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Paper des Monats
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Against the backdrop of numerous security breaches and cyber-attacks, organizations need to take measures to secure their data and information. However, the well-known management system standard ISO/IEC 27001 for information security has shown a lower adoption rate – in terms of annual ISO survey data – than was previously expected by scholars and practitioners. Through the lens of Rogers' diffusion of innovation theory, we consider the adoption of ISO/IEC 27001 as a 'preventive innovation' and aim to identify factors that help gain a better understanding of its adoption. Therefore, we conducted a survey among German organizations on the use and impact of management system standards, explicitly distinguishing between organizations that implement ISO/IEC 27001 and those that are additionally certified against this standard. This study provides insights and contributes to an advanced understanding of motives, impacts, barriers, and useful measures to increase adoption of ISO/IEC 27001. Our findings may be useful to organizations considering the adoption of this management system standard, to certification bodies providing certification services, and to policymakers seeking means to improve information security in organizations.
The processes of hydrogen reduction of silicon and germanium chlorides under the conditions of high-frequency (40.68 MHz) counteracted arc discharge stabilized between two rod electrodes are investigated. The main gas-phase and solid products of plasma-chemical transformations are determined. Thermodynamic analysis of SiCl4 + H2 and GeCl4 + H2 systems for optimal process parameters was carried out. Using the example of hydrogen reduction of SiCl4 by the method of numerical modeling, gas-dynamic and thermal processes for this type of discharge are investigated. The impurity composition of gas-phase and solid reaction products is investigated. The possibility of single-stage production of high-purity Si and Ge mainly in the form of compact ingots, as well as high-purity chlorosilanes and trichlorogermane, is shown.
AbstractAir‐coupled ultrasonic testing (ACU) is a pioneering technique in non‐destructive testing (NDT). While contact testing and fluid immersion testing are standard methods in many applications, the adoption of ACU is progressing slowly, especially in the low ultrasonic frequency range. A main reason for this development is the difficulty of generating high amplitude ultrasonic bursts with equipment that is robust enough to be applied outside a laboratory environment. This paper presents the fluidic ultrasonic transducer as a solution to this challenge. This novel aeroacoustic source uses the flow instability of a sonic jet in a bistable fluidic switch to generate ultrasonic bursts up to 60 kHz with a mean peak pressure of 320 Pa. The robust design allows operation in adverse environments, independent of the operating fluid. Non‐contact through‐transmission experiments are conducted on four materials and compared with the results of conventional transducers. For the first time, it is shown that the novel fluidic ultrasonic transducer provides a suitable acoustic signal for NDT tasks and has potential of furthering the implementation of ACU in industrial applications.This article is protected by copyright. All rights reserved
In ultrasonic testing, material and structural properties of a specimen can be derived from the time-of-flight (ToF). Using signal features, such as the first peak or envelope maximum, to calculate the ToF is error-prone in multipath arrangements or dispersive and attenuating materials, which is not the case for the signal onset. Borrowing from seismology, researchers used the Akaike information criterion (AIC) picker to automatically determine onset times. The most commonly used formulation, Maeda's AIC picker, is reassessed and found to be based on inappropriate assumptions for signals often used in ultrasonic testing and dependent on arbitrary parameters. Consequently, an onset picker for ultrasonic through-transmission measurements is proposed, based on a spectral entropy criterion (SEC) to model the signal using the AIC framework. This SEC picker takes into account the spectral properties of the ultrasonic signal and is virtually free of arbitrary parameters. Synthetic and experimental data are used to compare the performance of SEC and AIC pickers. It is shown that the accuracy of onset picking is improved for densely sampled data.
AbstractHigh-strength aluminum alloys used in aerospace and automotive applications obtain their strength through precipitation hardening. Achieving the desired mechanical properties requires precise control over the nanometer-sized precipitates. However, the microstructure of these alloys changes over time due to aging, leading to a deterioration in strength. Typically, the size, number, and distribution of precipitates for a quantitative assessment of microstructural changes are determined by manual analysis, which is subjective and time-consuming. In our work, we introduce a progressive and automatable approach that enables a more efficient, objective, and reproducible analysis of precipitates. The method involves several sequential steps using an image repository containing dark-field transmission electron microscopy (DF-TEM) images depicting various aging states of an aluminum alloy. During the process, precipitation contours are generated and quantitatively evaluated, and the results are comprehensibly transferred into semantic data structures. The use and deployment of Jupyter Notebooks, along with the beneficial implementation of Semantic Web technologies, significantly enhances the reproducibility and comparability of the findings. This work serves as an exemplar of FAIR image and research data management.
Simulation-Assisted Augmentation of Missing Wedge and Region-of-Interest Computed Tomography Data
(2024)
This study reports a strategy to use sophisticated, realistic X-ray Computed Tomography (CT) simulations to reduce Missing Wedge (MW) and Region-of-Interest (RoI) artifacts in FBP (Filtered Back-Projection) reconstructions. A 3D model of the object is used to simulate the projections that include the missing information inside the MW and outside the RoI. Such information augments the experimental projections, thereby drastically improving the reconstruction results. An X-ray CT dataset of a selected object is modified to mimic various degrees of RoI and MW problems. The results are evaluated in comparison to a standard FBP reconstruction of the complete dataset. In all cases, the reconstruction quality is significantly improved. Small inclusions present in the scanned object are better localized and quantified. The proposed method has the potential to improve the results of any CT reconstruction algorithm.
This study investigates the sintering and crystallization behavior and kinetic of the bioactive glass (BG) 13–93 with nominal composition (in mol%): 54.6 SiO2 - 1.7 P2O3 - 22.1 CaO - 6.0 Na2O - 7.9 K2O - 7.7 MgO. Sintering and crystallization were investigated non-isothermally for various particle size fractions smaller than 315 μm as well as for bulk samples. Densification was not hindered by the presence of crystalline phases across all particle size fractions. Afterwards, wollastonite was found as the dominant crystal phase at higher temperature which resorb primary surface precipitation-like quartz crystallites. The growth direction shifts into volume when the sample surface is nearly covered. The crystal growth rate of wollastonite was calculated from the crystalline surface layer thickness measured during heating. The findings of this study are relevant for the high temperature processing of BG 13–93.
Knowledge representation in the Materials Science and Engineering (MSE) domain is a vast and multi-faceted challenge: Overlap, ambiguity, and inconsistency in terminology are common. Invariant (consistent) and variant (context-specific) knowledge are difficult to align cross-domain. Generic top-level semantic terminology often is too abstract, while MSE domain terminology often is too specific. In this paper, an approach how to maintain a comprehensive MSE-centric terminology composing a mid-level ontology–the Platform MaterialDigital Core Ontology (PMDco)–via MSE community-based curation procedures is presented. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics. Additionally, it demonstrates how the PMDco lowers development and integration thresholds. Moreover, the research highlights how to fuel it with real-world data sources ranging from manually conducted experiments and simulations with continuously automated industrial applications.
The usefulness of seven different Tin catalysts, Bismuth subsalicylate and Titan tetra(ethoxide) for the polycondensation of ethyl L-lactate (ELA) was examined at 150 °C/6 d. Dibutyltin bis(phenoxides) proved to be particularly effective. Despite the low reactivity of ELA, weight average molecular masses (Mw) up to 12 500 were found along with partial crystallization. Furthermore, polylactides (PLAs) of similar molecular masses were prepared via ELA-initiated ROPs of L-lactide by means of the four most effective polycondensation catalysts. The crystalline linear PLAs were annealed at 140 or 160 °C in the presence of these catalysts. The consequences of the transesterification reactions in the solid PLAs were studied by means of matrix-assisted laser desorption/ionization (MALDI TOF) mass spectrometry, gel permeation chromatography (GPC) and small-angle X-ray scattering (SAXS). The results indicate that polycondensation and formation of cycles proceed in the solid state via formation of loops on the surface of the crystallites. In summary, five different transesterification reactions are required to explain all results.
Manufacturing austenitic stainless steels (ASSs) using additive manufacturing is of great interest for cryogenic applications. Here, the mechanical and microstructural responses of a 316L ASS built by laser powder bed fusion were revealed by performing in situ neutron diffraction tensile tests at the low-temperature range (from 373 to 10 K). The stacking fault energy almost linearly decreased from 29.2 ± 3.1 mJm⁻² at 373 K to 7.5 ± 1.7 mJm⁻² at 10 K, with a slope of 0.06 mJm⁻²K⁻¹, leading to the transition of the dominant deformation mechanism from strain-induced twinning to martensite formation. As a result, excellent combinations of strength and ductility were achieved at the low-temperature range.
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.