Analytische Chemie
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The environmental fate of the frequently used broad-spectrum β-lactam antibiotic amoxicillin (AMX) is of high concern regarding the potential evolution of antimicrobial resistance (AMR). Moreover, it is known that AMX is prone to hydrolysis, yielding a variety of hydrolysis products (HPs) with yet unknown effects. Studies to identify those HPs and investigate their formation mechanisms have been reported but a long-term study on their stability in real water samples was missing. In this regard, we investigated the hydrolysis of AMX at two concentration levels in four distinct water types under three different storage conditions over two months. Concentrations of AMX and four relevant HPs were monitored by an LC-MS/MS method revealing pronounced differences in the hydrolysis rate of AMX in tap water and mineral water on the one hand (fast) and surface water on the other(slow). In this context, the occurrence, relative intensities, and stability of certain HPs are more dependent on the water type than on the storage condition. As clarified by ICP-MS, the main difference between the water types was the content of the metals copper and zinc which are supposed to catalyze AMX hydrolysis demonstrating an effective method to degrade AMX at ambient conditions.
To better understand the dynamics in hazardous environments, gas distribution mapping aims to map the gas concentration levels of a specified area precisely. Sampling is typically carried out in a spatially sparse manner, either with a mobile robot or a sensor network and concentration values between known data points have to be interpolated. In this paper, we investigate sequential deep learning models that are able to map the gas distribution based on a multiple time step input from a sensor network. We propose a novel hybrid convolutional LSTM - transpose convolutional structure that we train with synthetic gas distribution data. Our results show that learning the spatial and temporal correlation of gas plume patterns outperforms a non-sequential neural network model.
Simulating a Gas Source Localization Algorithm with Gas Dispersion Produced by Recorded Outdoor Wind
(2023)
This paper reports the use of the first gas dispersion simulator capable of introducing large wind fluctuations into simulations. The proposed simulator enables testing of a modification made to a gas source localization algorithm in a realistic scenario in order to study how the change affects it. Gas source localization in an outdoor environment is a challenging task mainly due to the complexity of the gas spread caused by the unpredictable nature of constantly changing wind. Therefore, a novel use of outdoor wind in developing a gas source localization system by simulation is presented in this paper. To consider the characteristic of sudden but large and unpredictable changes in wind direction, we propose to use recorded outdoor wind to simulate a realistic outdoor gas dispersion which has been done for the first time to the best of our knowledge. With the use of this simulator, we have tested a modification to a mobile robot-based gas source localization algorithm. Multiple simulations of the modified and the original particle filter-based algorithm have been done to study the effect of the tested modification. The results showed that a small difference in the algorithm can greatly impact the results. From this study, we show that the use of simulation consisting of the necessary traits to evaluate outdoor gas source localization, has the potential to accelerate the development of a reliable localization system.
In this study, we explored the detection of weak bonds (WBs) due to contamination and faulty curing (FC) using linear ultrasound and machine learning. For this purpose, aluminium single-lap adhesive joints containing three variants of bonding quality were investigated: perfect bond, WB due to release agent (RA) contamination, and WB due to FC. The data, according to the deviation of the bonding protocol, were arranged in two groups, creating two datasets: distinct and complete. Each dataset included all bonding conditions (perfect, RA, and FC), although the distinct dataset contained only marginal cases, which were expected to be well separable, whereas the complete dataset included data with minor deviations from the bonding protocol. Pulse-echo C-scan images were acquired for all prepared samples in the immersion tank, and 45 features were initially extracted from the time traces representing each bonding group. The initial data were analysed via a t-test and pairwise correlation analysis to reveal statistically significant features. Then, we performed dimensionality reduction using tree-based, recursive, sequential, and linear discriminant analysis (LDA) feature selectors to explore feature importance and classification accuracy with different feature subsets. Finally, the important features identified with the different feature selectors were fed to support vector machine (SVM) classifiers, and the classification accuracies were compared amongst the different feature subsets. The classification accuracy using a distinct dataset in some cases demonstrated nearly 99% accuracy, indicating that significant bonding protocol deviations could be easily detected. It was demonstrated that classification accuracy increased with the number of features. However, even in the case of the 2D feature space obtained using linear discriminant analysis, the bonding quality classification accuracy remained higher than 84%. The feature subspace reduction with LDA demonstrated sufficient classification accuracy and an improvement of nearly 40% in training time compared with that for the initial feature set. Thus, the classical ultrasonic pulse-echo C-scan with an LDA feature transformation and SVM classifier could be used to identify the deviations in the bonding protocol in aluminium single-lap adhesive joints.
A certain group of mycotoxins, the ergot alkaloids, has caused countless deaths throughout human history. They are found in rye and other cereals and ingesting contaminated foods can cause serious health problems. To identify contaminated food exceeding the legal limits for ergot alkaloids, a portable and cost-effective test system is of great interest to the food industry. Rapid analysis can be achieved by screening for a marker compound, for which we chose ergometrine. We developed a magnetic bead-based immunoassay for ergometrine with amperometric detection in a flow injection system using a handheld potentiostat and a smartphone. With this assay a limit of detection of 3 nM (1 μg/L) was achieved. In spiked rye flour, ergometrine levels from 25 to 250 μg/kg could be quantified. All results could be verified by optical detection. The developed assay offers great promise to meet the demand for on-site ergometrine detection in the food industry.
Reliable and straightforward characterization and analysis of carbon-based nanomaterials on the atomic level is essential to exploring their potential for application. Here we use a combination of highly surface sensitive x-ray photoelectron (XP) spectroscopy and near edge x-ray absorption fine structure spectroscopy (NEXAFS) to study and quantify the covalent functionalization of nanographene and single-walled carbon nanotubes with nitrene [2 + 1]-cycloaddition. With this comprehensive analytical approach, we demonstrate that the π-conjugated system of functionalized carbon-based nanomaterials is preserved according to NEXAFS analysis, which is challenging to prove with XP spectroscopy investigation alone. Using this combination of analytical approaches, we show significant similarities after functionalization for various carbon-based nanomaterials. Both analytical methods are strongly suited to study possible post-modification reactions of functionalized carbon-based nanomaterials.
As virus outbreaks continue to pose a challenge, a nonspecific viral inhibitor can provide significant benefits, especially against respiratory viruses. Polyglycerol sulfates recently emerge as promising agents that mediate interactions between cells and viruses through electrostatics, leading to virus inhibition.
Similarly, hydrophobic C60 fullerene can prevent virus infection via interactions with hydrophobic cavities of surface proteins. Here, two strategies are combined to inhibit infection of SARS-CoV-2 variants in vitro. Effective inhibitory concentrations in the millimolar range highlight the significance of bare fullerene’s hydrophobic moiety and electrostatic interactions of polysulfates with surface proteins of SARS-CoV-2. Furthermore, microscale thermophoresis measurements support that fullerene linear polyglycerol sulfates interact with the SARS-CoV-2 virus via its spike protein, and highlight importance of electrostatic interactions within it. All-atom molecular dynamics simulations reveal that the fullerene binding site is situated close to the receptor binding domain, within 4 nm of polyglycerol sulfate binding sites, feasibly allowing both portions of the material to interact simultaneously.
X-ray scattering and sorption data associated with the publication "Antiaromatic Covalent Organic Frameworks Based on Dibenzopentalenes". X-ray scattering data is provided for COF and POP materials, including data from stability tests, as three-column ascii files with columns q (nm-1), I (m-1) and uncertainty on I, as well as being provided in 2θ.
Remote gas sensors mounted on mobile robots enable the mapping of gas distributions in large or poorly accessible areas. A challenging task however, is the generation of three-dimensional distribution maps from these spatially sparse gas measurements. To obtain high-quality reconstructions, the choice of optimal measuring poses is of great importance. Remote gas sensors, that are commonly used in Robot Assisted Gas Tomography (RAGT), require reflecting surfaces within the sensor’s range, limiting the possible sensing geometries, regardless of whether the robots are ground-based or airborne. By combining ground and aerial robots into a heterogeneous swarm whose agents are equipped with reflectors and remote gas sensors, remote inter-robot gas measurements become available, taking RAGT to the next dimension – releasing those constraints. In this paper, we demonstrate the feasibility of drone-to-drone measurements under realistic conditions and highlight the resulting opportunities.
This dataset contains the processed and analysed small-angle X-ray scattering data associated with all samples from the publications "Bio-SAXS of Single-Stranded DNA-Binding Proteins: Radiation Protection by the Compatible Solute Ectoine" (https://doi.org/10.1039/D2CP05053F).
Files associated with McSAS3 analyses are included, alongside the relevant SAXS data, with datasets labelled in accordance to the protein (G5P), its concentration (1, 2 or 4 mg/mL), and if Ectoine is present (Ect) or absent (Pure). PEPSIsaxs simulations of the GVP monomer (PDB structure: 1GV5 ) and dimer are also included.
TOPAS-bioSAXS-dosimetry extension for TOPAS-nBio based particle scattering simulations can be obtained from https://github.com/MarcBHahn/TOPAS-bioSAXS-dosimetry which is further described in https://doi.org/10.26272/opus4-55751.
This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under grant number 442240902 (HA 8528/2-1 and SE 2999/2-1). We acknowledge Diamond Light Source for time on Beamline B21 under Proposal SM29806. This work has been supported by iNEXT-Discovery, grant number 871037, funded by the Horizon 2020 program of the European Commission.
Uncertainty quantification of multimodal surface wave inversion using artificial neural networks
(2023)
An inversion of surface waves dispersion curves is a non-unique and ill-conditioned problem. The inversion result has a probabilistic nature, which becomes apparent when simultaneously restoring the shear wave (S-wave) velocity and layer thickness. Therefore, the problem of uncertainty quantification is relevant. Existing methods through deterministic or global optimization approaches of uncertainty quantification via posterior probability density (PPD) of the model parameters are not computationally efficient since they demand multiple solutions of the inverse problem. We present an alternative method based on a multi-layer fully connected artificial neural network (ANN). We improve the current uni-modal approach, which is known from publications, to multi-modal inversion. The learned ANN maps the phase velocity dispersion curves to values of the S-wave velocity and layers thickness. To estimate the uncertainties, we adapt the Monte-Carlo simulation strategy and project onto the resulting velocity model both frequency-dependent data noise and inverse operator errors, which are evaluated by the prediction of the training data set. The proposed combination of surface waves data processing methods, configured with each other, provides a novel surface waves multi-modal dispersion data inversion and uncertainty quantification approach. We first test our approach on synthetic experiments for various velocity models: a positive velocity gradient, a low-velocity layer and a high-velocity layer. This is done considering uni-modal inversion at first and then compared to the multi-modal inversion. Afterwards, we apply our approach to field data and compare resulting models with the body S-wave processing by the generalized reciprocal method (GRM). The experiments show high-potential results using ANN yields the possibility to accurately estimate PPD of restored model parameters without a significant computational effort. The PPD-based comparison demonstrates advantages of a multi-modal inversion over uni-modal inversion. The trained ANN provides reasonable model parameters predictions and related uncertainties in real-time.
This work explores the feasibility of producing bead-on-plate welds of a CrCoNi medium entropy alloy and a CrMnFeCoNi high entropy alloy using electron beam welding. The alloys were welded in two states: one in an as-cold-rolled condition and the other in an annealed condition. In addition, the materials are welded with two different parameters. The FCC microstructure of the welds is investigated using scanning electron microscopy assisted by energy-dispersive X-ray spectroscopy and electron-backscattered diffraction. The impact of the weld on the microstructure is discussed. The heat-affected zone is negligible for the annealed condition of both medium and high entropy alloys since there is no driving force for recrystallisation and the exposure time to high temperature is insufficient for grain coarsening. The texture formed in the fusion zone is also discussed and compared to the texture in the base metal and the heat-affected zone. Although the grain growth along the (100) crystallographic direction is preferential in all cases, the crystallographic texture type differs from each weld. Higher hardness values are measured in the medium entropy alloy’s base metal and fusion zone than in the high entropy alloy.
Simulates X-ray and Neutron scattering patterns from arbitrary shapes defined by STL files.
Features:
- Uses multithreading to compute a number of independent solutions, then uses the variance of the results to estimate an uncertainty on the output.
- Can be launched from the command line using an excel sheet to define settings, or from a jupyter notebook.
- Outputs scattering patterns in absolute units if the contrast is set.
- A Gaussian size distribution is available, where the relative scaling of objects for each repetion can be varied. Recommended to be used with limited width (max. 10%) to avoid artefacts.
- Writes results with settings to an archival HDF5 file.
Application examples:
This software has been used in several studies to date. For example, it has been used here to simulate a model scattering pattern for a cuboid shape, which was then fed forward into the McSAS3 analysis program for analyzing scattering patterns of polydisperse cuboids. A second use is here, where it was used for the modeling of flattened helices. In this paper, scattering pattern features could be matched with particular morphological changes in the structure. Lastly, this paper has an example where it was used to validate the analytical analysis model, and explore the realistic limits of application of the analytical model.
Sediments and soils can act as sinks of species of inorganic mercury (Hg2+), while they are simultaneously sources of organic species, such as monomethylmercury (MMHg). Although the fraction of MMHg in total Hg of sediments is suggested to be only 0.1–1%, MMHg poses a threat for humans and wildlife due to its toxic properties, high bioaccumulation potential and the ability to pass the blood-brain barrier. One example of a highly Hg contaminated waterbody is the Finow Canal, the oldest artificial waterway still in operation in Germany. Here, Hg mass fractions of up to 100 µg/g were found in the sediment in previous studies. These are suggested to be associated with a chemical plant producing mercury-based seed dressings. Despite this high mass fraction of Hg, no Hg speciation studies have been conducted there up to now.
In this study, Hg speciation in sediments of Finow Canal at locations before and after the known polluted site was conducted using species-specific isotope dilution (SSID) GC-ICP-ToF-MS. Mass fractions of up to 0.41 µg/g MMHg were determined. In addition, waterbodies around the initially polluted site were investigated and elevated concentrations were also determined around 14 km downstream. For MMHg analysis, the performance of ICP-ToF-MS for SSID GC/ICP-MS was compared with ICP-Q-MS and ICP-SF-MS. Here, isotope ratio precision was similar between the tested instruments. However, the (quasi-) simultaneous detection of the whole mass spectrum will probably offer a much higher precision of ICP-ToF-MS, when more than one isotope system is used.
These results are the first evidence of the occurrence of MMHg in this region and show the need for further investigations of the whole regional ecosystem, as well as the consideration of possible measures of remediation. SSID GC-ICP-(ToF)-MS is a suitable tool for investigating species-specific (multi) isotope systems for environmental monitoring.
OpenSCAD, STL and technical drawings for the capillary flow-through cell designed primarily for use with The MOUSE instruments.
This flow-through cell can be used in conjunction with:
- Modular sample holder (10.5281/zenodo.7499416)
- Solid sample rack/plate (10.5281/zenodo.7499424)
- Laser-cut sample holder (10.5281/zenodo.7499437)
Technical drawings and documents for building a compact, heated, vacuum compatible flow-through sample holder. This holder is in use at the BAM MOUSE instrument as well as at the I22 beamline at the Diamond Light Source (see references for instrument details).
This holder has several features:
- The holder can be used in vacuum environments as well as in atmosphere
- It has two G 1/4" UNF fittings to attach HPLC tubing for (optionally) flowing a medium through the sample cell
- There are two additional (unflowed) sample positions for backgrounds and calibrants, held at the same temperature
- The low-mass design coupled with a 250W heating element can achieve heating rates of 1 degree C per second, when coupled (for example) with an Omron E5CC PID controller.
- The sample holder insert can be made from various materials depending on the application. Sealing the sample from the vacuum can be achieved using kapton, teflon or Magic tape, depending on the temperature requirements. The inlet and outlet holes will need to be punctured with a needle to enable flow.
- Large exit cones ensure a clear exit angle of at least 45 degrees two theta.
- It has been tested with temperatures up to 400 degrees C.
- Compression area has been raised and polished to ensure a good vacuum seal.
OpenSCAD, STL and technical drawings for the solid sample rack designed primarily for use with The MOUSE instruments.
This solid sample rack can be used in conjunction with:
- Laser-cut sample holder (10.5281/zenodo.7499437)
- Modular sample holder (10.5281/zenodo.7499416)
- Capillary flow-cell for liquid samples (10.5281/zenodo.7499421)
PDF file for the laser-cut sample holder designed primarily for use with The MOUSE instruments.
This sample holder can be used in conjunction with:
- Solid sample rack/plate (10.5281/zenodo.7499424)
- Modular sample holder (10.5281/zenodo.7499416)
- Capillary flow-cell for liquid samples (10.5281/zenodo.7499421)
The need for quality assessment of anthropogenic impact on environmental pollution is increasing due to discharge from various industries, the use of chemicals in agriculture and the consumption of fossil fuels. Diminishing resources such as natural waters used for the cultivation of agricultural products, plant and animal habitats are under severe pollution pressure and are at constant risk. Several parameters, such as Pb, Cd, Ni, Hg were listed by Water Framework Directive in Directive(2008/105/EC) in the priority substances. Cadmium and Hg were identified as priority hazardous substances whereas As is an important contaminant for its potential toxicological and carcinogenic effects. An inter-comparison study is organised in EURAMET TC-MC in order to demonstrate the capability participants for measuring five elements in river water. The participants carried out measurements for analytes: Pb, Cd, Ni and As as mandatory elements, and Se as an optional one. Participants were asked to perform the measurements with respect to the protocol provided. 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).
The core−shell NaYF4:Yb3+/Tm3+@NaYF4:Yb3+ upconversion nanoparticles were successfully prepared by a solvothermal method, and a layer of mesoporous silica (mSiO2) was successfully coated on the periphery of the core−shell nanoparticles to transform their surface from lipophilic to hydrophilic, further expanding their applications in biological tissues. The physical phase, morphology, structure, and fluorescence properties were characterized by X-ray diffraction (XRD), field emission transmission electron microscopy (TEM), Fourier infrared spectroscopy (FT-IR), ζ potential analysis, and fluorescence spectroscopy. It was found that the material has a hexagonal structure with good hydrophilicity and emits intense fluorescence under 980 nm pump laser excitation. The non-contact temperature sensing performance of nanoparticles was evaluated by analyzing the upconversion fluorescence of Tm3+ (1G4 → 3F4 and 3F3 → 3H6) in the temperature range of 284−344 K. The absolute and relative sensitivities were found to be 0.0067 K−1 and 1.08 % K−1, respectively, with high-temperature measurement reliability and good temperature cycling performance. More importantly, its temperature measurement in phosphate-buffered saline (PBS) solution is accurate. In addition, the temperature of the cells can be increased by adjusting the laser power density and laser irradiation time. Therefore, an optical temperature sensing platform was built to realize the application of real-time monitoring of cancer cell temperature and the dual function of photothermal therapy.
Volatile organic compounds (VOCs) are of interest in many different fields. Among them are food and fragrance analysis, environmental and atmospheric research, industrial applications, security or medical and life science. In the past, the characterization of these compounds was mostly performed via sample collection and off-site analysis with gas chromatography coupled to mass spectrometry (GC-MS) as the gold standard. While powerful, this method also has several drawbacks such as being slow, expensive, and demanding on the user. For decades, intense research has been dedicated to find methods for fast VOC analysis on-site with time and spatial resolution. We present the working principles of the most important, utilized, and researched technologies for this purpose and highlight important publications from the last five years. In this overview, non-selective gas sensors, electronic noses, spectroscopic methods, miniaturized gas chromatography, ion mobility spectrometry and direct injection mass spectrometry are covered. The advantages and limitations of the different methods are compared. Finally, we give our outlook into the future progression of this field of research.
Concrete structures experience severe damage during service, for example due to pitting corrosion of rebars caused by the ingress of chlorine (Cl) into the porous concrete structure. The ingress can be monitored using laser-induced breakdown spectroscopy (LIBS), a recently introduced civil engineering technique used to detect Cl in concrete structures in addition to conventional wet chemistry methods. The key advantages of LIBS are high spatial resolution, which is important when analyzing heterogeneous concrete samples, as well as the almost complete absence of sample preparation. To assess LIBS as a reliable analytical method, its accuracy and robustness must be carefully tested. This paper presents the results of an interlaboratory comparison on the analysis of Cl in cement paste samples conducted by 12 laboratories in 10 countries. Two sets of samples were prepared with Cl content ranging from 0.06 to 1.95 wt% in the training set and 0.23–1.51 wt% in the test set, with additional variations in the type of cement and Cl source (salt type). The overall result shows that LIBS is suitable for the quantification of the studied samples: the average relative error was generally below 15%. The results demonstrate the true status quo of the LIBS method for this type of analysis, given that the laboratories were not instructed on how to perform the analysis or how to process the data.
The NaYF4: Yb3+/Tm3+@NaYF4@β-CD upconversion nanoparticles were successfully prepared by the solvothermal method, and the samples were pure hexagonal phase with good crystallinity and homogeneous size, asevidenced by XRD and TEM analysis. The FT-IR analysis shows that β-CD is successfully encapsulated on the surface of NaYF4: Yb3+/Tm3+@NaYF4 nanoparticles. The fluorescence intensity 3and lifetime were significantly increased after coating the inert layer on the surface of core nanoparticles. After further surface modification of β-CD, the fluorescence intensity and fluorescence lifetime were reduced, but the overall fluorescence was stronger. Temperature measurements using the fluorescence intensity ratio technique were found to have relatively low reliability and absolute sensitivity for temperature measurements using thermally coupled energy levels. However, the reliability of temperature measurements using non-thermally coupled energy levels is significantly higher and the absolute sensitivity is much higher than for measurements at thermally coupled levels. Since the maximum absolute sensitivity, maximum relative sensitivity and minimum temperature resolution are determined to be 0.1179 K-1, 2.19 %K 1 and 0.00019 K, respectively, NaYF4: Yb3+/Tm3+@NaYF4@β-CD upconversion nanoparticles are expected to be widely used in the biomedical field due to their feasibility, reliability, non-toxicity and harmlessness.
Optical Thermometry is popular among researchers because of its non-contact, high sensitivity, and fast measurement properties. In the present experiment, Er3+/Yb3+/K+ co-doped NaYF4 nanoparticles with different K+ concentrations were synthesized by solvothermal method, and the samples showed bright upconversion green emission under the excitation of a 980 nm laser. The powder X-ray diffractometer and transmission electron microscope were used to characterize the crystal structure and its surface morphology, respectively. The spectral characteristics of nanoparticles with K+ doping concentration from 10% to 30% (Molar ratio) were investigated by fluorescence spectroscopy, and it was observed that the fluorescence intensity reached the maximum at the K+ concentration of 20%, after which the intensity weakened when the K+ content continued to increase. According to the dependence between the luminescence intensity of the sample and the laser power density and fluorescence lifetime, the intrinsic mechanism was carefully investigated. Temperature-dependent spectra of the samples were recorded in the temperature range of 315–495 K, and the maximum values of absolute sensitivity (Sa) and relative sensitivity (Sr) were measured at 0.0041 K−1 (455 K) and 0.9220%K−1 (315 K). The experimental results show that K+/Er3+/Yb3+ triple-doped NaYF4 green fluorescent nanoparticles (GFNs) have good prospects for applications in display devices, temperature sensing, and other fields.
2PP-TestArtifact
(2023)
This repository contains a test artifact (TA), also called test structure, designed for two-photon polymerization (also known as Direct Laser Writing (DLW) or Two/Multi-photon lithography (2PA/MPA)). Test artifacts can be used to compare structures, to check options used by the slicer, check the state of the 2PP machine itself or to get a construction guidelines for a certain combination of power, velocity and settings.
The associated paper can be found here: https://dx.doi.org/10.1088/1361-6501/acc47a
General ideas behind the test artifact:
1. optimized for 2PP-DLW
2. should be fast and easy to analyse with optical microscopy or 3. scanning electron microscopy without tilt.
3. short time to fabricate
4. include a reasonable amount of different features
5. bulk and small structures on the substrate
The change of DNA radiation damage upon hydration: In-situ observations by near-ambient-pressure XPS
(2023)
Ionizing radiation damage to DNA plays a fundamental role in cancer therapy. X-ray photoelectron-spectroscopy (XPS) allows simultaneous irradiation and damage monitoring. Although water radiolysis is essential for radiation damage, all previous XPS studies were performed in vacuum. Here we present near-ambient-pressure XPS experiments to directly measure DNA damage under water atmosphere. They permit in-situ monitoring of the effects of radicals on fully hydrated double-stranded DNA. The results allow us to distinguish direct damage, by photons and secondary low-energy electrons (LEE), from damage by hydroxyl radicals or hydration induced modifications of damage pathways. The exposure of dry DNA to x-rays leads to strand-breaks at the sugar-phosphate backbone, while deoxyribose and nucleobases are less affected. In contrast, a strong increase of DNA damage is observed in water, where OH-radicals are produced. In consequence, base damage and base release become predominant, even though the number of strand-breaks increases further.
Small-angle X-ray scattering (SAXS) can be used for structural determination of biological macromolecules and polymers in their native states (e.g. liquid phase). This means that the structural changes of (bio-)polymers, such as proteins and DNA, can be monitored in situ to understand their sensitivity to changes in chemical environments. In an attempt to improve the reliability of such experiments, the reduction of radiation damage occurring from exposure to X-rays is required. One such method, is to use scavenger molecules to protect macromolecules against radicals produced during radiation exposure, such as reactive oxygen species (ROS). In this study we investigate the feasibility of applying the compatible solute, osmolyte and radiation protector Ectoine (THP(B)), as a scavenger molecule during SAXS measurements of the single-stranded DNA-binding protein Gene-V Protein (G5P/GVP). In this case, we monitor the radiation induced changes of G5P during bio-SAXS measurments and the resulting microscopic energy-damage relation was determined from microdosimetric calculations by Monte-Carlo based particle scattering simulations with TOPAS/Geant4 and a custom target-model. This resulted in a median-lethal energy deposit of pure G5P at 4 mg mL−1 of E1/2 = 7 ± 5 eV, whereas a threefold increase of energy-deposit was needed under the presence of Ectoine to reach the same level of damage. This indicates that Ectoine increases the possible exposure time before radiation-damage to G5P is observed. Furthermore, the dominant type of damage shifted from aggregation in pure solutions towards a fragmentation for solutions containing Ectoine as a cosolute. These results are interpreted in terms of indirect radiation damage by reactive secondary species, as well as post-irradiation effects, related to preferential-exclusion of the cosolute from the protein surface. Hence, Ectoine is shown to provide a non-disturbing way to improve structure-determination of proteins via bio-SAXS in future studies.
Benchtop 1H-NMR and FTIR have both been successfully developed for size-exclusion chromatography (SEC) applications. The latest implementations of these methods by Wilhelm and collaborators[1-3] have taken advantage of commerically available low-cost equipment, and a provide a means to obtain slice-by-slice spectra for the monitoring of functional groups in polymer separations. Demonstrated applications include the detection of highly diluted chains in a polymer blend (e.g., PS/PMMA), copolymer content determination (e.g., styrene-methyl methacrylate), and butadiene isomer detection. To synthesize and characterize an end-labelled low molecular wt. poly(ethylene glycol) as a model polymer to aid in the development and validation of spectroscopic detection (FTIR and 1H-NMR) for SEC applications. A particular focus is to improve quantitation and/or detection of highly diluted funtional groups (e.g., polymer chain ends or sparsely functionalized chains) In the first approach, an isocyanate with IR- and NMR-active functional groups was reacted with PEG (4000 and 10000 g/mol) to form end-functionalized chains by means of an addition reaction. The functionalization of the 10000 g/mol PEG was found to be non-homogeneous (not discussed further). The 4000 g/mol PEG was successfully functionalized to 100%, found to be homogeneous across the molecular weight distribution and could therefore serve as a model polymer for analysis by the coupled methods.
Microscopic knowledge of the structural, energetic, and electronic properties of scandium fluoride is still incomplete despite the relevance of this material as an intermediate for the manufacturing of Al−Sc alloys. In a work based on first-principles calculations and X-ray spectroscopy, we assess the stability and electronic structure of six computationally predicted ScF3 polymorphs, two of which correspond to experimentally resolved single-crystal phases. In the theoretical analysis based on density functional theory (DFT), we identify similarities among the polymorphs based on their formation energies, chargedensity distribution, and electronic properties (band gaps and density of states). We find striking analogies between the results obtained for the ow- and high-temperature phases of the material, indirectly confirming that the transition occurring between them mainly consists of a rigid rotation of the lattice. With this knowledge, we examine the X-ray absorption spectra from the Sc and F K-edge contrasting firstprinciples results obtained from the solution of the Bethe−Salpeter equation on top of all-electron DFT with high-energy-resolution fluorescence detection measurements. Analysis of the computational results sheds light on the electronic origin of the absorption maxima and provides information on the prominent excitonic effects that characterize all spectra. A comparison with measurements confirms that the sample is mainly composed of the high- and low-temperature polymorphs of ScF3. However, some fine details in the experimental results suggest that the probed powder sample may contain defects and/or residual traces of metastable polymorphs.
The greatest challenge when using deep convolutional neural networks (DCNNs) for automatic segmentation of microstructural X-ray computed tomography (XCT) data is the acquisition of sufficient and relevant data to train the working network. Traditionally, these have been attained by manually annotating a few slices for 2D DCNNs. However, complex multiphase microstructures would presumably be better segmented with 3D networks. However, manual segmentation labeling for 3D problems is prohibitive. In this work, we introduce a method for generating synthetic XCT data for a challenging six-phase Al–Si alloy composite reinforced with ceramic fibers and particles. Moreover, we propose certain data augmentations (brightness, contrast, noise, and blur), a special in-house designed deep convolutional neural network (Triple UNet), and a multi-view forwarding strategy to promote generalized learning from synthetic data and therefore achieve successful segmentations. We obtain an overall Dice score of 0.77. Lastly, we prove the detrimental effects of artifacts in the XCT data on achieving accurate segmentations when synthetic data are employed for training the DCNNs. The methods presented in this work are applicable to other materials and imaging techniques as well. Successful segmentation coupled with neural networks trained with synthetic data will accelerate scientific output.
X-ray photoelectron-spectroscopy (XPS) allows simultaneous irradiation and damage monitoring. Although water radiolysis is essential for radiation damage, all previous XPS studies were performed in vacuum. Here we present near-ambient-pressure XPS experiments to directly measure DNA damage under water atmosphere. They permit in-situ monitoring of the effects of radicals on fully hydrated double-stranded DNA. Our results allow us to distinguish direct damage, by photons and secondary low-energy electrons (LEE), from damage by hydroxyl radicals or hydration induced modifications of damage pathways. The exposure of dry DNA to x-rays leads to strand-breaks at the sugar-phosphate backbone, while deoxyribose and nucleobases are less affected. In contrast, a strong increase of DNA damage is observed in water, where OH-radicals are produced. In consequence, base damage and base release become predominant, even though the number of strand-breaks increases further. Furthermore, first data about the degradation of single-stranded DNA binding-proteins (G5P / GV5 and hmtSSB) under vacuum and NAP-XPS conditions are presented.
The overview of the activity of Federal Institute for Material Research and Testing (BAM, Belin, Germany) in the field of additively manufacturing material characterization will be presented. The research of our group is focused on the 3D imaging of AM materials by means of X-ray Computed Tomography at the lab and at synchrotron, and the residual stress characterization by diffraction (nondestructive technique). Also, two successful research project in collaboration with CAM2, Sweden are presented.
Laser-based active thermography is a contactless non-destructive testing method to detect material defects by heating the object and measuring its temperature increase with an infrared camera. Systematic deviations from predicted behavior provide insight into the inner structure of the object. However, its resolution in resolving internal structures is limited due to the diffusive nature of heat diffusion. Thermographic super resolution (SR) methods aim to overcome this limitation by combining multiple thermographic measurements and mathematical optimization algorithms to improve the defect reconstruction.
Thermographic SR reconstruction methods involve measuring the temperature change in an object under test (OuT) heated with multiple different spatially structured illuminations. Subsequently, these measurements are inputted into a severely ill-posed and heavily regularized inverse problem, producing a sparse map of the OuT’s internal defect structure. Solving this inverse problem relies on limited priors, such as defect-sparsity, and iterative numerical minimization techniques. Previously mostly experimentally limited to one-dimensional regions of interest (ROIs), this thesis aims to extend the method to the reconstruction of two-dimensionalROIs with arbitrary defect distributions while maintaining reasonable experimental complexity. Ultimately, the goal of this thesis is to make the method suitable for a technology transfer to industrial applications by advancing its technology readiness level (TRL).
In order to achieve the aforementioned goal, this thesis discusses the numerical expansion of a thermographic SR reconstruction method and introduces two novel algorithms to invert the underlying inverse problem. Furthermore, a forward solution to the inverse problem in terms of the applied SR reconstruction model is set up. In conjunction with an additionally proposed algorithm for the automated determination of a set of (optimal) regularization parameters, both create the possibility to conduct analytical simulations to characterize the influence of the experimental parameters on the achievable reconstruction quality. On the experimental side, the method is upgraded to deal with two-dimensional ROIs, and multiple measurement campaigns are performed to validate the proposed inversion algorithms, forward solution and two exemplary analytical studies. For the experimental implementation of the method, the use of a laser-coupled DLP-projector is introduced, which allows projecting binary pixel
patterns that cover the whole ROI, reducing the number of necessary measurements per ROI significantly (up to 20x).
Finally, the achieved reconstruction of the internal defect structure of a purpose-made OuT is qualitatively and qualitatively benchmarked against well-established thermographic testing methods based on homogeneous illumination of the ROI. Here, the background-noise-free two-dimensional photothermal SR reconstruction results show to outclass all defect reconstructions by the considered reference methods.
Gas source localization (GSL) helps mitigate the impact of industrial accidents and natural disasters. While GSL may be dangerous and time-consuming when performed by humans, swarms of agile and inexpensive nano aerial robots may increase the safety and efficiency of gas source localizations. Since the small payloads of nano aerial robots limit the sensing and computing resources, strategies adapted from biological swarms, such as colonies of social insects, are used to coordinate robot swarms. Most swarm GSL strategies are based on the assumption that the maxima of gas concentrations are sufficiently close to the gas sources. However, prior studies have indicated that the occurrence of “bouts”, a metric for the intermittency of gas distributions, may advantageously be used as a more accurate gas source proximity indicator. This paper presents a swarm GSL strategy employing bouts as source proximity indicators and a bio-inspired pheromone system for communication. Nano aerial robots, deployed in this study, act as agents and emit pheromone markers in an artificial environment upon detecting bouts. Leveraging the concept of artificial potential fields, the agents switch between exploiting the knowledge of the swarm by following pheromone gradients and exploring the search space by targeting a random point. The agents are repelled by each other and by walls to avoid collisions. The swarm GSL strategy is implemented into three nano aerial robots and validated in a real-world experiment in an indoor environment with a single gas source. The results indicate that the the swarm GSL strategy presented in this paper is capable of GSL in indoor environments and that the intermittency of gas distributions is a better source proximity indicator than the mean concentration.
Gas source localization (GSL) helps mitigate the impact of industrial accidents and natural disasters. While GSL may be dangerous and time-consuming when performed by humans, swarms of agile and inexpensive nano aerial robots may increase the safety and efficiency of gas source localizations. Since the small payloads of nano aerial robots limit the sensing and computing resources, strategies adapted from biological swarms, such as colonies of social insects, are used to coordinate robot
swarms. Most swarm GSL strategies are based on the assumption that the maxima of gas concentrations are sufficiently close to the gas sources. However, prior studies have indicated that the occurrence of “bouts”, a metric for the intermittency of gas distributions, may advantageously be used as a more accurate gas source proximity indicator. This paper presents a swarm GSL strategy employing bouts as source proximity indicators and a bio-inspired pheromone system for communication. Nano aerial robots, deployed in this study, act as agents and emit
pheromone markers in an artificial environment upon detecting bouts. Leveraging the concept of artificial potential fields, the agents switch between exploiting the knowledge of the swarm by following pheromone gradients and exploring the search space by targeting a random point. The agents are repelled by each other and by walls to avoid collisions. The swarm GSL strategy is implemented into three nano aerial robots and validated in a real-world experiment in an indoor environment with a single gas source. The results indicate that the the swarm GSL strategy
presented in this paper is capable of GSL in indoor environments and that the intermittency of gas distributions is a better source proximity indicator than the mean concentration.
This poster reports an improved outdoor gas source localization algorithm, showing promising results under simulations with a realistic gas plume. In the scenario assumed in this work, an unmanned ground vehicle searches for the location of a gas source in an open outdoor field. The simulated gas plume in this work consists of frequent and large meandering as a real outdoor plume. The source location is estimated using gas and wind measurements obtained from sensors fixed on a mobile platform. When a gas puff is detected, its source is likely to be in the upwind direction. Particle filter-based algorithms have been proposed in previous work to estimate the most likely source location from multiple gas detection events. In this work, the particle weight update function has been modified by adopting a 2D Gaussian plume model, to improve the accuracy in estimating the likelihood of the source location. We have evaluated the performance of this algorithm combined with an estimation-based route planning algorithm. The simulator uses wind data recorded outdoors to calculate transport of gas puffs allowing a formation of a gas plume containing large meandering, due to real fluctuations of outdoor wind. Simulations of the improved particle filter with the estimation-based route planning algorithm have yielded more accurate, stable and time-efficient results than the pre-modified version.
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).
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in Africa. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2023. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
This study is part of a global project that covers various other countries (see www.qi-fokus.de).
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.
This paper presents an automatic damage imaging technique by employing a signal processing approach based on applying hierarchically clustered filters across different domains. The technique involves time-frequency-wavenumber filter banks which are applied sequentially to ultrasonic guided wave (UGW) data. The study is conducted for a single lap joint composite specimen with a special focus on small voids which were formed due to manual adhesive component mixing. UGW data are acquired with a 3D Scanning Laser Doppler Vibrometer (LDV) over the scan area of the bonded plate. UGWs are excited at the central frequency of 100 kHz by a single piezoelectric transducer mounted on the surface of the single plate. Within each domain of time, frequency, and wavenumber, four filters are designed which results in 64 distinct filtered wavefields. From each filtered wavefield, an image is obtained by using root-mean-square (RMS) calculation of the signals. The obtained results are then combined to create a final, improved-resolution image of the scan area. The final image is compared to the image obtained through RMS calculation of full wavefield with interpolation through Delaunay triangulation and the image obtained by X-ray radiography. The results show that the smallest void that could be detected has a diameter of 2.14 mm.
Die Bezeichnung „Tinte auf Papier“ bietet einen guten Einstieg in die Beschreibung der Materialität von Musikhandschriften; so haben sich zahlreiche Manuskripte erhalten, die mit Eisengallustinte auf Hadernpapier verfasst wurden.
Das Papier besteht aus Fasern meist pflanzlicher Herkunft und wird durch Entwässerung einer Fasersuspension auf einem Sieb gebildet. Der Abdruck des Schöpfsiebes (die Papierstruktur) und ein vorhandenes Wasserzeichen bieten Anhaltspunkte für Provenienz und Datierung; daneben erlaubt die Analyse der Fasern, der Füllstoffe und der Leimung eine weitere Charakterisierung des Schriftträgers.
Spätestens seit dem Mittelalter sind es Eisengallustinten, die das schwarze bis bräunliche Erscheinungsbild vieler Manuskripte auf Papier hervorrufen. Daneben lassen sich auch schwarze Rußtuschen oder farbige Auszeichnungstuschen nachweisen. Eisengallustinten werden durch Mischung einer eisenhaltigen Komponente mit Gerbstoffen hergestellt. Eisensulfat ist die am häufigsten genannte Eisen liefernde Zutat, daneben sind aber auch eisenhaltige Minerale, Nägel oder Rost denkbar. Die Gallussäure leitet sich ab aus den Galläpfeln, der krankhaften Veränderung einzelner Planzenteile verschiedener Eichenarten. Diese werden durch die Eiablage von Schlupfwespen hervorgerufen.
Wie schon beim Papier ermöglicht der materialanalytische Nachweis charakteristischer Beimischungen oder Verunreinigungen innerhalb der Tinten die Beantwortung kulturhistorischer Fragestellungen – gemeint sind hier die Unterscheidung von Original und Korrektur oder die Sichtbarmachung späterer Ergänzungen.
Der Berufsverband GfKORR - Gesellschaft für Korrosionsschutz e.V. will mit der "Jungen GfKORR" ein attraktives Angebot für junge Leute schaffen, sich fachübergreifend zu vernetzen und somit einen Einstieg in die fachliche Arbeit des Verbands zu bieten. Das Netzwerk befindet sich zurzeit im Aufbau. Auf der Jahrestagung 2023 in Berlin wurde die Idee für das Netzwerk erstmals vorgestellt.
Detaillierte Kenntnisse der elastischen Materialeigenschaften sind in vielen ingenieurtechnischen Bereichen von grundlegender Bedeutung. Insbesondere für die Anwendung von Predictive Maintenance und Structural- Health-Monitoring Methoden mit Ultraschall ist die genaue Kenntnis der elastischen Materialkonstanten eine Grundvoraussetzung. Die von den Herstellern zur Verfügung gestellten Angaben zu den elastischen Materialkonstanten, insbesondere für Polymere und faserverstärkte Kunststoffe, sind jedoch oft unzureichend, da diese vom Produktionsprozess abhängig sind und sich zusätzlich aufgrund von Materialabbauprozessen oder Ermüdung ändern können. In der Praxis liegen polymere Werkstoffe, faserverstärkte Kunststoffe und Metalle oft als dünne, plattenförmige Strukturen vor, in welchen sich geführte Ultraschallwellen (UGWs) ausbreiten können. In der aktuellen Forschung sind bereits verschiedene Neuronale Modelle zur Bestimmung der elastischen Konstanten und der Materialcharakterisierung mittels UGWs bekannt. Ein einfaches neuronales Netz, mit aus Dispersionsbildern extrahierten Werten für Frequenz und Wellenzahl ausbeutungsfähiger Moden als Eingabe, zur Vorhersage der elastischen Konstanten wird in verwendet. Ein rekurrentes Neuronales Netz mit einem Zeit-Frequenz Vektor als Eingabe wird in angewandt, während in ein 1D- Convolutional-Neuronal-Networks (CNN) unter Verwendung der zeitlichen Auslenkung der Grundmoden und in ein 2D-CNN unter Verwendung einer polaren Gruppengeschwindigkeitsdarstellung zur Bestimmung der elastischen Konstanten verwendet wird. In diesem Vortrag wird ein Ansatz zur Bestimmung der isotropen elastischen Konstanten von dünnen Platten auf der Grundlage von UGWs unter Verwendung von Dispersionsbildern und 2D-CNNs vorgestellt. Dispersionsabbildungen aus numerischen Simulationen werden mithilfe verschiedener Methoden vorverarbeitet, um realistische Messdaten zu simulieren. Mit den modifizierten Daten wird das Modell trainiert und die Architektur optimiert. Anschließend wird die Genauigkeit des erzeugten Modells mit realen Messdaten validiert. Es wird gezeigt, dass 2D-CNNs in der Lage sind, die isotropen elastischen Konstanten anhand multimodaler Merkmale aus Dispersionsbildern vorherzusagen, ohne dass eine anfängliche Schätzung der Parameter oder manuelle Merkmalsextraktion erforderlich ist.
Early detection of cancer is essential for successful treatment and improvement in patient prognosis. Deregulation of post-translational modifications (PTMs) of proteins, especially phosphorylation, is present in many types of cancer. Therefore, the development of materials for the rapid sensing of low abundant phosphorylated peptides in biological samples can be of great therapeutic value. In this work, we have synthesised fluorescent molecularly imprinted polymers (fMIPs) for the detection of the phosphorylated tyrosine epitope of ZAP70, a cancer biomarker. The polymers were grafted as nanometer-thin shells from functionalised submicron-sized silica particles using a reversible addition-fragmentation chain-transfer (RAFT) polymerisation. Employing the combination of fluorescent urea and intrinsically cationic bis-imidazolium receptor cross-linkers, we have developed fluorescent sensory particles, showing an imprinting factor (IF) of 5.0. The imprinted polymer can successfully distinguish between phosphorylated and non-phosphorylated tripeptides, reaching lower micromolar sensitivity in organic solvents and specifically capture unprotected peptide complements in a neutral buffer. Additionally, we have shown the importance of assessing the influence of counterions present in the MIP system on the imprinting process and final material performance. The potential drawbacks of using epitopes with protective groups, which can co-imprint with targeted functionality, are also discussed.
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.
Tailor-made nanoparticles are of increasing interest in e.g. catalysis, as sensor materials, analytical assays, or can have superior photophysical properties. A major issue concerning the preparation of high-quality and functional nanoparticles is a good control of particle size, shape, polydispersity, and composition.
Small Angle X-ray Scattering (SAXS) is a non-destructive method for the analysis of nanostructures in a wide variety of materials. This method allows determining averaged structural parameters on a length scale from just above atomic sizes up to several 100 nanometers such as sizes, size distributions, volume fractions, and inner surface sizes. Moreover, anomalous Small Angle X-ray Scattering (ASAXS) exploits the anomalous dispersion of the scattering amplitudes near the X-ray absorption edges of the elements contained in the sample. These element sensitive contrast variations can be used to analyse average composition fluctuations on the nm scale. Two kinds of nanoparticles are chosen here to elaborate the advantages of ASAXS in the analysis of complex materials.
A facile and efficient methodology is developed for the thermal synthesis of size-tunable, stable, and uniform bimetallic NiCu core–shell nanoparticles (NPs) for various application in catalysis. Their diameter can be tuned in a range from 6 nm to 30 nm and the Ni:Cu ratio is adjustable in a wide range from 1:1 to 30:1. The NPs are structurally characterized by a method combination of transmission electron microscopy, anomalous small-angle X-ray scattering (ASAXS), X-ray absorption fine structure, and X-ray photoelectron spectroscopy. Here, we focus on the ASAXS method and its ability to analyses nanostructure parts and their compositions at once. As a result, a NiCu alloyed core surrounded by a Ni enriched shell and an outer NiO shell was found.
Semiconductor nanocrystals (quantum dots, QDs) are well known for their superior photophysical properties and enabled advancements in several key technologies of the 21st century and numerous technological applications like in photovoltaics, LED displays, photocatalysis, and biosensing. To achieve high photoluminescence quantum yields (PLQY) and enhanced photostability the QD core needs to be passivated by a second semiconductor, which possess a larger band gap to confine the charges within the QD core. An important parameter is thereby the lattice mismatch between the core and shell. To avoid strong lattice strain, which would alter the photophysical properties, an intermediary shell can be used as a lattice adapter between the core and the outer shell leading to core/shell/shell systems. These systems have shown to possess high PLQYs combined with a strong long-term stability and can be found in modern QLED displays. ASAXS was used here to better understand the core/shell/shell structure of InP/ZnSe/ZnS QDs to enable a correlation between their structural and photophysical properties.
The development of a Lab-on-a-Chip (LoC) is presented, which can detect reactive phosphorous compounds in the gas phase in combination with an optochemical hand-held sensor. The LoC prototype contains three pairs of sensing materials containing fluorescent indicator dyes in various carrier materials. By measuring the fluorescence response to phosphoryl chloride, a surrogate compound, the detection of chemical warfare agents (CWAs) in gas phase becomes possible within seconds, introducing a novel approach to CWA detection.
In particular, the rapid development of lateral flow assays as indispensable tools for everyone to contain the SARS-CoV-2 pandemic has fuelled the global demand for analytical tests that can be used outside dedicated laboratories. In addition to their use in medical diagnostics, rapid tests and assays have become increasingly important in various fields such as food safety, security, forensics, and environmental management. The advantage is obvious: taking the assay directly to the sample minimizes the time between suspicion and decision-making, allowing faster action. Especially today, when mobile communication devices with powerful computing capabilities and built-in cameras are ubiquitous, more people than ever before around the world have the basic skills to operate a powerful detector at their fingertips. This sets the stage for a much wider use of analytical measurements in terms of prognosis and prevention, enabling professional laypersons in particular.
However, current strip-based systems are primarily focused on single parameter analysis, whether it is SARS-CoV-2 biomarkers, blood glucose levels, or lead concentrations in water samples. Industrial applications of such methods also often still rely on single-parameter assays, requiring multiple runs even for a limited number of key parameters. Overcoming these limitations depends on developing low-number multiplexing strategies that ensure robustness, reliability, speed, ease of use, and sensitivity.
This lecture will give an overview of several generic approaches developed in recent years to address these challenges. It will highlight how the synergy of supramolecular (bio)chemistry, luminescence detection, hybrid (nano)materials and device miniaturization can result in powerful (bio)analytical assays that can be used at a point-of-need.1-5 Selected examples will introduce key aspects of such systems that include tailored signaling mechanisms and recognition elements, materials functionalization and device integration, including hybrid nanomaterials, gated indicator release systems, strip modification, and smartphone-based analysis.
Superparamagnetic hybrid polystyrene-core silica-shell beads have emerged as promising alternatives to traditional in flow cytometry-based competitive antibody assays [1]. These materials consist of a polystyrene core and a silica shell, in which magnetic nanoparticles are embedded, facilitating the handling and retention in tests. The outer silica surface allows for easy modification through silane chemistry, allowing the attachment of antibodies, or other molecules of interest. Ochratoxin A (OTA), a mycotoxin that can be found in grain products, coffee, cacao, or grapes, was chosen as the main target analyte to detect [2]. In this study, previously in house produced anti-OTA antibodies [3] were attached to the surface of the particles and the whole system was used as detection entity. In a first approach, the system was used for the development of a competitive cytometry assay using an OTA-fluorescein (OTA-F) adduct as competitor and marker. In this assay the fluorescence emitted by the OTA-F competitor on the surface of the particle was detected at a wavelength of 518 nm using a 533/30.H filter and was correlated to the forward scatter (FSC) to distinguish it from the excess of competitor still in solution. Under optimised conditions, the final assay showed a limit of detection of 0.03 nM. In a second approach, a simplified ready-to-inject fluidic system was built based on a laser (488 nm) and a photomultiplier detector to measure the signal of competitor still in solution. The competition step was carried out in a vial and the whole mixture was injected into the fluidic system. To avoid signal scattering, the particles were separated in-line using a magnet and only the OTA-F competitor still in solution was detected, reaching a limit of detection of 1.2 nM. With the aim to reduce user manipulation, the final assay is still under development for in-line incubation during the competitive step.
Robotic Measurement System Concept for Greenhouse Gas Tomography in Wastewater Treatment Plants
(2023)
This paper introduces a conceptual framework for a robotic greenhouse gas (GHG) measurement system designed for wastewater treatment plants (WWTPs). The emphasis is on accurate gas tomography measurement of emissions, crucial for national emission assessments. The proposed system is movable, semi-autonomous, and employs a combination of ground and air robots equipped with integral remote gas sensors and in-situ sensors. Employing a two/two configuration ensures comprehensive coverage of WWTPs, overcoming obstacles. The system concept lays the foundation for future implementation and evaluation, addressing the need for enhanced understanding of GHG emissions from WWTPs.
Soft polymers such as the investigated polyurethane, characterized by low Young’s moduli and prone to high shear deflection, are frequently applied in pneumatic cylinders. Their performance and lifetime without external lubrication are highly determined by the friction between seal and shaft and the wear rate. FEM simulation has established itself as a tool in seal design processes but requires input values for friction and wear depending on material, load, and velocity. This paper presents a tribological test configuration for long stroke, reciprocating movement, allowing the generation of data which meet the requirements of input parameters for FEM simulations without the geometrical influences of specific seal profiles. A numerical parameter study, performed with an FEM model, revealed the most eligible sample geometry as a flat, disc-shaped sample of the polymer glued on a stiff sample holder. At the same time, the study illustrates that the sensitivity of the contact pressure distribution to Poisson’s ratio and CoF can be minimized by the developed and verified setup. It ensures robust, reliable, and repeatable experimental results with uniform contact pressures and constant contact areas to be used in databases and FEM simulations of seals, enabling upscaling from generically shaped samples to complex seal profiles.
OpenSCAD, STL and technical drawings for the Modular sample holder designed primarily for use with The MOUSE instruments.
This modular sample holder can be used in conjunction with the following:
- Capillary flow-cell for liquid samples (10.5281/zenodo.7499421)
- Solid sample rack/plate (10.5281/zenodo.7499424)
- Laser-cut sample holder (10.5281/zenodo.7499437)
A phase-sensitive optical time domain reflectometer based on coherent heterodyne detection of geometric phase in the beat signal of light, is reported for the first time to our knowledge. The use of the geometric phase to extract strain makes it immune to polarisation diversity fading. This is because a polarisation mismatch between the interfering beams is not a hindrance to its measurement. The geometric phase is calculated using the amplitude of the beat signal and individual beam intensities without any need for phase unwrapping. It is measured per beat period and can be equated with the traditionally measured dynamic phase with appropriate scaling. The results show that the system based on the geometric phase successfully measures strain, free from polarisation mismatch fading and phase unwrapping errors, providing a completely novel solution to these problems.
Comprehensive evaluation of peptide de novo sequencing tools for monoclonal antibody assembly
(2023)
Monoclonal antibodies are biotechnologically produced proteins with various applications in research, therapeutics and diagnostics. Their ability to recognize and bind to specific molecule structures makes them essential research tools and therapeutic agents. Sequence information of antibodies is helpful for understanding antibody–antigen interactions and ensuring their affinity and specificity. De novo protein sequencing based on mass spectrometry is a valuable method to obtain the amino acid sequence of peptides and proteins without a priori knowledge. In this study, we evaluated six recently developed de novo peptide sequencing algorithms (Novor, pNovo 3, DeepNovo, SMSNet, PointNovo and Casanovo), which were not specifically designed for antibody data. We validated their ability to identify and assemble antibody sequences on three multi-enzymatic data sets. The deep learning-based tools Casanovo and PointNovo showed an increased peptide recall across different enzymes and data sets compared with spectrum-graph-based approaches. We evaluated different error types of de novo peptide sequencing tools and their performance for different numbers of missing cleavage sites, noisy spectra and peptides of various lengths. We achieved a sequence coverage of 97.69–99.53% on the light chains of three different antibody data sets using the de Bruijn assembler ALPS and the predictions from Casanovo. However, low sequence coverage and accuracy on the heavy chains demonstrate that complete de novo protein sequencing remains a challenging issue in proteomics that requires improved de novo error correction, alternative digestion strategies and hybrid approaches such as homology search to achieve high accuracy on long protein sequences.
Air-coupled ultrasound sensors have advantages over contact ultrasound sensors when a sample should not become contaminated or influenced by the couplant or the measurement has to be a fast and automated inline process. Thereby, air-coupled transducers must emit high-energy pulses due to the low air-to-solid power transmission ratios (10−3 to 10−8). Currently used resonant transducers trade bandwidth—a prerequisite for material parameter analysis—against pulse energy. Here we show that a combination of a non-resonant ultrasound emitter and a non-resonant detector enables the generation and detection of pulses that are both high in amplitude (130 dB) and bandwidth (2 µs pulse width). We further show an initial application: the detection of reflections inside of a carbon fiber reinforced plastic plate with thicknesses between 1.7 mm and 10 mm. As the sensors work contact-free, the time of flight and the period of the in-plate reflections are independent parameters. Hence, a variation of ultrasound velocity is distinguishable from a variation of plate thickness and both properties are determined simultaneously. The sensor combination is likely to find numerous industrial applications necessitating high automation capacity and opens possibilities for air-coupled, single-side ultrasonic inspection.
Despite their inherent instability, 4n π systems have recently received significant attention due to their unique optical and electronic properties. In dibenzopentalene (DBP), benzanellation stabilizes the highly antiaromatic pentalene core, without compromising its amphoteric redox behavior or small HOMO−LUMO energy gap. However, incorporating such molecules in organic devices as discrete small molecules or amorphous polymers can limit the performance (e.g., due to solubility in the battery electrolyte solution or low internal surface area). Covalent organic frameworks (COFs), on the contrary, are highly ordered, porous, and crystalline materials that can provide a platform to align molecules with specific properties in a well-defined, ordered environment. We synthesized the first antiaromatic framework materials and obtained a series of three highly crystalline and porous COFs based on DBP. Potential applications of such antiaromatic bulk materials were explored: COF films show a conductivity of 4 × 10−8 S cm−1 upon doping and exhibit photoconductivity upon irradiation with visible light. Application as positive electrode materials in Li-organic batteries demonstrates a significant enhancement of performance when the antiaromaticity of the DBP unit in the COF is exploited in its redox activity with a discharge capacity of 26 mA h g−1 at a potential of 3.9 V vs. Li/Li+ . This work showcases antiaromaticity as a new design principle for functional framework materials.
Large, ink-bottle-shaped pores in mesocellular foams (MCFs) are desired for various applications requiring enhanced mass transfer or the immobilization of larger compounds. Hence, the cylindrical pores of COK-12, an ordered mesoporous silica structurally comparable to SBA-15 but synthesized at room-temperature at quasi-neutral pH, are chemically swollen into ink-bottle pores. Therefore, p-xylene is used as a more sustainable swelling agent compared to popular alternatives. Its high boiling point allows for an additional thermal aging step to amplify the mesostructure enlargement without needing additional chemicals. For COK-12, the MCFs obtained at room temperature reach an unprecedented plateau for the modal mesopore cell and window diameter of 19.9 and 5.5 nm, respectively, with an underlying broad pore size distribution and distorted hexagonal lattice up to 14.5 nm, involving hexagonal and spherical structures. The combined chemical and thermal swelling resulted in the selective enlargement of the window diameter to more than 200% and a slightly increased cell diameter, pore size distribution, and hexagonal lattice distortion in comparison to the room temperature synthesis. Such materials are thought to be promising alternatives to SBA-15-based MCFs, often utilizing toxic catalysts during synthesis. The presented results pave the way for enhanced adsorptive, catalytic, and drug delivery performances for COK-12-based materials.
X-ray scattering datasets for samples described in the 2020 publication "Molecular Dynamics of Janus Polynorbornenes: Glass Transitions and Nanophase Separation". This dataset includes both raw and processed X-ray scattering data for samples PTCHSiO-Pr, Bu, Hx, Oc and De, alongside background measurements files (BKG). This data was collected using the MOUSE project (instrument and methodology).
X-ray scattering datasets for samples described in the 2022 publication "Molecular Mobility of Polynorbornenes with Trimethylsiloxysilyl side groups: Influence of the Polymerization Mechanism". This dataset includes both raw and processed X-ray scattering data for samples APTCN and MPTCN, alongside background measurements files (BKG).
X-ray scattering datasets for samples described in the 2022 publication "Side chain length dependent dynamics and conductivity in self assembled ion channels". This dataset includes both raw and processed X-ray scattering data for samples ILC8, ILC10, ILC12, ILC14 and ILC16 alongside background measurement files (BKG).
Pseudomonas aeruginosa is an opportunistic pathogen of considerable medical importance, owing to its pronounced antibiotic tolerance and association with cystic fibrosis and other life-threatening diseases. The aim of this study was to highlight the genes responsible for P. aeruginosa biofilm tolerance to antibiotics and thereby identify potential new targets for the development of drugs against biofilm-related infections. By developing a novel screening approach and utilizing a public P. aeruginosa transposon insertion library, several biofilm-relevant genes were identified. The Pf phage gene (PA0720) and flagellin gene (fliC) conferred biofilm-specific tolerance to gentamicin. Compared with the reference biofilms, the biofilms formed by PA0720 and fliC mutants were completely eliminated with a 4-fold-lower gentamicin concentration. Furthermore, the mreC, pprB, coxC, and PA3785 genes were demonstrated to play major roles in enhancing biofilm tolerance to gentamicin. The analysis of biofilm-relevant genes performed in this study provides important novel insights into the understanding of P. aeruginosa antibiotic tolerance, which will facilitate the detection of antibiotic resistance and the development of antibiofilm strategies against P. aeruginosa.
Chemical modification by peroxynitrite enhances TLR4 activation of the grass pollen allergen Phl p 5
(2023)
The chemical modification of aeroallergens by reactive oxygen and nitrogen species (ROS/RNS) may contribute to the growing prevalence of respiratory allergies in industrialized countries. Post-translational modifications can alter the immunological properties of proteins, but the underlying mechanisms and effects are not well understood. In this study, we investigate the Toll-like receptor 4 (TLR4) activation of the major birch and grass pollen allergens Bet v 1 and Phl p 5, and how the physiological oxidant peroxynitrite (ONOO–) changes the TLR4 activation through protein nitration and the formation of protein dimers and higher oligomers. Of the two allergens, Bet v 1 exhibited no TLR4 activation, but we found TLR4 activation of Phl p 5, which increased after modification with ONOO– and may play a role in the sensitization against this grass pollen allergen. We attribute the TLR4 activation mainly to the two-domain structure of Phl p 5 which may promote TLR4 dimerization and activation. The enhanced TLR4 signaling of the modified allergen indicates that the ONOO–-induced modifications affect relevant protein-receptor interactions. This may lead to increased sensitization to the grass pollen allergen and thus contribute to the increasing prevalence of allergies in the Anthropocene, the present era of globally pervasive anthropogenic influence on the environment.
The combination of acoustically levitated droplets, mid-IR laser evaporation, and subsequent post-ionization by secondary electrospray ionization was applied for monitoring the enzymatic digestion of various proteins. Acoustically levitated droplets are an ideal, wall-free model reactor, readily allowing compartmentalized microfluidic trypsin digestions. Time-resolved interrogation of the droplets yielded real-time information on the progress of the reaction and thus provided insights into reaction kinetics. After 30 min of digestion in the acoustic levitator, the obtained protein sequence coverages were identical to the reference overnight digestions. Importantly, our results clearly demonstrate that the applied experimental setup can be used for the real-time investigation of chemical reactions. Furthermore, the described methodology only uses a fraction of the typically applied amounts of solvent, analyte, and trypsin. Thus, the results exemplify the use of acoustic levitation as a green analytical chemistry alternative to the currently used batch reactions.
This thesis investigates ultrasonic guided waves (GW) in multi-layered plates with the focus on higher order modes. The aim is to develop techniques for hybrid structures such as of adhesive bonds and composite pressure vessels (COPV) which are widely used in automotive and aerospace industries and are still challenging to inspect non-destructively. To be able to analyse GW, numerical methods and precise material properties are required. For this purpose, an efficient semi-analytical approach, the Scaled Boundary Finite Element Method, is used. The material properties are inferred by a GW-based optimisation procedure and a sensitivity study is performed to demonstrate the influence of properties on GW. Then, an interesting feature, called mode repulsion, is investigated with respect to weak and strong adhesive bonds. The results show that the coupling between two layers influences the distance between coupled modes in a mode repulsion region, thus allowing for the characterisation of adhesive bonds. At next, wave-damage interaction is studied in the hybrid structure as of the COPV. Results show that the wave energy can be concentrated in a certain layer enabling damage localisation within different layers. Further investigations are carried out on the hybrid plate with an impact-induced damage. Two well-known wavenumber mapping techniques, which allow to quantify the damage in three dimensions, are implemented and their comparison is done for the first time.
Dose enhancement by gold nanoparticles (AuNP) increases the biological effectiveness of radiation damage in biomolecules and tissue. To apply them effectively during cancer therapy their influence on the locally delivered dose has to be determined.[1] Hereby, the AuNP locations strongly influence the energy deposit in the nucleus, mitochondria, membrane and the cytosol of the targeted cells. To estimate these effects, particle scattering simulations are applied. In general, different approaches for modeling the AuNP and their distribution within the cell are possible. In this work, two newly developed continuous and discrete-geometric models for simulations of AuNP in cells are presented. [2] These models are applicable to simulations of internal emitters and external radiation sources. Most of the current studies on AuNP focus on external beam therapy. In contrast, we apply the presented models in Monte-Carlo particle scattering simulations to characterize the energy deposit in cell organelles by radioactive 198AuNP. They emit beta and gamma rays and are therefore considered for applications with solid tumors. Differences in local dose enhancement between randomly distributed and nucleus targeted nanoparticles are compared. Hereby nucleus targeted nanoparticels showed a strong local dose enhancement in the radio sensitive nucleus. These results are the foundation for ongoing experimental work which aims to obtain a mechanistic understanding of cell death induced by radioactive 198Au.
The compatible solute and osmolyte ectoine is an effective protectant of biomolecules and whole cells against heating, freezing and high salinity. The protection of cells (human Keratinocytes) by ectoine against ultraviolet radiation was also reported by various authors, although the underlying mechanism is not yet understood. We present results on the irradiation of biomolecules (DNA) with ionizing radiation (high energy electrons) in fully aqueous environment in the presence of ectoine and high salt concentrations. The results demonstrate an effective radiation protection of DNA by ectoine against the induction of single strand breaks by ionizing radiation. The effect is explained by an increased in low-energy electron scattering at the enhanced free-vibrational density of states of water due to ectoine, as well as the action of ectoine as an OH-radical scavenger. This was demonstrated by Raman spectroscopy, electron paramagnetic resonance (EPR) and Monte-Carlo simulations (Geant4).
Showcasing research from the Federal Institute for Material Research and Testing Berlin and Fraunhofer Institute for Celltherapy and Immunology Branch Bioanalytics and Bioprocesses Potsdam.
Bio-SAXS of single-stranded DNA-binding proteins: Radiation protection by the compatible solute ectoine.
We aimed to increase the possible undisturbed exposure time during bio-SAXS measurements of single-stranded DNA-binding proteins. Therefore small angle X-ray scattering was performed on Gene-V Protein (G5P/GVP), which is involved in DNA repair processes. To achieve this, irradiations were performed in presence and absence of the hydroxyl-radical scavenger and osmolyte Ectoine, which showed efficient radiation protection and prevented protein aggregation, thus allows for a non-disturbing way to improve structure-determination of biomolecules.
After describing the basics of distributed fiber optic sensing in general and distributed fiber optic acoustic sensing (DAS) in particular, several currently and previously investigated fields of application of DASin infrastructure monitoring and seismic monitoring are presented. A focus is placed on seismic measurements and DAS measurements determining the dynamic responses of concrete structures to certain stimuli.
Inorganic nanocrystals with linear and nonlinear luminescence in the ultraviolet, visible, near infrared and short-wave infrared like semiconductor quantum dots and spectrally shifting lanthanide-based nanophosphors have meanwhile found applications in the life and material sciences ranging from optical reporters for bioimaging and sensing over security barcodes to solid state lighting and photovoltaics. These nanomaterials commonly have increasingly sophisticated core/shell particle architectures with shells of different chemical composition and thickness to minimize radiationless deactivation at the particle surface that is usually the main energy loss mechanism [1]. For lanthanide-based spectral shifters, particularly for very small nanoparticles, also surface coatings are needed which protect near-surface lanthanide ions from luminescence quenching by high energy vibrators like O-H groups and prevent the disintegration of these nanoparticles under high dilution conditions. [2,3,4]. The identification of optimum particle structures requires quantitative spectroscopic studies focusing on the key performance parameter photoluminescence quantum yield [5,6], ideally flanked by single particle studies to assess spectroscopic inhomogeneities on a particle-to-particle level for typical preparation methods [7,8], Moreover, in the case of upconversion nanoparticles with a multi-photonic and hence, excitation power density (P)-dependent luminescence, quantitative luminescence studies over a broad P range are required to identify particle architectures that are best suited for applications in fluorescence assays up to fluorescence microscopy. Here, we present methods to quantify the photoluminescence of these different types of emitters in the vis/NIR/SWIR and as function of P and demonstrate the importance of such measurements for a profound mechanistic understanding of the nonradiative deactivation pathways in semiconductor and upconversion nanocrystals of different size and particle architecture in different environments.
The surface chemistry of nanomaterials controls their interaction with the environment and biological species and their fate and is hence also relevant for their potential toxicity. This has meanwhile led to an increasing interest in validated and preferably standardized methods for the determination and quantification of surface functionalities on nanomaterials and initiated different standardization projects within ISO/TC 229 and IEC/TC 113 as well as interlaboratory comparisons (ILCs) of different analytical methods for the quantification of surface coatings by OECD. Here we present the results of a first ILC on the quantification of the amount of amino functionalities on differently sized inorganic nanoparticles done by division Biophotonics and the National Research Council of Canada (NRC) and the PWI 19257 on the Characterization and Quantification of Surface Functional Groups and Coatings on Nanoobjects approved by ISO/TC 229 (WG2) in fall 2022 that will result in a VAMAS study on this topic organized by division Biophotonics. Key words: nanoparticles, surface analysis, surface functional groups, quantification, optical assay, qNMR, VAMAS, standardization, ICL, quality assurance, reference material.
The overview of the activity of Federal Institute for Material Research and Testing (BAM, Belin, Germany) in the field of additively manufacturing material characterization will be presented. The research of our group is focused on the 3D imaging of AM materials by means of X-ray Computed Tomography at the lab and at synchrotron, and the residual stress characterization by diffraction (nondestructive technique).
Episodic failures of ice-dammed lakes have produced some of the largest floods in history, with disastrous consequences for communities in high mountains. Yet, estimating changes in the activity of ice-dam failures through time remains controversial because of inconsistent regional flood databases. Here, by collating 1,569 ice-dam failures in six major mountain regions, we systematically assess trends in peak discharge, volume, annual timing and source elevation between 1900 and 2021. We show that extreme peak flows and volumes (10 per cent highest) have declined by about an order of magnitude over this period in five of the six regions, whereas median flood discharges have fallen less or have remained unchanged.
Ice-dam floods worldwide today originate at higher elevations and happen about six weeks earlier in the year than in 1900. Individual ice-dammed lakes with repeated outbursts show similar negative trends in magnitude and earlier occurrence, although with only moderate correlation to glacier thinning8. We anticipate that ice dams will continue to fail in the near future, even as glaciers thin and recede. Yet widespread deglaciation, projected for nearly all regions by the end of the twenty-first century9, may bring most outburst activity to a halt.
Inductively coupled plasma mass spectrometry (ICP-MS) emerged as a powerful technique for trace analysis of soil due to its multi-element capability, high sensitivity and low sample consumption. However, despite its success and widespread use, ICP-MS has several persistent drawbacks, such as high argon gas consumption, argon-based polyatomic interferences and the need for complicated RF-power generators. Unlike argon-based ICP, the nitrogen microwave inductively coupled atmospheric pressure mass spectrometry (MICAP-MS) uses nitrogen as plasma gas, which eliminates high operating costs associated with argon-gas consumption as well as the argon-based interferences1. In this work, the applicability of MICAP-MS for elemental analysis in different matrices is investigated. For this purpose, reference soil samples and steel samples are digested with aqua regia and used for analysis. Concentrations of selected elements are determined using MICAP-MS and validated with ICP-MS und certified values. Sensitivities, limits of detection and gas consumption for both methods are compared and discussed in detail. Performance of MICAP-MS under different nitrogen plasma gas concentrations is investigated and compared. Moreover, the performance of MICAP-MS in alloy matrices is investigated and discussed.
Per- und polyfluorierte Alkylverbindungen (PFAS) sind eine Substanzklasse bestehend aus mehreren tausenden Einzelverbindungen. Unter PFAS zählen alle Verbindungen, die mindestens eine perfluorierte Methyl- (-CF3) oder Methylen-Gruppe (-CF2-) besitzen. Somit zählt auch ein großer Teil der fluorierten Medikamente, Pflanzenschutzmittel oder Biozide in die PFAS-Substanzklasse. Aufgrund der Persistenz, Bioakkumulation in Nahrungsketten, Toxizität und der ubiquitären Verbreitung von PFAS zählen sie zu den „emerging pollutants“. Die PFAS-Analytik ist wegen ihrer vielfältigen physikalisch-chemischen Eigenschaften und der sehr hohen Anzahl an PFAS eine große Herausforderung. Da es für viele Anwendungen noch ungewiss ist, welche PFAS verwendet werden, wie sie in die Umwelt gelangen und welche Transformations- bzw. Abbauprodukte entstehen, stoßen analytische Ansätze, die nur auf Einzelsubstanzen abzielen, hier an ihre Grenzen. PFAS-Summenparameter-Methoden, die darauf abzielen ein möglichst vollständiges Abbild der PFAS-Belastungssituation widerzuspiegeln, werden daher immer wichtiger.
Cardiac troponin I (cTnI) is a crucial biomarker for diagnosing cardiac vascular diseases, including acute myocardial infarction (AMI). This study presents a proof-of-concept chemiluminescence-based immunosensor for rapid and accurate measurement of cTnI, with the potential for online monitoring. The immunosensor incorporates a flow cell design and a sensitive complementary metal-oxide-semiconductor (CMOS) camera for optical readout. A microfluidic setup was established to enable selective and quasi-online determination of cTnI within ten minutes. The sensor was tested with recombinant cTnI in phosphate buffer, demonstrating measurements in the concentration range of 2–25 µg/L, with a limit of detection (LoD) of 0.6 µg/L (23 pmol/L) achieved using the optimized system. The immunosensor exhibited high selectivity, as no cross-reactivity was observed with other recombinant proteins such as cTnT and cTnC at a concentration of 16 µg/L. Measurements with diluted blood plasma and serum yielded an LoD of 60 µg/L (2.4 nmol/L) and 70 µg/L (2.9 nmol/L), respectively. This biosensor offers a promising approach for the rapid and sensitive detection of cTnI, contributing to the diagnosis and management of acute myocardial infarction and other cardiac vascular diseases.
Functionally graded porous scaffolds (FGPS) constructed with pores of different size arranged as spatially continuous structure based on sheet-based gyroid with three different scaling factors of 0.05, 0.1 and 0.2 were produced by electron beam powder bed fusion. The pore dimensions of the obtained scaffolds satisfy the values required for optimal bone tissue ingrowth. Agglomerates of residual powder were found inside all structures, which required post-manufacturing treatment. Using X-ray Computed Tomography powder agglomerations were visualized and average wall thickness, wall-to-wall distances, micro- and macro-porosities were evaluated. The initial cleaning by powder recovery system (PRS) was insufficient for complete powder removal. Additional treatment by dry ultrasonic vibration (USV) was applied and was found successful for gyroids with the scaling factors of 0.05 and 0.1. Mechanical properties of the samples, including quasi-elastic gradients and first maximum compressive strengths of the structures before and after USV were evaluated to prove that additional treatment does not produce structural damage. The estimated quasi-elastic gradients for gyroids with different scaling factors lie in a range between 2.5 and 2.9 GPa, while the first maximum compressive strength vary from 52.5 for to 59.8 MPa, compressive offset stress vary from 46.2 for to 53.2 MPa.
Virus-like particles are of great interest. Due to the lack of functional amino acids, they are non-infectious and are widely investigated for their usage in the biomedical field, such as nanomaterials, vaccines, drug delivery.
This thesis is about the engineering of virus-like particles, which are formed by self-assembly of LRV1 capsid proteins. Basis was a publication by Procházková et al. (2021), where the structure of virus-like particles, derived from recombinant LRV1 capsid proteins, was determined using cryo-electron microscopy.
Goal of my work was to investigate, whether it is possible to modify the surface of LRV1 virus-like particles by protein engineering. Next to an LRV1 capsid protein with a C-termini polyhistidine-tag like in the publication, a genetically modified LRV1 capsid protein with an internal polyhistidine-tag was supposed to be expressed. It was supposed to be analyzed, whether it still comes to a self-assembly of the capsid proteins.
The genetical constructs were generated by PCR based on a complementary LRV1 DNA, cloned into an expression vector, and using Sanger sequencing it was shown that the amino acid sequences were like expected. For the recombinant expression different E. coli (BL21 STAR (DE3), BL21 (DE3) pLysS, BL21 STAR (DE3) pRARE3 and T7 express lysY/Iq) strains were used, as well as different expression conditions tested by varying temperature, medium, isopropyl-ß-D-thiogalactoside oncentration, and induction duration. Best results were obtained expressing in T7 express lysY/Iq for 5 hours in Terrific Broth medium at 16 °C and 3 mM Isopropyl ß-D-1thiogalactopyranoside. After that, the recombinant proteins were purified under native conditions by their polyhistidine-tags using nickel affinity chromatography. Overall, a higher yield was obtained for the capsid protein with the C-termini polyhistidine-tag during expression, which was also visible in all following experiments. The expression of both constructs in E. coli was comparably low. Still, it was possible to validate for virus-like particles for both proteins using transmission electron microscopy. Thus, it was demonstrated for the first time that surface-modified LRV1 capsid proteins are able to assemble into virus-like particles. For further experiments and higher yield of soluble LRV1 capsid proteins for virus-like particle production, a different expression system should be used: Therefore, the LEXSY expression system should be optimal, it bases on Leishmania tarenolae, a natural LRV1 host system.
We present a temperature sensor based on a polymer exhibiting a Lower Critical Solution Temperature (LCST) in aqueous solution encapsulated in a capillary. Parameters are chosen such that the solution exhibits a cloud point in a temperature range of 30° C to 39°C. The characteristic of thermoresponsive polymers with an LCST, is that above that temperature phase separation of the polymer takes place which leads to a temperature-dependent formation of a cloudy suspension. An optical intensity measurement over the desired temperature range is established by an increase of optical attenuation inside the polymer solution caused by a rising temperature. For our purpose, the polymer capillary is connected to transmitter and receiver via a Polymer Optical Fibre (POF). Our intensity measurement is, to the best of our knowledge, a novel method and can be considered simple when compared to existing fibre-based temperature measurement techniques. Due to the lack of electrical components at the probe, this sensor is suitable for measurements in strong electromagnetic fields and environments for which flying sparks are hazardous, i.e., inflammable fluids or gases. Furthermore, all manufactured sensors share the same temperature dependence and, therefore, are well-suited for comparative measurement, e.g., flow measurement systems. With the given temperature range, a body temperature measurement is also suitable.
We present a high-precision fiber-optic temperature sensor based on a polymer possessing a Lower Critical Solution Temperature (LCST) in aqueous solution encapsulated in a capillary. For a temperature higher than the LCST the transparent homogenous polymer solution changes into a suspension which forms an opaque fluid. The resulting temperature-dependent turbidity influences the transmission characteristics measured using a simple fiber-optic system.
The presented development provides a small-sized, robust temperature sensor, patented by the BAM (patent nr.: EP 3 043 161 B1), easy to integrate in many application fields, especially for process monitoring.
Motivation: Inferring taxonomy in mass spectrometry-based shotgun proteomics is a complex task. In multi-species or viral samples of unknown taxonomic origin, the presence of proteins and corresponding taxa must be inferred from a list of identified peptides, which is often complicated by protein homology: many proteins do not only share peptides within a taxon but also between taxa. However, the correct taxonomic inference is crucial when identifying different viral strains with high-sequence homology—considering, e.g., the different epidemiological characteristics of the various strains of severe acute respiratory syndrome-related coronavirus-2. Additionally, many viruses mutate frequently, further complicating the correct identification of viral proteomic samples.
Results: We present PepGM, a probabilistic graphical model for the taxonomic assignment of virus proteomic samples with strain-level resolution and associated confidence scores. PepGM combines the results of a standard proteomic database search algorithm with belief propagation to calculate the marginal distributions, and thus confidence scores, for potential taxonomic assignments. We demonstrate the performance of PepGM using several publicly available virus proteomic datasets, showing its strain-level resolution performance. In two out of eight cases, the taxonomic assignments were only correct on the species level, which PepGM clearly indicates by lower confidence scores.
Availability and implementation: PepGM is written in Python and embedded into a Snakemake workflow. It is available at https://github.com/BAMeScience/PepGM.
In this study, we propose the use of nondestructive, depth-resolved, element-specific characterization using grazing exit X-ray absorption near-edge structure spectroscopy (GE-XANES) to investigate the corrosion process in compositionally complex alloys (CCAs). By combining grazing exit X-ray fluorescence spectroscopy (GE-XRF) geometry and a pnCCD detector, we provide a scanning-free, nondestructive, depth-resolved analysis in a sub-micrometer depth range, which is especially relevant for layered materials, such as corroded CCAs. Our setup allows for spatial and energy-resolved measurements and directly extracts the desired fluorescence line, free from scattering events and other overlapping lines. We demonstrate the potential of our approach on a compositionally complex CrCoNi alloy and a layered reference sample with known composition and specific layer thickness. Our findings indicate that this new GE-XANES approach has exciting opportunities for studying surface catalysis and corrosion processes in real-world materials.
With increasing demand and environmental concerns, researchers are exploring new materials that can perform as well or better than traditional materials while reducing environmental impact. The BAMline, a real-life sample materials research beamline, provides unique insights into materials’ electronic and chemical structure at different time and length scales. The beamline specializes in x-ray absorption spectroscopy, x-ray fluorescence spectroscopy, and tomography experiments. This enables real-time optimization of material properties and performance for various applications, such as energy transfer, energy storage, catalysis, and corrosion resistance. This paper gives an overview of the analytical methods and sample environments of the BAMline, which cover non-destructive testing experiments in materials science, chemistry, biology, medicine, and cultural heritage. We also present our own synthesis methods, processes, and equipment developed specifically for the BAMline, and we give examples of synthesized materials and their potential applications. Finally, this article discusses the future perspectives of the BAMline and its potential for further advances in sustainable materials research.
Im Rahmen des Seminars "Angewandte Forschungsthemen (SAFT)" am Institut für Geowissenschaften der Christian-Albrechts-Universität zu Kiel werden verschiedene geophysikalische Methoden vorgestellt, die bei der zerstörungsfreien Prüfung im Bauwesen zum Einsatz kommen. Neben einem Überblick der Arbeiten an der BAM im Allgemeinen und dem Fachbereich im Besonderen geht es vor allem um den Einsatz von Ultraschallmethoden. Drei wesentliche Schwerpunkte werden dabei beleuchtet:
1) (Geophysikalische) Antworten auf Herausforderungen bei Ultraschall-Anwendungen
2) Material research and multi-sensory monitoring for concrete sealing structures in rock salt unterground repositories (Projekt SealWasteSafe)
und 3) Untersuchung von Spritzbeton-Probekörpern unter Tage mit Ultraschall zur Qualitätssicherung von Verschlussbauwerken.
Insgesamt werden diverse Möglichkeiten für die Geophysik für Forschung und Studierende im Bereich der zerstörungsfreien Prüfung im Bauwesen aufgezeigt.
Quantitative Analysis and 2D/3D Elemental Imaging of Cocoa Beans Using X‑ray Fluorescence Techniques
(2023)
As an important raw material for the confectionery industry, the cocoa bean (Theobroma cacao L.) has to meet certain legal requirements in terms of food safety and maximum contaminant levels in order to enter the cocoa market. Understanding the enrichment and distribution of essential minerals but also toxic metals is of utmost importance for improving the nutritional quality of this economically important raw food material. We present three X-ray fluorescence (XRF) techniques for elemental bio-imaging of intact cocoa beans and one additional XRF technique for quantitative analysis of cocoa pellets. The interrelation of all the methods presented gives a detailed picture of the content and 3D-resolved distribution of elements in complete cocoa beans for the first time.
Moisture testing and mapping
(2023)
Synchrotron X-ray computed tomography (SXCT) at BAMline has been paired with in-situ tensile loading to monitor damage evolution in LPBF Metal Matrix Composite (MMC) 7017 Aluminium alloy + 3 wt% Zr + 0.5 wt% TiC. The processing of the material leads formation to different categories of Zr-rich inclusions, precipitates and defects. In-situ SXCT test disclosed the critical role of the pre-cracks in the reinforcement phases in the failure mechanisms of LPBF MMC. The damage was initiated from lack-of-fusion defects and cracks propagated through coalescence with other defects.
Mesoporous glasses are a promising class of bioresorbable biomaterials characterized by high surface area and extended porosity in the range of 2 to 50 nm. These peculiar properties make them ideal materials for the controlled release of therapeutic ions and molecules. Whilst mesoporous silicate-based glasses (MSG) have been widely investigated, much less work has been done on mesoporous phosphate-based glasses (MPG). In the present study, MPG in the P2O5–CaO–Na2O system, undoped and doped with 1, 3, and 5 mol% of Cu ions were synthesized via a combination of the sol–gel method and supramolecular templating. The non-ionic triblock copolymer Pluronic P123 was used as a templating agent. The porous structure was studied via a combination of Scanning Electron Microscopy (SEM), Small-Angle X-ray Scattering (SAXS), and N2 adsorption–desorption analysis at 77 K. The structure of the phosphate network was investigated via solid state 31P Magic Angle Spinning Nuclear Magnetic Resonance (31P MAS-NMR) and Fourier Transform Infrared (FTIR) spectroscopy. Degradation studies, performed in water via Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES), showed that phosphates, Ca2+, Na+ and Cu ions are released in a controlled manner over a 7 days period. The controlled release of Cu, proportional to the copper loading, imbues antibacterial properties to MPG. A significant statistical reduction of Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) bacterial viability was observed over a 3 days period. E. coli appeared to be more resistant than S. aureus to the antibacterial effect of copper. This study shows that copper doped MPG have great potential as bioresorbable materials for controlled delivery of antibacterial ions.
It can be difficult to efficiently model ultrasonic waves in 3D structures, especially when the computational model needs to account for complex geometries. This contribution presents a solution based on the Scaled Boundary Finite Element Method (SBFEM). It is a numerical tool suitable for elastodynamic problems. A space-tree discretisation, namely quad-trees, is used. This technique allows the decomposition of an image into quadrilaterals or quads, which are extruded to generate the 3D plate geometry. In particular, small quads resolve regions with discontinuities, allowing them to represent fine details in the structure. Moreover, this meshing technique allows for exploiting cell similarities, making the calculation procedure more efficient. The space-tree discretisations are generated from a high-resolution image containing all the information about damaged regions or boundary conditions. The resulting SBFEM polyhedral domains employ transition elements to ensure correct coupling between cells of different sizes. The analytical solution of a cylindrical scatterer serves as a reference to validate the proposed approach. Other examples also demonstrate the validity of the methodology and its flexibility.
This talk introduces the expanded view that comes from wide-range X-ray scattering investigations.
Compared to X-ray diffraction studies alone, the additional angular range of this technique provides information on the larger structural dimensions present in your samples. This allows for the extraction of information on the size and size distribution of nanostructural components, such as nanoparticles, nanovoids, and any other structure exhibiting an electron density contrast.
The talk introduces the technique, the MOUSE instrument used for these investigations, and provides several real-world examples of its uses. The audience is invited to choose which examples captures their interest from a range of options, in the latter segment of the talk.
In this work, the limits of using spatially structured heating combined with subsequent photothermal super resolution reconstruction for the thermographic detection and resolution of internal defects are investigated. The approach is based on the application of modern high-power laser projector technology, which is used to repeatedly project varying spatially structured 2D pixel patterns to photothermally heat the object under test. After processing the generated thermographic data using nonlinear convex optimisation in conjunction with exploiting the joint-sparse nature of the defect signals within the individual measurements, a high-resolution 2D-sparse defect/inhomogeneity map is obtained. The main focus of the investigation is set on the influence of the number of individual measurements on the achievable reconstruction quality. Using numerical simulations based on an analytical representation of the forward solution to the underlying inverse problem, the convergence rate over performed measurements of the achievable reconstruction quality is determined. Finally, all findings are experimentally validated by reconstructing a set of internal defects in an additively manufactured sample. In this work, it is shown that for a variety of different defect separation distances, the projection of 50 different pixel patterns allows for a good trade-off between experimental complexity and reconstruction quality.
Ionizing radiation damage to DNA plays a fundamental role in cancer therapy. X-ray photoelectron-spectroscopy (XPS) allows simultaneous irradiation and damage monitoring. Although water radiolysis is essential for radiation damage, all previous XPS studies were performed in vacuum. Here we present near-ambient-pressure XPS experiments to directly measure DNA damage under water atmosphere. They permit in-situ monitoring of the effects of radicals on fully hydrated double-stranded DNA. The results allow us to distinguish direct damage, by photons and secondary low-energy electrons (LEE), from damage by hydroxyl radicals or hydration induced modifications of damage pathways. The exposure of dry DNA to x-rays leads to strand-breaks at the sugar-phosphate backbone, while deoxyribose and nucleobases are less affected. In contrast, a strong increase of DNA damage is observed in water, where OH-radicals are produced. In consequence, base damage and base release become predominant, even though the number of strand-breaks increases further.
Geschlossene Materialkreisläufe und sortenreine Materialfraktionen sind erforderlich, um hohe Verwertungs und Recyclingquoten in der Bauindustrie zu erreichen Beim Recycling von Bau und Abbruchabfällen wurden bisher bevorzugt einfache, aber bewährte Techniken eingesetzt, um große Mengen Bauschutt in kurzer Zeit zu verarbeiten Dies steht im Gegensatz zu den immer komplexer werdenden Verbundwerkstoffen in der Mineralbaustoffindustrie Die aktuell oft praktizierte händische Klaubung bürgt viele Risiken und Gefahren für das ausführende Personal und basiert lediglich auf offensichtlichen, visuell erkennbaren Unterschieden zur Trennung Eine automatisierte, sensorgestützte Sortierung dieser Baustoffe könnte diese Praxis ergänzen oder ersetzen, um die Verarbeitungsgeschwindigkeit, die Recyclingraten, die Sortierqualität und die vorherrschenden Gesundheitsbedingungen zu verbessern.
Geschlossene Materialkreisläufe und sortenreine Materialfraktionen sind erforderlich, um hohe Verwertungs und Recyclingquoten in der Bauindustrie zu erreichen Beim Recycling von Bau und Abbruchabfällen wurden bisher bevorzugt einfache, aber bewährte Techniken eingesetzt, um große Mengen Bauschutt in kurzer Zeit zu verarbeiten Dies steht im Gegensatz zu den immer komplexer werdenden Verbundwerkstoffen in der Mineralbaustoffindustrie Die aktuell oft praktizierte händische Klaubung bürgt viele Risiken und Gefahren für das ausführende Personal und basiert lediglich auf offensichtlichen, visuell erkennbaren Unterschieden zur Trennung Eine automatisierte, sensorgestützte Sortierung dieser Baustoffe könnte diese Praxis ergänzen oder ersetzen, um die Verarbeitungsgeschwindigkeit, die Recyclingraten, die Sortierqualität und die vorherrschenden Gesundheitsbedingungen zu verbessern.
Functionalized Ti3C2Tx nanosheets based biosensor for point-of-care detection of SARS-CoV‑2 antigen
(2023)
MXenes are considered a promising class of two-dimensional materials with extraordinary physical and electrochemical properties. Distinguished features like high specific surface area and outstanding electrical conductivity make them suitable for electrochemical biosensing applications. Here, we report the development of a biosensor involving the functionalized MXene−titanium carbide nanosheets (Ti3C2Tx-NS) and monoclonal antibodies against the SARS-CoV-2 nucleocapsid protein (anti-SARS-CoV-2 mAb) to design a point-of-care device for detection of the SARS-CoV-2 nucleocapsid protein (SARS-CoV-2 NP) antigen. Few-layered titanium carbide nanosheets (denoted as FL-Ti3C2Tx-NS) have been synthesized using a single-step etching and delamination method and characterized using optical and electron microscopy techniques revealing the suitability for immunosensing applications. Binding studies revealed the excellent affinity between the biosensor and the SARS-CoV-2 NP. Electrochemical detection of SARS-CoV-2 NP is performed using differential pulse voltammetry and read by a smartphone-based user interface. The proposed FL-Ti3C2Tx-NS based biosensor offers the detection of SARS-CoV-2 NP with a limit of detection of 0.91 nM in a wide detection range in spiked saliva samples. Additionally, there is no cross-reactivity in the presence of potential interferants like SARS-CoV-2 spike glycoprotein and bovine serum albumin. These findings demonstrate the potential of MXenes in developing a rapid and reliable tool for SARS-CoV-2 NP detection. While we report the biosensing of SARS-CoV-2 NP, our system also paves the way for the detection of other SARS-CoV-2 antigens like spike protein or other biomolecules based on antigen−antibody interactions.
Human papillomavirus (HPV) DNA detection can enable the early diagnosis of high-risk HPV types responsible for cervical cancer. HPV detection is also essential for investigating the clinical behavior and epidemiology of particular HPV types, characterization of study populations in HPV vaccination trials and monitoring the efficacy of HPV vaccines. In this study, two azaBODIPY dyes (1 and 2) were used as references and were doped into polystyrene particles (PS40), while a short HPV DNA single strand was used as a target molecule and was covalently bound to the silica shell. These particles were employed as optical probes in 1:1 hybridization assays, and their potential applicability as a tool for multiplex assays for the detection of different strands of HPV was evaluated using flow cytometry. A good separation in the fluorescence of the four different voncentrations prepared for each dye was observed. To perform the hybridization assays, HPV18, HPV16, HPV11 and HPV6 single strands were attached to the particles through EDC-mediated coupling. The c-DNA-1-PS40 and c-DNA-2-PS40 particles exhibited low limit of detection (LOD) and quantification (LOQ) values for HPV11, and a narrow detection range was obtained. Multiplexed assay experiments were successfully performed for both particles, and the results proved that c-DNA-1-PS40 could potentially be used as a tool for multiplexing assays and merits further in-depth study in this context.
In this paper, we present a collection of machine learning assisted distributed fiber optic sensors (DFOS) for applications in the field of infrastructure monitoring. We employ advanced signal processing based on artificial neural networks (ANNs) to enhance the performance of the dynamic DFOS for strain and vibration sensing. Specifically, ANNs in comparison to conventional and computationally expensive correlation and linearization algorithms, deliver lower strain errors and speed up the signal processing allowing real time strain monitoring. Furthermore, convolutional neural networks (CNNs) are used to denoise the dynamic DFOS signal and enable useable sensing lengths of up to 100 km. Applications of the machine learning assisted dynamic DFOS in road traffic and railway infrastructure monitoring are demonstrated. In the field of static DFOS, machine learning is applied to the well-known Brillouin optical frequency domain analysis (BOFDA) system. Specifically, CNN are shown to be very tolerant against noisy spectra and contribute towards significantly shorter measurement times. Furthermore, different machine learning algorithms (linear and polynomial regression, decision trees, ANNs) are applied to solve the well-known problem of cross-sensitivity in cases when temperature and humidity are measured simultaneously. The presented machine learning assisted DFOS can potentially contribute towards enhanced, cost effective and reliable monitoring of infrastructures.