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Barriers to transitioning to a circular bio-based economy: Findings from an industrial perspective
(2024)
The transition from a linear fossil-based to a circular bio-based economy represents an opportunity and a suitable pathway for achieving several sustainable development goals. However, the transition is a complex process since it requires transformative policies, purposeful innovation, access to finance, risk-taking capacity as well as new and sustainable business models and markets. Accordingly, the first step in this transition process is the identification of barriers that are hampering the transition to a sustainable circular bio-based economy. With this motivation in mind, this study reviews grey literature to identify barriers focusing on four critical sectors facing major challenges within the current linear economy and requiring a sustainable transition most urgently: construction, chemicals, plastics, and textile sectors. Employing an adapted STEEP methodology (Social, Technological, Economical, Environmental, Political), a total of 193 different barriers have been identified and clustered under six categories: cultural, technical, economic, environmental, governance, and structural. Regardless of the sector, cultural and structural barriers are identified as the most prominent; the lack of incentives for consumer behaviour change and lack of stakeholder collaboration were the most cited barriers among the literature records. From a value chain perspective, most of the barriers are related to the material processing and product manufacturing stage. Finally, potential solutions, extracted from the grey literature, are proposed to fill the gaps and overcome the identified barriers. Many of the identified barriers are common across the four investigated sectors, indicating the solutions or measures can be applicable in a wider perspective to promote the transition in the right direction.
In this study, femtosecond laser-induced sub-micrometer structures are generated to modify polyethylene (PE) surface topographies. These surfaces were subjected to bacterial colonization studies with Escherichia coli and Staphylococcus aureus as test strains. The results reveal that the nanostructures do not influence S. aureus coverage, while the adhesion of E. coli is reduced.
Boron neutron capture therapy (BNCT) is a radiotherapeutic modality based on the nuclear capture of slow neutrons by stable 10B atoms followed by charged particle Emission that inducing extensive damage on a very localized level (<10 um). To be effcient, a suffcient amount of 10B should accumulate in the tumor area while being almost cleared from the normal surroundings. A water-soluble aza-boron-dipyrromethene dyes (BODIPY) fluorophore was reported to strongly accumulate in the tumor area with high and BNCT compatible Tumor/Healthy Tissue ratios.
The clinically used 10B-BSH (sodium borocaptate) was coupled to the water-soluble aza-BODIPY platform for enhanced 10B-BSH tumor vectorization. We demonstrated a strong uptake of the compound in tumor cells and determined its biodistribution in mice-bearing tumors. A model of chorioallantoic membrane-bearing glioblastoma xenograft was developed to evidence the BNCT potential of such compound, by subjecting it to slow neutrons. We demonstrated the Tumor accumulation of the compound in real-time using optical imaging and ex vivo using elemental imaging based on laser-induced breakdown spectroscopy. The tumor growth was significantly reduced as compared to BNCT with 10B-BSH. Altogether, the fluorescent aza-BODIPY/10B-BSH compound is able to vectorize and image the 10B-BSH in the tumor area, increasing its theranostic potential for effcient approach of BNCT.
Whereas the characterization of nanomaterials using different analytical techniques is often highly automated and standardized, the sample preparation that precedes it causes a bottleneck in nanomaterial analysis as it is performed manually. Usually, this pretreatment depends on the skills and experience of the analysts. Furthermore, adequate reporting of the sample preparation is often missing. In this overview, some solutions for techniques widely used in nano-analytics to overcome this problem are discussed. Two examples of sample preparation optimization by au-tomation are presented, which demonstrate that this approach is leading to increased analytical confidence. Our first example is motivated by the need to exclude human bias and focuses on the development of automation in sample introduction. To this end, a robotic system has been de-veloped, which can prepare stable and homogeneous nanomaterial suspensions amenable to a variety of well-established analytical methods, such as dynamic light scattering (DLS), small-angle X-ray scattering (SAXS), field-flow fractionation (FFF) or single-particle inductively coupled mass spectrometry (sp-ICP-MS). Our second example addresses biological samples, such as cells exposed to nanomaterials, which are still challenging for reliable analysis. An air–liquid interface has been developed for the exposure of biological samples to nanomaterial-containing aerosols. The system exposes transmission electron microscopy (TEM) grids under reproducible conditions, whilst also allowing characterization of aerosol composition with mass spectrometry. Such an approach enables correlative measurements combining biological with physicochemical analysis. These case studies demonstrate that standardization and automation of sample preparation setups, combined with appropriate measurement processes and data reduction are crucial steps towards more reliable and reproducible data.
To increase the competitiveness of jacket substructures compared to monopiles a changeover from an individual towards a serial jacket production based on automated manufactured tubular joints combined with standardized pipes has to be achieved. Therefore, this paper addresses fatigue tests of automatically welded tubular X-joints focusing on the location of the technical fatigue crack. The detected location of the technical crack is compared to numerical investigations predicting the most fatigue prone notch considering the structural stress approach as well as the notch stress approach. Besides, the welding process of the automated manufactured tubular X-joints is presented.
To increase the competitiveness of jacket substructures compared to monopiles a changeover from an individual towards a serial jacket production based on automated manufactured tubular joints combined with standardized pipes has to be achieved. Therefore, this paper addresses fatigue tests of automatically welded tubular X-joints focusing on the location of the technical fatigue crack. The detected location of the technical crack is compared to numerical investigations predicting the most fatigue prone notch considering the structural stress approach as well as the notch stress approach. Besides, the welding process of the automated manufactured tubular X-joints is presented.
In additive manufacturing (AM) directed energy deposition (DED), parts are built by welding layers of powder or wire feedstock onto a substrate with applications for steel powders in the fields of forging tools, spare parts, and structural components for various industries. For large and bulky parts, the choice of toolpaths influences the build rate, the mechanical performance, and the distortions in a highly geometry-dependent manner. With weld-path lengths in the range of hundreds of meters, a reliable, automated tool-path generation is essential for the usability of DED processes. This contribution presents automated tool-path generation approaches and discusses the results for arbitrary geometries. Socalled “zig-zag” and “contour-parallel” processing strategies are investigated and the tool-paths are automatically formatted into machine-readable g-code for experimental validation to build sample geometries. The results are discussed in regard to volume-fill, microstructure, and porosity in dependence of the path planning according to photographs and metallographic cross-sections.
The separation of colloidal nanocrystals from their original synthesis medium is an essential process step towards their application, however, the costs on a preparative scale are still a constraint. A new combination of approaches for the purification of hydrophobic Quantum Dots is presented, resulting in an efficient scalable process in regard to time and solvent consumption, using common laboratory equipment and low-cost materials. The procedure is based on a combination of solvent-induced adhesion and solid phase extraction. The platform allows the transition from manual handling towards automation, yielding an overall purification performance similar to one conventional batch precipitation/centrifugation step, which was investigated by thermogravimetry and gas chromatography. The distinct miscibility gaps between surfactants used as nanoparticle capping agents, original and extraction medium are clarified by their phase diagrams, which confirmed the outcome of the flow chemistry process. Furthermore, the solubility behavior of the Quantum Dots is put into context with the Hansen solubility parameters framework to reasonably decide upon appropriate solvent types.
Automated modal analysis for tracking structural change during construction and operation phases
(2019)
The automated modal analysis (AMA) technique has attracted significant interest over the last few years, because it can track variations in modal parameters and has the potential to detect structural changes. In this paper, an improved density-based spatial clustering of applications with noise (DBSCAN) is introduced to clean the abnormal poles in a stabilization diagram. Moreover, the optimal system model order is also discussed to obtain more stable poles. A numerical Simulation and a full-scale experiment of an arch bridge are carried out to validate the effectiveness of the proposed algorithm. Subsequently, the continuous dynamic monitoring system of the bridge and the proposed algorithm are implemented to track the structural changes during the construction phase. Finally, the artificial neural network (ANN) is used to remove the temperature effect on modal frequencies so that a health index can be constructed under operational conditions.
Automated bonding analysis software has been developed based on Crystal Orbital Hamilton Populations to facilitate high-throughput bonding analysis and machine-learning of bonding features. This work presents the software and discusses its applications to simple and complex materials such as GaN, NaCl, the oxynitrides XTaO2N (X=Ca, Ba, Sr) and Yb14Mn1Sb11.
To explore the impact of ambient and structural water on static fatigue, the initiation and growth of 3279 Vickers induced median radial cracks were automatically recorded and analyzed. We find that humidity is more efficient in initiating cracks and promoting their growth than water, which is dissolved in the glass structure. In particular for slow crack growth (< 3x10-6 m s-1), tests in dry nitrogen showed a considerable decrease in the crack growth exponent with increasing water content of the glasses. On the other hand, if tests were performed in humid air, the crack growth exponent was independent of the water content of the hydrous glasses, while stress intensity decreased slightly. These observations indicate that water promotes the processes at the crack-tip regardless of its origin. However, ambient water is more efficient.
In the past two decades, numerous relaxation or physical aging experiments of metallic glasses have revealed signatures of intermittent atomic-scale processes. Revealed via intensity cross-correlations from coherent scattering using X-ray photon correlation spectroscopy (XPCS), the observed abrupt changes in the time-domain of atomic motion does not fit the picture of gradual slowing down of relaxation times and their origin continues to remain unclear. Using a binary Lennard-Jones model glass subjected to microsecond-long isotherms, we show here that temporally and spatially heterogeneous atomic-cluster activity at different length-scales drive the emergence of highly non-monotonous intensity cross-correlations. The simulated XPCS experiments reveal a variety of time-dependent intensity-cross correlations that, depending on both the structural evolution and the 𝑞-space sampling, give detailed insights into the possible structural origins of intermittent aging measured with XPCS.
CFD simulations of near-ground gas dispersion depend significantly on the accuracy of the wind field. When simulating wind fields with conventional RANS turbulence models, the velocity and turbulence profiles specified as inlet boundary conditions change rapidly in the approach flow region. As a result, when hazardous materials are released, the extent of hazardous areas is calculated based on an approach flow that differs significantly from the boundary conditions defined. To solve this problem, a turbulence model with consistent boundary conditions was developed to ensure a horizontally homogeneous approach flow. Instead of the logarithmic vertical velocity profile, a power law is used to overcome the problem that with the logarithmic profile, negative velocities would be calculated for heights within the roughness length. With this, the problem that the distance of the wall-adjacent cell midpoint has to be higher than the roughness length is solved, so that a high grid resolution can be ensured even in the near-ground region which is required to simulate
gas dispersion. The evaluation of the developed CFD model using the German guideline VDI 3783/9 and wind tunnel experiments with realistic obstacle configurations showed a good agreement between the calculated and the measured values and the ability to achieve a horizontally homogenous approach flow.
The allergenic potential of airborne proteins may be enhanced via post-translational modification induced by air pollutants like ozone (O3) and nitrogen dioxide (NO2). The molecular mechanisms and kinetics of the chemical modifications that enhance the allergenicity of proteins, however, are still not fully understood. Here, protein tyrosine nitration and oligomerization upon simultaneous exposure of O3 and NO2 were studied in coated-wall flow-tube and bulk solution experiments under varying atmospherically relevant conditions (5–200 ppb O3, 5–200 ppb NO2, 45–96% RH), using bovine serum albumin as a model protein. Generally, more tyrosine residues were found to react via the nitration pathway than via the oligomerization pathway. Depending on reaction conditions, oligomer mass fractions and nitration degrees were in the ranges of 2.5–25% and 0.5–7%, respectively. The experimental results were well reproduced by the kinetic multilayer model of aerosol surface and bulk chemistry (KM-SUB). The extent of nitration and oligomerization strongly depends on relative humidity (RH) due to moisture-induced phase transition of proteins, highlighting the importance of cloud processing conditions for accelerated protein chemistry. Dimeric and nitrated species were major products in the liquid phase, while protein oligomerization was observed to a greater extent for the solid and semi-solid phase states of proteins. Our results show that the rate of both processes was sensitive towards ambient ozone concentration but rather insensitive towards different NO2 levels. An increase of tropospheric ozone concentrations in the Anthropocene may thus promote pro-allergic protein modifications and contribute to the observed increase of allergies over the past decades.
Asymmetrically bridged aroyl-S,N-ketene acetals and aroyl-S,N-ketene acetal multichromophores can be readily synthesized in consecutive three-, four-, or five-component syntheses in good to excellent yields by several successive Suzuki-couplings of aroyl-S,N-ketene acetals and bis(boronic)acid esters. Different aroyl-S,N-ketene acetals as well as linker molecules yield a library of 23 multichromophores with substitution and linker pattern-tunable emission properties. This allows control of different communication pathways between the chromophores and of aggregation-induced emission (AIE) and energy transfer (ET) properties, providing elaborate aggregation-based fluorescence switches.
Avoiding aerial microfibre contamination of environmental samples is essential for reliable analyses when it comes to the detection of ubiquitous microplastics. Almost all laboratories have contamination problems which are largely unavoidable without investments in clean-air devices. Therefore, our study supplies an approach to assess background microfibre contamination of samples in the laboratory under particle-free air conditions. We tested aerial contamination of samples indoor, in a mobile laboratory, within a laboratory fume hood and on a clean bench with particles filtration during the examining process of a fish. The used clean bench reduced aerial microfibre contamination in our laboratory by 96.5%. This highlights the value of suitable clean-air devices for valid microplastic pollution data. Our results indicate, that pollution levels by microfibres have been overestimated and actual pollution levels may be many times lower. Accordingly, such clean-air devices are recommended for microplastic laboratory applications in future research work to significantly lower error rate
In 2018, the production of Municipal SolidWaste (MSW) in EU-28 reached 250.6 Mt, with the adoption of different management strategies, involving recycling (48 wt %), incineration and thermal valorization (29 wt %) and landfilling (23 wt %). This work was based on the analysis of the baseline situation of MSW management in EU-28 in 2018, considering its progress in 2008–2018, and discussed the possible improvement perspectives based on a framework involving incineration and recycling as the only possible alternatives, specifically evaluating the capability of already-existing incineration plants to fulfill the EU needs in the proposed framework. The results of the assessment showed two main crucial issues that could play a pivotal role in the achievement of Circular Economy action plan targets: the need to increase the recycling quotas for specific MSW fractions through the separate collection, and therefore the improvement of definite treatment process chains; the optimization of the recovery of secondary raw materials from incineration bottom ash, involving the Recycling of ferrous and nonferrous metals and the mineral fraction. Both issues need to find an extensive application across all member states to decrease the actual differences in the adoption of sustainable MSW management options.
Various test methods are available for assessing the susceptibility of materials to solidification cracking during welding. In the widely used Varestraint test, the crack length is selected as a criterion as a function of the applied bending strain.
Unfortunately, the crack length does not characterize the material behavior alone but depends to varying degrees on the individual test parameters used, which makes the interpretation of the results difficult. In addition, the crack length is not comparable under different test conditions. To overcome these disadvantages, we have developed a novel evaluation methodology that decouples the machine influence from the material behavior. The measured crack length is related to the maximum possible value specified by welding speed and deformation time. This relative crack length is calculated numerically, considering the orientation of the cracks. Experiments on two high-alloy martensitic welding consumables show that, in contrast to the conventional evaluation, a comparison of different welding parameters becomes possible. Furthermore, the strain rate proved to be a suitable crack criterion in agreement with Prokhorov's hot cracking model.
The long-term leaching behavior of incineration bottom ash (IBA) was studied with large-scale samples from two German waste incinerators with grate technology. The observation period was up to 281 days. The aging processes proceeded faster in the outdoor storage of the samples. The dominant factor in the leaching behavior is the pH, which starts at values above 12 and decreases to values below 10 (outdoors, <11 indoors). Most heavy metals exhibit minimum solubility in this pH range. The solubility of Sb depends on the prevailing Ca concentration, due to the formation of low-soluble Ca antimonate. The very low sulfate concentrations observed in the leaching tests with fresh IBA could be explained by the presence of ettringite. In the course of the aging reaction, ettringite is transformed into gypsum. The results from batch tests were compared with those from column tests, showing reasonable agreement. Leaching dynamics can be better followed with column tests. All results confirm that the use of IBA is possible under German law.
To investigate the imaging performance of an elastin-specific molecular magnetic resonance imaging (MRI) probe with respect to the extracellular matrix (ECM) in an experimental hepatic cancer model. Twelve rabbits with hepatic VX2 tumors were examined using 3 T MRI 14, 21, and 28 days after tumor implantation for two subsequent days (gadobutrol, day 1; elastin-specific probe, day 2). The relative enhancement (RE) of segmented tumor regions (central and margin) and the peritumoral matrix was calculated using pre-contrast and delayed-phase T1w sequences. MRI measurements were correlated to histopathology and element-specific and spatially resolved mass spectrometry (MS). Mixed-model analysis was performed to assess the performance of the elastin-specific probe. In comparison to gadobutrol, the elastin probe showed significantly stronger RE, which was pronounced in the tumor margin (day 14–28: P ≤ 0.007). In addition, the elastin probe was superior in discriminating between tumor regions (χ2(4) = 65.87; P < 0.001). MRI-based measurements of the elastin probe significantly correlated with the ex vivo elastinstain (R = .84; P <0 .001) and absolute gadolinium concentrations (ICP-MS: R = .73, P <0 .01). LA-ICP-MS imaging confirmed the colocalization of the elastin-specific probe with elastic fibers. Elastin-specific molecular MRI is superior to non-specific gadolinium-based contrast agents in imaging the ECM of hepatic tumors and the peritumoral tissue.
Atherosclerosis is a progressive inflammatory vascular disease characterized by endothelial dysfunction and plaque burden. Extracellular matrix (ECM)-associated plasma proteins play an important role in disease development. Our magnetic resonance imaging (MRI) study investigates the feasibility of using two different molecular MRI probes for the simultaneous assessment of ECM-associated intraplaque albumin deposits caused by endothelial damage and progressive inflammation in atherosclerosis. Male apolipoprotein E-deficient (ApoE-/-)-mice were fed a high-fat diet (HFD) for 2 or 4 months. Another ApoE-/--group was treated with pravastatin and received a HFD for 4 months. T1- and T2*-weighted MRI was performed before and after albumin-specific MRI probe (gadofosveset) administration and a macrophage-specific contrast agent (ferumoxytol). Thereafter, laser ablation inductively coupled plasma mass spectrometry and histology were performed. With advancing atherosclerosis, albumin-based MRI signal enhancement and ferumoxytol-induced signal loss areas in T2*-weighted MRI increased. Significant correlations between contrast-to-noise-ratio (CNR) post-gadofosveset and albumin stain (R2 = 0.78, p < 0.05), and signal loss areas in T2*-weighted MRI with Perls’ Prussian blue stain (R2 = 0.83, p < 0.05) were observed. No interference of ferumoxytol with gadofosveset enhancement was detectable. Pravastatin led to decreased inflammation and intraplaque albumin. Multi-target MRI combining ferumoxytol and gadofosveset is a promising method to improve diagnosis and treatment monitoring in atherosclerosis.
The interest in using computer simulations of dimensional x-ray computed tomography (dXCT) for various metrological purposes—such as measurement planning, performance prediction, performance optimisation and, finally, measurement uncertainty estimation—is increasing along with the ever-growing demand for more reliable measurements with dXCT. However, before a piece of simulation software can be used for tasks related to coordinate metrology, it has to be ensured that it is able to simulate physical laws, characteristic effects and basic CT system functionalities correctly and with sufficient accuracy. In short, the software must be qualified for dimensional metrology tasks. As one part of such a qualification process, a method is presented here for determining conformity intervals of 2D tests (projection-based tests) based on 3D tests (testing based on dimensional evaluations in a reconstructed volume) for the assessment of dXCT simulation software. The method consists of varying relevant parameter values in order to verify their influence on 3D measurement results. The results of the 3D tests with varied parameter values are then transferred to the quantities tested in the 2D tests and used as the basis for determining conformity intervals. Two approaches are applied for determining whether or not a variation of a parameter value is significant: (a) statistical and (b) heuristic. Two examples are presented, each based on simulated images, which show the application of the two different approaches for determining conformity intervals for the results of the 2D tests.
Lanthanide-based, spectrally shifting, and multi-color luminescent upconverting nanoparticles (UCNPs) have received much attention in the last decades because of their applicability as reporter for bioimaging, super-resolution microscopy, and sensing as well as barcoding and anti-counterfeiting tags. A prerequisite for the broad application of UCNPs in areas such as sensing and encoding are simple, robust, and easily upscalable synthesis protocols that yield large quantities of UCNPs with sizes of 20 nm or more with precisely controlled and tunable physicochemical properties from lowcost reagents with a high reproducibility. In this context, we studied the reproducibility, robustness, and upscalability of the synthesis of β-NaYF4:Yb, Er UCNPs via thermal decomposition. Reaction parameters included solvent, precursor chemical compositions, ratio, and concentration. The resulting UCNPs were then examined regarding their application-relevant physicochemical properties such as size, size distribution, morphology, crystal phase, chemical composition, and photoluminescence.
Based on these screening studies, we propose a small volume and high-concentration synthesis approach that can provide UCNPs with different, yet controlled size, an excellent phase purity and tunable morphology in batch sizes of up to at least 5 g which are well suited for the fabrication of sensors, printable barcodes or authentication and recycling tags.
We studied the dissolution behavior of β NaYF4:Yb(20%), Er(2%) UCNP of two different sizes in biologically relevant media i.e., water (neutral pH), phosphate buffered saline (PBS), and Dulbecco’s modified Eagle medium (DMEM) at different temperatures and particle concentrations. Special emphasis was dedicated to assess the influence of different surface functionalizations, particularly the potential of mesoporous and microporous silica shells of different thicknesses for UCNP stabilization and protection. Dissolution was quantified electrochemically using a fluoride ion selective electrode (ISE) and by inductively coupled plasma optical emission spectrometry (ICP OES). In addition, dissolution was monitored fluorometrically. These experiments revealed that a thick microporous silica shell drastically decreased dissolution. Our results also underline the critical influence of the chemical composition of the aqueous environment on UCNP dissolution. In DMEM, we observed the formation of a layer of adsorbed molecules on the UCNP surface that protected the UCNP from dissolution and enhanced their fluorescence. Examination of this layer by X ray photoelectron spectroscopy (XPS) and mass spectrometry (MS) suggested that mainly phenylalanine, lysine, and glucose are adsorbed from DMEM. These findings should be considered in the future for cellular toxicity studies with UCNP and other nanoparticles and the design of new biocompatible surface coatings.
Due to rapid, localized heating and cooling, distortions accumulate in additive manufactured laser metal deposition (LMD) components, leading to a loss of dimensional accuracy or even cracking. Numerical welding simulations allow the prediction of these deviations and their optimization before conducting experiments. To assess the viability of the simulation tool for the use in a predictive manner, comprehensive systems as well as to choose the optimal product matches, product analysis methods are needed. Indeed, most of the known methods aim to analyze a product or one product family on the physical level. Different product families, however, may differ largely in terms of the number and nature of components. This fact impedes an efficient comparison and choice of appropriate product family combinations for the production system. A new methodology is proposed to analyze existing products in view of their functional and physical architecture. The aim is to Cluster these products in new assembly oriented product families for the optimization.
Luminescent semiconductor quantum dots (QDs) are frequently used in the life and material sciences as reporter for bioimaging studies and as active components in devices such as displays, light-emitting diodes, solar cells, and sensors. Increasing concerns regarding the use of toxic elements like cadmium and lead, and hazardous organic solvents during QD synthesis have meanwhile triggered the search for heavy-metal free QDs using green chemistry syntheses methods. Interesting candidates are ternary AgInS2 (AIS) QDs that exhibit broad photoluminescence (PL) bands, large effective Stokes shifts, high PL quantum yields (PL QYs), and long PL lifetimes, which are particularly beneficial for applications such as bioimaging, white light-emitting diodes, and solar concentrators. In addition, these nanomaterials can be prepared in high quality with a microwave-assisted (MW) synthesis in aqueous solution. The homogeneous heat diffusion and instant temperature rise of the MW synthesis enables a better control of QD nucleation and growth and thus increases the batch-to-batch reproducibility. In this study, we systematically explored the MW synthesis of AIS/ZnS QDs by varying parameters such as the order of reagent addition, precursor concentration, and type of stabilizing thiol ligand, and assessed their influence on the optical properties of the resulting AIS/ZnS QDs. Under optimized synthesis conditions, water-soluble AIS/ZnS QDs with a PL QY of 65% and excellent colloidal and long-term stability could be reproducible prepared.
Wood products are often treated by different techniques to improve their longevity when used as building materials. Most of the time, the goal is to increase their resistance to weathering effects, deformations in material dimensions or biotic decomposition. These wood treatment techniques have a significant impact on pyrolysis and burning behavior. The general effects of three different common wood treatments on flame retardancy were investigated by comparing treated woods with their untreated counterparts and with other kinds of wood. While the acetylation of beech leads to a slightly increased fire hazard, the thermal treatment of wood and crosslinking of cellulose microfibrils dimethyloldihydroxy-ethyleneurea show a limited flame retarding effect. Switching to woods with a higher lignin content, and thus higher char yield, however, results in a more pronounced improvement in flame retardancy performance. This article delivers a comprehensive and balanced assessment of the general impact of different wood modifications on the fire behavior. Further, it is a valuable benchmark for assessing the flame retardancy effect of other wood modifications.
Efficient water electrolysis requires highly active electrodes. The activity of corresponding catalytic coatings strongly depends on material properties such as film thickness, crystallinity, electrical conductivity, and chemical surface speciation. Measuring these properties with high accuracy in vacuum-free and nondestructive methods facilitates the elucidation of structure−activity relationships in realistic environments. Here, we report a novel approach to analyze the optical and electrical properties of highly active oxygen evolution reaction (OER) catalysts via spectroscopic ellipsometry (SE). Using a series of differently calcined, mesoporous, templated iridium oxide films as an example, we assess the film thickness, porosity, electrical resistivity, electron concentration, electron mobility, and interband and intraband transition energies by modeling of the optical spectra. Independently performed analyses using scanning electron microscopy, energy-dispersive X-ray spectroscopy, ellipsometric porosimetry, X-ray reflectometry, and absorption spectroscopy indicate a high accuracy of the deduced material properties. A comparison of the derived analytical data from SE, resonant photoemission spectroscopy, X-ray absorption spectroscopy, and X-ray photoelectron spectroscopy with activity measurements of the OER suggests that the intrinsic activity of iridium oxides scales with a shift of the Ir 5d t2g sub-level and an increase of p−d interband transition energies caused by a transition of μ1-OH to μ3-O species.
Reliability of NDT is affected by human factors, which have thus far received the least amount of attention in the reliability assessments. With increased use of automation, in terms of mechanised testing (automation-assisted inspection and the corresponding evaluation of data), higher reliability standards are believed to have been achieved. However, human inspectors, and thus human factors, still play an important role throughout this process and the risks involved in this application are unknown. The aim of this study was to explore for the first time the risks associated with mechanised NDT and find ways of mitigating their effects on the inspection performance. Hence, the objectives were to identify and Analyse potential risks in mechanised NDT and devise measures against them. To address those objectives, a risk assessment in form of a Failure Modes and Effects Analysis (FMEA) was conducted. This analysis revealed potential for failure during both the acquisition and evaluation of NDT data that could be assigned to human, technology, and organisation. Since the existing preventive measures were judged to be insufficient to defend the system from identified failures, new preventive measures were suggested.
Industry 4.0 is all about interconnectivity, sensor-enhanced process control, and data-driven systems. Process analytical technology (PAT) such as online nuclear magnetic resonance (NMR) spectroscopy is gaining in importance, as it increasingly contributes to automation and digitalization in production. In many cases up to now, however, a classical evaluation of process data and their transformation into knowledge is not possible or not economical due to the insufficiently large datasets available. When developing an automated method applicable in process control, sometimes only the basic data of a limited number of batch tests from typical product and process development campaigns are available. However, these datasets are not large enough for training machine-supported procedures. In this work, to overcome this limitation, a new procedure was developed, which allows physically motivated multiplication of the available reference data in order to obtain a sufficiently large dataset for training machine learning algorithms. The underlying example chemical synthesis was measured and analyzed with both application-relevant low-field NMR and high-field NMR spectroscopy as reference method. Artificial neural networks (ANNs) have the potential to infer valuable process information already from relatively limited input data. However, in order to predict the concentration at complex conditions (many reactants and wide concentration ranges), larger ANNs and, therefore, a larger Training dataset are required. We demonstrate that a moderately complex problem with four reactants can be addressed using ANNs in combination with the presented PAT method (low-field NMR) and with the proposed approach to generate meaningful training data.
Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are valuable analytical and quality control methods for most industrial chemical processes as they provide information on the concentrations of individual compounds and by-products. These processes are traditionally carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been realized to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra, to train an ANN with better prediction performance and speed than state-of-the-art analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control.
The current trend for future flame retardants (FRs) goes to novel efficient halogen-free materials, due to the ban of several halogenated FRs. Among the most promising alternatives are phosphorus-based FRs, and of those, polymeric materials with complex shape have been recently reported. Herein, we present novel halogen-free aromatic and aliphatic hyperbranched polyphosphoesters (hbPPEs), which were synthesized by olefin Metathesis polymerization and investigated them as a FR in epoxy resins. We compare their efficiency (aliphatic vs. aromatic) and further assess the differences between the monomeric compounds and the hbPPEs. The decomposition and vaporizing behavior of a compound is an important factor in its flame-retardant behavior, but also the interaction with the pyrolyzing matrix has a significant influence on the performance. Therefore, the challenge in designing a FR is to optimize the chemical structure and its decomposition pathway to the matrix, with regards to time and temperature. This behavior becomes obvious in this study, and explains the superior gas phase activity of the aliphatic FRs.
Cellulose ethers, like methyl cellulose (MC) or hydroxypropyl cellulose (HPC), are widely used in conservation. They also occur as additives and rheology modifiers in various products like dispersions or gels. Do such products release harmful volatile organic compounds (VOC) during their accelerated aging? A mass testing series utilizing the Oddy test of 60 commercial cellulose ethers ranks the products in safe for permanent use (P, no corrosion), only for temporary use (T, slight corrosion), and unsuitable at all (F, heavy corrosion). Results show that 55% of the products passed the test whereas 33% are for temporary use as slight corrosion occurred on at least one metal coupon and only 11% failed the Oddy test. Raman measurements of the corrosion products identified oxides like massicot, litharge, cuprite, and tenorite among carbonates (hydrocerussite, plumbonacrite), and acetates like basic lead acetate, lead acetate trihydrate as well as lead formate as main phases. For example, commercial, industrial Klucel® G (HPC) scored a T rating through slight corrosion on the lead coupon. Basic lead acetate among other phases indicates the presence of acetic acid. Additional measurements of the sample with thermal desorption GC–MS utilizing the BEMMA scheme confirm the high acetic acid outgassing and reveal the presence of a small amount of formaldehyde.
Aqueous Dispersions of Polypropylene: Toward Reference Materials for Characterizing Nanoplastics
(2023)
Microplastics and nanoplastics pollute the natural environment all over the world, but the full extent of the hazards posed by this waste is unclear. While research on microplastics is well advanced, little work has been done on nanoplastics. This discrepancy is mainly due to the lacking ability to detect nanoplastics in biologically and environmentally relevant matrices. Nanoplastics reference materials can help the development of suitable methods for identifying and quantifying nanoplastics in nature. The aim is to synthesize nanoplastics made from one of the most commonly used plastics, namely polypropylene. An easy way to produce long-term stable aqueous dispersions of polypropylene nanoparticles (nano polypropylene) is reported. The nanoplastic particles, prepared by mechanical breakdown, show a mean hydrodynamic diameter of D h = 180.5 ± 5.8 nm and a polydispersity index of PDI = 0.084 ± 0.02. No surfactant is needed to obtain dispersion which is stable for more than 6 months. The colloidal stability of the surfactant-free nano polypropylene dispersions is explained by their low zeta potential of 𝜻 = −43 ± 2 mV.
Approximation of the crack driving force for cracks at notches under static and cyclic loading
(2017)
The work deals with the efficient calculation of the elastic-plastic crack driving force (J-integral for monotonic loading andΔJ-integral under cyclic loading) for short cracks at notches as essential parameter for the reliable static and fatigue assessment of notched structures. The J- or ΔJ-integral is calculated based on analytical solutions for stress intensity factors, estimated by means of well-known weight function solutions in the case of cracks under power-law stress distributions. A plasticity-correction function is applied to the stress intensity factors to obtain the final expression of the crack driving force. The comparison between analytical solutions and finite element calculations in case of cracks at the weld toe in welded joints shows good agreement.
Approximant-based orientation determination of quasicrystals using electron backscatter diffraction
(2020)
Orientation mapping of quasicrystalline materials is demonstrated using crystalline approximant structures in the technique of electron backscatter diffraction (EBSD). The approximant-based orientations are symmetrised according to the rotational point group of the quasicrystal, including the visualization of orientation maps using proper colour keys for quasicrystal symmetries. Alternatively, approximant-based orientation data can also be treated using pseudosymmetry post-processing options in the EBSD system software, which enables basic grain size estimations. Approximant-based orientation analyses are demonstrated for icosahedral and decagonal quasicrystals.
The visualization of index-of-refraction (IoR) distribution is one of the common methods to investigate fluid flow or pressure fields. While schlieren and shadowgraphy imaging techniques are widely accepted, their inherent limitations often lead to difficulties in elucidating the IoR distribution and extracting the true IoR information from the resulting images. While sophisticated solutions exist, the IoR-gradient-to-image was achieved by purposely introducing a commonly avoided “defect” into the optical path of a conventional coincident schlieren/shadowgraphy setup; the defect is a combination of slight defocusing and the use of non-conjugate optical components. As such, the method presented in this work is referred to as defocusing shadowgraphy, or DF-shadowgraphy. While retaining the ease of a conventional schlieren/shadowgraphy geometry, this DF approach allows direct visualization of complicated resonant acoustic fields even without any data processing. For instance, the transient acoustic fields of a common linear acoustic resonator and a two-dimensional one were directly visualized without inversion. Moreover, the optical process involved in DF-shadowgraphy was investigated from a theoretical perspective. A numerical solution of the sophisticated impulse response function was obtained, which converts the phase distortion into intensity distributions. Based on this solution, the IoRs of various gas streams (e.g., CO2 and isopropanol vapor) were determined from single images.
Each engineering decision is based on a number of more or less accurate information. In assessment of existing structures, additional relevant information collected with on-site inspections facilitate better decisions. However, observed data basically represents the physical characteristic of interest with an uncertainty. This uncertainty is a measure of the inspection quality and can be quantified by expressing the measurement uncertainty. The internationally accepted rules for calculating measurement uncertainty are well established and can be applied straightforwardly in many practical cases. Nevertheless, the calculations require the occasionally time-consuming development of an individually suitable measurement model. This contribution attempts to emphasize proposals for modelling the non-destructive depth measurement of tendons in concrete using the ultrasonic echo technique. The proposed model can serve as guideline for the determination of the quality of the measured information in future comparable inspection scenarios.
Welded joints show large variation of the weld toe geometry along the weld seam, which is one important reason for the comparably large scatter in fatigue life. Therefore, it is crucial to take the local geometry at the weld toe into account, to reduce the conservatism in fatigue assessment of welded joints. This study is based on the IBESS procedure for the calculation of the fatigue strength, whereby the evaluation of local geometrical parameters is carried out by means of 3D surface scans. The approach is validated against 26 fatigue test series. The fatigue life is in general overpredicted, whereas good agreement is achieved for high stress ratio (R = 0.5). A sensitivity analysis conducted with IBESS shows that weld toe radii ρ < 2 mm and flank angle α < 30° have a significant influence on the calculated fatigue strength. In contrast to this, no strong correlation between ρ and the fatigue strength was determined experimentally in this study.
In this study, a signal processing approach for heterodyne Փ-OTDR and C-OTDR systems that can obtain external perturbation and its frequency content in a faster way is proposed. We can detect vibrations with the same or better SNR using this processing approach, only with a single step and fast calculation. Fig. 12 shows the comparison of the normalized measurement time for the gamma matrix method and the conventional method throughout the three experiments. The speed of processing using a gamma matrix is ~35%–50% faster compared to a conventional method in high frequency test (PZT), low frequency test (walking) and street monitoring test. The processing speed in low frequency test is normally a bit lower than the similar high frequency one, since we must use higher number of time frames. Also, in street test we have higher speed because we can select wider gauges.
Tomography data obtained from transmission electron microscopes are especially attractive due to their unrivaled spatial resolution in the nanometer range or even less, but they require enormous efforts in sample preparation and suffer from a diverse accumulation of experimental restrictions, which unavoidably result in fundamental reconstruction artifacts. These restrictions refer to: partial opacity, a limited view (limited angle or missing wedge), very few angles (with respect to the detector size), limited to a region of interest (ROI; due to the sample size), variable angular increments as well as sample degradation due the interactions with the electron beam. An advanced version of the DIRECTT (Direct Iterative Reconstruction of Computed Tomography Trajectories) algorithm proves to cope with most of these severe deviations from ideal CT measuring conditions. However, careful data preprocessing is required in order to exploit the capabilities of the algorithm.
Nanometer sized Ruthenium catalyst particles for fuel cell applications are 3D imaged at a few Ångström resolution in order to estimate their partial free surface on carbon black supports, which rule the efficiency of the catalytic activity.
Comparisons of DIRECTT reconstructions to the conventional filtered back projection, prove the significant improvements.
Alkali-activated materials are ideal for the repair of concrete structures in harsh environmental conditions due to their high durability in chemically aggressive environments. However, slag-based mortars, in particular, are prone to shrinkage and associated cracks. In this respect, the application of steel fibres is one solution to reduce the formation of shrinkage induced cracks and to improve post cracking behaviour of these mortars. This study investigated the influence of two different types of steel fibres on the tensile properties of two alkali-activated mortars. Direct tensile tests and single fibre pull-outs were performed to analyse the determining failure modes both on macro and micro scale. Mechanical testing was accompanied by non-destructive testing methods such as digital image correlation and acoustic emission for a detailed analysis of the fracture process.
Nondestructive testing (NDT) methods are applicable in many ways for defect detection as well as optimization of packaging production processes. The visual inspection method is the technique which is mostly used, although neither the customer nor a skilled inspector may be aware of this.
Techniques like ultrasound for wall thickness measurement, the application of x-ray techniques or the use of dye penetrant techniques for crack detection are rather well known to the NDT family. However, acoustic emission techniques can also be helpful for the characterization of packaging materials. In this paper the employment of x-ray computer tomography (CT) for measurement of wall thickness in plastic jerrycans, especially on the edges, and its possible optimization of production processes will be discussed.
A comparison of the CT and ultrasonic examinations of wall thickness and the reliability of this measured data are also important points for the discussion, especially if some safety factors can be derived from the results.
The leakage test is also good for jerrycans, IBCs or other kinds of drums for the transportation and storage of dangerous goods. The disadvantage of this kind of test is that a lack of quality, e.g. wall thickness deterioration, cannot be detected if the wall thickness withstands the internal pressure. Therefore, especially for Quality assurance, the other, previously mentioned techniques are better for a statistical assessment of a batch. This paper is focused on the comparison of different NDT results with special emphasis on the large range of material mechanical properties.
The ultrasonic echo technique is widely used in non-destructive testing (NDT) of concrete objects for thickness measurements, geometry determinations and localization of built-in components. To improve ultrasonic imaging of complex concrete structures, we transferred a seismic imaging technique, the Reverse Time Migration (RTM), to NDT in civil engineering. RTM, in contrast to the conventionally used synthetic aperture focusing technique (SAFT) algorithms, considers all wavefield types and thus, can handle complex wave propagations in any direction with no limit on velocity variations and reflector dip. In this paper, we focused on the development, application and evaluation of a two-dimensional elastic RTM algorithm considering horizontally polarized shear (SH) waves only. We applied the elastic SH RTM routine to synthetic ultrasonic echo SH-wave data generated with a concrete model incorporating several steps and circular cavities. As these features can often be found in real-world NDT use cases, their imaging is extremely important. By using elastic SH RTM, we were able to clearly reproduce almost all reflectors inside the concrete model including the vertical step edges and the cross sections of the cavities.We were also capable to show that more features could be mapped compared to SAFT, and that imaging of complex reflectors could be sharpened compared to elastic P-SV (compressional-vertically polarized shear) RTM. Our promising results illustrate that elastic SH RTM has the potential to significantly enhance the reconstruction of challenging concrete structures, representing an important step forward for precise, high-quality ultrasonic NDT in civil engineering.
The ultrasonic echo technique is broadly applied in non‐destructive testing (NDT) of concrete structures involving tasks such as measuring thickness, determining geometry and locating built‐in elements. To address the challenge of enhancing ultrasonic imaging for complex concrete constructions, we adapted a seismic imaging algorithm – reverse time migration (RTM) – for NDT in civil engineering. Unlike the traditionally applied synthetic aperture focusing technique (SAFT), RTM takes into account the full wavefield including primary and reflected arrivals as well as multiples. This capability enables RTM to effectively handle all wave phenomena, unlimited by changes in velocity and reflector inclinations. This paper concentrates on applying and evaluating a two‐dimensional elastic RTM algorithm that specifically addresses horizontally polarized shear (SH) waves only, as these are predominantly used in ultrasonic NDT of concrete structures. The elastic SH RTM algorithm was deployed for imaging real ultrasonic echo SH‐wave data obtained at a concrete specimen exhibiting a complex back wall geometry and containing four tendon ducts. As these features are frequently encountered in practical NDT scenarios, their precise imaging holds significant importance. By applying the elastic SH RTM algorithm, we successfully reproduced nearly all reflectors within the concrete specimen. In particular, we were capable of accurately reconstructing all vertically oriented reflectors as well as the circular cross sections of three tendon ducts, which was not achievable with traditional SAFT imaging. These findings demonstrate that elastic SH RTM holds the ability to considerably improve the imaging of complex concrete geometries, marking a crucial advancement for accurate, high‐quality ultrasonic NDT in civil engineering.
Application of Intensity-Based Coherent Optical Time Domain Reflectometry to Bridge Monitoring
(2022)
Although distributed fiber sensing techniques have been widely used in structural health monitoring, the measurement results of bridge monitoring, particularly under destructive testing, have rarely been reported. To the best of our knowledge, this paper is the first report of distributed vibration measurement results, which we obtained during a three-day destructive test on an abolished bridge. A coherent optical time domain reflectometry (COTDR) was used to acquire the vibration information while the bridge was being sawed. The obtained signal was analyzed in time and frequency domain. Some characteristics of the sawing-induced vibration were retrieved by the short-time Fourier transform; the vibration exhibited several high frequency components within the measured range up to 20 kHz and all the components appeared in the same time slot. Some unexpected signals were also detected. Thorough analysis showed that they are quite different from the sawing-induced vibration and are believed to originate from internal damage to the bridge (probably the occurrence of cracks).
In this study, the feasibility of using non-contact Infrared thermography as a potential tool to monitor the CMT welding process is explored. The presence of internal defects such as porosity, lack of filler material deposition and formation of improper weld bead produce perturbations in the surface temperature which can be identified using an Infrared thermography technique. We present recent results obtained from online monitoring of the the dissimilar joining using CMT weld brazing of Aluminum and Steel using a transmission mode measurement approach. The effect of loss of zinc coating on the weldability of the cold metal transfer joining of aluminum to galvanised steel was investigated. A correlation between measured online thermal indications with the weld anomalies is successfully attempted and the results are compared with the conventional post-weld NDT inspection methods.
Critical defects, also known as device killers, in wide bandgap semiconductors significantly affect the performance of power electronic devices. We used the methods imaging ellipsometry (IE) and white light interference microscopy (WLIM) in a hybrid optical metrology study for fast and non-destructive detection, classification, and characterisation of defects in 4H–SiC homoepitaxial layers on 4H–SiC substrates. Ellipsometry measurement results are confirmed by WLIM. They can be successfully applied for wafer characterisation already during production of SiC epilayers and for subsequent industrial quality control.
Hybrid laser-arc welding (HLAW) was applied for butt welding of 14.5 mm thick plates of ferritic cryogenic steel X8Ni9 containing 9% Ni, which is used for manufacturing storage and transport facilities of liquefied natural gas (LNG). The weld seam formation and the achievable metallurgical and mechanical properties of the hybrid welds were investigated experimentally for two types of filler wire, an austenitic wire dissimilar to the base metal (BM) and an experimentally produced matching ferritic wire. Safe penetration and uniform distribution of the austenitic filler metal in the narrow hybrid weld could only be achieved in the upper, arcdominated part of the weld. The pronounced heterogeneous distribution of the austenitic filler metal in the middle part and in the root area of the weld could not ensure sufficient notched impact toughness of the weld metal (WM). As a result, a decrease in the impact energy down to 17±3 J was observed, which is below the acceptance level of ≥34 J for cryogenic applications. In contrast, the use of a matching ferritic filler wire resulted in satisfactory impact energy of the hybrid welds of up to 134±52 J at the concerned cryogenic temperature of -196 °C. The obtained results contribute to an important and remarkable conversion in automated manufacturing of LNG facilities. In other words, the results will help to develop a new laser-based welding technology, where both quality and productivity are considered.The efficiency of the developed welding process has been demonstrated by manufacturing a prototype where a segment of the inner wall of large size LNG storage tank was constructed. In this concern, hybrid laser arc welding was conducted in both horizontal (2G) and vertical (3G) positions as a simulation to the actual onsite manufacturing. The prototype was fabricated twice where its quality was confirmed based on non-destructive and destructive examinations.
Application of electrochemical methods for studying steel corrosion in alkali-activated materials
(2023)
Alkali-activated materials (AAMs) are binders that can complement and partially substitute the current use of conventional cement. However, the present knowledge about how AAMs protect steel reinforcement in concrete elements is incomplete, and uncertainties exist regarding the application of electrochemical methods to investigate this issue. The present review by EFC WP11-Task Force ‘Corrosion of steel in alkali-activated materials’ demonstrates that important differences exist between AAMs and Portland cement, and between different classes of AAMs, which are mainly caused by differing pore solution compositions, and which affect the outcomes of electrochemical measurements. The high sulfide concentrations in blast furnace slag-based AAMs lead to distinct anodic polarisation curves, unusually low open circuit potentials, and low polarisation resistances, which might be incorrectly interpreted as indicating active corrosion of steel reinforcement. No systematic study of the influence of the steel–concrete interface on the susceptibility of steel to corrosion in AAMs is available. Less common electrochemical methods present an opportunity for future progress in the field.