Chemie und Prozesstechnik
Filtern
Dokumenttyp
- Zeitschriftenartikel (1173) (entfernen)
Sprache
- Englisch (1173) (entfernen)
Schlagworte
- Fluorescence (62)
- Quantum yield (49)
- Nanoparticles (39)
- Mechanochemistry (36)
- Quality assurance (31)
- Mass spectrometry (30)
- SAXS (30)
- Sensor (30)
- Imaging (29)
- XPS (29)
Organisationseinheit der BAM
- 1 Analytische Chemie; Referenzmaterialien (495)
- 6 Materialchemie (393)
- 8 Zerstörungsfreie Prüfung (242)
- 6.3 Strukturanalytik (170)
- 6.1 Oberflächen- und Dünnschichtanalyse (137)
- 1.1 Anorganische Spurenanalytik (119)
- 1.2 Biophotonik (104)
- 1.7 Organische Spuren- und Lebensmittelanalytik (77)
- 8.2 Zerstörungsfreie Prüfmethoden für das Bauwesen (70)
- 8.0 Abteilungsleitung und andere (66)
Paper des Monats
- ja (26)
The statistical tool eCerto was developed for the evaluation of measurement data to assign property values and associated uncertainties of reference materials. The analysis is based on collaborative studies of expert laboratories and was implemented using the R software environment. Emphasis was put on comparability of eCerto with SoftCRM, a statistical tool based on the certification strategy of the former Community Bureau of Reference. Additionally, special attention was directed towards easy usability from data collection through processing, archiving, and reporting. While the effects of outlier removal can be flexibly explored, eCerto always retains the original data set and any manipulation such as outlier removal is (graphically and tabularly) documented adequately in the report. As a major reference materials producer, the Bundesanstalt für Materialforschung und -prüfung (BAM) developed and will maintain a tool to meet the needs of modern data processing, documentation requirements, and emerging fields of RM activity. The main features of eCerto are discussed using previously certified reference materials.
Human factors (HFs) are a frequently mentioned topic when talking about the reliability of non-destructive testing (NDT). However, probability of detection (POD), the commonly used measure of NDT reliability, only looks at the technical capability of an NDT system to detect a defect.
After several decades of research on the influence of HFs on NDT reliability, there is still no commonly accepted approach to rendering HFs visible in reliability assessment. This paper provides an overview of possible quantitative and qualitative methods for integrating HFs into the reliability assessment. It is concluded that reliability assessment is best carried out using both quantifiable and non-quantifiable approaches to HFs.
Here, we elucidate nonclassical multistep crystallization pathways of transition metal phosphates from aqueous solutions. We followed precipitation processes of M-struvites, NH4MPO4·6H2O, and M-phosphate octahydrates, M3(PO4)2·8H2O, where M = Ni, Co, or NixCo1–x, by using in situ scattering and spectroscopy-based techniques, supported by elemental mass spectrometry analyses and advanced electron microscopy. Ni and Co phosphates crystallize via intermediate colloidal amorphous nanophases, which change their complex structures while agglomerating, condensing, and densifying throughout the extended reaction times. We reconstructed the three-dimensional morphology of these precursors by employing cryo-electron tomography (cryo-ET). We found that the complex interplay between metastable amorphous colloids and protocrystalline units determines the reaction pathways. Ultimately, the same crystalline structure, such as struvite, is formed. However, the multistep process stages vary in complexity and can last from a few minutes to several hours depending on the selected transition metal(s), their concentration, and the Ni/Co ratio.
The digitalization of quality control processes and the underlying data infrastructures for safety relevant components, such as hydrogen pressure vessels, plays a significant role in the transition towards Industry 4.0. In the current safety regulations for hydrogen pressure vessels, there is no established concept for structural health monitoring. The development of a reliable structural health monitoring methodology for monitoring the structural integrity of pressure vessels enables a fast-forward transition from personnel- and costintensive recurring inspections, a.k.a. periodic maintenance, to predictive maintenance. In the work presented; we investigated the application of ultrasonic guided wave propagation to monitor and assess the condition of Type IV composite overwrapped pressure vessel (COPV). A sensor network of fifteen piezo-electric wafers is placed on the carbon fibre reinforced composite cylinder. Five different artificial damage configurations are created by gluing two different weight blocks on three different locations. The database containing measured guided wave data sets is enriched by two different boundary conditions. We utilized an open-source software, openBIS labnotebook, to store and analyse experimental datasets. The guided wave ultrasonic signals were investigated and analysed by using commonly used ultrasonic features (e.g., amplitude, frequency, time of flight) as well as non-traditional time-series features (kurtosis, skewness, variance). The features were used to calculate damage index and the detection performance for the results has been evaluated. The results suggest that both traditional and non-traditional features assume significant importance in artificial damage detection. The future works will additionally involve the impacts of operational conditions, such as periodic pressure variations temperature loadings as well as material degradations.
The application of composite overwrapped pressure vessels (COPV) to store hydrogen and other compressed gases, especially when operating at high pressures, imposed the need for an innovative and reliable approach to ensure the safe operation of the system. Continuous structural health monitoring (SHM) based on ultrasonic guided waves (GWs) is a promising approach due to the ability of the wave to propagate for long distances and go around complex structures, moreover the high sensitivity to various failure modes such as delamination, matrix cracking and debonding. In this study, we scrutinize the behavior of (GWs) within the COPV using a network of PZT elements that are used for excitation and sensing. A laser doppler vibrometer (LDV) was also used to scan the surface of the vessel in various directions. L(0,1) and L(0,2) were observed in the captured signal. The L(0, 2) appeared to be a dominant mode in the COPV and was capable of propagating along the entire length and maintaining a good signal-to-noise ratio. The L(0,2) mode maintained the same phase velocity when it is captured at various excitation angles (0, 45, and 90 degrees). The reduced effect of the orthotropy of the materials on the propagating waves is an important result as it will reduce the complexity in data processing when performing damage identification.
It is shown that preconditioning of experimental X‐ray computed tomography (XCT) data is critical to achieve high‐precision segmentation scores. The challenging experimental XCT datasets and deep convolutional neural networks (DCNNs) are used that are trained with low‐resemblance synthetic XCT data. The material used is a 6‐phase Al–Si metal matrix composite‐reinforced with ceramic fibers and particles. To achieve generalization, in our past studies, specific data augmentation techniques were proposed for the synthetic XCT training data. In addition, two toolsets are devised: (1) special 3D DCNN architecture (3D Triple_UNet), slicing the experimental XCT data from multiple views (MultiView Forwarding), the i.S.Sy.Da.T.A. iterative segmentation algorithm, and (2) nonlocal means (NLM) conditioning (filtering) for the experimental XCT data. This results in good segmentation Dice scores across all phases compared to more standard approaches (i.e., standard UNet architecture, single view slicing, standard single training, and NLM conditioning). Herein, the NLM filter is replaced with the deep conditioning framework BAM SynthCOND introduced in a previous publication, which can be trained with synthetic XCT data. This leads to a significant segmentation precision increase for all phases. The proposed methods are potentially applicable to other materials and imaging techniques.
The applications of composite overwrapped pressure vessels (COPVs) in extreme conditions, such as storing hydrogen gases at very high pressure, impose new requirements related to the system's integrity and safety. The development of a structural health monitoring (SHM) system that allows for continuous monitoring of the COPVs provides rich information about the structural integrity of the component. Furthermore, the collected data can be used for different purposes such as increasing the periodic inspection intervals, providing a remaining lifetime prognosis, and also ensuring optimal operating conditions. Ultimately this information can be complementary to the development of the envisioned digital twin of the monitored COPVs. Guided waves (GWs) are preferred to be used in continuous SHM given their ability to travel in complex structures for long distances. However, obtained GW signals are complex and require advanced processing techniques. Machine learning (ML) is increasingly utilized as the main part of the processing pipeline to automatically detect anomalies in the system's integrity. Hence, in this study, we are scrutinizing the potential of using ML to provide continuous monitoring of COPVs based on ultrasonic GW data. Data is collected from a network of sensors consisting of fifteen Piezoelectric (PZT) wafers that were surface mounted on the COPV. Two ML algorithms are used in the automated evaluation procedure (i) a long short-term memory (LSTM) autoencoder for anomaly detection (defects/impact), and (ii) a convolutional neural network (CNN) model for feature extraction and classification of the artificial damage sizes and locations. Additional data augmentation steps are introduced such as modification and addition of random noise to original signals to enhance the model's robustness to uncertainties. Overall, it was shown that the ML algorithms used were able to detect and classify the simulated damage with high accuracy.
Demonstrating competency and equivalence for the measurement capacity of contaminants and nutrients in primary foodstuffs is a priority of the OAWG 10-year strategy for Track A core comparisons. Such measurements have posed significant challenges for reference material producers and calibration service providers. This key comparison (KC), under the topic of “non- polar analyte in high carbohydrate food matrix: trans-Zearalenone (trans-ZEN) in maize powder” , was a sector of the model system selected to align with this class within the OAWG strategy. Evidence of successful participation in formal, relevant international comparisons is needed to demonstrate the Calibration and Measurement Capabilities (CMCs) of national metrology institutes (NMIs) and designated institutes (DIs).
17 NMIs and DIs participated in the Track A KC CCQM- 168 “non-polar analyte in high carbohydrate food matrix: trans-ZEN in maize powder” . Participants were requested to evaluate the mass fraction (μg/kg) of trans-ZEN in maize powder material. Methods like liquid-liquid extraction and SPE were applied in the pre-treatment, and HPLC-MS/MS and HPLC-FLD were used for detection by the participants. The mass fractions for trans-ZEN were in the range of (91.8 to 169) μg/kg with standard uncertainties of (1.5 to 24.7) μg/kg, and corresponding relative standard uncertainties from 1.5% to 14.6%. Two labs, INTI and BAM were excluded from the KCRV evaluation. INTI result was identified as an outlier and confirmed their method had insufficient specificity. For BAM the calibration approach they used does not meet the CIPM traceability requirements. The other 15 labs included in the calculation of the consensus KCRV all agreed within their standard uncertainties. Hierarchical Bayes was used as estimators in calculating KCRV and standard uncertainty.
Successful participation in CCQM-K168 demonstrates the measurement capabilities in determining mass fraction of organic compounds, with molecular mass of 100 g/mol to 500 g/mol, having low polarity pKow < -2, in mass fraction range from 1 μg/kg to 1000 μg/kg in a high carbohydrate food matrix.
Trace element (TE) analysis of pyrite via LA-ICP-MS can be used to reconstruct the conditions of pyrite formation in complex mineral systems. The Carpentaria province in northern Australia is host to some of the world’s highest value Zn-Pb (+Ag, Cu) deposits. The genesis of many of these deposits is controversial, with competing models of single-vs. multi-stage ore formation. In this study, LA-ICP-MS data of paragenetically constrained pyrite from the George Fisher Zn-Pb-Ag deposit has been analysed to investigate the chemistry of different stages of ore formation. Pyrite from correlative unmineralized host rocks has also been analysed to investigate evidence of distal hydrothermal anomalism. All LA-ICP-MS data have been statistically evaluated (principal component analysis) and interpreted together with whole rock lithogeochemical data of the same samples. Pre-ore diagenetic pyrite is compositionally similar to other Proterozoic diagenetic pyrite, with some evidence of minor hydrothermal anomalism that with further analysis could help define distal alteration. Pyrite from the different ore stages are compositionally distinct, consistent with a multi-stage system. Ore stage 1 pyrite exceeds background contents of Co, Cu, Zn, As, Ag, Sb, Tl, and Pb and has elevated Co/Ni ratios, whereas only Ni and Co are above background abundances in ore stage 2 and 3 pyrite, of which only ore stage 3 pyrite has high Co/Ni ratios. Ore stage 1 pyrite has a similar composition to hydrothermal pyrite in the undeformed northern Carpentaria CD-type deposits and was likely syn-diagenesis. Ore stage 2 was syn-deformation, and resulted in replacement and recrystallization of pre-existing pyrite, and the expulsion of incompatible TEs. Ore stage 3 formed via a later Cu-Zn-Pb mineralizing event that resulted in a new geochemically distinct generation of Co-rich pyrite. Overall, this study demonstrates the value of paragenetically-constrained pyrite TE data for refining genetic models in complex sediment hosted mineral systems.
AbstractThe minor and trace element composition of minerals provides critical insights into a variety of geological processes. Multi-element mapping by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) is an important technique applied for this purpose and although the method is rapidly advancing, there remains a fundamental compromise between spatial resolution, detection limit, and experiment duration when using sequential mass analyzers. To address the limitation of limited analyte selection for high spatial resolution maps imposed by the sequential nature of typical quadrupole (Q)-ICP-MS, we tested the Aerosol Rapid Introduction System (ARIS) for repeat mapping of the same area. The ARIS is a high-speed transfer tubing system that reduces aerosol washout times, permitting resolution of individual pulses at 40–60 Hz. Here, the ARIS was tested not for pulse resolution but with novel operating conditions optimized to perform fast, high spatial resolution mapping of minor and trace element distribution in pyrite and marcasite. For this purpose, ablation was conducted with a 5 µm beam aperture, a repetition rate of 50 Hz, and a continuous stage scan speed of 40 µm s−1. For each LA-Q-ICP-MS map, data were acquired for six elements with an acquisition time of 20 ms per element. This deliberately reduced the individual pulse resolution of the ARIS but instead exploited the spatial resolution and sensitivity gains afforded by the high-laser repetition rate combined with efficient aerosol transfer. The new method successfully mapped trace elements at single to double-digit parts per million levels, and the maps reveal fine-scale zoning of trace elements with an effective x and y resolution of 5 µm, while white light interferometry showed that for each experiment, only ca. 1 µm of the sample was removed. Repeated mapping of the same area showed excellent correspondence not only between element concentrations in successive experiments but also in the shape, dimension, and location of regions of interest defined by concentration criteria. The very good repeatability of the elemental maps indicates that for studies requiring more analytes, successive mapping of additional elements is possible. By contrast with conventional very small spot (i.e., 5 µm) analysis, fast repetition rate and stage scan speed mapping avoids down-hole fractionation effects and minimizes accidental analysis of buried invisible inclusions. Compared to conventional LA-ICP-MS mapping, the method reduces the experiment time by 4–8 times.
Molten sulfur is found in various subaerial volcanoes. However, limited records of the pools and flows of molten sulfur have been reported: therefore, questions remain regarding the physicochemical processes behind this phenomenon. A suite of new sulfur flows, some of which active, was identified at the Lastarria volcano (northern Chile) and studied using satellite imagery, in situ probing, and temperature and video recording. This finding provides a unique opportunity to better understand the emplacement mechanisms and mineral and chemical compositions of molten sulfur, in addition to gaining insight into its origin. Molten sulfur presented temperatures of 124–158°C, with the most prolonged sulfur flow reaching 12 m from the source. Photogrammetric tools permitted the identification of levees and channel structures, with an estimated average flow speed of 0.069 m/s. Field measurements yielded a total volume of 1.45 ± 0.29 m3 of sulfur (equivalent to ∼2.07 tons) mobilized during the January 2019 event for at least 408 min. Solidified sulfur was composed of native sulfur with minor galena and arsenic- and iodine-bearing minerals. Trace element analysis indicated substantial enrichment of Bi, Sb, Sn, Cd, as well as a very high concentration of As (&gt;40.000 ppm). The January 2019 molten sulfur manifestations in Lastarria appear to be more enriched in As compared to the worldwide known volcanoes with molten sulfur records, such as the Shiretoko-Iozan and Poás volcanoes. Furthermore, their rheological properties suggest that the “time of activity” in events such as this could be underestimated as flows in Lastarria have moved significantly slower than previously thought. The origin of molten sulfur is ascribed to the favorable S-rich chemistry of fumarolic gases and changes in host rock permeability (fracture opening). Molten sulfur in Lastarria correlates with a peak in activity characterized by high emissions of SO2 and other acid species, such as HF and HCl, in addition to ground deformation. Consequently, molten sulfur was framed within a period of volcanic unrest in Lastarria, triggered by changes in the magmatic-hydrothermal system. The appearance of molten sulfur is related to physicochemical perturbations inside the volcanic system and is perhaps a precursor of eruptive activity, as observed in the Poás and Turrialba volcanoes.
High polarity analyte(s) in aqueous media: determination of L-PFOA and L-PFOS in ground water
(2022)
The CCQM-K156 comparison was coordinated by TUBITAK UME on behalf of the Organic Analysis Working Group (OAWG) of the Comité Consultatif pour la Quantité de Matière (CCQM) for National Measurement Institutes (NMIs) and Designated Institutes (DIs) which provide measurement services in organic analysis under the 'Comité International des Poids et Mesures' Mutual Recognition Arrangement (CIPM MRA).
Perfluoro alkyl substances (PFAS) such as PFOS and PFOA have been used in numerous industrial applications and products. Because of their high stability and resistance to biodegradation, atmospheric photooxidation, direct photolysis and hydrolysis, they are extremely persistent in the environment. The European Union (EU) Water Framework Directive lists PFOS as a priority hazardous substance that poses a significant risk to the aquatic environment. The use of PFOS-containing Aqueous Film-Forming Foams (AFFFs) has been banned since June 2011 in the EU. As relatively water-soluble, effectively non-degradable compounds, PFOS and PFOA migrate to ground water. They are not removed in the conventional drinking water treatment, and therefore cause health risks in polluted areas. The EU Drinking Water Directive and the European Commission has proposed a limit value of 100 ng/L for the sum of 20 PFAS, including PFOS and PFOA.
This study provides the means for assessing measurement capabilities for determination of high polarity measurands in a procedure that requires extraction, clean-up, analytical separation and detection. Successful participation in CCQM-K156 demonstrates measurement capabilities in determining mass fraction of organic compounds, with a molecular mass of 200 g/mol to 700 g/mol, having high polarity pKow -2, in a mass fraction range from 0.5 ng/kg to 500 ng/kg in aqueous media.
Nine NMIs and DIs participated in the CCQM-K156 key comparison. Seven institutes reported their results. SPE was applied in the sample pre-treatment and LC-MS was applied for detection. All participating laboratories applied isotope dilution mass spectrometry (IDMS) techniques for quantification. Participants established the metrological traceability of their results using certified reference materials (CRMs) from NMIs with stated traceability; where commercially available high purity materials were used the purity was determined in-house. The CCQM-K156 results for L-PFOA and L-PFOS range from 2.75 ng/kg to 5.50 ng/kg with a % RSD of 19.5 % for L-PFOA and from 2.04 ng/kg to 4.45 ng/kg with a % RSD of 21.3 % for L-PFOS. The KCRV was assigned using a Hierarchical Bayesian Random Effects Model (HB REM) estimator from the values reported by six of the participants. One participant result of L-PFOS and one result of L-PFOA were excluded from the KCRV for technical reasons. The KCRV was 4.9 ng/kg ± 0.4 ng/kg for L-PFOA and 3.8 ng/kg ± 0.4 ng/kg for L-PFOS. The six institutes that were included in the assignment of consensus KCRV all agreed within their standard uncertainties.
To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/.
The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
AbstractIn this study, we present a screening method based on molecular absorption spectrometry to study PFAS uptake and fate in plants. To evaluate the suitability of this method we analyzed plant extracts with molecular absorption spectrometry (MAS) as well as liquid chromatography–tandem mass spectrometry (LC–MS/MS) for mass balance studies (w(F)). French bean plants (Phaseolus vulgaris) were grown on soil spiked using eight PFAS substances that vary in chain length and functional group composition. Specifically, these include three short-chained (C4–C5), five long-chained (C7–C10) carboxylic acids, one sulfonic acid and one sulfonic amide moieties. To investigate substance-specific PFAS uptake systematically, PFAS were spiked as single substance spike. Additionally, we studied one mixture of the investigated substances in equal proportions regarding w(F) and four PFAS mixtures of unknown composition. After 6 weeks, the plants were separated into four compartments. We analyzed the four compartments as well as the soil for extractable organically bound fluorine (EOF) by high resolution-continuum source-graphite furnace-molecular absorption spectrometry (HR-CS-GFMAS) as well as for sum of ten target-PFAS by LC–MS/MS. All three short-chained PFAS perfluorobutanoic acid (PFBA), perfluorobutanoic sulfonic acid (PFBS) and perfluoropentanoic acid (PFPeA) were determined in high concentrations mainly in the fruits of the investigated plants while long-chained PFAS perfluorononanoic acid (PFNA) and perfluorodecanoic acid (PFDA) were mainly determined in roots. PFBS was determined in remarkably high concentrations in leaves compartment by both quantification methods. Overall, comprehensive results of single substance spikes were in good agreement for both methods except for a few cases. Hence, two phenomena were identified: for mixed PFAS spikes of unknown composition huge differences between EOF and sum of target PFAS were observed with systematically higher EOF values. Overall, both methods indicate comparable results with MS being more reliable for known PFAS contamination and MAS being more valuable to identify PFAS exposure of unknown composition.
Graphical Abstract
Ergot alkaloids are a group of toxic compounds, formed by fungi on infested grasses. In 2022, the European Commission set into effect maximum levels for the sum of the twelve major ergot alkaloids in multiple foods. To facilitate the laborious and costly individual quantification of the twelve major ergot alkaloids by HPLC–MS/MS or -FLD, we recently reported a sum parameter method (SPM) for ergot alkaloid quantification. Here, derivatization to lysergic acid hydrazide—a derivative of the mutual ergoline backbone in all ergot alkaloids—allowed simplified determination of all ergot alkaloids in flour via HPLC-FLD. For the measurement of more complex matrices like processed foods, we now developed a MS/MS-based SPM. Two internal standards (IS), isotopically labelled at different positions of the molecule, were synthesized and employed in the MS/MS-measurements. Method performance using either the 13CD3-labelled or the 15N2-labelled IS was evaluated on naturally contaminated rye and wheat flour samples as well as on processed food matrices. Employing the 13CD3-labelled IS leads to lower variances and better consistency with the reference data (obtained by the FLD-based SPM) in flour samples compared to the 15N2-labelled IS. The novel method significantly improves the measurement of ergot alkaloids in complex food matrices, due to their increased selectivity and thus lower interferences. Furthermore, the application of isotope labelled IS obviates the need for time-consuming steps like the determination of recovery rate based, matrix specific correction factors as described in the MS/MS-based European standard method for ergot alkaloid quantification (EN 17425).
Gold-based nanoparticles below 2 nm in size are promising as luminescent probes for in vivo bioimaging, owing to their brightness and rapid renal clearance. However, their use as contrast agents in the near-infrared II (NIR-II, 1000–1700 nm) range remains challenging due to their low photoluminescence (PL) quantum yield. To address this, PL enhancement can be achieved by either rigidifying the ligand-shell structure or increasing the size of the ligand shell. In this study, we synthesized ultra-small gold nanoparticles stabilized by co-ligands, namely monothiol and short dithiol molecules. By precisely controlling the amount of reducing agent used during particle preparation, we successfully modulated the physicochemical properties of the co-ligand shell, including its size, composition, and structure. Consequently, we achieved a remarkable 60-fold increase in the absorption cross-section at 990 nm while maintaining the small size of the 1.5-nm metal core. The analytical and optical characterization of our thiol-capped gold nanoparticles indicates that the ligand shell size is governed by the quantity of the reducing agent, which, in turn, impacts the balance between radiative and non-radiative processes, thereby influencing the PL quantum yield.
Fungal pigments such as melanin and carotenoids are distinctive markers of animal and plant pathogenic fungi as well as their environmental relatives. These complex pigments play important roles in pathogenicity and stress tolerance while also being useful as biomarkers. Accordingly, it is important to be able to identify in situ the pigments in black fungi, a group of clinical and environmental importance. In this study, wild-type and genetically modified strains of Knufia petricola A95 and wild fungal cells attached to ancient rock were investigated for their spectroscopic and microscopic Raman features and morphological appearance. Knockout mutants of melanin synthesis genes pks1 (polyketide synthase), sdh1 (scytalone dehydratase), and both pks1 and the carotenoid synthesis gene phd1 (phytoene desaturase) were studied We applied two different Raman microscopes using two lasers, with 633 nm and 488 nm wavelengths. We analyzed and compared Raman spectra between the measured reference substances and the mutant and wild-type strains. In the wild strain WT:A95, the peaks close to melanin peals were found at 1353 cm−1 and 1611 cm−1. There are no characteristic melanin peaks at 1580–1600 cm−1 and around 1350 cm−1 at the spectrum of the Δpks1/Δphd1 mutant and the Δsdh1 mutant. The Δpks1 mutant spectrum has the peaks at the beta-carotene v2 C-C in-plane stretch at 1155 cm−1 and v3 C-CH3 deformation at 1005 cm−1. The peaks of carotenoids and melanin were found in all mutants and the wild strain, except the Δpks1/Δphd1 mutant. Raman spectra allow for discrimination between the various pigments. Hence, interactions between natural fungal melanin, as well as other protective pigments, and complex environmental matrices can be characterized on a range of spatial and temporal scales.
Research on per- and polyfluoroalkyl substances (PFAS) frequently incorporates organofluorine measurements, particularly because they could support a class-based approach to regulation. However, standardized methods for organofluorine analysis in a broad suite of matrices are currently unavailable, including a method for extractable organofluorine (EOF) measured using combustion ion chromatography (CIC). Here, we report the results of an international interlaboratory comparison. Seven laboratories representing academia, government, and the private sector measured paired EOF and PFAS concentrations in groundwater and eel (Anguilla rostrata) from a site contaminated by aqueous film-forming foam. Among all laboratories, targeted PFAS could not explain all EOF in groundwater but accounted for most EOF in eel. EOF results from all laboratories for at least one replicate extract fell within one standard deviation of the interlaboratory mean for groundwater and five out of seven laboratories for eel. PFAS spike mixture recoveries for EOF measurements in groundwater and eel were close to the criterion (±30%) for standardized targeted PFAS methods. Instrumental operation of the CIC such as replicate sample injections was a major source of measurement uncertainty. Blank contamination and incomplete inorganic fluorine removal may introduce additional uncertainties. To elucidate the presence of unknown organofluorine using paired EOF and PFAS measurements, we recommend that analysts carefully consider confounding methodological uncertainties such as differences in precision between measurements, data processing steps such as blank subtraction and replicate analyses, and the relative recoveries of PFAS and other fluorine compounds.
A round-robin study has been carried out to estimate the impact of the human element in small-angle scattering data analysis. Four corrected datasets were provided to participants ready for analysis. All datasets were measured on samples containing spherical scatterers, with two datasets in dilute dispersions and two from powders. Most of the 46 participants correctly identified the number of populations in the dilute dispersions, with half of the population mean entries within 1.5% and half of the population width entries within 40%. Due to the added complexity of the structure factor, far fewer people submitted answers on the powder datasets. For those that did, half of the entries for the means and widths were within 44 and 86%, respectively. This round-robin experiment highlights several causes for the discrepancies, for which solutions are proposed.
Inputs of plastic impurities into the environment via the application of fertilizers are regulated in Germany and the EU by means of ordinances. Robust and fast analytical methods are the basis of legal regulations. Currently, only macro- and large microplastic contents (>1 mm) are measured. Microplastics (1–1,000 µm), are not yet monitored. Thermal analytical methods are suitable for this purpose, which can determine the mass content and can also be operated fully automatically in routine mode. Thermal extraction desorption-gas chromatography/mass spectrometry (TED-GC/MS) allows the identification of polymers and the determination of mass contents in solid samples from natural environments. In accordance with the German or European Commission (EC) Fertiliser Ordinance, composting plants should be monitored for microplastic particles with this method in the future. In this context a compost plant was sampled. At the end of the rotting process, the compost was sieved and separated in a coarse (>1 mm) and a fine fraction (<1 mm). The fine fraction was processed using density separation comparing NaCl and NaI as possible salt alternative and screened for microplastic masses by TED-GC/MS with additional validation and quality assurance experiments. With TED-GC/MS total microplastics mass contents of 1.1–3.0 μg/mg in finished compost could be detected with polyethylene mainly. What differs much to the total mass of plastics in the coarse fraction with up to 60 μg/mg, which were visually searched, identified via ATR-FTIR and gravimetrically weighted.
Covalent organic frameworks (COFs) are a prominent class of organic materials constructed from versatile building blocks via reversible reactions. The quality of imine-linked COFs can be improved by using amine monomers protected with benzophenone forming benzophenone imines. Here, we present a study on substituted benzophenones in COF synthesis via formal transimination. 12 para-substituted N-aryl benzophenone imines, with a range of electron-rich to electron-poor substituents, were prepared and their hydrolysis kinetics were studied spectroscopically. All substituted benzophenone imines can be employed in COF synthesis and lead to COFs with high crystallinity and high porosity. The substituents act innocent to COF formation as the substituted benzophenones are cleaved off. Imines can be tailored to their synthetic demands and utilized in COF formation. This concept can make access to previously unattainable, synthetically complex COF monomers feasible.
Electromagnetic stirring is known to promote material flow, reduce porosity, uniform elements distribution, and refine grain in laser beam welding (LBW), which enhances the applicability of LBW in various industries. In this study, a phase-field model of dendrite growth in AA5754 Al alloy electromagnetic stirring laser beam welding was established. The model considered the thermal electromagnetic Lorentz force resulting from the interaction between the electric field generated by the Seebeck effect and the magnetic field, as well as the temperature gradient and solidification rate of the solidification interface obtained from the computational fluid dynamics electromagnetic stirring LBW model. The variation rules of dendrite growth with different magnetic parameters and effects are analyzed. Comprehensively, the magnetic field promotes the solidification rate, thus promoting interfacial instability and a large magnetic flux density leads to a faster interface instability. The solidification rate as well as the temperature gradient affect the growth rate, and the accelerated growth caused by the so lidification rate with a high frequency and a large magnetic flux density effectively inhibits the slow growth caused by the temperature gradient. The thermal electromagnetic Lorentz force is the main factor for the branch increment at low frequencies, while both thermal electromagnetic Lorentz force and temperature gradient in crease the number of branches at high frequencies. The calculated average branch numbers considering various factors in the stable stage under different magnetic parameters were consistent with the results of the scanning electron microscope tests.
Information about an existing structure can be collected at certain costs to evaluate the reliability and condition as realistically as necessary. This information can be relevant or irrelevant, true or biased, precise or imprecise. The incorporation of relevant and quality-assessed measured information into reliability reassessment offers the chance to extend remaining lifetimes and support decision making about optimal actions or maintenance strategies. This paper shows recent developments in a national research project that aims to produce a guideline on the NDT-based, structure-specific modification of partial safety factors. The general methodology, results from recalculations according to the Eurocodes and metrologically solvable testing tasks relevant in the recalculation of the concrete bridges are shown and compared with the non-destructive testing methods applicable to concrete bridges. A case study is used to demonstrate that as-built drawings, in this case of the positions of tendons and shear reinforcement, can be verified using the radar method.
High energy X-ray synchrotron diffraction is used to investigate the elastic anisotropy of the nickel-based superalloy IN718 produced by laser powder bed fusion (PBF-LB). This material is characterized by a columnar grain morphology with some crystallographic texture. The material is subjected to elastic loading to determine the diffraction elastic constants (DECs). Furthermore, the single-crystal elastic constants (SCEC) are refined from these experiments using different micromechanical models. The results show that each micromechanical model predicts a specific set of SCEC that well describes the elastic anisotropy of PBF-LB/IN718.
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.
Almost all building materials in civil engineering have an open porosity and interact with or are affected by the environmental conditions. Structures might suffer from effects such as moisture adsorption, carbonation, corrosion, penetration of salt ions and chemical substances, etc. In the hygroscopic range, these processes are mostly driven by diffusion. Due to the confinement of small pores (less than1 µm), the Knudsen effect reduces the molecular diffusion. This reduction can become more significant in case of temporal changing pore systems because of physisorption of water vapor, carbonation, or chemisorption.
In this study, unstabilised earth blocks and earth masonry are investigated. In a first step, the pore size distribution of the blocks is measured and sorption isotherms are recorded in experiments. Besides the ordinary physisorption, the involved clay minerals undergo swelling or shrinking due to chemisorption. The following two effects must be considered: first, the reduction of the available pore space by the adsorbed water layer. For this, the Hillerborg sorption theory is used, which is a combination of the well-known Brunauer-Emmett-Teller sorption theory and the Kelvin equation. This allows the computation of adsorbed water layers even in curved pore geometries. Second, the variation of the initial pore size distribution due to chemisorption needs to be modelled. Based on these two models, the effective diffusion coefficient can be predicted. For validation, arrays of relative humidity sensors were embedded into a free-standing earth masonry wall. This monitoring was carried out over more than a year to have a broad variety of environmental conditions and was located in Berlin, Germany.
The prediction of the effective diffusion coefficient can also be transferred to other processes and allows the investigation of materials having temporarily changing pore systems. Examples are the carbonation of cementitious materials, alkali silica reaction, calcium leaching of long-lasting structures, etc. These effects are prominent in the meso-pore range and might significantly alter the effective diffusion coefficient.
Solid wastewater-based fertilizers were screened for per- and polyfluoroalkyl substances (PFAS) by the extractable organic fluorine (EOF) sum parameter method. The EOF values for ten sewage sludges from Germany and Switzerland range from 154 to 7209 mg kg−1. For thermal treated sewage sludge and struvite the EOF were lower with values up to 121 mg kg−1. Moreover, the application of PFAS targeted
and suspect screening analysis of selected sewage sludge samples showed that only a small part of the EOF sum parameter values can be explained by the usually screened legacy PFAS. The hitherto unknown part of EOF sum parameter contains also fluorinated pesticides, pharmaceutical and aromatic compounds. Because these partly fluorinated compounds can degrade to (ultra-)short PFAS in wastewater treatment plants they should be considered as significant sources of organic fluorine in the environment. The combined results of sum parameter analysis and suspect screening reveal the need to update current regulations, such as the German fertilizer ordinance, to focus not solely on a few selected PFAS such as perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) but
consider an additional sum parameter approach as a more holistic alternative. Moreover, diffusion gradient in thin-films (DGT) passive samplers were utilized as an alternative simplified extraction method for PFAS in solid wastewater-based fertilizers and subsequently quantified via combustion ion chromatography. However, the DGT method was less sensitive and only comparable to the EOF values
of the fertilizers in samples with >150 mg kg−1, because of different diffusion properties for various PFAS, but also kinetic exchange limitations.
A spatial heterodyne spectrometer (SHS) was combined with a flame atomic absorption (FAA) setup to reveal the analytical potential of SHS to be used as a tool for high-resolution atomic absorption studies. Exploiting the advances in modern computational power, the spectral information encoded in the interferograms was extracted and separated. Consequently, unseeable interferometric ingredients corresponding to narrow-band absorption lines could be recognized. Namely, a single SHS absorption interferogram simultaneously contains both illumination background and absorption information, which can be distinguished through a series of computational steps. In the examples given by this work, we demonstrate the construction of Na absorbance spectra from a single image. The described single-image approach can be used to investigate highly dynamic systems, whereby background collections can be obviated.
Laser-induced breakdown spectroscopy (LIBS) is becoming a more mature technology every year with new variants such as laser ablation molecular isotopic spectrometry, reheating by various discharge techniques, and multiple pulse excitation schemes, in which sometimes lasers of different pulse lengths are used. However, lasers with inherent parameters like pulse length and repetition rate are still almost exclusively employed. Recent years have witnessed the advent of novel high-repetition-rate laser concepts for machining processes, like welding, milling, and engraving. Here, a comprehensive study of single-pulse LIBS spectra of a single aluminum target is presented to showcase the applicability of flexible high duty-cycle master oscillator power amplifier (MOPA) lasers. Although traditional flashlamp-pumped Fabry–Pérot lasers only permit a variation in the pulse energy and are operated at very low duty-cycles, MOPA lasers add repetition rate and pulse length as variable parameters. A thorough analysis of the temporal plasma behavior revealed the emission dynamic to closely match the excitation laser pulse pattern. An aluminum sample’s spectral response was shown to be significantly impacted by variations in both rate and length. Although the spectral emission strength of the elemental lines of Al, Sr, and Ca all peaked at slightly different parameter settings, the strongest impact was found on the relative abundance of molecular AlO bands. Unlike in previous laser ablation molecular isotopic spectrometry (LAMIS) publications, the latter could be readily detected with a good intensity and well-resolved spectral features without any temporal gating of the detector. This finding, together with the fact that MOPA lasers are both inexpensive and dependable, makes for a promising combination for future studies including the detection of diatomic band structures.
Gene-V protein (G5P/GVP) is a single-stranded (ss)DNA-binding protein (SBP) of bacteriophage f1 that is required for DNA synthesis and repair. In solution, it exists as a dimer that binds two antiparallel ssDNA strands with high affinity in a cooperative manner, forming a left-handed helical protein–DNA filament. Here, we report on fluorescence studies of the interaction of G5P with different DNA oligonucleotides having a hairpin structure (molecular beacon, MB) with a seven base-pair stem (dT24-stem7, dT18-stem7), as well as with DNA oligonucleotides (dT38, dT24) without a defined secondary structure. All oligonucleotides were end-labeled with a Cy3-fluorophore and a BHQ2-quencher. In the case of DNA oligonucleotides without a secondary structure, an almost complete quenching of their strong fluorescence (with about 5% residual intensity) was observed upon the binding of G5P. This implies an exact alignment of the ends of the DNA strand(s) in the saturated complex. The interaction of the DNA hairpins with G5P led to the unzipping of the base-paired stem, as revealed by fluorescence measurements, fluorescence microfluidic mixing experiments, and electrophoretic mobility shift assay data. Importantly, the disruption of ssDNA’s secondary structure agrees with the behavior of other single-stranded DNA-binding proteins (SBPs). In addition, substantial protein-induced fluorescence enhancement (PIFE) of the Cy3-fluorescence was observed.
An isotopic effect of normal (H2O) vs. heavy water (D2O) is well known to fundamentally affect structure and chemical properties of proteins, for instance. Here we correlate results from small angle X-ray and neutron scattering (SAXS, SANS) with high-resolution scanning transmission electron microscopy to track the evolution of CdS nanoparticle size and crystallinity from aqeuous solution in presence of the organic ligand ethylenediaminetetraacetate (EDTA) at room temperature in both H2O and D2O. We provide evidence via SANS experiments that exchanging H2O by D2O impacts nanoparticle formation by changing the equilibria and dynamics of EDTA clusters in solution as investigated by nuclear magnetic resonance. The colloidal stability of the CdS nanoparticles, covered by a layer of [Cd(EDTA)]2- complexes, is significantly reduced in D2O despite the strong stabilizing effect of EDTA in suspensions of normal water. Hence, conclusions about nanoparticle formation mechanisms from D2O solutions can bare limited transferability to reactions in normal water due to isotopic effects, which thus need to be discussed for contrast match experiments.
In this study, the wavefield radiated from a building to its surroundings is identified and extracted from M4.6 earthquake recordings collected by sensors installed in a building and on the nearby athletic field in Matera (Italy) using a new approach for soil-structure interaction assessment. The proposed approach for earthquake data analysis combines in an innovative way two methods already used in seismology and engineering seismology: deconvolution and polarization analysis. The approach enables the identification, reconstruction, and characterization of the wavefield radiated from a vibrating building into its surroundings, and the estimation of the amount of energy associated with it. The approach consists of four steps: estimation of the resonant frequencies of the building, deconvolution of the earthquake recordings from a building and its surroundings, identification of the seismic phases, reconstruction of the signal transmitted from the building to its surroundings, and estimation of its energy, and polarization analysis. Analysis of recordings of the M4.6 event highlighted that the motion related to the wavefield radiated from the building to the ground was mostly linearly polarized in the radial and transverse planes, while a clear ellipticity was observed only in the horizontal plane. The wavefield radiated from the building might be dominated by unconventionally polarized surface waves, i.e., quasi-Rayleigh waves or a combination of quasi-Rayleigh and quasi-Love waves. The results indicated that the energy transmitted from the analyzed vibrating building to its surroundings was significant and decreased the ground motion shaking due to the out-of-phase motion.
Hierarchically porous, high‐surface‐area silica materials are excellent candidates for multiple applications like catalysis and environmental remediation. Shaping these materials with additive manufacturing (AM) techniques, like robocasting, could enable their use with the benefit of on‐demand, customized shaping and maximizing performance. Herein, ordered mesoporous silica COK‐12 slurries were robocasted into monoliths, containing different ratios of uncalcined COK‐12 and sodium bentonite (0–25 wt.%). The rheology of the mixed slurries is characterized by lower flow indexes (0.69 vs. 0.32) and higher yield stresses (96 vs. 259 Pa) compared to pure COK‐12 ones. Monoliths were printed in woodpile structures and calcined at 600°C. Micro‐CT measurements showed a linear shrinkage of 25% after calcination. Mechanical characterization showed increased uniaxial strength (0.20 ± 0.07 to 1.0 ± 0.3 MPa) with increasing binder/solids ratio from 13 to 25%. The amorphous, mesoporous structure of COK‐12 was retained. The structures exhibited open porosities of 52 ± 4% and showed higher specific mesopore volumes, and increased average mesopore size (6 vs. 8 nm) compared to COK‐12. Small‐angle x‐ray scattering analysis revealed an increased lattice parameter (10.3 vs. 11.0 nm) and reduced wall thickness (3.1 nm vs. 4.1 nm) of the COK‐12 in the monoliths. These properties indicate suitability for their application as porous supports and adsorbents.
Due to the extremely high specific surface area of nanoparticles and corresponding potential for adsorption, the results of surface analysis can be highly dependent on the history of the particles, particularly regarding sample preparation and storage. The sample preparation method has, therefore, the potential to have a significant influence on the results. This report describes an interlaboratory comparison (ILC) with the aim of assessing which sample preparation methods for ToF-SIMS analysis of nanoparticles provided the most intra- and interlaboratory consistency and the least amount of sample contamination. The BAM reference material BAM-P110 (TiO2 nanoparticles with a mean Feret diameter of 19 nm) was used as a sample representing typical nanoparticles. A total of 11 participants returned ToF-SIMS data,in positive and (optionally) negative polarity, using sample preparation methods of “stick-and-go” as well as optionally “drop-dry” and “spin-coat.” The results showed that the largest sources of variation within the entire data set were caused by adventitious hydrocarbon contamination or insufficient sample coverage, with the spin-coating protocol applied in this ILC showing a tendency toward insufficient sample coverage; the sample preparation method or the participant had a lesser influence on results.
The performance of second generation ICP-TOFMS, equipped with a micro-channel plate (MCP) enabling multi-isotope detection, in terms of isotope ratio precision and instrumental isotopic fractionation (IIF) for (multi-)isotope ratio analysis was thoroughly assessed for B, Sr and Pb. Experimental isotope ratio precision of 0.14 % for 11B/10B intensity ratio, 0.15 % for 87Sr/86Sr intensity ratio and 0.07% for 208Pb/206Pb intensity ratio were obtained at high signal levels ($500 mg L−1) which is comparable to first generation ICP-TOFMS. The long-term stability of isotope ratios, measured over several hours and expressed as repeatability, is between 0.05 % and 1.8 % for B, Sr and Pb. The observed IIF per mass unit is negative for B (i.e., −11 % for 11B/10B) which is in accordance with measurements using sector field (MC) ICP-MS. But the observed IIF per mass unit is positive for Sr (i.e., 2 % for 87Sr/86Sr) and Pb (i.e., 4.5 % for 208Pb/206Pb) which is not in accordance with measurements using sector field (MC) ICP-MS. Furthermore, different IIFs per mass unit were observed for different isotope pairs of the same isotopic system (i.e., Sr, Pb) and adjacent isotopic systems (i.e., Pb vs. Tl). This and the observations from three-isotope plots for Sr and Pb show that ion formation, ion extraction, ion transmission, ion separation and ion detection in second generation ICP-TOFMS is subject to IIF that does not follow the known mass dependent fractionation laws and is possibly caused by mass independent fractionation and/or multiple (contradictory) fractionation processes with varying contributions. The non-mass dependent IIF behavior observed for second generation ICP TOFMS has profound consequences for the IIF correction of isotope raw data, including application of multi-isotope dilution mass spectrometry (IDMS) using ICP-TOFMS. Hence, only IIF correction models that correct also for mass independent fractionation are applicable to calculate reliable isotope ratios using second generation ICP-TOFMS. In the present study, reliable d11B values, and absolute B, Sr and Pb isotope ratios could be determined using the SSB approach in single-element solutions as well as in a mixture of B, Sr and Pb, where the isotopes were measured simultaneously.
The present work is part of the AIFRI project (Artificial Intelligence For Rail Inspection), where we and our project partners train a neural network for defect detection and classification. Our goal at BAM is to generate artificial ultrasound and eddy current training data for the A.I. This paper has an exploratory nature, where we focus on the simulation of eddy current signals for head check cracks, one of the most important rail surface defects. The goal of this paper is twofold. On the one hand, we present our general simulation setup. This includes geometric models for head check cracks with features like branching and direction change, a model for the HC10 rail testing probe, and the configuration of the Faraday simulation software.
On the other hand, we use the Faraday software to simulate eddy current testing signals with a strong focus on the influence of the damage depth on the signal, while differentiating between different crack geometries. Here, we observe an early saturation effect of the test signal at a damage depth of 2 mm (at a crack angle of 25◦ to the surface). That is about 2 mm earlier than we would expect from measurements at a crack angle of 90◦. This behavior will be investigated further in a future paper. Finally, we interpolate the simulated signals in a two-step curve fitting process. With these interpolations we may generate eddy current test signals for any damage depth within the simulated range.
Iron Oxide Nanocubes as a New Certified Reference Material for Nanoparticle Size Measurements
(2023)
The rational design and increasing industrial use of nanomaterials require a reliable characterization of their physicochemical key properties like size, size distribution, shape, and surface chemistry. This calls for nanoscale reference materials (nanoRMs) for the validation and standardization of commonly used characterization methods closely matching real-world nonspherical nano-objects. This encouraged us to develop a nonspherical nanoRM of very small size consisting of 8 nm iron oxide nanocubes (BAM-N012) to complement spherical gold, silica, and polymer nanoRMs. In the following, the development and production of this nanoRM are highlighted including the characterization by transmission electron microscopy (TEM) and small-angle X-ray scattering (SAXS) as complementary methods for size and shape parameters, homogeneity and stability studies, and calculation of a complete uncertainty budget of the size features. The determination of the nanocubes’ edge length by TEM and SAXS allows a method comparison. In addition, SAXS measurements can also provide the mean particle number density and the mass concentration. The certified size parameters, area equivalent circular diameter and square edge length, determined by TEM with a relative expanded uncertainty below 9%, are metrologically traceable to a natural constant for length, the very precisely known (111) lattice spacing of silicon. Cubic BAM-N012 qualifies as a certified nanoRM for estimating the precision and trueness, validation, and quality assurance of particle size and shape measurements with electron microscopy and SAXS as well as other sizing methods suitable for nanomaterials. The production of this new iron oxide nanocube RM presents an important achievement for the nanomaterial community, nanomaterial manufacturers, and regulators.
With femtosecond-laser direct writing (fs-LDW) maturing in all aspects as a manufacturing technology, a toolset for quality assurance must be developed. In this work we introduce a first of its kind test artifact. Test artifacts are standardized 3D models with specific geometric features to evaluate the performance of writing parameters. Test artifacts are already common in other 3D additive manufacturing technologies e.g. selective laser melting. The test artifact introduced in this work was developed in particular to accommodate the high geometrical resolution of fs-LDW structures and the limited possibilities to examine the resulting structure. Geometric accuracy, surface adhesion as well as confocal Raman spectroscopy results were considered when evaluating the design of the test artifact. We will explain the individual features and design considerations of our fs-LDW test artifact. The difference between two slicers, Cura and 3DPoli, and the implications on measured feature sizes and the general shape is quantified. The measured geometries are used to derive a general design guide for a specific combination of photoresists, laser power and scanning speed and to analyze the geometric accuracy of a structure produced using these guidelines. The shown test artifact is publicly available as STL file on GitHub (https://github.com/BAMresearch/2PP-TestArtifact) and in the supplement.
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.
Surface-functionalized polymer beads encoded with molecular luminophores and nanocrystalline emitters such as semiconductor nanocrystals, often referred to as quantum dots (QDs), or magnetic nanoparticles are broadly used in the life sciences as reporters and carrier beads. Many of these applications require a profound knowledge of the chemical nature and total number of their surface functional groups (FGs), that control bead charge, colloidal stability, hydrophobicity, and the interaction with the environment and biological systems. For bioanalytical applications, also the
number of groups accessible for the subsequent functionalization with, e.g., biomolecules or targeting ligands is relevant. In this study, we explore the influence of QD encoding on the amount of carboxylic acid (COOH) surface FGs of 2 μm polystyrene microparticles (PSMPs). This is done for frequently employed oleic acid and oleylamine stabilized, luminescent core/shell CdSe QDs and two commonly used encoding procedures. This included QD addition during bead formation by a thermally induced polymerization reaction and a post synthetic swelling procedure. The accessible number of COOH groups on the surface of QD-encoded and pristine beads was quantified by two colorimetric assays, utilizing differently sized reporters and electrostatic and covalent interactions. The results were compared to the total number of FGs obtained by a conductometric titration and Fourier transform infrared spectroscopy (FTIR). In addition, a comparison of the impact of QD and dye encoding on the bead surface chemistry was performed. Our results demonstrate the influence of QD encoding and the QD-encoding strategy on the number of surface FG that is ascribed to an interaction of the QDs with the carboxylic acid groups on the bead surface. These findings are of considerable relevance for applications of nanoparticle-encoded beads and safe-by-design concepts for nanomaterials.
Volumetric changes follow Portland cement hydration reactions: aluminates' hydration is generally expansive, whereas silicates' reaction leads to shrinkage. Determining the volumetric variation at very early ages (i.e., first minutes/hours) presents operational challenges; most standards prescribe the measurement on specimens that are already hardened, while measurements from the fresh state are not standardized. This article reports the first attempt to use in-situ X-ray diffraction (XRD) to measure the early-age volumetric variation of a cementitious paste. For this purpose, a C3A + gypsum paste was assessed for 36 h, measuring its vertical displacement over time through XRD. The results showed that the expansion increased in the first ∼13 h, in line with the ettringite formed up to ∼11 h. In addition, the volumetric expansion agreed well with the heat release in calorimetry. It is concluded that the volumetric variation measurement of cementitious pastes through in-situ XRD is a promising technique, but further studies are needed to make this technique consolidated.
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.
The increasing amount and complexity of clinical data require an appropriate way of storing and analyzing those data. Traditional approaches use a tabular structure (relational databases) for storing data and thereby complicate storing and retrieving interlinked data from the clinical domain. Graph databases provide a great solution for this by storing data in a graph as nodes (vertices) that are connected by edges (links). The underlying graph structure can be used for the subsequent data analysis (graph learning). Graph learning consists of two parts: graph representation learning and graph analytics. Graph representation learning aims to reduce high-dimensional input graphs to low-dimensional representations. Then, graph analytics uses the obtained representations for analytical tasks like visualization, classification, link prediction and clustering which can be used to solve domain-specific problems. In this survey, we review current state-of-the-art graph database management systems, graph learning algorithms and a variety of graph applications in the clinical domain. Furthermore, we provide a comprehensive use case for a clearer understanding of complex graph learning algorithms.
Integrated multi-omics analyses of microbiomes have become increasingly common in recent years as the emerging omics technologies provide an unprecedented opportunity to better understand the structural and functional properties of microbial communities. Consequently, there is a growing need for and interest in the concepts, approaches, considerations, and available tools for investigating diverse environmental and host-associated microbial communities in an integrative manner. In this review, we first provide a general overview of each omics analysis type, including a brief history, typical workflow, primary applications, strengths, and limitations. Then, we inform on both experimental design and bioinformatics analysis considerations in integrated multi-omics analyses, elaborate on the current approaches and commonly used tools, and highlight the current challenges. Finally, we discuss the expected key advances, emerging trends, potential implications on various fields from human health to biotechnology, and future directions.
In precision agriculture, the estimation of soil parameters via sensors and the creation of nutrient maps are a prerequisite for farmers to take targeted measures such as spatially resolved fertilization. In this work, 68 soil samples uniformly distributed over a field near Bonn are investigated using laser-induced breakdown spectroscopy (LIBS). These investigations include the determination of the total contents of macro- and micronutrients as well as further soil parameters such as soil pH, soil organic matter (SOM) content, and soil texture. The applied LIBS instruments are a handheld and a platform spectrometer, which potentially allows for the single-point measurement and scanning of whole fields, respectively. Their results are compared with a high-resolution lab spectrometer.
The prediction of soil parameters was based on multivariate methods. Different feature selection methods and regression methods like PLS, PCR, SVM, Lasso, and Gaussian processes were tested and compared. While good predictions were obtained for Ca, Mg, P, Mn, Cu, and silt content, excellent predictions were obtained for K, Fe, and clay content. The comparison of the three different spectrometers showed that although the lab spectrometer gives the best results, measurements with both field spectrometers also yield good results. This allows for a method transfer to the in-field measurements
New insights into pertinent Fe-complexes for the synthesis of iron via the instant polyol process
(2023)
Chemically synthesized iron is in demand for biomedical applications due to its large saturation magnetization compared to iron oxides. The polyol process, suitable for obtaining Co and Ni particles and their alloys, is laborious in synthesizing Fe. The reaction yields iron oxides, and the reaction pathway remains unexplored. This study shows that a vicinal polyol, such as 1,2-propanediol, is suitable for obtaining Fe rather than 1,3-propanediol owing to the formation of a reducible Fe intermediate complex. X-ray absorption spectroscopy analysis reveals the ferric octahedral geometry and tetrahedral geometry in the ferrous state of the reaction intermediates in 1,2-propanediol and 1,3-propanediol, respectively. The final product obtained using a vicinal polyol is Fe with a γ-Fe2O3 shell, while the terminal polyol is favourable for Fe3O4. The distinct Fe–Fe and Fe–O bond lengths suggest the presence of a carboxylate group and a terminal alkoxide ligand in the intermediate of 1,2-propanediol. A large Fe–Fe bond distance suggests diiron complexes with bidentate carboxylate bridges. Prominent high-spin and low-spin states indicate the possibility of transition, which favors the reduction of iron ions in the reaction using 1,2-propanediol.
The ultrasonic echo technique is frequently used in non-destructive testing (NDT) of concrete structures for thickness measurements, geometry determinations as well as localization of built-in components. To improve ultrasonic imaging of complex structures in concrete, we transferred a geophysical imaging technique, the reverse time migration (RTM), to NDT in civil engineering. In contrast to the conventionally used synthetic aperture focusing technique (SAFT) algorithms, RTM is a wavefield continuation method in time and uses the full wave equation. Thus, RTM can handle complicated wave propagations in any direction without dip limitation. In this paper, we focused on the application and evaluation of a two-dimensional (2D) elastic RTM algorithm considering compressional waves, vertically polarized shear waves, and Rayleigh waves. We tested the elastic RTM routine on synthetic ultrasonic echo data generated with a 2D concrete model consisting of several steps and circular air inclusions. As these complex structures can often be found in real-world NDT use cases, their imaging is especially important. By using elastic RTM, we were able to clearly reproduce vertical reflectors and lower edges of circular air voids inside our numerical concrete model. Such structures cannot be imaged with conventional SAFT algorithms. Furthermore, the used elastic RTM approach also yielded a better reconstruction of a horizontal reflector and upper boundaries of circular air inclusions. Our encouraging results demonstrate that elastic RTM has the potential to significantly improve the imaging of complex concrete structures and, thus, is a step forward for detailed, high-quality ultrasonic NDT in civil engineering.
The Boltzmann plot method is widely used to determine the temperature of laser induced plasma. It involves the use of individual lines that are not easy to find in complex spectra and/or in the spectral range available. If the number of such lines is not enough to build a reliable Boltzmann plot, overlapping lines are often used, which are separated by software. However, line separation is a rather imprecise procedure, which, in addition, requires significant computational costs. This study proposes an extension of the Boltzmann plot method that allows a specific group of unresolved lines to be included in a Boltzmann plot without the need to separate them. This group of lines are multiplets, lines of the same element with similar upper and lower transition states. The multiplet lines along with the individual lines are included in the algorithm, which also includes a correction for self-absorption and is used to determine the plasma temperature. The algorithm is tested on synthetic spectra which are consistent with the model of a homogeneous isothermal plasma in local thermodynamic equilibrium and is shown to be superior to the standard Boltzmann plot method both in more accurate determination of the plasma temperature and in a significant reduction in the computational time. The advantages and disadvantages of the method are discussed in the context of its applications in laser induced breakdown spectroscopy.
Accurate and precise isotope ratio measurements of heavy elements are playing an increasinglyimportant role in modern analytical sciences and have numerous applications. Today, isotope ratio measurements are typically performed with two principal techniques: thermal ionization mass spectrometry (TIMS) and multiple collector-inductively coupled plasma mass spectrometry (MC-ICP-MS). To obtain accurate results by mass spectrometry, isotopic certified reference materials (iCRMs) are needed for mass bias correction and for the validation of the method used for analysis.Thus, it is of paramount importance to achieve measurement comparability of all data reported, and to assess measurement capability of each CRM producer/National Metrology Institute (NMI). Therefore, the international comparison (CCQM-P213) was performed to assess the analytical capabilities of NMIs for the accurate determination of copper isotope ratio delta values in high purity materials. The study was proposed by the coordinating laboratories, National Research Council Canada (NRC), National Institute of Standards and Technology (NIST), Bundesanstalt für Materialforschung und -prüfung (BAM) and Physikalisch-Technische Bundesanstalt (PTB), as an activity of the Isotope Ratio Working Group (IRWG) of the Consultative Committee for Amount of Substance - Metrology in Chemistry and Biology (CCQM). Participants included six NMIs and one designated institute (DI) from the six countries. Although no measurement method was prescribed by the coordinating laboratories, MC-ICP-MS with either standard-sample bracketing (SSB) or combined SSB with internal normalization (C-SSBIN) models for mass bias correction were recommended. Results obtained from the six NMIs and one DI were in good agreement.
This study describes an interlaboratory comparison (ILC) among nine (9) laboratories to evaluate and validate the standard operation procedure (SOP) for single-particle (sp) ICP-TOFMS developed within the context of the Horizon 2020 project ACEnano. The ILC was based on the characterization of two different Pt nanoparticle (NP) suspensions in terms of particle mass, particle number concentration, and isotopic composition. The two Pt NP suspensions were measured using icpTOF instruments (TOFWERK AG, Switzerland).
Two Pt NP samples were characterized and mass equivalent spherical sizes (MESSs) of 40.4 ± 7 nm and 58.8 ± 8 nm were obtained, respectively. MESSs showed <16% relative standard deviation (RSD) among all participating labs and <4% RSD after exclusion of the two outliers. A good agreement was achieved between the different participating laboratories regarding particle mass, but the particle number concentration results were more scattered, with <53% RSD among all laboratories, which is consistent with results from previous ILC studies conducted using ICP-MS instrumentation equipped with a sequential mass spectrometer. Additionally, the capabilities of sp-ICP-TOFMS to determine masses on a particle basis are discussed with respect to the potential for particle density determination. Finally, because quasi-simultaneous multi-isotope and multielement determinations are a strength of ICP-TOFMS instrumentation, the precision and trueness of isotope ratio determinations were assessed. The average of 1000 measured particles yielded a precision of below ±1% for intensity ratios of the most abundant Pt isotopes, i.e. 194Pt and 195Pt, while the accuracy of isotope ratios with the lower abundant isotopes was limited by counting statistics.
Per- and polyfuoroalkyl substances (PFAS) are emerging organic pollutants and can occur in surface and groundwater. To identify the degree of pollution in surface water with PFAS, often targeted HPLC–ESI–MS/MS has been employed in which commonly 30–40 compounds are analyzed. However, other PFAS and organofuorines remain undetected. We sampled surface water of the river Spree and the Teltow Canal in Berlin, Germany, which are afected by the efuent discharge of wastewater treatment plants. Here, we employed high-resolution continuum source graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) for measuring extractable organofuorines (EOF) and compared in a mass balance approach the total fuorine to the identifed and quantifed PFAS from the targeted analysis. The analysis highlights that the EOF are in the range expected for an urban river system (Winchell et al. in Sci Total Environ 774, 2021). However, downstream of an efuent discharge, the EOF increased by one order of magnitude, e.g., 40.3 to 574 ng F L−1, along the Teltow Canal. From our target analytes, mostly short-chained perfuorinated carboxylic acids and sulfonates occur in the water, which however makes up less than 10% of the EOF. The increase in EOF in the Teltow Canal correlates well with the increase of perfuorohexanoic acid (PFHxA), indicating that PFHxA is characteristic for the discharged EOF but not responsible for the increase. Hence, it points to PFHxA precursor discharge. The study highlights that EOF screening using HR-CS-GFMAS is necessary to identify the full scale of pollution with regard to PFAS and other organofuorines such as pharmaceutical compounds from the efuent of WWTPs.
An interlaboratory comparison (ILC)was organised to characterise 87Sr/86Sr isotope ratios in geological and industrial reference materials by applying the so-called conventional method for determining 87Sr/86Sr isotope ratios. Four cements (VDZ 100a,VDZ 200a, VDZ 300a, IAG OPC-1), one limestone (IAG CGL ML-3) and one slate (IAG OU-6) reference materials were selected, covering a wide range of naturally occurring Sr isotopic signatures. Thirteen laboratories received aliquots of these six reference materials together with a detailed technical protocol. The consensus values for the six reference materials and their associated measurement uncertainties were obtained by applying a Gaussian, linear mixed effects model fitted to all the measurement results. By combining the consensus values and their uncertainties with an uncertainty contribution for potential heterogeneity, reference values ranging from 0.708134 mol mol-1 to 0.729778 mol mol-1 were obtained with relative expanded uncertainties of ≤ 0.007 %. This study represents an ILC on conventional 87Sr/86Sr isotope ratios, within which metrological principles were considered and the compatibility of measurement results obtained by MC-ICP-MS and by MC-TIMS is demonstrated. The materials characterised in this study can be used as reference materials for validation and quality control purposes and to estimate measurement uncertainties in conventional 87Sr/86Sr isotope ratio measurement.
This study uses conventional 87Sr/86Sr and 143Nd/144Nd isotope and interelement ratios of Ca, Sr, K, Mn, Mg and Ti as fingerprints for provenancing ordinary Portland cements (OPC). Herein, the first database of Sr and Nd isotope ratios investigated in OPCs, stemming from 29 cement plants located worldwide, was created. The results show that the Sr isotope ratios of OPCs are higher than those of seawater from the observed geological period. The spread of 143Nd/144Nd in OPCs is not as large as the spread for 87Sr/86Sr isotope ratios. However, the combination of both Sr and Nd isotope ratios provides the potential for distinguishing between cements of different production sites. Most of the OPCs investigated have measurable differences in their 87Sr/86Sr and 143Nd/144Nd isotope ratios, which can be employed as a valuable analytical fingerprinting tool. In the case of equivocal results, divisive hierarchical clustering was employed to help overcome this issue. The construction of geochemical profiles allowed the computing of suitably defined distances between cements and clustering them according to their chemical similarity. By applying this methodology, successful fingerprinting was achieved in 27 out of the 29 ordinary Portland cements that were analysed.
Per- and polyfluoroalkyl substances (PFAS) are widely used for durable water-repellent finishing of different fabrics and textiles like outdoor clothing, carpets, medical textiles and more. Existing PFAS extraction techniques followed by target analysis are often insufficient in detecting widely used side-chain fluorinated polymers (SFPs) that are barely or non-extractable. SFPs are typically copolymers consisting of a non-fluorinated backbone with perfluoroalkyl side-chains to obtain desired properties. We compared the accessible analytical information and performance of complementary techniques based on oxidation (dTOP assay, PhotoTOP), hydrolysis (THP assay), standard extraction, extractable organic fluorine (EOF), and total fluorine (TF) with five functional textiles and characterized 7 further textiles only by PhotoTOP oxidation. The results show that when applied directly to textile samples, oxidation by dTOP and PhotoTOP and also hydrolysis by the THP are able to capture large fractions of the TF in form of perfluoroalkyl side-chains present in the textiles while methods relying on extracts (EOF, target and non-target analysis) were much lower (e.g., factor ~25-50 lower). The conversion of large fractions of the measured TF into PFCAs or FTOHs from fluorinated side chains is in contrast to previous studies. Concentrations ranged from <LOQ to over ~1000 mg F/kg after oxidation/hydrolysis and <LOQ to over 2000 mg F/kg for TF, while EOF and target PFAS in extracts were detected at much lower concentrations (up to ~ 60 mg F/kg) (amount of fluorine in the order: extraction << EOF << oxidation/hydrolysis ≤ TF). Perfluoroalkyl carboxylic acids (PFCAs) and fluorotelomer alcohols (FTOHs) from THP and PhotoTOP both represented the chain-length distribution in the textiles showing that long-chain SFPs are still used in current textiles. Further advantages and disadvantages of the applied methods are discussed.
Mistle: bringing spectral library predictions to metaproteomics with an efficient search index
(2023)
Motivation: Deep learning has moved to the forefront of tandem mass spectrometry-driven proteomics and authentic prediction for peptide fragmentation is more feasible than ever. Still, at this point spectral prediction is mainly used to validate database search results or for confined search spaces. Fully predicted spectral libraries have not yet been efficiently adapted to large search space problems that often occur in metaproteomics or proteogenomics.
Results: In this study, we showcase a workflow that uses Prosit for spectral library predictions on two common metaproteomes and implement an indexing and search algorithm, Mistle, to efficiently identify experimental mass spectra within the library. Hence, the workflow emulates a classic protein sequence database search with protein digestion but builds a searchable index from spectral predictions as an in-between step.
We compare Mistle to popular search engines, both on a spectral and database search level, and provide evidence that this approach is more accurate than a database search using MSFragger. Mistle outperforms other spectral library search engines in terms of run time and proves to be extremely memory efficient with a 4- to 22-fold decrease in RAM usage. This makes Mistle universally applicable to large search spaces, e.g. covering comprehensive sequence databases of diverse microbiomes.
Availability and implementation: Mistle is freely available on GitHub at https://github.com/BAMeScience/Mistle.
Human factors (HF) are little understood, and particularly in non-destructive testing (NDT) experimental data is rare, samples are often small, and statistical methods are rarely used to evaluate results. HF have been widely implicated in major occurrences of technical failure, for example at North Anna Power Plant and on United Airlines Flight 232. Understanding HF is vital for reliable detection and prevention of failures. Reliability assessments, though known to be affected by intrinsic capability, application factors, and HF, have thus far only concentrated to a sufficient degree on intrinsic capability. The addition of HF to that assessment has proven difficult due to the lack of a method of quantifying HF. This paper presents the first attempt from a psychological perspective to quantify HF from qualitative data.
HF data was derived from qualitative human-oriented Failure Modes and Effects Analysis (Human-FMEA) workshops for visual inspection of tunnels by laser scanning and for ultrasonic testing of welds. Data was collected on human failure modes, causes, consequences and preventive measures, as well as eliciting a risk priority number (RPN). Using this data, a system of quantitative weightings was created to allocate errors to inductively derived HF categories for further allocation to existing HF categorisation models.
This weighting model proved useful for creating quantitative summaries of HF, informing and validating qualitative FMEA results, and comparing existing HF categorisation models. Further potential lies within a planned interface to quantitative reliability assessment methods such as POD (Probability of Detection). While providing quantifications, the method retains a qualitative and holistic nature, can, thus, bridge the gap between psychological and engineering concerns of HF and reliability, contributing to future interdisciplinary work.
Regardless of the experimental care practiced in acquiring X-ray computed tomography (XCT) data, artifacts might still exist, such as noise and blur. This is typical for fast XCT data acquisitions (e.g., in-situ investigations), or low-dose XCT. Such artifacts can complicate subsequent analysis of the data. Digital filters can moderately cure extensive artifacts. The selection of filter type, intensity, and order of application is not always straight forward. To tackle these problems, a complete sequential multilevel, multi-scale framework: BAM SynthCOND, employing newly designed deep convolutional neural networks (DCNNs), was formulated. Although data conditioning with neural networks is not uncommon, the main complication is that completely artifact-free XCT data for training do not exist. Thus, training data were acquired from an in-house developed library (BAM SynthMAT) capable of generating synthetic XCT material microstructures. Some novel DCNN architectures were introduced (2D/3D ACEnet_Denoise, 2D/3D ACEnet_Deblur) along with the concept of Assertive Contrast Enhancement (ACE) training, which boosts the performance of neural networks trained with continuous loss functions. The proposed methodology accomplished very good generalization from low resemblance synthetic training data. Indeed, denoising, sharpening (deblurring), and even ring artifact removal performance were achieved on experimental post-CT scans of challenging multiphase Al-Si Metal Matrix Composite (MMC) microstructures. The conditioning efficiencies were: 92% for combined denoising/sharpening, 99% for standalone denoising, and 95% for standalone sharpening. The results proved to be independent of the artifact intensity. We believe that the novel concepts and methodology developed in this work can be directly applied on the CT projections prior to reconstruction, or easily be extended to other imaging techniques such as: Microscopy, Neutron Tomography, Ultrasonics, etc.
Since its isolation, graphene has received growing attention from academia and industry due to its unique properties. However, the “what is my material” barrier hinders further commercialization. X-ray photoelectron spectroscopy (XPS) is considered as a method of choice for the determination of the elemental and chemical composition. In this work the influence of the morphology of graphene particles on the XPS results is studied and investigated as a function of X-ray energy, using conventional XPS with Al K𝜶 radiation and hard X-ray photoemission spectroscopy (HAXPES) using Cr K𝜶 radiation. Thereby, the information depth is varied between 10 and 30 nm. For this purpose, two commercial powders containing graphene nanoplatelets with lateral dimensions of either ≈100 nm or in the micrometer range are compared. These larger ones exist as stack of graphene layers which is inspected with scanning electron microscopy. Both kinds of particles are then functionalized with either oxygen or fluorine. The size of the graphene particles is found to influence the degree of functionalization. Only the combination of XPS and HAXPES allows to detect the functionalization at the outermost surface of the particles or even of the stacks and to provide new insights into the functionalization process.
Although layer-based additive manufacturing methods such as laser powder bed fusion (PBF-LB) offer an immense geometrical freedom in design, they are typically subject to a build-up of internal stress (i.e. thermal stress) during manufacturing. As a consequence, significant residual stress (RS) is retained in the final part as a footprint of these internal stresses. Furthermore, localized melting and solidification inherently induce columnar-type grain growth accompanied by crystallographic texture. Although diffraction-based methods are commonly used to determine the RS distribution in PBF-LB parts, such features pose metrological challenges in their application. In theory, preferred grain orientation invalidates the hypothesis of isotropic material behavior underlying the common methods to determine RS. In this work, more refined methods are employed to determine RS in PBF-LB/M/IN718 prisms, based on crystallographic texture data. In fact, the employment of direction-dependent elastic constants (i.e. stress factors) for the calculation of RS results in insignificant differences from conventional approaches based on the hypothesis of isotropic mechanical properties. It can be concluded that this result is directly linked to the fact that the {311} lattice planes typically used for RS analysis in nickel-based alloys have high multiplicity and less strong texture intensities compared with other lattice planes. It is also found that the length of the laser scan vectors determines the surface RS distribution in prisms prior to their removal from the baseplate. On removal from the baseplate the surface RS considerably relaxes and/or redistributes; a combination of the geometry and the scanning strategy dictates the sub-surface RS distribution.
Quantitative Analysis and 2D/3D Elemental Imaging of Cocoa Beans Using X‑ray Fluorescence Techniques
(2023)
As an important raw material for the confectionery industry, the cocoa bean (Theobroma cacao L.) has to meet certain legal requirements in terms of food safety and maximum contaminant levels in order to enter the cocoa market. Understanding the enrichment and distribution of essential minerals but also toxic metals is of utmost importance for improving the nutritional quality of this economically important raw food material. We present three X-ray fluorescence (XRF) techniques for elemental bio-imaging of intact cocoa beans and one additional XRF technique for quantitative analysis of cocoa pellets. The interrelation of all the methods presented gives a detailed picture of the content and 3D-resolved distribution of elements in complete cocoa beans for the first time.
The huge atomic heterogeneity of high-entropy materials along with a possibility to unravel the behavior of individual components at the atomic scale suggests a great promise in designing new compositionally complex systems with the desired multi-functionality. Herein, we apply multi-edge X-ray absorption spectroscopy (extended X-ray absorption fine structure (EXAFS), X-ray absorption near edge structure (XANES), and X-ray magnetic circular dichroism (XMCD)) to probe the structural, electronic, and magnetic properties of all individual constituents in the single-phase face-centered cubic (fcc)-structured nanocrystalline thin film of Cr20Mn26Fe18Co19Ni17 (at.%) high-entropy alloy on the local scale. The local crystallographic ordering and component-dependent lattice displacements were explored within the reverse Monte Carlo approach applied to EXAFS spectra collected at the K absorption edges of several constituents at room temperature. A homogeneous short-range fcc atomic environment around the absorbers of each type with very similar statistically averaged interatomic distances (2.54–2.55 Å) to their nearest-neighbors and enlarged structural relaxations of Cr atoms were revealed. XANES and XMCD spectra collected at the L2,3 absorption edges of all principal components at low temperature from the oxidized and in situ cleaned surfaces were used to probe the oxidation states, the changes in the electronic structure, and magnetic behavior of all constituents at the surface and in the sub-surface volume of the film. The spin and orbital magnetic moments of Fe, Co, and Ni components were quantitatively evaluated. The presence of magnetic phase transitions and the co-existence of different magnetic phases were uncovered by conventional magnetometry in a broad temperature range.
With increasing demand and environmental concerns, researchers are exploring new materials that can perform as well or better than traditional materials while reducing environmental impact. The BAMline, a real-life sample materials research beamline, provides unique insights into materials’ electronic and chemical structure at different time and length scales. The beamline specializes in x-ray absorption spectroscopy, x-ray fluorescence spectroscopy, and tomography experiments. This enables real-time optimization of material properties and performance for various applications, such as energy transfer, energy storage, catalysis, and corrosion resistance. This paper gives an overview of the analytical methods and sample environments of the BAMline, which cover non-destructive testing experiments in materials science, chemistry, biology, medicine, and cultural heritage. We also present our own synthesis methods, processes, and equipment developed specifically for the BAMline, and we give examples of synthesized materials and their potential applications. Finally, this article discusses the future perspectives of the BAMline and its potential for further advances in sustainable materials research.
In this study, we propose the use of nondestructive, depth-resolved, element-specific characterization using grazing exit X-ray absorption near-edge structure spectroscopy (GE-XANES) to investigate the corrosion process in compositionally complex alloys (CCAs). By combining grazing exit X-ray fluorescence spectroscopy (GE-XRF) geometry and a pnCCD detector, we provide a scanning-free, nondestructive, depth-resolved analysis in a sub-micrometer depth range, which is especially relevant for layered materials, such as corroded CCAs. Our setup allows for spatial and energy-resolved measurements and directly extracts the desired fluorescence line, free from scattering events and other overlapping lines. We demonstrate the potential of our approach on a compositionally complex CrCoNi alloy and a layered reference sample with known composition and specific layer thickness. Our findings indicate that this new GE-XANES approach has exciting opportunities for studying surface catalysis and corrosion processes in real-world materials.
Mesoporous glasses are a promising class of bioresorbable biomaterials characterized by high surface area and extended porosity in the range of 2 to 50 nm. These peculiar properties make them ideal materials for the controlled release of therapeutic ions and molecules. Whilst mesoporous silicate-based glasses (MSG) have been widely investigated, much less work has been done on mesoporous phosphate-based glasses (MPG). In the present study, MPG in the P2O5–CaO–Na2O system, undoped and doped with 1, 3, and 5 mol% of Cu ions were synthesized via a combination of the sol–gel method and supramolecular templating. The non-ionic triblock copolymer Pluronic P123 was used as a templating agent. The porous structure was studied via a combination of Scanning Electron Microscopy (SEM), Small-Angle X-ray Scattering (SAXS), and N2 adsorption–desorption analysis at 77 K. The structure of the phosphate network was investigated via solid state 31P Magic Angle Spinning Nuclear Magnetic Resonance (31P MAS-NMR) and Fourier Transform Infrared (FTIR) spectroscopy. Degradation studies, performed in water via Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES), showed that phosphates, Ca2+, Na+ and Cu ions are released in a controlled manner over a 7 days period. The controlled release of Cu, proportional to the copper loading, imbues antibacterial properties to MPG. A significant statistical reduction of Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) bacterial viability was observed over a 3 days period. E. coli appeared to be more resistant than S. aureus to the antibacterial effect of copper. This study shows that copper doped MPG have great potential as bioresorbable materials for controlled delivery of antibacterial ions.
In this work, the limits of using spatially structured heating combined with subsequent photothermal super resolution reconstruction for the thermographic detection and resolution of internal defects are investigated. The approach is based on the application of modern high-power laser projector technology, which is used to repeatedly project varying spatially structured 2D pixel patterns to photothermally heat the object under test. After processing the generated thermographic data using nonlinear convex optimisation in conjunction with exploiting the joint-sparse nature of the defect signals within the individual measurements, a high-resolution 2D-sparse defect/inhomogeneity map is obtained. The main focus of the investigation is set on the influence of the number of individual measurements on the achievable reconstruction quality. Using numerical simulations based on an analytical representation of the forward solution to the underlying inverse problem, the convergence rate over performed measurements of the achievable reconstruction quality is determined. Finally, all findings are experimentally validated by reconstructing a set of internal defects in an additively manufactured sample. In this work, it is shown that for a variety of different defect separation distances, the projection of 50 different pixel patterns allows for a good trade-off between experimental complexity and reconstruction quality.
It can be difficult to efficiently model ultrasonic waves in 3D structures, especially when the computational model needs to account for complex geometries. This contribution presents a solution based on the Scaled Boundary Finite Element Method (SBFEM). It is a numerical tool suitable for elastodynamic problems. A space-tree discretisation, namely quad-trees, is used. This technique allows the decomposition of an image into quadrilaterals or quads, which are extruded to generate the 3D plate geometry. In particular, small quads resolve regions with discontinuities, allowing them to represent fine details in the structure. Moreover, this meshing technique allows for exploiting cell similarities, making the calculation procedure more efficient. The space-tree discretisations are generated from a high-resolution image containing all the information about damaged regions or boundary conditions. The resulting SBFEM polyhedral domains employ transition elements to ensure correct coupling between cells of different sizes. The analytical solution of a cylindrical scatterer serves as a reference to validate the proposed approach. Other examples also demonstrate the validity of the methodology and its flexibility.
Motivation: Inferring taxonomy in mass spectrometry-based shotgun proteomics is a complex task. In multi-species or viral samples of unknown taxonomic origin, the presence of proteins and corresponding taxa must be inferred from a list of identified peptides, which is often complicated by protein homology: many proteins do not only share peptides within a taxon but also between taxa. However, the correct taxonomic inference is crucial when identifying different viral strains with high-sequence homology—considering, e.g., the different epidemiological characteristics of the various strains of severe acute respiratory syndrome-related coronavirus-2. Additionally, many viruses mutate frequently, further complicating the correct identification of viral proteomic samples.
Results: We present PepGM, a probabilistic graphical model for the taxonomic assignment of virus proteomic samples with strain-level resolution and associated confidence scores. PepGM combines the results of a standard proteomic database search algorithm with belief propagation to calculate the marginal distributions, and thus confidence scores, for potential taxonomic assignments. We demonstrate the performance of PepGM using several publicly available virus proteomic datasets, showing its strain-level resolution performance. In two out of eight cases, the taxonomic assignments were only correct on the species level, which PepGM clearly indicates by lower confidence scores.
Availability and implementation: PepGM is written in Python and embedded into a Snakemake workflow. It is available at https://github.com/BAMeScience/PepGM.
Comparative study of the co-assembly behaviour of 3-chloro-4-hydroxy-phenylazo dyes with DTAB
(2023)
The co-assembly of three one-fold negatively charged 3-chloro-4-hydroxy-phenylazo dyes (Yellow, Blue and Red) with the cationic surfactant dodecyltrimethylammoniumbromide (DTAB) was studied to probe dye–DTAB binding stoichiometry and assembly morphology. For each dye, phase separation was observed above a given dye : DTAB ratio with the ratio depending on the dye. While Yellow and DTAB showed liquid/liquid phase separation above Yellow : DTAB = 1 : 1.67, crystalline dye–DTAB complexes were observed for Blue–DTAB and Red–DTAB above Blue : DTAB = 1 : 2.56 and Red : DTAB = 1 : 2.94 respecively. In homogeneous solution, UV/vis spectroscopic investigations suggest stochiometries of Yellow : DTAB = 1 : 2, Blue : DTAB = 1 : 3 and Red : DTAB = 1 : 4. It was concluded, that Yellow exhibits the highest dye : DTAB binding stoichiometry in both, dye–surfactant complexes in the 2-phase region and in solution, whereas the lowest dye : DTAB binding stoichiometry was observed for Red–DTAB in both cases. The observed stoichiometries are inversely correlated to the impact dye addition has on the morphology of DTAB micelles. Generally, addition of dye to DTAB micelles leads to a reduction in spontaneous curvature of these micelles and to the formation of triaxial ellipsoidal or cylindrical micelles from oblate ellipsoidal DTAB micelles. At a DTAB concentration of 30 mM and a dye concentration of 5 mM, this effect was most pronounced for Red and least pronounced for Yellow, whilst Blue showed an intermediate effect.
X-ray photoelectron spectroscopy (XPS) is widely used for characterising the chemistry of graphene-related two-dimensional materials (GR2M), however the careful preparation of the sample for analysis is important in obtaining representative quantifications. We report an investigation by three laboratories showing that the preparation method for oxygen-functionalised graphene nanoplatelet (GNP) powders has a significant effect on the homogeneous-equivalent elemental composition measured in XPS. We show that pressing GNP powders onto adhesive tapes, into recesses, or into solid pellets results in inconsistencies in the XPS quantification. The measured oxygen-to-carbon atomic ratio from GNP pellets depends upon the die pressure used to form them and the morphology of the GNPs themselves. We recommend that powder samples of GR2Ms are pelletised prior to XPS analysis to improve repeatability and reproducibility of measurements.
Functionally graded porous scaffolds (FGPS) constructed with pores of different size arranged as spatially continuous structure based on sheet-based gyroid with three different scaling factors of 0.05, 0.1 and 0.2 were produced by electron beam powder bed fusion. The pore dimensions of the obtained scaffolds satisfy the values required for optimal bone tissue ingrowth. Agglomerates of residual powder were found inside all structures, which required post-manufacturing treatment. Using X-ray Computed Tomography powder agglomerations were visualized and average wall thickness, wall-to-wall distances, micro- and macro-porosities were evaluated. The initial cleaning by powder recovery system (PRS) was insufficient for complete powder removal. Additional treatment by dry ultrasonic vibration (USV) was applied and was found successful for gyroids with the scaling factors of 0.05 and 0.1. Mechanical properties of the samples, including quasi-elastic gradients and first maximum compressive strengths of the structures before and after USV were evaluated to prove that additional treatment does not produce structural damage. The estimated quasi-elastic gradients for gyroids with different scaling factors lie in a range between 2.5 and 2.9 GPa, while the first maximum compressive strength vary from 52.5 for to 59.8 MPa, compressive offset stress vary from 46.2 for to 53.2 MPa.
This paper reports the results of an international interlaboratory study sponsored by the Versailles Project on Advanced Materials and Standards (VAMAS) and led by the National Institute of Standards and Technology (NIST) on the measurement of water vapor sorption isotherms at 25 °C on a pelletized nanoporous carbon (BAM-P109, a certified reference material). Thirteen laboratories participated in the study and contributed nine pure water vapor isotherms and four relative humidity isotherms, using nitrogen as the carrier gas. From these data, reference isotherms, along with the 95% uncertainty interval (Uk=2), were determined and are reported in a tabular format.
Asymmetrical Flow Field-Flow Fractionation (AF4), as a cleaning technique, was combined on-line with the multielemental analytical capabilities of an Inductively Coupled Plasma-Time of Flight-Mass Spectrometer (ICP-ToF-MS). In that manner, the heavy ionic matrix effect of untreated cells' samples can be significantly reduced. As a proof of concept, commercial baker's yeast cells were analysed.
We investigated the performance of nitrogen microwave inductively coupled atmospheric-pressure plasma mass spectrometry (MICAP-MS) under matrix effects and its applicability to trace element analysis in steels. Influences of different gas flows and ion optics on the matrix tolerance are studied, indicating that nebulizer gas flow has the most significant impact. Optimization of ion optics improves matrix tolerance for light elements due to the reduction of the inelastic collisional scattering effect. With optimized operating conditions, MICAP-MS achieves an internal standard intensity recovery of over 90% at an Fe concentration of 500 mg L−1. Even at an Fe concentration of 1 g L−1, the recovery remains above 80%. Three certified reference materials – non-alloy, low-alloy and high-alloy steel – were analyzed using MICAP-MS. The determined mass concentrations of the trace and minor components show metrological compatibility to the reference values. No significant differences are observed between the results obtained with aqueous and matrix-matched calibration, demonstrating the strong matrix tolerance of MICAP-MS, and its promising applicability to steel analysis.
Cardiac troponin I (cTnI) is a crucial biomarker for diagnosing cardiac vascular diseases, including acute myocardial infarction (AMI). This study presents a proof-of-concept chemiluminescence-based immunosensor for rapid and accurate measurement of cTnI, with the potential for online monitoring. The immunosensor incorporates a flow cell design and a sensitive complementary metal-oxide-semiconductor (CMOS) camera for optical readout. A microfluidic setup was established to enable selective and quasi-online determination of cTnI within ten minutes. The sensor was tested with recombinant cTnI in phosphate buffer, demonstrating measurements in the concentration range of 2–25 µg/L, with a limit of detection (LoD) of 0.6 µg/L (23 pmol/L) achieved using the optimized system. The immunosensor exhibited high selectivity, as no cross-reactivity was observed with other recombinant proteins such as cTnT and cTnC at a concentration of 16 µg/L. Measurements with diluted blood plasma and serum yielded an LoD of 60 µg/L (2.4 nmol/L) and 70 µg/L (2.9 nmol/L), respectively. This biosensor offers a promising approach for the rapid and sensitive detection of cTnI, contributing to the diagnosis and management of acute myocardial infarction and other cardiac vascular diseases.
Creep-resistant steels such as the 13CrMoV9-10, used in the construction of thick-walled pressure vessels, are most commonly submerged arc welded (SAW). These steels can develop stress relief cracks (SRC) if the mandatory post weld heat treatment (PWHT) is performed improperly. Current PWHT parameters, such as heating rate and holding time at a specific holding temperature, are based on both empirical experience and conventional free shrinking welding experiments to characterize the SRC-susceptibility of the weld. These cannot adequately depict the higher residual stresses caused by the structurally induced stiffness of the surrounding construction. This study discusses the development of a repeatable, precise, and time-efficient methodology to study the effects of different stress levels and heating rates on the SRC susceptibility of the coarse grain heat-affected zone (CGHAZ). For that purpose, samples were thermically treated to simulate a coarse grain heat-affected zone (CGHAZ) and subsequently exposed to representative levels of stress during the heating phase of a PWHT. The recorded stress and heating rate–dependent strains were mathematically analyzed via curve tracing/calculus to identify interdependent effects. This procedure facilitates the measurement of material characteristics such as carbide growth on grain boundaries at the µm-scale via an integrated value over the entire sample volume. The first and second derivatives show a slight, precipitate-dependent, increase in hardness of the sample, depending on the heating rate and applied stress. This new methodology generates an improved assessment of the SRC susceptibility of SAW microstructures of creep-resistant CrMoV steels.
The complex nature of liquid water saturation of polymer electrolyte fuel cell (PEFC) catalyst layers (CLs) greatly affects the device performance. To investigate this problem, we present a method to quantify the presence of liquid water in a PEFC CL using small-angle X-ray scattering (SAXS). This method leverages the differences in electron densities between the solid catalyst matrix and the liquid water filled pores of the CL under both dry and wet conditions. This approach is validated using ex situ wetting experiments, which aid the study of the transient saturation of a CL in a flow cell configuration in situ. The azimuthally integrated scattering data are fitted using 3D morphology models of the CL under dry conditions. Different wetting scenarios are realized in silico, and the corresponding SAXS data are numerically simulated by a direct 3D Fourier transformation. The simulated SAXS profiles of the different wetting scenarios are used to interpret the measured SAXS data which allows the derivation of the most probable wetting mechanism within a flow cell electrode.
Immobilized metal affinity chromatography (IMAC) is a widely used technique for purifying polyhistidine-tagged recombinant proteins. However, it often has practical limitations that require complex optimizations and additional steps for purification. In this study, we introduce functionalized corundum particles as a novel, efficient, and economical method for purifying recombinant proteins in a column-free format. The corundum surface is modified with amino silane APTES, followed by EDTA dianhydride, and then loaded with nickel ions. We used the Kaiser test to monitor the modification process and ICP-MS to quantify the metal-binding capacity. To evaluate the system, we used His-tagged protein A/G (PAG) mixed with bovine serum albumin (BSA). The corundum particles exhibited a binding capacity of approximately 3 mg of protein per gram of corundum or 2.4 mg per 1 mL of corundum suspension. We also examined cytoplasm obtained from different E. coli strains as an example of a complex matrix. Varying the imidazole concentration in the loading and washing buffers showed that higher concentrations during loading improved purity. Even with sample volumes as large as one liter, we successfully isolated recombinant proteins down to a concentration of 1 µg/mL. We found higher purity levels with corundum when comparing the corundum material to standard Ni–NTA agarose beads. We successfully purified His6-MBP-mSA2, a fusion protein comprising monomeric streptavidin and maltose-binding protein, from E. coli cytoplasm, demonstrating the method's applicability. We also purified SARS-CoV-2-S-RBD-His8 expressed in human Expi293F cells, confirming its suitability for mammalian cell culture supernatants. The material cost of the nickel-loaded corundum material (without regeneration) is estimated to be less than 30 cents per gram of functionalized support or 10 cents per milligram of isolated protein. Another advantage of this system is the exceptional physical and chemical stability of corundum particles. Overall, we have demonstrated that this novel material offers an efficient, robust, and cost-effective purification platform for His-tagged proteins, even in challenging, complex matrices and large sample volumes with low product concentrations. This method has potential applications in both small laboratories and large-scale industrial settings.
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.
This paper reports a systematic study into the effect of nitrogen on iron-catalyzed graphitization of biomass. Chitin, chitosan, N-acetylglucosamine, gelatin and glycine were selected to represent nitrogen-rich saccharides and amino-acid/polypeptide biomass precursors. The materials were pyrolyzed with an iron catalyst to produce carbons with a wide range of chemical and structural features such as mesoporosity and nitrogen-doping. Many authors have reported the synthesis of nitrogen-doped carbons by pyrolysis and these have diverse applications. However, this is the first systematic study of how nitrogen affects pyrolysis of biomass and importantly the catalytic graphitization step. Our data demonstrates that nitrogen inhibits graphitization but that some nitrogen survives the catalytic graphitization process to become incorporated into various chemical environments in the carbon product.
The dataset contains raw data gathered with the ultrasonic pulse-echo method on concrete specimens. The surfaces of the measuring objects were automatically scanned point by point. Pulse-echo measurements were performed at each of these measuring points. The test specimens represent two typical testing tasks in construction industry: the detection of objects and the determination of dimensions to describe the geometry of components. By automating the measurement process, the different test scenarios are examined with a high repeatability, precision and measuring point density. Longitu- dinal and transversal waves were used and the geometrical aperture of the testing system was varied. The low-frequency probes operate in a range of up to approximately 150 kHz. In addition to the specification of the geometrical dimensions of the individual probes, the directivity pattern and the sound field characteristics are provided. The raw data are stored in a universally readable format. The length of each time signal (A-scan) is two milliseconds and the sampling rate is two mega-samples per second. The provided data can be used for comparative studies in signal analysis, imag- ing and interpretation as well as for evaluation pur- poses in different, practically relevant testing scenarios.
The prediction of porosity is a crucial task for metal based additive manufacturing techniques such as laser powder bed fusion. Short wave infrared thermography as an in-situ monitoring tool enables the measurement of the surface radiosity during the laser exposure. Based on the thermogram data, the thermal history of the component can be reconstructed which is closely related to the resulting mechanical properties and to the formation of porosity in the part. In this study, we present a novel framework for the local prediction of porosity based on extracted features from thermogram data. The framework consists of a data pre-processing workflow and a supervised deep learning classifier architecture. The data pre-processing
workflow generates samples from thermogram feature data by including feature information from multiple subsequent layers.
Thereby, the prediction of the occurrence of complex process phenomena such as keyhole pores is enabled. A custom convolutional neural network model is used for classification. Themodel is trained and tested on a dataset from thermographic in-situ monitoring of the manufacturing of an AISI 316L stainless steel test component. The impact of the pre-processing parameters and the local void distribution on the classification performance is studied in detail. The presented model achieves an accuracy of 0.96 and an f1-Score of 0.86 for predicting keyhole porosity in small sub-volumes with a dimension of (700 × 700 × 50) μm3. Furthermore, we show that pre-processing parameters such as the porosity threshold for sample
labeling and the number of included subsequent layers are influential for the model performance. Moreover, the model prediction is shown to be sensitive to local porosity changes although it is trained on binary labeled data that disregards the actual sample porosity.
We propose a novel iterative segmentation algorithm (i.S.Sy.Da.T.A: Iterative Segmentation Synthetic Data Training Algorithm) employing Deep Convolutional Neural Networks and synthetic training data for X-ray tomographic reconstructions of complex microstructures. In our method, we reinforce the synthetic training data with experimental XCT datasets that were automatically segmented in the previous iteration. This strategy produces better segmentations in successive iterations. We test our algorithm with experimental XCT re constructions of a 6-phase Al-Si Matrix Composite reinforced with ceramic fibers and particles. We perform the analysis in 3D with a special network architecture that demonstrates good generalization with synthetic training data. We show that our iterative algorithm returns better segmentations compared to the standard single training approach. More specifically, phases possessing similar attenuation coefficients can be better segmented: for Al2O3 fibers, SiC particles, and Intermetallics, we see an increase of the Dice score with respect to the classic approach: from 0.49 to 0.54, from 0.66 to 0.72, and from 0.55 to 0.66 respectively. Furthermore, the overall Dice score increases from 0.77 to 0.79. The methods presented in this work are also applicable to other materials and imaging techniques.
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.
Two test series were examined using nondestructive measuring methods by six independent laboratories before determining their compressive strength. The nondestructive test methods used were the rebound hammer and ultrasonic pulse velocity measurement. Two types of geometries were investigated: drilled cores and cubes. The measurement procedure for each of these datasets is conditioned to the geometry and is therefore different.
The first series consists of 20 drilled cores (approximately diameter/height = 10 cm/20 cm) from the 55-year-old Lahntal Viaduct near Limburg, Germany. After preparation in the first laboratory, the lateral surface of the drilled cores was tested with the rebound hammer using a given pattern. Every laboratory tested every drilled core at different locations.
Ultrasonic measurements in transmission were performed repeatedly at predefined points on the flat surfaces of the specimen.
The second series consisted of 25 newly manufactured concrete cubes of a mix with a target concrete strength class of C30/37. The edge length was 15 cm. Each laboratory received five specimens of this test series. Thus, contrary to the first series, each specimen was tested by only one laboratory. Two side faces of each cube were tested with the rebound hammer. In addition, ultrasonic measurements were performed by one laboratory. The time of flight was measured between the tested side faces of the rebound hammer at different positions.
For both series, rebound hammers were used to determine the R-value as well as the Q-value. The rebound hammer models within the laboratories were always the same, while they differed between the laboratories. The ultrasonic measurements took place with different measurement systems and couplants. Finally, both specimen series were tested destructively for compressive strength.
The dataset contains the raw data summarized in tabular form. In addition, relevant calculated data are included in some cases. For the ultrasonic measurements, the time of flight has already been converted into the ultrasonic velocity. Besides, in addition to the raw data of the compressive strength test (force, weight, and geometry values), the calculated compressive strengths and densities are also provided.
The glass transition behavior of thin films of poly(bisphenol A carbonate) (PBAC) was studied employing ellipsometry. The glass transition temperature increases with the reduction of the film thickness. This result is attributed to the formation of an adsorbed layer with a reduced mobility compared to bulk PBAC. Therefore, for the first time, the growth kinetics of the adsorbed layer of PBAC was investigated, prepared by leaching samples from a 200 nm thin film which were annealed for several times at three different temperatures. The thickness of each prepared adsorbed layer was measured by multiple scans using atomic force microscopy (AFM). Additionally, an unannealed sample was measured. Comparison of the measurements of the unannealed and the annealed samples provides proof of a pre-growth regime for all annealing temperatures which was not observed for other polymers. For the lowest annealing temperature after the pre-growth stage only a growth regime with a linear time dependence is observed. For higher annealing temperatures the growth kinetics changes from a linear to a logarithmic growth regime at a critical time. At the longest annealing times the films showed signs of dewetting where segments of the adsorbed film were removed from the substrate (dewetting by desorption). The dependence of the surface roughness of the PBAC surface on annealing time also confirmed that the films annealed at highest temperatures for the longest times desorbed from the substrate.
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 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.
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.
Ergot alkaloids are a group of mycotoxins occurring in products derived from various grasses (e.g., rye) and have been regulated in the EU recently. The new maximum levels refer to the sum of the six most common ergot alkaloids in their two stereoisomeric forms in different food matrices. Typically, these twelve compounds are individually quantified via HPLC-MS/MS or -FLD and subsequently summed up to evaluate food safety in a time-consuming process. Since all these structures share the same ergoline backbone, we developed a novel sum parameter method (SPM) targeting all ergot alkaloids simultaneously via lysergic acid hydrazide. After extraction and clean-up, in analogy to the current European standard method EN 17425 (ESM) for ergot alkaloid quantitation, the samples were derivatized by an optimized hydrazinolysis protocol, which allowed quantitative conversion after 20 min at 100 °C. The new SPM was evaluated against another established HPLC-FLD-based method (LFGB) and the HPLC-MS/MS-based ESM using six naturally contaminated rye and wheat matrix reference materials. While the SPM provided comparable values to the ESM, LFGB showed deviating results. Determined recovery rates, limits of detection and quantification of all three employed methods confirm that the new SPM is a promising alternative to the classical approaches for ergot alkaloid screening in food.
In this work, we employed glow discharge optical emission spectrometry (GD-OES) depth profiling as a fast and semi-quantitative method to investigate the aluminum (Al) current collector degradation in commercial lithium cobalt oxide (LCO) pouch cells with no Al2O3 pretreatment. After battery aging, a heterogeneous deposit was found on the surface of the cathode. Gray hotspot areas within an extensive pale white region were formed. Consistent with energy dispersive X-ray (EDX) analysis of micro-cross sections milled via targeted focused ion beam (FIB), an Al-containing layer of approximately 3 µm can be observed using GD-OES. We attribute one main cause of this layer is the degradation of the Al current collector. The nonuniform growth of this layer was investigated by performing GD-OES depth profiling at different in-plane positions. We found that the gray area has a higher mass concentration of Al, probably in metallic form, whereas the white area was probably covered more homogeneously with Al2O3, resulting from the inhomogeneous distribution of the pitting positions on the current collector. Compared to FIB-EDX, GD-OES enables a faster and more convenient depth profile analysis, which allows the more productive characterization of lithium-ion batteries (LIBs), and consequently benefits the development of preferable battery materials.
NMR is becoming increasingly popular for the investigation of building materials as it is a non-invasive technology that does not require any sample preparation nor causes damage to the material. Depending on the specific application it can offer insights into properties like porosity and spatial saturation degree as well as pore structure. Moreover it enables the determination of moisture transport properties and the (re-)distribution of internal moisture into different reservoirs or chemical phases upon damage and curing. However, as yet most investigations were carried out using devices originally either designed for geophysical applications or the analysis of rather homogeneous small scale (< 10 mL) samples. This paper describes the capabilities of an NMR tomograph, which has been specifically optimized for the investigation of larger, heterogeneous building material samples (diameters of up to 72 mm, length of up to 700 mm) with a high flexibility due to interchangeable coils allowing for a high SNR and short echo times (50 - 80 m s).
Comparing the performance of molecular and nanoscale luminophores and luminescent microand nanoparticles and estimating achievable signal amplitudes and limits of detection requires a standardizable intensity scale. This initiated the development of the relative MESF (number of molecules of equivalent soluble fluorochromes) and ERF (equivalent reference fluorophores) scales for flow cytometry and fluorescence microscopy. Both intensity scales rely on fluorescence intensity values assigned to fluorescent calibration beads by an intensity comparison to spectrally closely matching fluorophore solutions of known concentration using a spectrofluorometer. Alternatively, the luminophore or bead brightness (B) can be determined that equals the product of the absorption cross section (σa) at the excitation wavelength (σa(λex)) and the photoluminescence quantum yield (Φpl).
Thereby, an absolute scale based on fundamental and measurable spectroscopic properties can be realized which is independent of particle size, material, and luminophore staining or labeling density and considers the sensitivity of the optical properties of luminophores to their environment. Aiming for establishing such a brightness scale for light-scattering dispersions of luminescent particles with sizes exceeding a few ten nanometers, we demonstrate how the brightness of quasi-monodisperse 25 nm, 100 nm, and 1 μm sized polystyrene particles (PSP), loaded with two different dyes in varying concentrations, can be obtained with a single custom-designed integrating sphere setup that enables the absolute determination of Φpl and transmittance and diffuse reflectance measurements. The resulting Φpl, σa(λex), imaginary parts of the refractive index, and calculated B values of these samples are given in dependence of the number of incorporated dye molecule per particle. Finally, a unitless luminescence efficiency (LE) is defined allowing for the direct comparison of luminescence efficiencies of particles with different sizes.
Optimizing the Green Synthesis of ZIF-8 by Reactive Extrusion Using In Situ Raman Spectroscopy
(2023)
We report the scale-up of a batch solid synthesis of zeolitic imidazolate framework-8 (ZIF-8) for reactive extrusion. The crystalline product forms in the extruder directly under the mixture of solid 2-methylimidazole and basic zinc carbonate in the presence of a catalytic amount of liquid. The process parameters such as temperature, liquid type, feeding rate, and linker excess were optimized using the setup specifically designed for in situ Raman spectroscopy. Highly crystalline ZIF-8 with a Brunauer–Emmett–Teller (BET) surface area of 1816 m2 g–1 was quantitatively prepared at mild temperature using a catalytic amount of ethanol and a small excess of the linker. Finally, we developed a simple and comprehensive approach to evaluating the environmental friendliness and scalability of metal–organic framework (MOF) syntheses in view of their large-scale production.
Photodynamic therapy (PDT) used for treating cancer relies on the generation of highly reactive oxygen species, for example, singlet oxygen 1O2, by light-induced excitation of a photosensitizer (PS) in the presence of molecular oxygen, inducing DNA damage in close proximity of the PS. Although many precious metal complexes have been explored as PS for PDT and received clinical approval, only recently, the potential of photoactive complexes of nonnoble metals as PS has been discovered. Using the DNA origami technology that can absolutely quantify DNA strand break cross sections, we assessed the potential of the luminescent transition metal complex [Cr(ddpd)2]3+ (ddpd=N,N’-dimethyl-N,N’-dipyridine-2-ylpyridine-2,6-diamine) to damage DNA in an air-saturated aqueous environment upon UV/Vis illumination. The quantum yield for strand breakage, that is, the ratio of DNA strand breaks to the number of absorbed photons, was determined to 1–4%, indicating efficient transformation of photons into DNA strand breaks by [Cr(ddpd)2]3+.
This article describes the elaboration and characterization of diethylphosphonate-containing polymers coated electrodes as sensors for the detection of heavy metalstraces, by electrochemical impedance spectroscopy. Diethylphosphonate groupswere chosen as heavy metals binding sites. Two different series of polymers bearingthese anchoring groups were synthesized. Whereas the diethylphosphonate groupsare directly incorporated in the aromatic macromolecular chain in some polymers, analiphatic spacer is removing the chelating site from the polymer backbone in others.The influence of the macromolecular structure on the sensing response was studied,especially for the detection of Pb2+,Ni2+,Cd2+and Hg2+. Polymer P6, including thehigher amount of diethylphosphonate groups removed from the polymer chain by ashort alkyl spacer gave the higher sensitivity of detection of lead ions, with a detec-tion limit of 50 pM
Wavefield measurements by a scanning laser Doppler vibrometer are generally carried out in a cartesian coordinate. As a piezoelectric transducer generates Lamb waves following radial paths, the use of a polar coordinate can be a suitable alternative to the use of a cartesian coordinate. Therefore, in the proposed method, using a single transducer placed on the center of the specimen, the measured wavefields are transformed into polar coordinates, making several identical radial line inspections from the center in a direction of incident waves. Taking advantage of the properties of the polar coordinates, a signal processing technique is proposed through a frequency-wavenumber filtering process in these coordinates. In this technique, by using proper filters, unwanted wave modes of the incident wave along with all reflected waves are filtered out. In addition, the conventional features of RMS and Euclidean distance are adapted for the polar coordinate system to image the bonded plate. The proposed signal processing and damage imaging are first introduced through a numerical simulation. Then, the performance of the proposed technique is presented by experimental measurements of two specimens including adhesively bonded carbon fiber-reinforced plastic composite plates and bonded aluminum plates.
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.
Accessing radiation damage to biomolecules on the nanoscale by particle-scattering simulations
(2023)
Radiation damage to DNA plays a central role in radiation therapy to cure cancer. The physico-chemical and biological processes involved encompass huge time and spatial scales. To obtain a comprehensive understanding on the nano and the macro scale is a very challenging tasks for experimental techniques alone. Therefore particle-scattering simulations are often applied to complement measurements and aide their interpretation, to help in the planning of experiments, to predict their outcome and to test damage models. In the last years, powerful multipurpose particle-scattering framework based on the Monte-Carlo simulation (MCS) method, such as Geant4 and Geant4-DNA, were extended by user friendly interfaces such as TOPAS and TOPAS-nBio. This shifts their applicability from the realm of dedicated specialists to a broader range of scientists. In the present review we aim to give an overview over MCS based approaches to understand radiation interaction on a broad scale, ranging from cancerous tissue, cells and their organelles including the nucleus, mitochondria and membranes, over radiosensitizer such as metallic nanoparticles, and water with additional radical scavenger, down to isolated biomolecules in the form of DNA, RNA, proteins and DNA-protein complexes. Hereby the degradation of biomolecules by direct damage from inelastic scattering processes during the physical stage, and the indirect damage caused by radicals during the chemical stage as well as some parts of the early biological response is covered. Due to their high abundance the action of hydroxyl radicals (•OH) and secondary low energy electrons (LEE) as well as prehydrated electrons are covered in additional detail. Applications in the prediction of DNA damage, DNA repair processes, cell survival and apoptosis, influence of radiosensitizer on the dose distribution within cells and their organelles, the study of linear energy transfer (LET), the relative biological effectiveness (RBE), ion beam cancer therapy, microbeam radiation therapy (MRT), the FLASH effect, and the radiation induced bystander effect are reviewed.
Thermo-Desorption Gas Chromatography-Mass Spectrometry (TD-GC-MS) was used to investigate the thermal degradation of two different polyurethanes (PU). PU samples were heated at different heating rates and the desorbed products were collected in a cold injection system and thereafter submitted to GC-MS. Prospects and limitations of the detection and quantification of semi-volatile degradation products were investigated. A temperature dependent PU depolymerization was
found at temperatures above 200 °C proved by an increasing release of 1,4-butanediol and methylene diphenyl diisocyanate (MDI) representing the main building blocks of both polymers. Their release was monitored quantitatively based on external calibration with authentic compounds. Size Exclusion Chromatography (SEC) of the residues obtained after thermodesorption confirmed the initial competitive degradation mechanism indicating an equilibrium of crosslinking and depolymerization as previously suggested. Matrix-Assisted Laser Desorption Ionization (MALDI) mass spectrometry of SEC fractions of thermally degraded PUs provided additional hints on degradation mechanism.
Using fluorescence-guided surgery (FGS) to cytoreductive surgery helps achieving complete resection of microscopic ovarian tumors. The use of visible and NIR-I fluorophores has led to beneficial results in clinical trials; however, involving NIR-II dyes seems to outperform those benefits due to the deeper tissue imaging and higher signal/noise ratio attained within the NIR-II optical window. In this context, we developed NIR-II emitting dyes targeting human epidermal growth factor receptor 2 (HER2)-positive ovarian tumors by coupling water-soluble NIR-II aza-BODIPY dyes to the FDA-approved anti-HER2 antibody, namely, trastuzumab. These bioconjugated NIR-II-emitting dyes displayed a prolonged stability in serum and a maintained affinity toward HER2 in vitro. We obtained selective targeting of HER2 positive tumors (SKOV-3) in vivo, with a favorable tumor accumulation. We demonstrated the fluorescence properties and the specific HER2 binding of the bioconjugated dyes in vivo and thus their potential for NIR-II FGS in the cancer setting.