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Diclofenac (DCF) is a non-steroidal anti-inflammatory drug (NSAID) with analgetic, anti-inflammatory, and antipyretic properties. The mechanism of action of diclofenac, like that of other NSAIDs, involves inhibition of cyclooxygenase (COX-1 and COX-2). Another pharmacological effect is preventing of prostaglandin synthesis in vitro. Prostaglandins are mediators of inflammation, because diclofenac is an inhibitor of prostaglandin synthesis.
A method has been developed to analyse for diclofenac (DCF) in the milk.
The investigation of metabolic fluxes and metabolite distributions within cells by means of tracer molecules is a valuable tool to unravel the complexity of biological systems. Technological advances in mass spectrometry (MS) technology such as atmospheric pressure chemical ionization (APCI) coupled with high resolution (HR), not only allows for highly sensitive analyses but also broadens the usefulness of tracer‐based experiments, as interesting signals can be annotated de novo when not yet present in a compound library. However, several effects in the APCI ion source, i.e., fragmentation and rearrangement, lead to superimposed mass isotopologue distributions (MID) within the mass spectra, which need to be corrected during data evaluation as they will impair enrichment calculation otherwise. Here, we present and evaluate a novel software tool to automatically perform such corrections. We discuss the different effects, explain the implemented
algorithm, and show its application on several experimental datasets. This adjustable tool is available as an R package from CRAN.
The Scaled Boundary Finite Element Method (SBFEM) for prismatic structures is an efficient method for the simulation of acoustic behavior. Hence a further development of the method is of great interest. The wave propagation can be calculated for isotropic and anisotropic materials in solids. As for many applications the acoustic behavior in fluids and the behavior in case of fluid-structure interaction (FSI) is subject of research, the implementation of a fluid model in SBFEM for prismatic structures is needed. In case of FSI the coupling between fluid and solid domains can be performed without additional effort when describing both domains in the same variables. Hence a displacement-based fluid description is used. As the discretized formulation leads to spurious modes, a penalty method to suppress the unphysical behavior is chosen. To validate the derived model a comparison with analytical solutions of purely fluid domains is made. As to verify that in case of FSI the model shows the right behavior, dispersion curves of water-filled pipes are calculated and compared to results obtained with Comsol.
The Scaled Boundary Finite Element Method is known as an efficient method for the simulation of ultrasonic wave propagation. As to investigate acoustic wave behavior in case of fluid‐structure interaction, a fluid model is implemented in the SBFEM for prismatic structures. To omit coupling terms a displacement‐based formulation is used. Spurious modes, which occur in the solution, are suppressed using a penalty parameter. To verify this formulation dispersion curves obtained with Comsol Multiphysics are compared to results of SBFEM. The results of both methods are in very good agreement
A general method to carry out the fluorination of metal oxides with poly(tetrafluoroethylene) (PTFE, Teflon) waste by spark plasma sintering (SPS) on a minute scale with Teflon is reported. The potential of this new approach is highlighted by the following results. i) The tantalum oxyfluorides Ta3O7F and TaO2F are obtained from plastic scrap without using toxic or caustic chemicals for fluorination. ii) Short reaction times (minutes rather than days) reduce the process time the energy costs by almost three orders of magnitude. iii) The oxyfluorides Ta3O7F and TaO2F are produced in gram amounts of nanoparticles. Their synthesis can be upscaled to the kg range with industrial sintering equipment. iv) SPS processing changes the catalytic properties: while conventionally prepared Ta3O7F and TaO2F show little catalytic activity, SPS-prepared Ta3O7F and TaO2F exhibit high activity for photocatalytic oxygen evolution, reaching photoconversion efficiencies up to 24.7% and applied bias to photoconversion values of 0.86%. This study shows that the materials properties are dictated by the processing which poses new challenges to understand and predict the underlying factors.
Synthetic peptide pools are used in antigen-specific T-cell assays, which are an important part in vaccine and immunotherapeutic clinical trials. As the analytical characterization is challenging due to the similarity of the single peptides or is expensive due to isotope labeled standards, usually only a pre-characterization of the single peptides is performed. However, a regular quality control of the peptide mix would be highly desirable. Therefore, a cost-efficient high performance liquid chromatography-high resolution mass spectrometry (HPLC-HRMS) method for quality control of a model peptide pool is developed.
Peptides were synthesized using peptides&elephants proprietary libraries of individual peptides (LIPS) technology and purified by reversed-phase chromatography to > 90% each. The lyophilized single peptides were combined to a model peptide pool and analyzed by reversed-phase high-performance capillary liquid chromatography coupled to an orbitrap mass spectrometer. Separation was performed on a capillary reversed phase column (2 μm, ID x L 300 μm x 150 mm) with a linear gradient of acetonitrile + 0,05% trifluoroacetic acid.
After optimizing the injection mode, the gradient elution, the temperature and the additives a model peptide pool was separated. The extracted ion chromatogram (XIC) was studied to confirm the exact masses.
By combination of capillary HPLC and HRMS a new cost-efficient quality control method could be developed for the separation and identification of complex synthetic peptide pools.
The common characterization and identification of pollen is a time-consuming task that mainly relies on microscopic determination of the genus-specific pollen morphology. A variety of spectroscopic and spectrometric approaches have been proposed to develop a fast and reliable pollen identification using specific molecular information. Amongst them, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) shows a high potential for the successful investigation of such complex biological samples. Based on optimized MALDI sample preparation using conductive carbon tape, the application of multivariate statistics (e.g. principal components analysis, PCA) yields an enormous improvement concerning taxonomic classification of pollen species compared to common microscopic techniques.
Since multivariate evaluation of the recorded mass spectra is of vital importance for classification, it’s helpful to implement the applied sequence of standard Matlab functions into a graphical user interface (GUI). In this presentation, a stand-alone application (GUI) is shown, which provides multiple functions to perform fast multivariate analysis on multiple datasets. The use of a GUI enables a first overview on the measured dataset, conducts spectral pretreatment and can give classification information based on HCA and PCA evaluation. Moreover, it can be used to improve fast spectral classification and supports the development of a simple routine method to identify pollen based on mass spectrometry.
The very strong Lewis acid aluminium chlorofluo-ride (ACF) was loaded with anhydrous HF. The interactionbetween the surface of the catalyst and HF was investigatedusing a variety of characterization methods, which revealed he formation of polyfluorides. Moreover, the reactivity ofthe HF-loaded ACF towards the hydrofluorination of alkyneswas studied.
This paper presents an approach to the automatic enrichment of finite elements in the vicinity of a stress singularity. The enrichment consists of semi-analytical singular modes constructed using the Scaled Boundary Finite Element Method (SBFEM).
In contrast to analytical methods, the SBFEM provides modes for inhomogeneous and anisotropic materials without additional effort. The finite element basis can be of arbitrary order and remains unaltered by the enrichment. The approach requires enrichment in only one layer of elements around a node. Due to the compatibility of SBFEM with FEM, there is no Need for transitional elements, and there are no parasitic terms. The approach is tested for several benchmark problems. The stress intensity factors are computed based on techniques inspired by the SBFEM. The proposed procedure is compared to a Standard finite element implementation and shows a significant improvement in the error of the displacement field for problems involving singular stresses.
In our (dramatically understaffed) X-ray scattering laboratory, developing a systematic, holistic methodology1 let us provide scattering and diffraction information for more than 2100 samples for 200+ projects led by 120+ collaborators over the last five years. Combined with universal, automat-ed data correction pipelines, as well as our analysis and simulation software, this led to more than 40 papers2 in the last 5 years with just over 2 full-time staff members.
While this approach greatly improved the consistency of the results, the consistency of the samples and sample series provided by the users was less reliable nor necessarily reproducible. To address this issue, we built an EPICS-controlled, modular synthesis platform to add to our laboratory. To date, this has prepared over 1200 additional (Metal-Organic Framework) samples for us to meas-ure, analyse and catalogue. By virtue of the automation, the synthesis of these samples is automat-ically documented in excruciating detail, preparing them for upload and exploitation in large-scale materials databases alongside the morphological results obtained from the automated X-ray scat-tering analysis.
Having developed these proof-of-concepts, we find that the consistency of results are greatly im-proved by virtue of their reproducibility, hopefully adding to the reliability of the scientific findings as well. Additionally, the nature of the experiments has changed greatly, with much more emphasis on preparation and careful planning. This talk will discuss the advantages and disadvantages of this highly integrated approach and will touch upon upcoming developments.
Modeling is an important tool for understanding a physical phenomenon. It helps to interpret results of experiments and optimize experimental parameters for obtaining a desirable result. Modeling laser induced plasma is beneficial for many scientific and industrial fields, e.g., analytical chemistry, pulsed laser deposition, plasma enhanced chemical vapor deposition, laser welding, additive manufacturing etc. In this presentation, a personal experience in development of a physical model of laser induced plasma will be given in a chronological sequence starting from early 2000th and until now.
Over the time, the model evolved from its simple analytical form that described plasma emission spectra to its current numerical form that describes plasma dynamics, chemistry, and interaction with a substrate surface. Several examples will be given for the application of the model to practical problems such as spectroscopic chemical analysis, plasma enhanced chemical vapor deposition, and surface modification by laser ablation.
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.
Natural and synthetic estrogens are key endocrine-disrupting chemicals. Despite occurring at ultra-trace levels (below ng L-1), it is believed that they are contributing to an increase in feminized fish and other endocrine disruptive effects, and hence, their inclusion in the Watch list was not unexpected. One of the main sources ofestrogens to surface waters is wastewater effluent. Once in surface waters, they can partition into different compartments, i.e., water and suspended particulate matter. For this reason, there is an urgent need for a methodology to monitor estrogen levels below the environmental quality standards (EQS) set by the Water Framework Directive requirements.
In this study, a precise and accurate gas chromatography-mass spectrometry method (GC-MS/MS) for the analysis of estrone (E1), 17β-estradiol (17β-E2), 17α-estradiol (17α- E2), 17-alpha-ethinylestradiol (EE2), and estriol (E3) in whole water samples with ng L-1 limit of quantification (LOQ) was developed and validated in accordance with CEN/TS 16800:2020 guidelines.
Statistic process control as well as process capability demand for calibrated determination of layer thicknesses in various industries, e.g. automotive, aerospace, microelectronics manufacturing. Calibration requires well know and well characterized samples. A calibration laboratory accredited according to DIN EN ISO 17025 has the objective to distribute standards traceable to SI units to industrial laboratories for quality control of manufacturing of various products. Especially, the thickness determination of thin metallic coatings e.g. from galvanic processes or layer deposition using X-Ray Fluorescence can be significantly improved by customized calibration samples. This is essential as the measurement uncertainty directly correlates to the capability performing reliable control of processes with high yield. For calibration laboratories, the validation of results using round robins and the direct comparison to national metrology institutes is a prerequisite to demonstrate the competence to perform calibration services.
In this paper a strategy to obtain traceability and validation for thin alloy layers as well as first results are presented. The combined use of the accredited method for determination of mass per area from measurement of mass and area combined with standard free X-Ray Fluorescence as well as chemical analysis of dissolved samples with thin layers is deployed for material systems as NixZn1-x as well as NixP1-x. The obtained results are compared to reference free X-Ray Fluorescence at the BESSY II laboratories of Physikalisch-Technische Bundesanstalt. An excellent agreement of the obtained measured values as mass per unit area and alloy concentrations from the different applied methods within the measurement uncertainty was observed for NixP1-x showing the successful performed traceability of the calibration samples to SI units in combination with a validation of results by national metrology institutes and the round robin approach.
The presence of microplastic (MP) particles in aquatic environments raised concern About possible enrichment of organic and inorganic pollutants due to their specific surface and chemical properties. In particular the role of metals within this context is still poorly understood. Therefore, the aim of this work was to develop a fully validated acid digestion protocol for metal analysis in different polymers, which is a prerequisite to study such interactions.
The proposed digestion protocol was validated using six different certified reference materials in the microplastic size range consisting of polyethylene, polypropylene, acrylonitrile butadiene styrene and polyvinyl chloride. As ICP-MS/MS enabled time-efficient, sensitive and robust analysis of 56 metals in one measurement, the method was suitable to provide mass fractions for a multitude of other elements beside the certified ones (As, Cd, Cr, Hg, Pb, Sb, Sn and Zn). Three different microwaves, different acid mixtures as well as different temperatures in combination with different hold times were tested for optimization purposes.
With the exception of Cr in acrylonitrile butadiene styrene, recovery rates obtained using the optimized protocol for all six certified reference materials fell within a range from 95.9% ± 2.7% to 112% ± 7%. Subsequent optimization further enhanced both precision and recoveries ranging from 103% ± 5% to 107 ± 4% (U; k = 2 (n = 3)) for all certified metals (incl. Cr) in acrylonitrile butadiene styrene. The results clearly show the analytical challenges that come along with metal analysis in chemically resistant plastics. Addressing specific analysis Tools for different sorption scenarios and processes as well as the underlying kinetics was beyond this study’s scope. However, the future application of the two recommended thoroughly validated total acid digestion protocols as a first step in the direction of harmonization of metal analysis in/on MP will enhance the significance and comparability of the generated data. It will contribute to a better understanding of the role of MP as vector for trace metals in the environment.
Attenuation of ultrasonic signals in concrete has the potential to carry much information about the microstructure of the material. In this work a series of concrete specimens of varying porosities and pore size distributions were internally imaged with x-ray computed tomography (CT), and then subsequently examined with throughtransmission ultrasound. The CT images were used to quantify both capillary porosity of cement paste as well as internal interfaces that are likely to produce elastic wave scattering. Ultrasound signals were represented as a diffusion process such that absorption and scattering attenuation could be isolated. As implemented, the diffusion model was a poor predictor of capillary porosity, while diffusivity was a reasonable predictor of scattering interfaces. Diffusivity was found to scale extremely well with small scale porosity, which made it a good predictor of compressive strength.
Reliability assessment of Structural Health Monitoring (SHM) systems
poses new challenges pushing the research community to address many questions which are still open. For guided wave-based SHM it is not possible to evaluate the system performance without taking into account the target structure and applied system parameters. This range of variables would result in countless measurements.
Factors like environmental conditions, structural dependencies and wave characteristics demand novel solutions for performance analysis of SHM systems compared to those relying on classical non-destructive evaluation. Such novel approaches typically require model-assisted investigations which may not only help to explain and understand performance assessment results but also enable complete studies without costly experiments. Within this contribution, a multi input multi output approach using a sparse transducer array permanently installed on a composite structure to excite and sense guided waves is considered. Firstly, the method and the analysis of path-based performance assessment are presented considering an open-access dataset from the Open Guided Wave platform. Then, a performance analysis of a guided wave-based SHM system using Probability of Detection is presented. To explain some unexpected results, the model-assisted investigations are used to understand the physical phenomena of wave propagation in the test specimen including the interaction with damage. Finally, issues and future steps in SHM systems’ performance assessment and their development are discussed.
The presentation provides an overview and introduction to the need and drivers for the digital transformation of the quality infrastructure (QI). It illustrates the tools and processes that are the fundation of a digital QI and how the initiatve QI-Digital aims at developing accordant solutions. Special emphasis is given to the pilot projects at BAM.
Engineered nanomaterials (NM) with their large surface-to-volume ratios and their for some materials observed size-dependent functional properties are of increasing relevance for current and future developments in various fields such as medical and pharmaceutical industry, computing and electronics or food and consumer products. The performance and safety of NM are determined by the sum of their intrinsic physicochemical properties. Especially, the particle surface chemistry, which is largely controlled by the chemical nature and density of functional groups (FG) and ligands, is an important key driver for NM performance, stability, and processibility as well as the interaction of NM with the environment. Thus, methods for FG quantification can foster the sustainable development of functional and safe(r) NM.
Aiming at the development of simple, versatile, and multimodal tools for the quantification of many bioanalytically relevant FG and ligands, we investigated and compared various analytical methods commonly used for FG quantification. This includes electrochemical titration methods, dye-based optical assays, and other instrumental analytical techniques such as nuclear magnetic resonance and thermal analysis methods.
The potential of our multimodal approach for FG quantification was demonstrated for commercial and custom-made polymeric and silica particles of varying FG, used as optical pH sensors. In the future, our strategy can contribute to establish multi-method characterization strategies to provide a more detailed picture of the structure-properties relationship.