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Increasing contamination of environmental waters with pharmaceuticals represents an emerging threat for the drinking water quality and safety. In this regard, fast and reliable analytical methods are required to allow quick countermeasures in case of contamination. Here, we report the development of a magnetic bead-based immunoassay (MBBA) for the fast and cost-effective determination of the analgesic diclofenac (DCF) in water samples, based on diclofenac-coupled magnetic beads and a robust monoclonal anti-DCF antibody. A novel synthetic strategy for preparation of the beads resulted in an assay that enabled for the determination of diclofenac with a significantly lower limit of detection (400 ng/L) than the respective enzyme-linked immunosorbent assay (ELISA). With shorter incubation times and only one manual washing step required, the assay demands for remarkably shorter time to result (< 45 min) and less equipment than ELISA. Evaluation of assay precision and accuracy with a series of spiked water samples yielded results with low to moderate intra- and inter-assay variations and in good agreement with LC–MS/MS reference analysis. The assay principle can be transferred to other, e.g., microfluidic, formats, as well as applied to other analytes and may replace ELISA as the standard immunochemical method.
An in-depth insight into the chemistry and nature of the individual chemical bonds is essential for understanding materials. Bonding analysis is thus expected to provide important features for large-scale data analysis and machine learning of material properties. Such chemical bonding information can be computed using the LOBSTER software package, which post-processes modern density functional theory data by projecting the plane wave-based wave functions onto an atomic orbital basis. With the help of a fully automatic workflow, the VASP and LOBSTER software packages are used to generate the data. We then perform bonding analyses on 1520 compounds (insulators and semiconductors) and provide the results as a database. The projected densities of states and bonding indicators are benchmarked on standard density-functional theory computations and available heuristics, respectively. Lastly, we illustrate the predictive power of bonding descriptors by constructing a machine learning model for phononic properties, which shows an increase in prediction accuracies by 27% (mean absolute errors) compared to a benchmark model differing only by not relying on any quantum-chemical bonding features.
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.
This paper describes a new ultrasonic measuring device called “W-Box”. It was developed based on the requirements of the DFG Forschergruppe (research unit) CoDA for a portable device for monitoring of concrete specimens, models and actual structures using embedded ultrasonic transducers as well as temperature and humidity sensors. The W-Box can send ultrasonic pulses with a variable frequency of 50–100 kHz to one selectable transducer and records signals from up to 75 multiplexed channels with a sample rate of 1 MHz and a resolution of 14 bits. In addition, it measures temperature and humidity with high accuracy, adjustable amplification, restarts automatically after a power failure and can be fully controlled remotely. The measured data are automatically stored locally on-site data quality checks and transferred to remote servers. The comparison of the W-Box with a laboratory setup using commercial devices proves that it is equally reliable and precise, at much lower cost. The W-Box also shows that their measurement capacities, with the used embedded ultrasonic transducers, can reach above 6 m in concrete.
Using the Modular Reliability Model the three different main influencing elements, i.e. intrinsic capability (IC), application parameters (AP) and the human factors (HF), are, in the first instance, investigated separately. The intrinsic capability stands for the pure physical-technological process of the signal detection caused by the waves or the rays from a material defect in the presence of noise (driven by the material and the devices). This intrinsic capability is the upper bound of the possible reliability. Already when measuring this intrinsic capability for thick walled components the original one-parameter POD must be extended to a multiparameter POD, where, in addition to the defect size, a number of additional physical parameters, such as the grain size distribution (or attenuation), defect depth, and angle or surface roughness, must be considered. For real life cycle assessments it is necessary to evaluate the signal response from real defects. The industrial application factors, e.g. coupling conditions, limited accessibility, heat and environmental vibrations, diminish the reliability. The amount of reduction can be determined quantitatively, if the underlying conditions are controlled. In case they are not controlled it is necessary to count for a fluctuation in the reliability in the field anyway. The third group of important influencing factors are the human factors, which do not only cover the individual performance capability of the inspectors but also the design of the working place,the procedure, the teamwork quality, interaction with systems, the organization, and finally, the relationship between the companies involved in the inspection process and to which extend the responsible parties are aware of it. When comparing an “ideal inspection” with a “real inspection” it is worth while to look how the existing practices, rules and standards support reliable testing and where the “delta” is. In the context of vigor, with respect to the industrial end user, it needs to be shown how the level of reliability of NDE, influenced by the different factors, has an impact on acceptance or rejection of safety critical parts.
In this contribution, we present a physically motivated heat source model for the numerical modeling of laser beam welding processes. Since the calibration of existing heat source models, such as the conic or Goldak model, is difficult, the representation of the heat source using so-called Lamé curves has been established, relying on prior Computational Fluid Dynamics (CFD) simulations.
Lamé curves, which describe the melting isotherm, are used in a subsequent finite-element (FE) simulation to define a moving Dirichlet boundary condition, which prescribes a constant temperature in the melt pool. As an alternative to this approach, we developed a physically motivated heat source model, which prescribes the heat input as a body load directly. The new model also relies on prior CFD simulations to identify the melting isotherm. We demonstrate numerical results of the new heat source model on boundary-value problems from the field of laser beam welding and compare it with the prior CFD simulation and the results of the Lamé curve model and experimental data.
Virulence determines the impact a pathogen has on the fitness of its host, yet current understanding of the evolutionary origins and causes of virulence of many pathogens is surprisingly incomplete. Here, we explore the evolution of Marek’s disease virus (MDV), a herpesvirus commonly afflicting chickens and rarely other avian species. The history of MDV in the 20th century represents an important case study in the evolution of virulence. The severity of MDV infection in chickens has been rising steadily since the adoption of intensive farming techniques and vaccination programs in the 1950s and 1970s, respectively. It has remained uncertain, however, which of these factors is causally more responsible for the observed increase in virulence of circulating viruses. We conducted a phylogenomic study to understand the evolution of MDV in the context of dramatic changes to poultry farming and disease control. Our analysis reveals evidence of geographical structuring of MDV strains, with reconstructions supporting the emergence of virulent viruses independently in North America and Eurasia. Of note, the emergence of virulent viruses appears to coincide approximately with the introduction of comprehensive vaccination on both continents. The time-dated phylogeny also indicated that MDV has a mean evolutionary rate of ~1.6 × 10−5 substitutions per site per year. An examination of gene-linked mutations did not identify a strong association between mutational variation and virulence phenotypes, indicating that MDV may evolve readily and rapidly under strong selective pressures and that multiple genotypic pathways may underlie virulence adaptation in MDV.
A novel photoswitchable rotaxane was synthesised and its switching behaviour in solution was analysed with NMR and UV-Vis. A monolayer of rotaxanes was deposited on glass surfaces and the on-surface photoswitching was investigated. Angle-resolved NEXAFS spectra revealed a preferential orientation that reversibly changes upon switching.
A phenomenological criterion for an optical assessment of PE-HD fracture surfaces obtained from FNCT
(2021)
The full-notch creep test (FNCT) is a common test method to evaluate the environmental stress cracking (ESC) behavior of high-density polyethylene (PE-HD), e.g. for container materials. The test procedure as specified in ISO 16770 provides a comparative measure of the resistance against ESC using the time to failure of PE-HD specimens under constant mechanical load in a well-defined liquid test environment. Since the craze-crack damage mechanism underlying the ESC phenomenon is associated with brittle failure, the occurrence of a predominantly brittle fracture surface is a prerequisite to consider an FNCT measurement as representative for ESC, i.e. a time to failure dominated by craze-crack propagation.
The craze-crack propagation continuously reduces the effective residual cross-sectional area of the specimen during the test, which results in a corresponding increase of the effective mechanical stress. Thus, a transition to ductile shear deformation is inevitable at later stages of the test, leading usually to a pronounced central ligament.
Therefore, an optical evaluation of FNCT fracture surfaces concerning their brittleness is essential. An enhanced imaging analysis of FNCT fracture surfaces enables a detailed assessment of craze-crack Propagation during ESC. In this study, laser scanning microscopy (LSM) was employed to evaluate whether FNCT fracture surfaces are representative with respect to craze-crack propagation and ESC. Based on LSM height data, a phenomenological criterion is proposed to assess the validity of distinct FNCT measurements. This criterion is
supposed to facilitate a quick evaluation of FNCT results in practical routine testing. Its applicability is verified on a sample basis for seven different commercial PE-HD container materials.
The amount of data generated worldwide is constantly increasing. These data come from a wide variety of sources and systems, are processed differently, have a multitude of formats, and are stored in an untraceable and unstructured manner, predominantly in natural language in data silos. This problem can be equally applied to the heterogeneous research data from materials science and engineering. In this domain, ways and solutions are increasingly being generated to smartly link material data together with their contextual information in a uniform and well-structured manner on platforms, thus making them discoverable, retrievable, and reusable for research and industry. Ontologies play a key role in this context. They enable the sustainable representation of expert knowledge and the semantically structured filling of databases with computer-processable data triples.
In this perspective article, we present the project initiative Materials-open-Laboratory (Mat-o-Lab) that aims to provide a collaborative environment for domain experts to digitize their research results and processes and make them fit for data-driven materials research and development. The overarching challenge is to generate connection points to further link data from other domains to harness the promised potential of big materials data and harvest new knowledge.