless steel welds of EN grade 1.4404 and 1.4435 were investigated using laser-induced breakdown spectroscopy (LIBS) on the completed welds. This study aims to reveal the welding parameters’ influence on the resulting local chemical compositions of the stainless steel welds. We demonstrated Mn vaporize before Cr due to its lower latent enthalpy of vaporization. Hence, Mn accumulates on the heat-affected zone (HAZ) both sides across the weld bead by being swept away through the circulation flow of the welding plasma. Additionally, increasing the heat input tends to enhance the accumulated Mn content on the HAZ as well as increasing the shielding gas flow rate. The results are in good agreement with the literature and proved that LIBS is an effective method to inspect completed welds.
Within the scope of this work, a new surface engineering technology named laser implantation has been investigated, in order to improve the tribological performance of hot stamping tools. This technique is based on manufacturing highly wear-resistant, separated, and elevated microfeatures by embedding hard ceramic particles into the tool surface via pulsed laser radiation.
Hence, the topography and material properties of the tool are modified, which influences the thermal and tribological interactions at the blank-die interface. To verify these assumptions and to clarify the cause–effect relations, different titanium-based particles (TiB2, TiC, TiN) were laser-implanted and subsequently analyzed regarding to their geometrical shape and mechanical properties. Afterwards, quenching tests as well as tribological experiments were carried out by using titanium-diboride as the most promising implantation material for reducing the tribological load due to high hardness value of the generated implants. Compared to conventional tooling systems, the modified tool surfaces revealed a significantly higher wear resistance as well as reduced friction forces while offering the possibility to adjust the thermal interactions at the blank-die interface. Based on these results, a tailored tool surface modification can be pursued in future research work, in order to enhance the effectiveness of the hot stamping technology.
One of the most important goals in civil engineering is to guarantee the safety of the construction. Standards prescribe a required failure probability in the order of 10−4 to 10−6. Generally, it is not possible to compute the failure probability analytically.
Therefore, many approximation methods have been developed to estimate the failure probability. Nevertheless, these methods still require a large number of evaluations of the investigated structure, usually finite element (FE) simulations, making full probabilistic design studies not feasible for relevant applications. The aim of this paper is to increase the efficiency of structural reliability analysis by means of reduced order models. The developed method paves the way for using full probabilistic approaches in industrial applications. In the proposed PGD reliability analysis, the solution of the structural computation is directly obtained from evaluating the PGD solution for a specific parameter set without computing a full FE simulation. Additionally, an adaptive importance sampling scheme is used to minimize the total number of required samples. The accuracy of the failure probability depends on the accuracy of the PGD model (mainly influenced on mesh discretization and mode truncation) as well as the number of samples in the sampling algorithm. Therefore, a general iterative PGD reliability procedure is developed to automatically verify the accuracy of the computed failure probability. It is based on a goal-oriented refinement of the PGD model around the adaptively approximated design point. The methodology is applied and evaluated for 1D and 2D examples. The computational savings compared to the method based on a FE model is shown and the influence of the accuracy of the PGD model on the failure probability is studied.
The possibility of creating patient-specific individual implants makes Additive Manufacturing technologies of special interest for the medical sector. For substitution of bone defects, powder based Additive Manufacturing by Binder Jetting is a suitable method to produce complex scaffold-like structures made of bioceramics with easily adapted geometries and controlled porosity. The process inherent residual porosity in the printed part, even though desired as it supports bone ingrowth, also leads to limited mechanical strength. Currently, bioceramic scaffolds made by Binder Jetting feature suitable biocompatible and biodegradable properties, while a sufficient mechanical stability is rather challenging. The purpose of this work is to apply the gas flow assisted powder deposition introduced in 2014 by Zocca et al., to the powder bed during printing of bioceramic tablets and scaffolds using α-TCP powder as feedstock. This enables exploiting the advantages of an increased powder bed density, thereby improving the mechanical properties of the printed parts.
A new approach for fabrication of ceramic components with inner channels is proposed, as a result of the combination of two additive and one subtractive manufacturing processes. In this project, porcelain parts are manufactured by the Layerwise Slurry Deposition (LSD) process, meanwhile end milling and Direct Ink Writing (DIW) are applied to create channels on the surface of the deposited ceramic. Unique to the LSD process is the Formation of a freestanding powder bed with a mechanical strength comparable to conventional slip casted ceramic green bodies. Combining these three processes allows the manufacturing of ceramic objects containing an internal path of ink, which in this case was a graphite-based ink that can be further eliminated by heat treatment to obtain a porcelain object embedded with channels. The results show the capabilities of this method and its potential to fabricate not only parts with inner channels, but also multi-material and multi-functional components (such as integrated electronic circuits).
The invention of new miniaturized and smart medical implants continues in all medical fields, including miniaturized heart pacemakers. These implants often come with a titanium (Ti) casing, which may have to be removed after several months or years and shall therefore not be completely overgrown by cells or scar tissue after implantation. Scar tissue is mainly formed by fibroblast cells and extracellular matrix proteins like collagen produced by them. Suppression of fibroblast growth at Ti surfaces could be achieved by 800 nm femtosecond laser-ablation creating self-organized sharp spikes with dimensions in the 10 μm-range which are superposed by fine sub-μm parallel ripples. On flat Ti control samples, the best results regarding suppression of cell growth were obtained on spike-structures which were additionally electrochemically anodized under acidic conditions. When Ti cylinders with a diameter of 8 mm (similar as the pacemakers) were placed upright in a culture of murine fibroblasts, a multi-layer cell growth up to a height of at least 1.5 mm occurred within 19–22 days. We have demonstrated that a laser-structured and anodized ring around the Ti cylinder surface is an effective way to create a barrier that murine fibroblasts were not able to overgrow within this time.
A European EMPIR project, which aims to use large-scale piezoresistive microprobes for contact resonance applications, a well-established measurement mode of atomic force microscopes (AFMs), is being funded. As the probes used in this project are much larger in size than typical AFM probes some of the simplifications and assumptions made for AFM probes are not applicable. This study presents a guide on how to systematically create a model that replicates the dynamic behavior of microprobes, including air damping, nonlinear sensitivities, and frequency dependencies. The model is then verified by analyzing a series of measurements.
Simultaneous characterization of poly(acrylic acid) andpolysaccharide polymers and copolymers
(2020)
Copolymer products that result from grafting acrylic acid and other hydrophilicmonomers onto polysaccharides have recently gained significant interest in researchand industry. Originating from renewable sources, these biodegradable, low toxicity,and polar copolymer products exhibit potential to replace polymers from fossil sourcesin several applications and industries. The methods usually employed to character-ize these copolymers are, however, quite limited, especially for the measurement ofbulk properties. With more sophisticated applications, for example, in pharmaceu-tics requiring a more detailed analysis of the chemical structure, we describe a newapproach for this kind of complex polymers. Our approach utilizes chromatographyin combination with several detection methods to separate and characterize reactionproducts of the copolymerization of acrylic acid and chemically hydrolyzed starch.These samples consisted of a mixture of homopolymer poly (acrylic acid), homopoly-mer hydrolyzed starch, and – in a lower amount – the formed copolymers. Several chro-matographic methods exist that are capable of characterizing either poly (acrylic acid)or hydrolyzed starch. In contrast, our approach offers simultaneous characterization ofboth polymers. The combination of LC and UV/RI offered insight into the compositionand copolymer content of the samples. Size exclusion chromatography experimentsrevealed the molar mass distribution of homopolymers and copolymers. FTIR inves-tigations confirmed the formation of copolymers while ESI-MS gave more details onthe end groups of hydrolyzed starches and poly (acrylic acids). Evidence of copolymerstructures was obtained through NMR measurements. Finally, two-dimensional chro-matography led to the separation of the copolymers from both homopolymers as wellas the additional separation of sodium clusters. The methods described in this work area powerful toolset to characterize copolymerization products of hydrolyzed starch andpoly(acrylic acid). Together, our approach successfully correlates the physicochemicalproperties of such complex mixtures with their actual composition.
The accurate determination of wear volumes is a prerequisite for the study of numerous tribological phenomena. Wear volumes can be measured with different techniques or else be calculated starting from some quantities measured from the wear scar. Advantages and drawbacks of the measuring techniques are shown by means of wear scars and calottes resulting from ball-on-plane tests with 100Cr6 specimens. When measuring wear volumes, white light interferometry results to be one of the most suitable techniques. When wear volumes are calculated, errors result mainly from two sources: (1) the arbitrary choice of one or few line profiles for the determination of the width and of the planimetric wear, and (2) approximations in the calculation, which are even necessary when values of the wear volumes of the single tribological partners and not only the total volume are of interest. The effect of both error sources on the accuracy in the determination of wear volumes is characterized and elucidated by examples. It is found that errors due to approximations are negligible when compared to errors due to the arbitrary choice of one line profile.
Hydrogen-charged supermartensitic steel samples were used to systematically investigate imaging artifacts in neutron radiography. Cadmium stencils were placed around the samples to shield the scintillator from excessive neutron radiation and to investigate the influence of the backlight effect. The contribution of scattered neutrons to the total detected intensity was investigated by additionally varying the sample-detector distance and applying a functional correlation between distance and intensity. Furthermore, the influence of the surface roughness on the edge effect due to refraction was investigated.
Laser material processing is an emerging technology that generates surface functionalities on the basis of optical, mechanical, or chemical properties. In the form of laser surface texturing (LST), it has attracted a remarkable amount of research to tailor surface properties towards various tribological applications. The main advantages of this single-step, laser-based technology are the contactless machining, featuring a high flexibility, efficiency, and speed, along with the excellent quality of the processed products. LST can be applied precisely localized to sub-micrometric areas, but, via laser beam scanning, it is also feasible for structuring large surface areas at the square meter size.
This Special Issue focuses on the latest developments concerning the tribological performance of laser-generated periodic surface nano- and microstructures and their applications. This includes the laser-based processing of different surface patterns, such as “self-organized” laser-induced periodic surface structures (LIPSS, ripples), grooves, micro-spikes, hierarchical hybrid nano-/micro-structures, microfeatures generated by direct laser interference patterning (DLIP), or even dimples or other topographic geometries shaped by direct laser modification or ablation. The applications of these periodically nano- and micro-patterned surfaces may improve the lubricated or non-lubricated tribological performance of surfaces in conformal and even non-conformal contact through a reduction of wear, a variation of the coefficient of friction, altered load carrying capacity, etc., resulting in energy saving, improved reliability, increased lifetimes as well as durability, leading in turn to extended maintenance intervals/reduced down-time. This can be beneficial in terms of bearings, gears, engines, seals, cutting tools, or other tribological components. Fundamental aspects addressed may involve the investigation of the relevant physical and chemical effects accompanying the laser-generated nano- and microscale topographies, such as alterations of the material structures, the hardness, superficial oxidation, the role of additives contained in lubricants, surface wettability, micro-hydrodynamic effects, etc.
For this Special Issue we aim to attract both academic and industrial researchers and would like to provide a bridge between research in the fields of tribology and laser material processing in order to foster the current knowledge and present new ideas for future applications and new technologies.
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.
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.
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.