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The microstructure of an apatite-wollastonite (code name AP40) glass-ceramic is analyzed in this study by combining 2D microscopy, phase analysis, X-ray absorption and synchrotron X-ray refraction computed tomography (XCT and SXRCT, respectively). It is shown that this combination provides a useful toolbox to characterize the global microstructure in a wide scale range, from sub-micrometer to millimeter. The material displays a complex microstructure comprising a glassy matrix with embedded fluorapatite and wollastonite small crystals. In this matrix, large (up to 200 μm) spike-shaped structures are distributed. Such microstructural features are oriented around a central sphere, thereby forming a structure resembling a sea urchin. A unique feature of SXRCT, in contrast to XCT, is that internal interfaces are visualized; this allows one to show the 3D distribution of these urchins with exceptionally good contrast. Furthermore, it is revealed that the spike-shaped structures are not single crystals, but rather composed of sub-micrometric crystals, which are identified as fluorapatite and diopside phases by SEM-EDX analysis.
In this study, we employed nitrogen microwave inductively coupled atmospheric-pressure plasma (MICAP) combined with quadrupole mass spectrometry (MS) and a liquid sample introduction system to analyze heavy metals in soils. The vanadium, cobalt, nickel, zinc, copper, chromium, arsenic, lead, and cadmium contents in seven reference and three environmental soil samples determined using MICAP-MS were within the uncertainty of the reference values, indicating that MICAP-MS is promising for soil analysis similar to the conventional inductively coupled plasma mass spectrometry (ICP-MS) technique. In addition, the limits of detection (LODs) and sensitivity of both techniques using N2 and Ar plasma were of the same order of magnitude. Furthermore, the performance of MICAP-MS under different N2 purity was investigated, and we found that the plasma formation and ionization efficiency were not influenced by the impurities in the gas. A prominent advantage of MICAP-MS is the low operating cost associated with gas consumption. In this work, MICAP-MS used nitrogen, which is cheaper than argon, and consumed 25% less gas than ICP-MS. Using low-purity N2 can further reduce the gas cost, making MICAP-MS more cost effective than ICP-MS. These results suggest that MICAP-MS is a promising alternative to ICP-MS for the analysis of heavy metals in the soil.
Large-scale nanoimprinted metasurfaces based on silicon photonic crystal slabs were produced and coated with a NaYF4:Yb3+/Er3+ upconversion nanoparticle (UCNP) layer. UCNPs on these metasurfaces yield a more than 500-fold enhanced upconversion emission compared to UCNPs on planar surfaces. It is also demonstrated how the optical response of the UCNPs can be used to estimate the local field energy in the coating layer. Optical simulations using the finite element method validate the experimental results and the calculated spatial three-dimensional field Energy distribution helps us to understand the emission enhancement mechanism of the UCNPs closely attached to the metasurface. In addition, we analyzed the spectral shifts of the resonances for uncoated and coated metasurfaces and metasurfaces submerged in water to enable a prediction of the optimum layer thicknesses for different excitation wavelengths, paving the way to applications such as electromagnetic field sensors or bioassays.
Phosphorus (P) fertilizers from secondary resources became increasingly important in the last years. However, these novel P-fertilizers can also contain toxic pollutants such as chromium in its hexavalent state (Cr(VI)). This hazardous form of chromium is therefore regulated with low limit values for agricultural products even though the correct determination of Cr(VI) in these fertilizers may be hampered by redox processes, leading to false results. Thus, we applied the novel diffusive gradients in thin-films (DGT) technique for Cr(VI) in fertilizers and compared the results with the standard wet chemical extraction method (German norm DIN EN 15192) and Cr K-edge X-ray Absorption near-edge structure (XANES) spectroscopy. We determined an overall good correlation between the wet chemical extraction and the DGT method. DGT was very sensitive and for most tested materials selective for the analysis of Cr(VI) in P-fertilizers. However, hardly soluble Cr(VI) compounds cannot be detected with the DGT method since only mobile Cr(VI) is analyzed. Furthermore, Cr K-edge XANES spectroscopy showed that the DGT binding layer also adsorbs small amounts of mobile Cr(III) so that Cr(VI) values are overestimated. Since certain types of the P fertilizers contain mobile Cr(III) or partly immobile Cr(VI), it is necessary to optimize the DGT binding layers to avoid aforementioned over- or underestimation. Furthermore, our investigations showed that the Cr K-edge XANES spectroscopy technique is unsuitable to determine small amounts of Cr(VI) in fertilizers (below approx. 1% of Cr(VI) in relation to total Cr).
The combination of acoustically levitated droplets, mid-IR laser evaporation, and subsequent post-ionization by secondary electrospray ionization was applied for monitoring the enzymatic digestion of various proteins. Acoustically levitated droplets are an ideal, wall-free model reactor, readily allowing compartmentalized microfluidic trypsin digestions. Time-resolved interrogation of the droplets yielded real-time information on the progress of the reaction and thus provided insights into reaction kinetics. After 30 min of digestion in the acoustic levitator, the obtained protein sequence coverages were identical to the reference overnight digestions. Importantly, our results clearly demonstrate that the applied experimental setup can be used for the real-time investigation of chemical reactions. Furthermore, the described methodology only uses a fraction of the typically applied amounts of solvent, analyte, and trypsin. Thus, the results exemplify the use of acoustic levitation as a green analytical chemistry alternative to the currently used batch reactions.
The application and benefits of Semantic Web Technologies (SWT) for managing, sharing, and (re-)using of research data are demonstrated in implementations in the field of Materials Science and Engineering (MSE). However, a compilation and classification are needed to fully recognize the scattered published works with its unique added values. Here, the primary use of SWT at the interface with MSE is identified using specifically created categories. This overview highlights promising opportunities for the application of SWT to MSE, such as enhancing the quality of experimental processes, enriching data with contextual information in knowledge graphs, or using ontologies to perform specific queries on semantically structured data. While interdisciplinary work between the two fields is still in its early stages, a great need is identified to facilitate access for nonexperts and develop and provide user-friendly tools and workflows. The full potential of SWT can best be achieved in the long term by the broad acceptance and active participation of the MSE community. In perspective, these technological solutions will advance the field of MSE by making data FAIR. Data-driven approaches will benefit from these data structures and their connections to catalyze knowledge generation in MSE.
The complex effects of nanoparticles on a thermosetting material based on an anhydride cured DGEBA/Boehmite nanocomposite with different particle concentrations is considered. A combination of X-ray scattering, calorimetry, including fast scanning calorimetry as well as temperature modulated calorimetry and dielectric spectroscopy, was employed to study the structure, the vitrification kinetics and the molecular dynamics of the nanocomposites. For the first time in the literature for an epoxy-based composite a detailed analysis of the X-ray data was carried out. Moreover, the unfilled polymer was found to be intrinsically heterogeneous, showing regions with different crosslinking density, indicated by two separate dynamic glass transitions. The glass transition temperature decreases with increasing nanoparticle concentration, resulting from a change in the crosslinking density. Moreover, on the one hand, for nanocomposites the incorporation of nanofiller increased the number of mobile segments for low nanoparticle concentrations, due to the altered crosslinking density. On the other hand, for higher loading degrees the number of mobile segments decreased, resulting from the formation of an immobilized interphase (RAF). The simultaneous mobilization and immobilization of the segmental dynamics cannot be separated unambiguously. Taking the sample with highest number of mobile segments as reference state it was possible to estimate the amount of RAF.
Ratiometric green–red fluorescent nanosensors for fluorometrically monitoring pH in the acidic range were designed from 80 nm-sized polystyrene (PS) and silica (SiO2) nanoparticles (NPs), red emissive reference dyes, and a green emissive naphthalimide pH probe, analytically and spectroscopically characterized, and compared regarding their sensing performance in aqueous dispersion and in cellular uptake studies. Preparation of these optical probes, which are excitable by 405 nm laser or LED light sources, involved the encapsulation of the pH-inert red-fuorescent dye Nile Red (NR) in the core of self-made carboxylated PSNPs by a simple swelling procedure and the fabrication of rhodamine B (RhB)-stained SiO2-NPs from a silane derivative of pH-insensitive RhB. Subsequently, the custom-made naphthalimide pH probe, that utilizes a protonation-controlled photoinduced electron transfer process, was covalently attached to the carboxylic acid groups at the surface of both types of NPs. Fluorescence microscopy studies with the molecular and nanoscale optical probes and A549 lung cancer cells confirmed the cellular uptake of all probes and their penetration into acidic cell compartments, i.e., the lysosomes, indicated by the switching ON of the green naphthalimide fluorescence. This underlines their suitability for intracellular pH sensing, with the SiO2-based nanosensor revealing the best performance regarding uptake speed and stability.
In this study, we compare analytical methods for PFAS determination–target analysis, non-target screening (NTS), direct total oxidizable precursor assay (dTOPA) and extractable organically bound fluorine (EOF). Therefore, suspended particulate matter (SPM) samples from German rivers at different locations in time series from2005 to 2020 were analyzed to investigate temporal and spatially resolved trends. In this study 3 PFAS mass balances approaches were utilized: (i) PFAA target vs. PFAS dTOPA, (ii) PFAS target vs. EOF and (iii) PFAS target vs. PFAS dTOPA vs. organofluorines NTS vs. EOF. Mass balance approach (i) revealed high proportions of precursor substances in SPM samples. For the time resolved analysis an increase from 94% (2005) to 97% in 2019 was observable. Also for the spatial resolved analysis precursor proportions were high with >84% at all sampling sites. Mass balance approach (ii) showed that the unidentified EOF (uEOF) fraction increased over time from82% (2005) to 99% (2019). Furthermore, along the river courses the uEOF increased. In the combined mass balance approach (iii) using 4 different analytical approaches EOF fractions were further unraveled. The EOF pattern was fully explainable at the sampling sites at Saar and Elbe rivers. For the time resolved analysis, an increased proportion of the EOF was now explainable. However, still 27% of the EOF for the time resolved analysis and 25% of the EOF for the spatial resolved analysis remained unknown. Therefore, in a complementary approach, both the EOF and dTOPA reveal unknown gaps in the PFAS mass balance and are valuable contributions to PFAS risk assessment. Further research is needed to identify organofluorines summarized in the EOF parameter.
Wood-based composites hold the promise of sustainable construction. Understanding the influence on wood cellular microstructure in the macroscopic mechanical behavior is key for engineering highperformance composites. In this work, we report a novel Individual Cell Tracking (ICT) approach for in-situ quantification of nanometer-scale deformations of individual wood cells during mechanical loading of macroscopic millimeter-scale wood samples. Softwood samples containing > 104 cells were subjected to controlled radial tensile and longitudinal compressive load in a synchrotron radiation micro-computed tomography (SRμCT) setup. Tracheid and wood ray cells were automatically segmented, and their geometric variations were tracked during load. Finally, interactions between microstructure deformations (lumen geometry, cell wall thickness), cellular arrangement (annual growth rings, anisotropy, wood ray presence) with the macroscopic deformation response were investigated. The results provide cellular insight into macroscopic relations, such as anisotropic Poisson effects, and allow direct observation of previously suspected wood ray reinforcing effects.
The method is also appropriate for investigation of non-linear deformation effects, such as buckling and deformation recovery after failure, and gives insight into less studied aspects, such as changes in lumen diameter and cell wall thickness during uniaxial load. ICT provides an experimental tool for direct validation of hierarchical mechanical models on real biological composites.
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.
We present a workflow for obtaining fully trained artificial neural networks that can perform automatic particle segmentations of agglomerated, non-spherical nanoparticles from scanning electron microscopy images “from scratch”, without the need for large training data sets of manually annotated images. The whole process only requires about 15 minutes of hands-on time by a user and can typically be finished within less than 12 hours when training on a single graphics card (GPU). After training, SEM image analysis can be carried out by the artificial neural network within seconds. This is achieved by using unsupervised learning for most of the training dataset generation, making heavy use of generative adversarial networks and especially unpaired image-to-image translation via cycle-consistent adversarial networks. We compare the segmentation masks obtained with our suggested workflow qualitatively and quantitatively to state-of-the-art methods using various metrics. Finally, we used the segmentation masks for automatically extracting particle size distributions from the SEM images of TiO2 particles, which were in excellent agreement with particle size distributions obtained manually but could be obtained in a fraction of the time.
The corner echo is a well-known effect in ultrasonic testing, which allows detection of surface breaking cracks with predominantly perpendicular orientation to the surface as, for example, corrosion cracks in metal pipes or shafts. This echo is formed by two planes, the surface of the crack and the surface which the crack breaks. It can also be classified as a half-skip method, since a reflection of the pulse occurs on the backwall before the reflection at the defect takes place. In combination with the diffraction from the crack tip, the corner echo also allows crack sizing. As shown in this paper, the corner reflection can be used in civil engineering for nondestructive inspection of concrete. Commercially available low frequency ultrasonic arrays with dry point contact sources generate SH transversal waves with sufficient divergence of the sound field in order to detect corner reflections. Ultrasonic line-scans and area-scans were acquired with a linear array on flat concrete specimens, and the data were reconstructed by the Synthetic aperture focusing technique. If the angles and the area of reconstruction are chosen accordingly, the corner echo reflection can be distinguished from other ultrasonic information. The corner echo can thus be used as a method for deciding whether a crack is a partial-depth crack or a full-depth crack and thus for obtaining a statement about crack depth. This paper presents corresponding experimental results obtained on concrete specimens with artificial test defects and cracks induced under controlled conditions.
The rational design of next generation molecular and nanoscale reporters and the comparison of different emitter classes require the determination of the fluorometric key performance parameter fluorescence quantum yield (Φf), i.e., the number of emitted photons per number of absorbed photons. Main prerequisites for reliable Φf measurements, which are for transparent luminophore solutions commonly done relative to a reference, i.e., a fluorescence quantum yield standard of known Φf, are reliable and validated instrument calibration procedures to consider wavelength-, polarization-, and time-dependent instrument specific signal contributions, and sufficiently well characterized fluorescence quantum yield standards. As the standard’s Φf value directly contributes to the calculation of the sample’s Φf, its accuracy presents one of the main sources of uncertainty of relative Φf measurements. To close this gap, we developed a first set of 12 fluorescence quantum yield standards, which absorb and emit in the wavelength region of 330−1000 nm and absolutely determined their Φf values with two independently calibrated integrating sphere setups.
Criteria for standard selection and the configuration of these novel fluorescence reference materials are given, and the certification procedure is presented including homogeneity and stability studies and the calculation of complete uncertainty budgets for the certified Φf values. The ultimate goal is to provide the community of fluorescence users with available reference materials as a basis for an improved comparability and reliability of quantum yield data since the measurement of this spectroscopic key property is an essential part of the characterization of any new emitter.
Laser powder bed fusion is one of the most promising additive manufacturing techniques for printing complex-shaped metal components. However, the formation of subsurface porosity poses a significant risk to the service lifetime of the printed parts. In-situ monitoring offers the possibility to detect porosity already during manufacturing. Thereby, process feedback control or a manual process interruption to cut financial losses is enabled.
Short-wave infrared thermography can monitor the thermal history of manufactured parts which is closely connected to the probability of porosity formation. Artificial intelligence methods are increasingly used for porosity prediction from the obtained large amounts of complex monitoring data. In this study, we aim to identify the potential and the challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring.
Therefore, the porosity prediction task is studied in detail using an exemplary dataset from the manufacturing of two Haynes282 cuboid components. Our trained 1D convolutional neural network model shows high performance (R² score of 0.90) for the prediction of local porosity in discrete sub-volumes with dimensions of (700 x 700 x 40) μm³.
It could be demonstrated that the regressor correctly predicts layer-wise porosity changes but presumably has limited capability to predict differences in local porosity. Furthermore, there is a need to study the significance of the used thermogram feature inputs to streamline the model and to adjust the monitoring hardware. Moreover, we identified multiple sources of data uncertainty resulting from the in-situ monitoring setup, the registration with the ground truth X-ray-computed tomography data and the used pre-processing workflow that might influence the model’s performance detrimentally.
Quaternary ammonium compounds (QACs) are widely used as active agents in disinfectants, antiseptics, and preservatives. Despite being in use since the 1940s, there remain multiple open questions regarding their detailed mode-of-action and the mechanisms, including phenotypic heterogeneity, that can make bacteria less susceptible to QACs. To facilitate studies on resistance mechanisms towards QACs, we synthesized a fluorescent quaternary ammonium compound, namely N-dodecyl-N,N-dimethyl-[2-[(4-nitro-2,1,3-benzoxadiazol-7-yl)amino]ethyl]azanium-iodide (NBD-DDA). NBD-DDA is readily detected by flow cytometry and fluorescence microscopy with standard GFP/FITC-settings, making it suitable for molecular and single-cell studies. As a proof-of-concept, NBD-DDA was then used to investigate resistance mechanisms which can be heterogeneous among individual bacterial cells. Our results reveal that the antimicrobial activity of NBD-DDA against Escherichia coli, Staphylococcus aureus and Pseudomonas aeruginosa is comparable to that of benzalkonium chloride (BAC), a widely used QAC, and benzyl-dimethyl-dodecylammonium chloride (BAC12), a mono-constituent BAC with alkyl-chain length of 12 and high structural similarity to NBD-DDA. Characteristic time-kill kinetics and increased tolerance of a BAC tolerant E. coli strain against NBD-DDA suggest that the mode of action of NBD-DDA is similar to that of BAC. As revealed by confocal laser scanning microscopy (CLSM), NBD-DDA is preferentially localized to the cell envelope of E. coli, which is a primary target of BAC and other QACs. Leveraging these findings and NBD-DDA‘s fluorescent properties, we show that reduced cellular accumulation is responsible for the evolved BAC tolerance in the BAC tolerant E. coli strain and that NBD-DDA is subject to efflux mediated by TolC. Overall, NBD-DDA’s antimicrobial activity, its fluorescent properties, and its ease of detection render it a powerful tool to study resistance mechanisms of QACs in bacteria and highlight its potential to gain detailed insights into its mode-of-action.
An automated and straightforward detection and data treatment strategy for the determination of the protein relative concentration in individual human cells by single cell–inductively coupled plasma–time-of-flight mass spectrometry (sc-ICP-ToF-MS) is proposed. Metal nanocluster (NC)-labeled specific antibodies for the target proteins were employed, and ruthenium red (RR) staining, which binds to the cells surface, was used to determine the number of cell events as well as to evaluate the relative volume of the cells. As a proof of concept, the expression of hepcidin, metallothionein-2, and ferroportin employing specific antibodies labeled with IrNCs, PtNCs, and AuNCs, respectively, was investigated by sc-ICP-ToF-MS in human ARPE-19 cells. Taking into account that ARPE-19 cells are spherical in suspension and RR binds to the surface of the cells, the Ru intensity was related to the cell volume (i.e., the cell volume is directly proportional to (Ru intensity)3/2), making it possible to determine not only the mass of the target proteins in each individual cell but also the relative concentration. The proposed approach is of particular interest in comparing cell cultures subjected to different supplementations. ARPE-19 cell cultures under two stress conditions were compared: a hyperglycemic model and an oxidative stress model. The comparison of the control with treated cells shows not only the mass of analyzed species but also the relative changes in the cell volume and concentration of target proteins, clearly allowing the identification of subpopulations under the respective treatment.
Contamination of natural bodies of water or soil with oils and lubricants (or generally, hydrocarbon derivatives such as petrol, fuels, and others) is a commonly found phenomenon around the world due to the extensive production, transfer, and use of fossil fuels. In this work, we develop a simple system for the on-field detection of total petroleum hydrocarbons (TPHs) in water and soil. The test is based on the measurement of the fluorescence signal emitted by the molecular rotor 2-[ethyl[4-[2-(4-nitrophenyl)ethenyl]phenyl]amino]ethanol (4-DNS-OH). This dye is embedded in a hydrophobic polymeric matrix (polyvinylidene fluoride), avoiding interactions with water and providing a robust support for use in a test strip fashion. Together with the strips, an embedded optical system was designed for fluorescence signal read-out, featuring a Bluetooth low-energy connection to a commercial tablet device for data processing and analysis. This system works for the detection and quantification of TPHs in water and soil through a simple extraction protocol using a cycloalkane solvent with a limit of detection of 6 ppm. Assays in surface and sea waters were conclusive, proving the feasibility of the method for in-the-field operation.
In this work, molecular imprinting was combined with direct fluorescence detection of the pesticide Glyphosate (GPS). Firstly, the solubility of highly polar GPS in organic solvents was improved by using lipophilic tetrabutylammonium (TBA+) and tetrahexylammonium (THA+) counterions. Secondly, to achieve fluorescence detection, a fluorescent crosslinker containing urea-binding motifs was used as a probe for GPS-TBA and GPS-THA salts in chloroform, generating stable complexes through hydrogen bond formation. The GPS/fluorescent dye complexes were imprinted into 2–3 nm fluorescent molecularly imprinted polymer (MIP) shells on the surface of sub-micron silica particles using chloroform as porogen. Thus, the MIP binding behavior could be easily evaluated by fluorescence titrations in suspension to monitor the spectral changes upon addition of the GPS analytes. While MIPs prepared with GPS-TBA and GPS-THA both displayed satisfactory imprinting following titration with the corresponding analytes in chloroform, GPS-THA MIPs displayed better selectivity against competing molecules. Moreover, the THA+ counterion was found to be a more powerful phase transfer agent than TBA+ in a biphasic assay, enabling the direct fluorescence detection and quantification of GPS in water. A limit of detection of 1.45 μM and a linear range of 5–55 μM were obtained, which match well with WHO guidelines for the acceptable daily intake of GPS in water (5.32 μM).
Small-angle X-ray scattering (SAXS) can be used for structural determination of biological macromolecules and polymers in their native states (e.g. liquid phase). This means that the structural changes of (bio-)polymers, such as proteins and DNA, can be monitored in situ to understand their sensitivity to changes in chemical environments. In an attempt to improve the reliability of such experiments, the reduction of radiation damage occurring from exposure to X-rays is required. One such method, is to use scavenger molecules to protect macromolecules against radicals produced during radiation exposure, such as reactive oxygen species (ROS). In this study we investigate the feasibility of applying the compatible solute, osmolyte and radiation protector Ectoine (THP(B)), as a scavenger molecule during SAXS measurements of the single-stranded DNA-binding protein Gene-V Protein (G5P/GVP). In this case, we monitor the radiation induced changes of G5P during bio-SAXS measurments and the resulting microscopic energy-damage relation was determined from microdosimetric calculations by Monte-Carlo based particle scattering simulations with TOPAS/Geant4 and a custom target-model. This resulted in a median-lethal energy deposit of pure G5P at 4 mg mL−1 of E1/2 = 7 ± 5 eV, whereas a threefold increase of energy-deposit was needed under the presence of Ectoine to reach the same level of damage. This indicates that Ectoine increases the possible exposure time before radiation-damage to G5P is observed. Furthermore, the dominant type of damage shifted from aggregation in pure solutions towards a fragmentation for solutions containing Ectoine as a cosolute. These results are interpreted in terms of indirect radiation damage by reactive secondary species, as well as post-irradiation effects, related to preferential-exclusion of the cosolute from the protein surface. Hence, Ectoine is shown to provide a non-disturbing way to improve structure-determination of proteins via bio-SAXS in future studies.