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Paper des Monats
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Validation of a fast and traceable radiographic scale calibration of dimensional computed tomography
(2022)
A fast and highly precise method of determining the geometrical scale factor of computed tomography (CT) measurements has been validated successfully by Bundesanstalt für Materialforschung und -prüfung (BAM), the Federal Institute of Metrology (METAS) and Physikalisch-Technische Bundesanstalt (PTB) within the scope of AdvanCT (Advanced Computed Tomography for dimensional and surface measurements in industry), a project funded in the European Metrology Programme for Innovation and Research (EMPIR). The method has been developed by PTB and requires only two radiographic images of a calibrated thin 2D standard (hole grid standard) from two opposite directions. The mean grid distance is determined from both radiographs. From this and with the help of the calibration result, the radiographic scale and therefore the voxel size is determined. The procedure takes only a few minutes and avoids a time-consuming CT scan. To validate the method, the voxel sizes determined via this method were compared with voxel sizes determined from CT scans of calibrated objects. Relative deviations between the voxel sizes in the range of 10−5 were
achieved with minimal effort using cone-beam CT systems at moderate magnifications.
Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) is increasingly used to study the distribution of metal-containing drugs, imaging probes and nanomaterials in connection with disease related changes and therapy progress. Additionally, biomolecules can be detected indirectly by using metal-tagged antibodies.
The extracellular matrix (ECM) is, besides the cells, an important component of all body tissues. The macromolecular network of the ECM consists of structural proteins (e.g., collagen, elastin) and proteoglycans composed of highly negatively charged carbohydrates, the glycosaminoglycans (GAGs), which are covalently linked to a protein core. Many diseases, including inflammatory processes and tumors, are associated with characteristic ECM changes at an early stage. Recent studies have shown that contrast agents for magnetic resonance imaging (MRI), which are based on gadolinium containing chelate complexes or iron oxide nanoparticles, can bind themselves to ECM components.
To elucidate the role of GAGs like keratan sulfate (KS) and its modification state in disease, highly specific tools are necessary. As a complement to conventional immunohistochemistry LA-ICP-MS was applied to investigate the distribution of KS in tissue thin sections using a well characterized anti-KS antibody labelled with metal ions. Furthermore, LA-ICP-MS was used for the detection of MRI contrast agents and the identification of their target cells and molecules in tissue samples from animal models, e.g. for cardiovascular diseases. The results show the possibilities of LA-ICP-MS for the elucidation of pathological tissue changes.
Probe diagnostics is used to determine the electron temperature and electron number density in a low pressure inductively coupled plasma (ICP) ignited in the mixture of SiF4, Ar and H2. Emission spectra of mixtures with different stoichiometry of components are investigated and the electron density distribution function (EDDF) is estimated. The optimal conditions for high conversion of SiF4 into Si are found by studying the dependence of the yield of silicon upon the ratio of reagents. The maximum achieved yield of silicon is 85% under the optimal conditions. Based on the analysis of IR and MS spectra of exhaust gases, 5% of initial SiF4 converts into volatile fluorosilanes. A rate of production of Si is 0.9 g/h at the energy consumption 0.56 kWh /g.
Nanoforms with at least one dimension below 100 nm have an important part to play in more and more areas of our daily life. Therefore, risk assessment of these materials is becoming increasingly important. In this context, the European Chemical Agency (ECHA) considered eleven physico-chemical properties as relevant, of which the following six are essential for the registration: chemical composition, crystallinity, particle size, particle shape, surface chemistry and specific surface area. Four of these priority properties can be obtained with electron microscopy and surface analytics like XPS and ToF-SIMS. The reliability of this data must be ensured, especially for their use for grouping and read across approaches. On the other hand, the “reproducibility” crisis has revealed major shortcomings in the reliability of published data.
In a case study, we show how the quality of the data can be ensured by using existing standards and protocols of each step in the workflow of sample characterization. As exemplary samples, two Al-coated TiO2 samples as nanopowders were selected from the JRC repository, capped either with a hydrophilic or a hydrophobic organic ultrathin shell. SEM results provided the size and shape of the nanoparticles, a first overview about the composition was obtained with EDS. XPS and ToF-SIMS supplied the surface chemistry, especially information about the shell and the coating of the particles. Standards and protocols of all steps of the analytical workflow including preparation and data reduction are discussed regarding reliable and reproducible data. Additionally, uncertainties for the different steps are specified.
Only such a detailed description of all these factors allows a comprehensive physico-chemical characterization of the nanoparticles with understanding of their potential risk assessment.
The recent development of x-ray photoelectron spectroscopy using excitation sources different from the usual lab-source Mg Kα and Al Kα and spectrometers with more sophisticated lens systems requires flexible approaches for determining the transmission function. Therefore, the approach using quantified peak areas (QPA) was refined.1 A new algorithm allows a more precise estimation of the transmission function which could be shown by comparing the results obtained with the new version with former calculations. Furthermore, next to the established reference materials Cu, Ag and Au, ionic liquids can be used for estimating the transmission function at beamlines with variable excitation energies. Comparison between the measured and stoichiometric composition shows that a transmission function was determined which allows a reasonable quantification.
microscopy (AFM), or X-ray reflectometry. For the additional determination of thin film composition, techniques like X-ray photoelectron spectroscopy (XPS) or mass spectrometry-based techniques can be used. An alternative non-destructive technique is electron probe microanalysis (EPMA). This method assumes a sample of homogenous (bulk) chemical composition, so that it cannot be usually applied to thin film samples. However, in combination with the thin film software StrataGEM, the thickness as well as the composition of such films on a substrate can be determined.
This has been demonstrated for FeNi on Si and SiGe on Al2O3 film systems. For both systems five samples with different elemental composition and a reference were produced and characterised by Korean research institute KRISS using inductively coupled plasma mass spectrometry (ICP-MS), Rutherford backscattering (RBS), and transmission electron microscopy (TEM). These samples were used for an international round robin test.
In 2021, a new and open-source thin film evaluation programme called BadgerFilm has been released. It can also be used to determine thin film composition and thickness from intensity ratios of the unknown sample and standards (k-ratios).
In this contribution, we re-evaluated the data acquired for the FeNi and SiGe systems using the BadgerFilm software package and compared the resulting composition and thickness with the results of the established StrataGEM software and other reference methods. With the current evaluation, the BadgerFilm software shows good agreement with the composition and thickness calculated by StrataGEM and as the reference values provided by the KRISS.
The residual stresses and load transfer in multiphase metal alloys and their composites (with both random planar-oriented short fibers and particles) will be shown, as studied by neutron diffraction, by X-ray computed tomography, and by a model based on the reformulation of classic Maxwell’s homogenization method.
Contrary to common understanding and state-of-the-art models, we experimentally observe that randomly oriented phases possess non-hydrostatic residual stress. Moreover, we disclose that the unreinforced matrix alloy stays under hydrostatic compression even under external uniaxial compression.
The recently developed modeling approach allows calculating the residual stress in all phases of the composites. It rationalizes the presence of deviatoric stresses accounting for the interaction of random oriented phases with fibers having preferential orientation. It also allows the explanation of the unconventional in-situ behavior of the unreinforced alloy and the prediction of the micromechanical behavior of other similar alloys.
Even though we often do not knowingly recognize them, nanoparticles are present these days in most areas of our daily life, including food and its packaging, medicine, pharmaceuticals, cosmetics, pigments as well as electronic products, such as computer screens. The majority of these particles exhibits a core-shell morphology either intendedly or unintendedly. For the purpose of practicability, this core-shell nanoparticle (CSNP) morphology is often assumed to be ideal, namely a spherical core fully encapsulated by a shell of homogeneous thickness with a sharp interface between core and shell material. It is furthermore widely presumed that all nanoparticles in the sample possess the same shell thickness. As a matter of fact, most real CSNPs deviate in several ways from this ideal model with quite often severe impact on how efficiently they perform in a specific application.
The topic of this cumulative PhD thesis is the accurate characterization of the actual morphology of CSNPs by advanced X-ray analytical techniques, namely X-ray photoelectron spectroscopy (XPS) and scanning transmission X-ray microscopy (STXM). A special focus is on CSNPs which deviate from an ideal core-shell morphology. In the paper from 2019 nanoparticle shell thicknesses are extracted from the elastic-peak intensities in an XPS spectrum based on an ideal particle morphology. This happens for a series of CSNP samples comprising a poly(tetrafluoroethylene) (PTFE) core and either a poly(methyl methacrylate) (PMMA) or polystyrene (PS) shell. The same paper as well as the paper from 2020 demonstrate for the first time, that the analysis of the inelastic background in an XPS spectrum of CSNPs can identify and quantify the heterogeneity of the shell and the incomplete encapsulation of the core.
The result from an XPS experiment is always an average across a large nanoparticle ensemble. Deviations from an ideal morphology within a single particle of the sample cannot be assessed separately. As opposed to that, a spatial resolution of 35 nm enables STXM to visualize the interior of single CSNPs which exhibit a sufficient X-ray absorption contrast between core and shell material. In the paper from 2018 a STXM analysis is demonstrated based on the example of the PTFE-PS CSNP samples already mentioned in the previous paragraph.
In the publication from 2021 (Ca/Sr)F₂ core-shell like nanoparticle ensembles for the practical use in, among others, antireflective coatings are investigated. These nanoparticles do not possess a sharp interface between core and shell material, which is why a shell thickness determination as described in the second paragraph is inappropriate. Instead, in-depth profiles of the chemical composition are obtained by XPS experiments based on synchrotron radiation with variable X-ray photon energy to elucidate the internal morphology of the particles. Additionally, theoretical in-depth profiles of Ca and Sr XPS peak intensities are simulated, in order to facilitate the interpretation of the experiments. Thus, an enrichment of CaF₂ at the particle surface was determined, which could hardly have been assessed by any other analytical technique. Because this kind of non-destructive depth profiling by XPS is very demanding, more than usual effort is spent on gapless documentation of the experiments to ensure full reproducibility.
Due to the vast diversity of nanoparticles differing in material, composition and shape, a measurement procedure cannot unalteredly be transferred from one sample to another. Nevertheless, because the papers in this thesis present a greater depth of reporting on the experiments than comparable publications, they constitute an important guidance for other scientists on how to obtain meaningful information about CSNPs from surface analysis.
The fabrication of laser-generated surface structures on titanium and titanium alloys has recently gained remarkable interests, being technologically relevant for applications in optics, medicine, fluid transport, tribology, and wetting of surfaces. The morphology of these structures, and so their chemistry, is influenced by the different laser processing parameters such as the laser fluence, wavelength, pulse repetition rate, the effective number of laser pulses per beam spot area, etc. A simple way to characterize laser-generated surface structures is by means of optical microscopy (OM) or white light interference microscopy (WLIM). The latter can address the surface topography, while having a lateral resolution limit of ~(lambda)/2 (lambda = illumination wavelength). To resolve morphologies with spatial periods significantly smaller than (lambda)/2, scanning electron microscopy (SEM) is often used, taking benefit of the reduced de Broglie wavelength associated to the electrons of several keV energy. However, all the above-mentioned techniques lack the necessary depth-resolution to reveal and quantify sub-surface material modifications of these laser-generated structures. Time-of-Flight secondary ion mass spectrometry (ToF-SIMS) represents a promising surface analytical technique for studying laser-induced chemical surface alterations since the method combines a high surface sensitivity with the capability to perform a depth-profiling of the laser-affected surface zone. In this study we combine WLIM and high-resolution SEM with ToF-SIMS to fully characterize the evolution of various types of laser-generated micro- and nanostructures formed on Ti-6Al-4V alloys upon irradiation by near infrared ultrashort laser pulses (1030 nm, 925 fs) at different laser fluence levels, effective number of pulses, and at different pulse repetition rates (1 – 400 kHz). We show how this combined surface analytical approach allows to evaluate alterations in the surface chemistry and topography of the laser-generated surface structures depending on the laser processing parameters
We demonstrate here using a disulfide system the first example of reversible, selective, and quantitative transformation between three crystalline polymorphs by ball mill grinding. This includes the discovery of a previously unknown polymorph. Each polymorph is reproducibly obtained under well-defined neat or liquid-assisted grinding conditions, revealing subtle control over the apparent thermodynamic stability. We discovered that the presence of a contaminant as low as 1.5% mol mol−1 acting as a template is required to enable all these three polymorph transformations. The relative stabilities of the polymorphs are determined by the sizes of the nanocrystals produced under different conditions and by surface interactions with small amounts of added solvent. For the first time, we show evidence that each of the three polymorphs is obtained with a unique and reproducible crystalline size. This mechanochemical approach gives access to bulk quantities of metastable polymorphs that are inaccessible through recrystallisation.
The overview of the activity of group 8.5 Micro-NDT (BAM, Belin, Germany) in the field of additively manufacturing material characterization will be presented. The challenges in the residual stress analysis of AM components are discussed on the basis on the show studies performed in BAM. Also, the synchrotron X-ray refraction technique, available in BAM, is presented, showing example of in-situ heating test of Al10SiMg AM material.
Till now application of printed magnetoelectronics is hindered by lack of large area exchange coupled metallic multilayers required to produce printable magneto-sensory inks. Large-scale roll-to-roll (R2R) fabrication process is an attractive approach owing to its capabilities for high volume, high throughput, and large area manufacturing. Precise and high performance R2R sputtering technology is developed to fabricate large area giant magnetoresistive (GMR) thin-films stacks that contain 30 metallic bilayers prepared by continuous R2R sputtering of Co and Cu sequential on a hundred meters long polyethylene terephthalate (PET) web. The R2R sputtered Co/Cu multilayer on a 0.2 × 100 m2 PET web exhibits a GMR ratio of ≈40% achieving the largest area exchange coupled room temperature magneto-sensitive system demonstrated to date. The prepared GMR thin-film is converted to magnetosensitive ink that enables printing of magnetic sensors with high performance in a cost-efficient way, which promotes integration with printed electronics. An average GMR ratio of ≈18% is obtained for 370 printed magnetic sensors. The realized precise R2R sputtering approach can also be extended to a wide range of hybrid thin-film material systems opening up a path for new functional inks applied with printing technologies.
Acoustic methods are ideally suited for determining the mechanical properties of different materials non-destructively. The availability of such methods is particularly important for fiber-reinforced polymers (FRPs) because their properties strongly depend on the manufacturing process and in-service conditions. Since FRPs are mostly used in thin-walled components, properties can be derived from the dispersion curves of ultrasonic guided waves (UGWs).
Our approach is based on an inverse procedure in which the numerically calcu-lated dispersion curves are fitted to the measured curves. The acquisition is done by applying a broadband piezoelectric transducer (PZT) to excite and a 3D laser Doppler vibrometer (3D LDV) to record the waves. Compared to the ap-proaches based on laser excitation, the PZT provides a better signal-to-noise ra-tio because more energy is brought into the structure. Whereas the 3D LDV compared to a 1D LDV or a PZT allows capturing in-plane and out-of-plane components and thus providing more dispersion information. Since the inverse procedure requires many iterations before elastic properties are retrieved, an ef-ficient tool for the calculation of the dispersion curves is necessary. For this, the Scaled Boundary Finite Element Method is used. All in all, a good agreement between theoretical and experimental curves is demonstrated.
Several aspects were explored towards the standardization of a suitable procedure. The use of gaseous standards is necessary and a standard gas mixture containing 60 substances was successfully generated and employed for further investigations. The suitability of different chromatography columns was addressed: The use of PLOT (Porous Layer Open Tubular) columns is well suitable for VVOC analysis. The recoveries of the 60 analytes on several adsorbents and their combinations were determined: A combination of a graphitized carbon black and a carbon molecular sieve showed great results for all analytes. Carbon molecular sieves adsorb water which can impair the analysis. Different options such as purging, the use of a drying system or splitting were investigated for water removal. This contribution will present experimental results supporting the standardization of a method for VVOC analysis.
EXAFS analysis of pure elements, binary and ternary equiatomic refractory alloys within the Nb-Zr-Ti-Hf- Ta system is performed at the Nb and Zr K-edges to analyze the evolution of the chemical local environ- ment and the lattice distortion. A good mixing of the elements is found at the atomic scale. For some compounds, a distribution of distances between the central atom and its neighbors suggests a distortion of the structure. Finally, analysis of the Debye-Waller parameters shows some correlation with the lat- tice distortion parameter δ², and allows to quantify experimentally the static disorder in medium entropy alloys.
Fire-gilding is a historic technique for the application of golden layers on a number of different base materials utilizing a gold amalgam. This technique leaves a significant amount of Hg in the golden layer, giving archeometrists a reliable indicator to identify firegildings.
Recent findings on presumably fire-gilded objects have shown in several cases significantly lower Hg content than previously studied objects. This prompted a synchrotron-based X-ray fluorescence investigation into the Hg distribution along the material–gilding interface, as well as a series of measurements regarding the Hg content development in fire-gilded samples during artificial aging. This work presents findings on laboratory-prepared fire-gildings, indicating an Hg enrichment at the interface of firegilded silver samples. Notably, such an enrichment is missing in fire-gilded copper samples. Further, it is confirmed that fire-gilded layers typically do not undercut an Hg bulk content of 5%. In this light, it seems improbable that ancient samples that contain <5% Hg are fire-gilded. The results presented in this study might lead to a non-destructive method to identify the Hg enrichment at the interface. This might be obtained by a combination of different non-destructive measurements and might also work unambiguously in samples in which the gold top layer is altered.
Introduction: The influence of copper, iron and zinc concentrations on the formation of ß-amyloid plaques and neurofibrillary tangles in Alzheimer’s disease (AD) is widely discussed in the community. The results from human and animal studies so far are mixed with some studies showing a correlation and others not. From a number of studies, it is known that disease state and isotopic composition of essential elements can be coupled.
Aim: The aim of the study was to identify changes in element content and isotopic composition in two transgenic mouse models used in AD research compared to their genetic WT relatives and to establish whether element content and isotopic signature between different laboratories is comparable.
Methods: ß-amyloid (5xFAD) and tau overexpressing (L66) mice together with their matching wild-types were bred at dedicated facilities in accordance with the European Communities Council Directive (63/2010/EU). Serum and brain were sampled after sacrifice and the samples distributed among the participants of the study. The tissues were acid digested for total element determination and high-precision isotope ratio determination. Element content was determined by either sector-field or quadrupole-based inductively coupled plasma mass spectrometry (ICPMS). For the determination of isotope ratios multi-collector ICPMS was used.
Results: Total copper content was significantly higher for L66 and their matched WT compared to 5xFAD and WT. Brains of L66 mice contained more Fe in brain than their WT, Zn and Cu were not significantly different between L66 and WT. Whereas 5xFAD mice had a slightly lower Cu and slightly higher Zn concentration in brain compared to WT. The isotopic signature in brain of L66 mice for Fe was different from their controls, whereas Zn isotope ratios were influenced in 5xFAD mice compared to their WT. The Cu isotopic ratio did not seem to be influenced in either strain. In serum, the shifts were less pronounced.
Conclusion: Even though neither Tau-protein nor amyloid precursor protein are known to be metal-dependent / -containing proteins, the overexpression of both influences the Fe, Cu and Zn metabolism in brain and to some extent also in serum as can be seen not only using total element determination but probably more clearly studying the isotopic signature of Fe, Cu and Zn.
The spatial distribution and concentration of lanthanide activator and sensitizer dopant ions are of key importance for the luminescence color and efficiency of upconverting nanoparticles (UCNPs). Quantifying dopant ion distributions and intermixing, and correlating them with synthesis methods require suitable analytical techniques. Here, X-ray photoelectron spectroscopy depth-profiling with tender X-rays (2000–6000 eV), providing probe depths ideally matched to UCNP sizes, is used to measure the depth-dependent concentration ratios of Er3+ to Yb3+, [Er3+]/[Yb3+], in three types of UCNPs prepared using different reagents and synthesis methods. This is combined with data simulations and inductively coupled plasma-optical emission spectroscopy (ICP-OES) measurements of the lanthanide ion concentrations to construct models of the UCNPs’ dopant ion distributions. The UCNP sizes and architectures are chosen to demonstrate the potential of this approach. Core-only UCNPs synthesized with XCl3·6H2O precursors (β-phase) exhibit a homogeneous distribution of lanthanide ions, but a slightly surface-enhanced [Er3+]/[Yb3+] is observed for UCNPs prepared with trifluroacetate precursors (α-phase). Examination of Yb-core@Er-shell UCNPs reveals a co-doped, intermixed region between the single-doped core and shell. The impact of these different dopant ion distributions on the UCNP's optical properties is discussed to highlight their importance for UCNP functionality and the design of efficient UCNPs.
Quantification of the Total and Accessible Number of Functional Groups and Ligands on Nanomaterials
(2022)
Surface-functionalized organic and inorganic nanoparticles (NP) are of great interest in the life and material sciences, as they can be used e.g. as drug carriers, fluorescent sensors, and multimodal labels in bioanalytical assays and imaging applications. NP performance in such applications depends not only on particle size, size distribution, and morphology, but also on surface chemistry, i.e. the total number of surface functional groups (FG) and the number of FG accessible for subsequent functionalization with ligands or biomolecules, which in turn determines surface charge, colloidal stability, biocompatibility, and toxicity. Methods for FG quantification should be simple, robust, reliable, fast, and inexpensive, and allow for the characteriza-tion of a broad variety of nanomaterials differing in size, chemical composition, and optical properties.
Aiming at the development of simple, versatile, and multimodal tools for the quantification of many bioanalytically relevant FG such as amine, carboxy, thiol and aldehyde functionalities, we investigated and compared various analytical methods commonly used for functional group quantification. This includes electrochemical titration methods, dye-based optical assays, and other instrumental analytical techniques such as nuclear magnetic resonance, mass spectrometry, and thermal analysis methods.
Temperature Compensation Strategies for Lamb Wave Inspection using Distributed Sensor Networks
(2022)
The application of temperature compensation strategies is crucial in structural health monitoring approaches based on guided waves. Actually, the varying temperature influences the performance of the inspection system inducing false alarms or missed detection, with a consequent reduction of reliability. This paper quantitatively describes a method to compensate the temperature effect, namely the optimal baseline selection (OBS), extending its application to the case of distributed sensor networks (DSN). The effect of temperature separation between baseline time-traces in OBS are investigated considering multiple couples of sensors employed in the DSN. A combined strategy that uses both OBS and frequent value warning is considered. Theoretical results are compared, using data from two several experiments, which use different frequency analysis with either predominantly A0 mode or S0 mode data or both. The focus is given on the fact that different paths are available in a sensor network and several possible combination of results are available. Nonetheless, introducing a frequent value warning it is possible to increase the efficiency of the OBS approach making use of fewer signal processing algorithms. These confirm that the performance of OBS quantitatively agrees with predictions and also demonstrate that the use of compensation strategies improve detectability of damage.
Performance assessment for GuidedWave (GW)-based Structural Health Monitoring (SHM) systems is of major importance for industrial deployment.
With conventional feature extraction methods like damage indices, pathbased probability of detection (POD) analysis can be realized. To achieve reliability quantification enough data needs to be available, which is rarely the case.
Alternatives like methods for performance assessment on system level are still in development and in a discussion phase. In this contribution, POD results using an Artificial Intelligence (AI)-based data analysis are compared with those delivered by conventional data analysis. Using an open-access dataset from Open Guided Wave platform, the possibility of performance assessment for GW-based SHM systems using AI-based data analysis is shown in detail. An artificial neural network (ANN) classifier is trained to detect artificial damage in a stiffened CFRP plate. As input for the ANN, classical damage indicators are used. The ANN is tested to detect damage at another position, whose inspection data were not previously used in training. The findings show very high detection capabilities without sorting any specific path but only having a global view of current damage metrics. The systematic evaluation of the ANN predictions with respect to specific damage sizes allows to compute a probability of correct identification versus flaw dimension, somehow equivalent to and compared with the results achieved through classic path-based POD analysis. Also, sensitive paths are detected by ANN predictions allowing for evaluation of maximal distances between path and damage position. Finally, it is shown that the prediction performance of the ANN can be improved significantly by combining different damage indicators as inputs.
Reliability assessment of Structural Health Monitoring (SHM) systems
poses new challenges pushing the research community to address many questions which are still open. For guided wave-based SHM it is not possible to evaluate the system performance without taking into account the target structure and applied system parameters. This range of variables would result in countless measurements.
Factors like environmental conditions, structural dependencies and wave characteristics demand novel solutions for performance analysis of SHM systems compared to those relying on classical non-destructive evaluation. Such novel approaches typically require model-assisted investigations which may not only help to explain and understand performance assessment results but also enable complete studies without costly experiments. Within this contribution, a multi input multi output approach using a sparse transducer array permanently installed on a composite structure to excite and sense guided waves is considered. Firstly, the method and the analysis of path-based performance assessment are presented considering an open-access dataset from the Open Guided Wave platform. Then, a performance analysis of a guided wave-based SHM system using Probability of Detection is presented. To explain some unexpected results, the model-assisted investigations are used to understand the physical phenomena of wave propagation in the test specimen including the interaction with damage. Finally, issues and future steps in SHM systems’ performance assessment and their development are discussed.
This dataset contains raw data resulting from Impact-Echo measurements at the reference concrete block "IE Platte", located at BAM (German Federal Institute for Materials Research and Testing).
The specimen contains three polystyrene slabs and one polyethylene foil to act as reflectors. The specimen was produced in a three-step process. First, the base plate was cast. Second, the reflectors were taped to the base plate. Finally, the upper layer was cast on top of base plate and reflectors. A drawing is contained in the dataset.
The Impact-Echo method is based on the excitation of the zero-group-velocity frequency of the first symmetric Lamb mode of a plate-like structure, in order to assess its thickness. Numerous publications elaborate on Impact-Echo theory, examples are (Gibson and Popovics 2005, Schubert and Köhler 2008 , Abraham and Popovics 2010).
The measurements have been conducted using a setup that contains only commercially available components. The setup consists of an Olson CTG-2 concrete thickness gauge (Olsen Instruments, USA) for actuation and sensing and an 8-bit NI USB-5132 digital storage oscilloscope (National Instruments, USA) combined with the Echolyst software (Schweizerischer Verein für technische Inspektionen (SVTI), Switzerland) for data acquisition.
Measurements were conducted using a grid of 29x29 points with a spacing of 50 mm. At each point 8192 samples were recorded at a sampling rate of 1 MS/s.
The dataset contains the (X,Y) location in mm of the individual measurement points as well as the raw measurement data at those points.
The data is provided in the formats *.mir/*.mhdr (Echolyst), *.npy (Python) and *.mat (Matlab) and *.csv to ease the import in various post-processing tools.
Molecularly imprinted polymers (MIPs) against sialic acid (SA) have been developed as a detection tool to target cancer cells. Before proceeding to in vivo studies, a better knowledge of the overall effects of MIPs on the innate immune system is needed. The aim of this study thus was to exemplarily assess whether SA-MIPs lead to inflammatory and/or cytotoxic responses when administered to phagocytosing cells in the innate immune system. The response of monocytic/macrophage cell lines to two different reference particles, Alhydrogel and PLGA, was compared to their response to SA-MIPs. In vitro culture showed a cellular association of SA-MIPs and Alhydrogel, as analyzed by flow cytometry. The reference particle Alhydrogel induced secretion of IL-1b from the monocytic cell line THP-1, whereas almost no secretion was provoked for SA-MIPs. A reduced number of both THP-1 and RAW 264.7 cells were observed after incubation with SA-MIPs and this was not caused by cytotoxicity. Digital holographic cytometry showed that SA-MIP treatment affected cell division, with
much fewer cells dividing. Thus, the reduced number of cells after SA-MIP treatment was not linked to SA-MIPs cytotoxicity. In conclusion, SA-MIPs have a low degree of inflammatory properties, are not cytotoxic, and can be applicable for future in vivo studies.
Additively manufactured (AM) metallic sheet-based Triply Periodic Minimal Surface Structures (TPMSS) meet several requirements in both bio-medical and engineering fields: Tunable mechanical properties, low sensitivity to manufacturing defects, mechanical stability, and high energy absorption. However, they also present some challenges related to quality control. In fact, the optimization of both the AM process and the properties of TPMSS is impossible without considering structural characteristics as manufacturing accuracy, internal defects, and as well as surface topography and roughness. In this study, the quantitative non-destructive analysis of TPMSS manufactured from Ti-6Al-4V alloy by electron beam melting was performed by means of laboratory X-ray computed tomography (XCT).
Here, we present a study on agarose thin-film samples that represent a model system for the exopolysaccharide matrix of biofilms. Povidone-iodide (PVP-I) was selected as an antibacterial agent to evaluate our x-ray photoelectron spectroscopy (XPS)-based methodology to trace specific marker elements, here iodine, commonly found in organic matrices of antibiotics. The in-depth distribution of iodine was determined by XPS analyses with variable excitation energies and in combination with argon gas cluster ion beam sputter cycles. On mixed agarose/PVP-I nanometer-thin films, both methods were found to solve the analytical task and deliver independently comparable results. In the mixed agarose/PVP-I thin film, we found the outermost surface layer depleted in iodine, whereas the iodine is homogeneously distributed in the depth region between this outermost surface layer and the interface between the thin film and the substrate. Depletion of iodine from the uppermost surface in the thin-film samples is assumed to be caused by ultrahigh vacuum exposure resulting in a loss of molecular iodine (I2) as reported earlier for other iodine-doped polymers.
Morpho-Chemical Characterisation of Me-TiO2 Nanoparticles for Enhanced Photocatalytical Activity
(2022)
The conversion of solar energy into electricity and solar fuels is of crucial importance for a green and sustainable future. Water splitting using semiconductor photo-catalysts is considered a sustainable method to produce clean hydrogen (H2) fuel. Nevertheless, H2 photo-production efficiency remains still low, although extensive research works to understand better the mechanisms of the Hydrogen Evolution Reaction (HER) and the Oxygen Evolution Reaction (OER) are being carried out. In this respect, TiO2 is a key photoactive material, usually employed with a co-catalyst deposited onto the surface to enhance charge carriers’ separation and catalyze surface charge transfer reactions. The deposition of a co-catalyst on the TiO2 nanoparticle surface represents one successful way to enhance the activity of the photocatalyst through a modification of its surface and redox properties. In this context, high-resolution scanning electron microscopy coupled with elemental analysis by energy-dispersive X-ray spectroscopy (EDS) is fundamental for studying and understanding the effect of the nanoparticle morphology on the functional properties of shape-controlled TiO2 crystals (bipyramides, platelets, and elongated particles). Different types of metal-semiconductor combinations, TiO2 shapes and dopant metals (Ag, Pt, etc) and metal concentrations will be discussed.
A large and increasing number of scientific domains pushes for high neutron imaging resolution achieved in reasonable times. Here we present the principle, design and performance of a detector based on infinity corrected optics combined with a crystalline Gd3Ga5O12 : Eu scintillator, which provides an isotropic sub-4 μm true resolution. The exposure times are only of a few minutes per image. This is made possible also by the uniquely intense cold neutron flux available at the imaging beamline NeXT-Grenoble. These comparatively rapid acquisitions are compatible with multiple high quality tomographic acquisitions, opening new venues for in-operando testing, as briefly exemplified here.
Gas distribution mapping is important to have an accurate understanding of gas concentration levels in hazardous environments. A major problem is that in-situ gas sensors are only able to measure concentrations at their specific location. The gas distribution in-between the sampling locations must therefore be modeled. In this research, we interpret the task of spatial interpolation between sparsely distributed sensors as a task of enhancing an image's resolution, namely super-resolution. Because autoencoders are proven to perform well for this super-resolution task, we trained a convolutional encoder-decoder neural network to map the gas distribution over a spatially sparse sensor network. Due to the difficulty to collect real-world gas distribution data and missing ground truth, we used synthetic data generated with a gas distribution simulator for training and evaluation of the model. Our results show that the neural network was able to learn the behavior of gas plumes and outperforms simpler interpolation techniques.
Gas distribution mapping is important to have an accurate understanding of gas concentration levels in hazardous environments. A major problem is that in-situ gas sensors are only able to measure concentrations at their specific location. The gas distribution in-between the sampling locations must therefore be modeled. In this research, we interpret the task of spatial interpolation between sparsely distributed sensors as a task of enhancing an image's resolution, namely super-resolution. Because autoencoders are proven to perform well for this super-resolution task, we trained a convolutional encoder-decoder neural network to map the gas distribution over a spatially sparse sensor network. Due to the difficulty to collect real-world gas distribution data and missing ground truth, we used synthetic data generated with a gas distribution simulator for training and evaluation of the model. Our results show that the neural network was able to learn the behavior of gas plumes and outperforms simpler interpolation techniques.
In this study, carried out within the Joint Danube Survey 4, a comprehensive microplastic screening in the water column within a large European river basin from its source to estuary, including major tributaries, was realized. The objective was to develop principles of a systematic and practicable microplastic monitoring strategy using sedimentation boxes for collection of suspended particulate matter followed by its subsequent analysis using thermal extraction desorption-gas chromatography/mass spectrometry. In total, 18 sampling sites in the Danube River Basin were investigated. The obtained suspended particulate matter samples were subdivided into the fractions of >100 μm and <100 μm and subsequently analyzed for microplastic mass contents. The results showed that microplastics were detected in all samples, with polyethylene being the predominant polymer with maximum contents of 22.24 μg/mg, 3.23 μg/mg for polystyrene, 1.03 μg/mg for styrene-butadiene-rubber, and 0.45 μg/mg for polypropylene. Further, polymers such as different sorts of polyester, polyacrylates, polylactide, and natural rubber were not detected or below the detection limit. Additional investigations on possible interference of polyethylene signals by algae-derived fatty acids were assessed. In the context of targeted monitoring, repeated measurements provide more certainty in the interpretation of the results for the individual sites. Nevertheless, it can be stated that the chosen approach using an integrative sampling and determination of total plastic content proved to be successful.
Silicon photonic micro-ring resonators (MRR) developed on the silicon-on-insulator (SOI) platform, owing to their high sensitivity and small footprint, show great potential for many chemical and biological sensing applications such as label-free detection in environmental monitoring, biomedical engineering, and food analysis. In this tutorial,we provide the theoretical background and give design guidelines for SOI-based MRR as well as examples of surface functionalization procedures for label-free detection of molecules. After introducing the advantages and perspectives of MRR, fundamentals of MRR are described in detail, followed by an introduction to the fabrication methods, which are based on a complementary metal-oxide semiconductor (CMOS) technology. Optimization of MRR for chemical and biological sensing is provided, with special emphasis on the optimization of waveguide geometry. At this point, the difference between chemical bulk sensing and label-free surface sensing is explained, and definitions like waveguide sensitivity, ring sensitivity, overall sensitivity as well as the limit of detection (LoD) of MRR are introduced. Further, we show and explain chemical bulk sensing of sodium chloride (NaCl) in water and provide a recipe for label-free surface sensing.
Laser-induced plasmas are widely used in many areas of science and technology; examples include spectrochemical analysis, thin film deposition, and material processing. Several topics will be addressed. First, general phenomenology of laser-induced plasmas will be discussed. Then, a chemical model will be presented based on a coupled solution of Navier-Stokes, state, radiative transfer, material transport, and chemical equations. Results of computer simulations for several chemical systems will be shown and compared to experimental observations obtained by optical imaging, spectroscopy, and tomography. The latter diagnostic tools will also be briefly discussed. Finally, a prospective application of laser-induced plasma and plasma modeling will be illustrated on the example of chemical vapor deposition of molybdenum borides and micro processing and coating of titanium dental implants.
We present our achievements in the development of distributed fiber optic sensing systems based on Brillouin optical frequency-domain analysis for structural health monitoring. The focus of the applications is on the gapless monitoring of geotechnical structures, large area infrastructures and electrical grids. The work includes the latest use of machine learning algorithms to reduce measurement time by coexistent increasing the measurement accuracy.
Inductively coupled plasma-mass spectrometry (ICP-MS) is a well-established analytical method offering high sensitivity and multi-element analysis. ICP-MS has found acceptance in various application areas ranging from material analysis to applications in the life sciences. Within the last 15 years new strategies for the sensitive detection and accurate quantification of biomolecules in complex biomedical samples have been developed. Recent instrumental improvements have contributed to this progress.
As most of the biomolecules do not contain endogenous metals etectable with ICP-MS, bioconjugation with artificial metal-containing tags based on metal-loaded chelate complexes or nanoparticles is increasingly applied to determine biomolecules indirectly. Especially, the combination of immunohistochemical workflows using lanthanoid-tagged antibodies and ICP-MS detection provides new insights in the complexity and interdependency of cellular processes. Single-cell ICP-MS, also termed as mass cytometry, allows high-dimensional analysis of biomarkers in cell populations at single-cell resolution. For that purpose, lanthanoid isotope labelled antibodies are used to detect their corresponding target molecules. The visualisation of the elemental distribution is possible with laser ablation ICP-MS (LA-ICPMS) at high spatial resolution. Especially, the combination of LA with ICP time-of-flight mass spectrometry, also referred to as imaging mass cytometry (IMC), opens new possibilities for multiparametric tissue imaging at the single-cell level and even below. The lanthanoid localisation and concentration can be linked to their conjugated antibody target providing valuable information about surface markers, intracellular signalling molecules to measure biological function, and the network state of an individual cell in a tissue.
This book chapter focuses on new applications, where the multi-element capabilities of ICP-MS are used for the detection of lanthanoids applied as artificial elemental stains or tags for biomolecules and in particular antibodies.
Closed material cycles and unmixed material fractions are required to achieve high recovery and recycling rates in the building industry. The growing diversity of construction and demolition waste is leading to increasing difficulties in separating the individual materials. Manual sorting involves many risks and dangers for the executing staff and is merely based on obvious, visually detectable differences for separation. An automated, sensor-based sorting of these building materials could complement or replace this practice to improve processing speed, recycling rates, sorting quality, and prevailing health conditions.
A joint project of partners from industry and research institutions approaches this task by investigating and testing the combination of laser-induced breakdown spectroscopy (LIBS) and visual (VIS)/ near-infrared (NIR) spectroscopy. Joint processing of information (data fusion) is expected to significantly improve the sorting quality of various materials like concrete, main masonry building materials, organic components, etc., and may enable the detection and separation of impurities such as SO3-containing building materials (gypsum, aerated concrete, etc.). Focusing on Berlin as an example, the entire value chain will be analyzed to minimize economic/technological barriers and obstacles at the cluster level and to sustainably increase recovery and recycling rates.
First LIBS measurements show promising results in distinguishing various material types. A meaningful validation shall be achieved with further practical samples. Future works will investigate the combination of LIBS and VIS/NIR spectroscopy in a fully automated measurement setup with conveyor belt speeds of 3 m/s.
Per- and polyfluorinated alkyl substances (PFASs) are a substance class of over 4730 individual compounds. Several PFASs are extremely persistent, bioaccumulative and toxic. The analysis of PFASs is challenging because of their different chemical and physical properties as well as the high number of target substances. Target-based approaches (e.g., LC-MS/MS) are limited to the availability of analytical grade standards and are not suitable for the analysis of new/unknown PFASs and transformation products. Therefore, PFAS sum parameter methods become increasingly important to indicate a realistic PFAS pollution level.
PFAS sum parameters compromise the proportion of organically bound fluorine that can either be extracted (EOF) or adsorbed to activated carbon (AOF). For the instrumental analysis of such sum parameters, a fluorine selective detector is needed. High resolution-continuum source-graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) is a sensitive and highly selective tool for indirect fluorine determination. The method is based on the in situ formation of diatomic gallium-mono fluoride (GaF) in a graphite furnace at a temperature of 1550°C. The molecular absorption of GaF can be detected at its most sensitive wavelength at 211.248 nm providing limits of quantification of c(F) 2.7 µg/L.
Here, we describe a fast and simple extraction method for the determination of the EOF using HR-CS-GFMAS in soil samples. Common approaches for the EOF determination use solid phase extraction (SPE). To omit the bias of this time consuming and expensive step we optimized a fast and simple SPE-free extraction method. The developed extraction method consists of a liquid-solid extraction using acidified methanol. Comparison of the method with and without an SPE clean-up step revealed a drastic underestimation of EOF concentrations using SPE. In the next step, the applicability of our method was tested for other solid matrices. In view of steadily increasing numbers of PFASs, our method will make an important contribution in assessing the pollution situation as well as support policy makers in deriving exposure limits for PFASs in the future.
Catalysts are important components in chemical processes because they lower the activation energy and thus determine the rate, efficiency and selectivity of a chemical reaction. This property plays an important role in many of today’s processes, including the electrochemical splitting of water. Due to the continuous development of catalyst materials, they are becoming more complex, which makes a reliable evaluation of physicochemical properties challenging even for modern analytical measurement techniques and industrial manufacturing.
We present a fast, vacuum-free and non-destructive analytical approach using multi-sample spectroscopic ellipsometry to determine relevant material parameters such as film thickness, porosity and composition of mesoporous IrOx–TiOy films. Mesoporous IrOx–TiOy films were deposited on Si wafers by sol–gel synthesis, varying the composition of the mixed oxide films between 0 and 100 wt%Ir. The ellipsometric modeling is based on an anisotropic Bruggeman effective medium approximation (a-BEMA) to determine the film thickness and volume fraction of the material and pores. The volume fraction of the material was again modeled using a Bruggeman EMA to determine the chemical composition of the materials. The ellipsometric fitting results were compared with complementary methods, such as scanning electron microscopy (SEM), electron probe microanalysis (EPMA) as well as environmental ellipsometric porosimetry (EEP).
Due to the fast growth of industry and the use of metal-containing compounds such as sewage sludge in agricultural fields, soil pollution associated with heavy metals presents a terrifying threat to the environment. Throughout the world, there are already 5 million sites of soil contaminated by heavy metals1. Some heavy metals pollutants can influence food chain safety and food quality, which in turn affects human health. According to the German Federal Soil Protection and Contaminated Site Ordinance (BBodSchV) 13 heavy metals such as arsenic (As), lead (Pb) and cadmium (Cd) are classified as heavily toxic to human health2. Therefore, elemental analysis and precise quantification of the heavy metals in soil are of great importance.
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 interferences3. For the first time, the applicability of MICAP-MS for elemental analysis of environmental soils is investigated in this work. For this purpose, 7 reference- and 3 random soil samples containing vanadium (V), cobalt (Co), zink (Zn), copper (Cu), chrome (Cr), mercury (Hg), As, Pb and Cd are digested with aqua regia and used for analysis. Concentrations of selected elements are determined using MICAP-MS and validated using ICP-MS. Sensitivities, limits of detection and gas consumption for both methods are compared and discussed in detail. Moreover, the performance of MICAP-MS under different nitrogen plasma gas concentrations is investigated and compared
Brillouin Optical Frequency Domain Analysis (BOFDA) is a powerful and well-established method for static distributed sensing of temperature and strain. Recently, we demonstrated a BOFDA system based on convolutional neural network which shortens the measurement time considerably. In this paper, we apply leave-one-out cross validation to evaluate the generalization performance and provide an unbiased and reliable machine learning model for a time-efficient BOFDA system.
Luminescence-encoded microbeads are important tools for many applications in the life and material sciences that utilize luminescence detection as well as multiplexing and barcoding strategies. The preparation of such beads often involves the staining of premanufactured beads with molecular luminophores using simple swelling procedures or surface functionalization with layer-by-layer (LbL) techniques. Alternatively, these luminophores are sterically incorporated during the polymerization reaction yielding the polymer beads. The favorable optical properties of semiconductor quantum dots (QDs), which present broadly excitable, size-tunable, narrow emission bands and low photobleaching sensitivity, triggered the preparation of beads stained with QDs. However, the colloidal nature and the surface chemistry of these QDs, which largely controls their luminescence properties, introduce new challenges to bead encoding that have been barely systematically assessed. To establish a straightforward approach for the bead encoding with QDs with minimized loss in luminescence, we systematically assessed the incorporation of oleic acid/oleylamine-stabilized CdSe/CdS-core/shell-QDs into 0.5–2.5 μm-sized polystyrene (PS) microspheres by a simple dispersion polymerization synthesis that was first optimized with the organic dye Nile Red. Parameters addressed for the preparation of luminophore-encoded beads include the use of a polymer-compatible ligand such as benzyldimethyloctadecylammonium chloride (OBDAC) for the QDs, and crosslinking to prevent luminophore leakage. The physico-chemical and optical properties of the resulting beads were investigated with electron microscopy, dynamic light scattering, optical spectroscopy, and fluorescence microscopy. Particle size distribution, fluorescence quantum yield of the encapsulated QDs, and QD leaking stability were used as measures for bead quality. The derived optimized bead encoding procedure enables the reproducible preparation of bright PS microbeads encoded with organic dyes as well as with CdSe/CdS-QDs. Although these beads show a reduced photoluminescence quantum yield compared to the initially very strongly luminescent QDs, with values of about 35%, their photoluminescence quantum yield is nevertheless still moderate.
Fluid inclusion microthermometry is one of the analytical approaches that has been proposed for speleothem-based temperature reconstructions. The proxy of this paleothermometer is the density of drip water relicts that have been enclosed in microscopic fluid inclusions during speleothem growth. Prior to microthermometric analyses, the monophase liquid inclusions need to be transferred from a metastable liquid into a stable liquid-vapour two-phase state by stimulating vapour bubble nucleation by means of single ultra-short laser pulses. Subsequent microthermometric analyses determine the temperature at which the vapour bubble disappears again, the so-called liquid-vapour homogenisation temperature (Th(obs) ). The observed homogenisation temperature depends not only on the water density but also on the inclusion volume. In order to determine the water density, a thermodynamic model is used that takes account of the effect of surface tension on Th(obs) to calculate Th∞. This is the corresponding homogenisation temperature at saturation pressure that determines the water density and defines the formation temperature of the fluid inclusion. The analytical precision of the method ranges between 0.1 and 0.3 °C depending on the size of the inclusions.
In this study, the concept of a Zero Mass Flow Liner is evaluated. The concept enables impedance control by the induction of periodic bias flow through the perforated facing sheet of the liner. The periodic bias flow is generated by a secondary high amplitude acoustic actuation. By means of the periodic bias flow, the liner can be tuned to different operating points in a given range of grazing flow velocities. The equivalent fluid impedance model for perforated plates is modified to account for the effects of periodic bias flow and grazing flow. An optimization routine, based on a genetic algorithm, is implemented. The method is applicable to any liner concept and uses the impedance of the lined surface as boundary condition in a numerical simulation. Thereby, a set of liner parameters is derived in order to obtain the desired damping characteristics. Based on the results of the optimization, a Zero Mass Flow Liner is manufactured and consequently evaluated experimentally. The damping characteristics are evaluated in form of the dissipated energy along the lined surface. Prediction and measurements show agreement. The Zero Mass
Flow Liner delivers broad band dissipation of high peak value over a range of grazing flow Mach numbers. Under grazing ow conditions, the effect of periodic bias flow is reduced. This poses high energy requirements in high Mach number flow regimes which might restrict the applicability of the Zero Mass Flow concept to grazing flows of low Mach numbers.
Sound production due to main-flow oriented vorticity-nozzle interaction in absence of a net swirl
(2022)
The downstream acoustic response due to the interaction of main-flow oriented vorticity with a choked nozzle in a swirl-free flow was experimentally demonstrated. The response was obtained by means of impulsive radial air injection in the pipe upstream from the nozzle. The resulting downstream acoustic data are shown to obey a scaling rule that differs, from the one for swirl-nozzle interaction, which according to the literature is proportional to the square of the swirl number. In contrast, here evidence is presented that points to the scaling of main-flow oriented vorticity noise with the cross-sectional average of the square of the transversal velocity at the throat divided by the square of the critical sound speed.
The finite volume method (FVM), like the finite element method (FEM), is a numerical method for determining an approximate solution for partial differential equations. The derivation of the two methods is based on very different considerations, as they have historically evolved from two distinct engineering disciplines, namely solid mechanics and fluid mechanics. This makes FVM difficult to learn for someone familiar with FEM. In this paper we want to show that a slight modification of the FEM procedure leads to an alternative derivation of the FVM. Both numerical methods are starting from the same strong formulation of the problem represented by differential equations, which are only satisfied by their exact solution. For an approximation of the exact solution, the strong formulation must be converted to a so-called weak form. From here on, the two numerical methods differ. By appropriate choice of the trial function and the test function, we can obtain different numerical methods for solving the weak formulation of the problem. While typically in FEM the basis functions of the trial function and test function are identical, in FVM they are chosen differently. In this paper, we show which trial and test function must be chosen to derive the FVM alternatively: The trial function of the FVM is a “shifted” trial function of the FEM, where the nodal points are now located in the middle of an integration interval rather than at the ends. Moreover, the basis functions of the test function are no longer the same as those of the trial function as in the FEM, but are shown to be a constant equal to 1. This is demonstrated by the example of a 1D Poisson equation.
Laser metal deposition is a rapidly evolving method for additive manufacturing that combines high performance and simplified production routine. Quality of production depends on an instrumental design and operational parameters, which require constant control during the process. In this work, feasibility of using optical spectroscopy as a control method is studied via modeling and experimentally. A simplified thermal model is developed based on the time-dependent diffusion-conduction heat equation and geometrical light collection into detection optics. Intense light emitted by a laser-heated spot moving across a sample surface is collected and processed to yield the temperature and other temperature-related parameters. In the presence of surface defects, the temperature field is distorted in a specific manner that depends on shape and size of the defect. Optical signals produced by such the distorted temperature fields are simulated and verified experimentally using a 3D metal printer and a sample with artificially carved defects. Three quantities are tested as possible metrics for monitoring the process: temperature, integral intensity, and correlation coefficient. The shapes of the simulated signals qualitatively agree with the experimental signals; this allows for a cautious inference that optical spectroscopy can detect surface defects and, possibly, predict their characters, e.g., inner or protruding.
Phosphotyrosine residues are essential functional switches in health and disease. Thus, phosphotyrosine biomimetics are crucial for the development of chemical tools and drug molecules. We report here the discovery and investigation of pentafluorophosphato amino acids as novel phosphotyrosine biomimetics. A mild acidic pentafluorination protocol was developed and two PF5-amino acids were prepared and employed in peptide synthesis. Their structures, reactivities, and fluorine-specific interactions were studied by NMR and IR spectroscopy, X-ray diffraction, and in bioactivity assays. The mono-anionic PF5 motif displayed an amphiphilic character binding to hydrophobic surfaces, to water molecules, and to protein-binding sites, exploiting charge and H−F-bonding interactions. The novel motifs bind 25- to 30-fold stronger to the phosphotyrosine binding site of the protein tyrosine phosphatase PTP1B than the best current biomimetics, as rationalized by computational methods, including molecular dynamics simulations.
Functionalized nanomaterials (NM) with their unique size-dependent properties are of increasing relevance for current and future developments in various fields such as medical and pharmaceutical industry, computing, electronics or food and consumer products. The performance and safety of NM are determined by the sum of their intrinsic physicochemical properties.1 Besides other key parameters, the particle surface chemistry, which is largely controlled by the chemical nature and density of functional groups and ligands, must be considered for a better performance, stability, and processibility of NM, as well as their interaction with the environment. Thus, particle standards with well-designed surfaces and methods for functional group quantification can foster the sustainable development of functional and safe(r) NM.2 Here we provide a brief overview of the ongoing research in division Biophotonics to design tailored amorphous silica reference particles with bioanalytically relevant functional groups and ligands, for the development of standardized and validated surface functional group quantification methods.
Prostate cancer (PCa) is one of the most common cancers in men. For detection and diagnosis of PCa, non-invasive methods, including magnetic resonance imaging (MRI), can reduce the risk potential of surgical intervention. To explore the molecular characteristics of the tumor, we investigated the applicability of ferumoxytol in PCa in a xenograft mouse model in two different tumor volumes, 500 mm3 and 1000 mm3. Macrophages play a key role in tumor progression, and they are able to internalize iron-oxide particles, such as ferumoxytol. When evaluating T2*-weighted sequences on MRI, a significant decrease of signal intensity between pre- and post-contrast images for each tumor volume (n = 14; p < 0.001) was measured. We, furthermore, observed a higher signal loss for a tumor volume of 500 mm3 than for 1000 mm3. These findings were confirmed by histological examinations and laser ablation inductively coupled plasma-mass spectrometry. The 500 mm3 tumors had 1.5% iron content (n = 14; sigma = 1.1), while the 1000 mm3 tumors contained only 0.4% iron (n = 14; sigma = 0.2). In vivo MRI data demonstrated a correlation with the ex vivo data (R2 = 0.75). The results of elemental analysis by inductively coupled plasma-mass spectrometry correlated strongly with the MRI data (R2 = 0.83) (n = 4). Due to its long retention time in the blood, biodegradability, and low toxicity to patients, ferumoxytol has great potential as a contrast agent for visualization PCa.
Global supply chains rely on the compliance and safety of their products, processes, and facilities. These vital services (often referred to as ‘quality assurance’ or ‘conformity assessment’ services) are provided by Conformity Assessment Bodies (CABs). This empirical study explores the impact of the COVID-19 pandemic on CABs as well as their response to the resulting challenges. Data was gathered through an online survey among all accredited CABs in Germany, which resulted in 555 valid responses. Taking a resilience perspective, we reveal that CABs were hit hard by the disruptions caused by the pandemic, albeit to different degrees, in part due to their type of services, size, and sectors served. Furthermore, we find that contingency plans do not directly cushion order declines (as the main indicator of the economic impact of the pandemic) but rather indirectly through helping CABs respond more quickly, which in turn mitigates their order declines. However, our results show that contingency plans can also have adverse effects if they hinder flexible reaction to the crisis. The findings of our study help managers and policymakers learn from the COVID-19 pandemic and improve the resilience of the conformity assessment sector and quality assurance in the event of future crises.
Asymmetrically bridged aroyl-S,N-ketene acetals and aroyl-S,N-ketene acetal multichromophores can be readily synthesized in consecutive three-, four-, or five-component syntheses in good to excellent yields by several successive Suzuki-couplings of aroyl-S,N-ketene acetals and bis(boronic)acid esters. Different aroyl-S,N-ketene acetals as well as linker molecules yield a library of 23 multichromophores with substitution and linker pattern-tunable emission properties. This allows control of different communication pathways between the chromophores and of aggregation-induced emission (AIE) and energy transfer (ET) properties, providing elaborate aggregation-based fluorescence switches.
Current trends in materials and life sciences are flanked by the need to push detection limits to single molecules or single cells, enable the characterization of increasingly complex matrices or sophisticated nanostructures, speed up the time of analysis, reduce instrument complexity and costs, and improve the reliability of data. This requires suitable analytical tools such as spectroscopic, separation and imaging techniques, mass spectrometry, and hyphenated techniques as well as sensors and their adaptation to application-specific challenges in the environmental, food, consumer product, health sector, nanotechnology, and bioanalysis. Increasing concerns about health threatening known or emerging pollutants in drinking water, consumer products, and food and about the safety of nanomaterials led to a new awareness of the importance of analytical sciences. Another important driver in this direction is the increasing demand by legislation, particularly in view of the 17 sustainable development goals by the United Nations addressing clean energy, industry, and innovation, sustainable cities, clean water, and responsible consumption and production. In this respect, also the development of analytical methods that enable the characterization of material flows in production processes and support recycling concepts of precious raw materials becomes more and more relevant. In the future, this will provide the basis for greener production in the chemical industry utilizing recycled or sustainable starting materials.
This makes analytical chemistry an essential player in terms of the circular economy helping to increase the sustainability of production processes. In the life sciences sector, products based on proteins, such as therapeutic and diagnostic antibodies, increase in importance. These increasingly biotechnologically produced functional biomolecules pose a high level of complexity of matrix and structural features that can be met only by highly advanced methods for separation, characterization, and detection. In addition, metrological traceability and target definition are still significant challenges for the future, particularly in the life sciences.
However, innovative reference materials as required for the health and food sector and the characterization of advanced materials can only be developed when suitable analytical protocols are available. The so-called reproducibility crisis in sciences underlines the importance of improved measures of quality control for all kinds of measurements and material characterization. This calls for thorough method validation concepts, suitable reference materials, and regular interlaboratory comparisons of measurements as well as better training of scientists in analytical sciences.
The important contribution of analytical sciences to these developments is highlighted by a broad collection of research papers, trend articles, and critical reviews from these different application fields. Special emphasis is dedicated to often-overlooked quality assurance and reference materials.
Biofilms are ubiquitous in nature and in the man-made environment. Given their harmful effects on human health, an in-depth understanding of biofilms and the monitoring of their formation and growth are important. Particularly relevant for many metabolic processes and survival strategies of biofilms is their extracellular pH. However, most conventional techniques are not suited for minimally invasive pH measurements of living biofilms. Here, a fluorescent nanosensor is presented for ratiometric measurements of pH in biofilms in the range of pH 4.5–9.5 using confocal laser scanning microscopy. The nanosensor consists of biocompatible polystyrene nanoparticles loaded with pH-inert dye Nile Red and is surface functionalized with a pH-responsive fluorescein dye. Its performance was validated by fluorometrically monitoring the time-dependent changes in pH in E. coli biofilms after glucose inoculation at 37 °C and 4 °C. This revealed a temperature-dependent decrease in pH over a 4-h period caused by the acidifying glucose metabolism of E. coli. These studies demonstrate the applicability of this nanosensor to characterize the chemical microenvironment in biofilms with fluorescence methods.
In the last few years, the use of machine learning has emerged in the field of distributed fiber optic sensors as a promising approach to enhance their performance and provide new capabilities. In this study, we use machine learning for simultaneous measurements of temperature and humidity in polyimide (PI)-coated optical fibers based on Brillouin Brillouin optical frequency domain analysis (BOFDA). Different non-linear machine learning algorithms are employed, namely polynomial regression, decision trees and artificial neural networks (ANNs), and their discrimination performance is benchmarked against that of the conventional linear regression. The performance is evaluated using leave-one-out cross-validation to ensure that the models are reliable and able to generalize well on new data. We show that nonlinear machine learning algorithms outperform the conventional linear regression and thus could pave the way towards simultaneous cost-effective temperature and humidity distributed sensing, which has the potential to find attractive new applications in the field of civil and geotechnical engineering, from structural health monitoring of dikes and bridges to subsea cables and long pipelines corrosion detection.
Brillouin Optical Frequency Domain Analysis (BOFDA) is a powerful and well-established method for static distributed sensing of temperature and strain. Recently, we demonstrated a BOFDA system based on convolutional neural network which shortens the measurement time considerably. In this paper, we apply leave-one-out cross validation to evaluate the generalization performance and provide an unbiased and reliable machine learning model for a time-efficient BOFDA system.
Equilibrium model of titanium laser induced plasma in air with reverse deposition of titanium oxides
(2022)
A chemical-hydrodynamic model of laser induced plasma is developed to study a process of deposition of titanium oxides from titanium laser induced plasma to the titanium target surface. The model is relevant to texturing and coating of titanium bone implants that is done by scanning the ablation laser across implant surfaces. Such the procedure improves the biocompatibility and durability of the implants. The model considers plasma chemical reactions, formation of condensed species inside the plasma plume, and deposition and accumulation of these species on the ablation surface. A chemical part of the model is based on minimization of Gibbs free energy of the chemical system; it is used to calculate the chemical composition of the plasma. A hydrodynamic part uses the 2D fluid-dynamic equations that model a 3D axisymmetric plasma plume and assumes the mass and energy exchange between the plasma and the surface. The initial parameters for the model are inferred from experiment.
The model shows that condensed titanium oxides, mostly TiO2, form in a peripheral plasma zone and gradually adhere to the surface during the plasma plume evolution. The model predicts the major component and thickness of the deposit and can be applied for the optimization of experiments aimed at surface modification.
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.
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.
In this work, we present the recent in-situ imaging developments at the BAMline (of synchrotron BESSY II, HZB), focused on the in-situ characterization and understanding of microstructural evolution of additively manufactured materials subjected to different environments. Two show cases are presented. In the first, X-ray refraction radiography (SXRR) was combined with in-situ heat treatment to monitor the microstructural evolution as a function of temperature in a laser powder bed fusion (LPBF) manufactured AlSi10Mg alloy. We show that SXRR allows detecting the changes in the Si-phase morphology upon heating using statistically relevant volumes. SXRR also allows observing the growth of pores (i.e., thermally induced porosity), usually studied via X-ray computed tomography (XCT), but using much smaller fields-of-view. In the second case study, XCT was combined with in-situ tensile test to investigate the damage mechanism in a LPBF Aluminum Metal Matrix Composite (MMC). In-situ SXCT test disclosed the critical role of the defects in the failure mechanism along with pre-cracks in the reinforcement phase of MMC. We found that cracks were initiated from lack-of-fusion defects and propagated through coalescence with other defects.
Mechanochemistry offers a unique opportunity to modify and manipulate crystal forms, often providing new products as compared with conventional solution methods. While promising, there is little known about how to control the solid form through mechanochemical means, demanding dedicated investigations. Using a model organic cocrystal system (isonicotinamide:glutaric acid), we here demonstrate that with mechanochemistry, polymorphism can be induced in molecular solids under conditions seemingly different to their conventional thermodynamic (thermal) transition point. Whereas Form II converts to Form I upon heating to 363 K, the same transition can be initiated under ball milling conditions at markedly lower temperatures (348 K). Our results indicate that mechanochemical techniques can help to reduce the energy barriers to solid form transitions, offering new insights into controlling polymorphic forms. Moreover, our results suggest that the nature of mechanochemical transformations could make it difficult to interpret mechanochemical solid form landscapes using conventional equilibrium-based tools.
Mechanochemistry offers a unique opportunity to modify or synthesize new crystal forms. Although the method is very promising, little is known about the mechanochemical means to control the synthesis of a solid form. Using an polymorphic organic cocrystal system, we show here that mechanochemistry can be used to obtain a polymorph transformation under the apparently conventional (thermal) transition point.
The rising popularity of additive manufacturing processes leads to an increased interest in possibilities and methods for related process monitoring. Such methods ensure improved process quality and increase the understanding of the manufacturing process, which in turn is the basis for stable component quality, e.g., required in the aerospace industry or in the medical sector. For laser powder bed fusion, a handful of process monitoring tools already exist, such as optical tomography, thermography, pyrometry, imaging, or laser power monitoring. Although these tools provide helpful information about the process, more information is required for an accurate in-depth understanding. In this article, advanced approaches in eddy current testing (ET) are combined, such as single wire excitation, magnetoresistive (MR) sensor arrays, and heterodyning to build up a system that can be used for online process monitoring of laser powder bed fusion. In addition to detailed information about the developed ET system and underlying signal processing, the first results of magnetoresistance-basedonline ET during the laser powder fusion process are presented. While producing a step-shaped cuboid, each layer is tested during recoating.
Test results show that not only the contours of the topmost layer are detected but also the contours of previous layers covered by powder. At an excitation frequency of 1 MHz, a penetration depth of approx. 400 μm is obtained. To highlight the possibilities of ET for online process monitoring of laser powder bed fusion, results are compared with postexposure images of the integrated layer control system (LCS).
ADAMTS4-specific MR-probe to assess aortic aneurysms in vivo using synthetic peptide libraries
(2022)
The incidence of abdominal aortic aneurysms (AAAs) has substantially increased during the last 20 years and their rupture remains the third most common cause of sudden death in the cardiovascular field after myocardial infarction and stroke. The only established clinical parameter to assess AAAs is based on the aneurysm size. Novel biomarkers are needed to improve the assessment of the risk of rupture. ADAMTS4 (A Disintegrin And Metalloproteinase with ThromboSpondin motifs 4) is a strongly upregulated proteoglycan cleaving enzyme in the unstable course of AAAs. In the screening of a one-bead-one-compound library against ADAMTS4, a low-molecular-weight cyclic peptide is discovered with favorable properties for in vivo molecular magnetic resonance imaging applications. After identification and characterization, it’s potential is evaluated in an AAA mouse model. The ADAMTS4-specific probe enables the in vivo imaging-based prediction of aneurysm expansion and rupture.
In the present talk the basics of the Raman spectroscopy and particularly of Raman microscopy are explained. Advantages and disadvantages of the method are highlighted through selected case studies. In the second part of the lecture examples of correlative imaging with electron, X-ray, ion and optical microscopies from micro- to the nanoscale are highlighted.
Efforts are rising in opening up science by making data more transparent and more easily available, including the data reduction and evaluation procedures and code. A strong foundation for this is the F.A.I.R. principle, building on Findability, Accessibility, Interoperability, and Reuse of digital assets, complemented by the letter T for trustworthyness of the data. Here, we have used data, which was made available by the Institute Laue-Langevin and can be identified using a DOI, to follow the F.A.I.R.+T. principle in extracting, evaluating and publishing triple axis data, recorded at IN3.
This guideline was drafted following and complementing the norm ISO 22232-2:2020(E) to include air-coupled ultrasonic transducers. This document specifies the characteristics of probes used for non-destructive air-coupled ultrasonic testing with center frequencies above 20 kHz, with focusing or without focusing means.
The use of polycapillary optics in confocal micro-X-ray fluorescence analysis (CMXRF) enables the destruction-free 3D investigation of the elemental composition of samples. The energy-dependent transmission properties, concerning intensity and spatial beam propagation of three polycapillary half lenses, which are vital for the quantitative interpretation of such CMXRF measurements, are investigated in a monochromatic confocal laboratory setup at the Atominstitut of TU Wien, and a synchrotron setup on the BAMline beamline at the BESSY II Synchrotron, Helmholtz-Zentrum-Berlin. The empirically established results, concerning the intensity of the transmitted beam, are compared with theoretical values calculated with the polycap software package and a newly presented analytical model for the transmission function.
The resulting form of the newly modelled energy-dependent transmission function is shown to be in good agreement with Monte Carlo simulated results for the complete energy regime, as well as the empirically established results for the energy regime between 6 keV and 20 keV. An analysis of possible fabrication errors was conducted via pinhole scans showing only minor fabrication errors in two of the investigated polycapillary optics. The energy-dependent focal spot size of the primary polycapillary was investigated in the laboratory via the channel-wise evaluation of knife-edge scans. Experimental results are compared with data given by the manufacturer as well as geometric estimations for the minimal focal spot size. Again, the resulting measurement points show a trend in agreement with geometrically estimated results and manufacturer data.
n this study, two green synthesis routes were used for the synthesis of Ag/ZnO nanoparticles, using cassava starch as a simple and low-cost effective fuel and Aloe vera as a reducing and stabilizing agent. The Ag/ZnO nanoparticles were characterized and used for bacterial dis-
infection of lake water contaminated with Escherichia coli (E. coli). Characterization indicated the formation of a face-centered cubic structure of metallic silver nanoparticles with no insertion of Ag into the ZnO hexagonal wurtzite structure. Physicochemical and bacteriological analyses described in “Standard Methods for the Examination of Water and Wastewater” were used to evaluate the efficiency of the treatment. In comparison to pure ZnO, the synthesized Ag/ZnO nanoparticles showed high efficiencies against Escherichia coli (E. coli) and general coliforms present in the lake
water. These pathogens were absent after treatment using Ag/ZnO nanoparticles. The results indicate that Ag/ZnO nanoparticles synthesized via green chemistry are a promising candidate for the treatment of wastewaters contaminated by bacteria, due to their facile preparation, low-cost synthesis,and disinfection efficiency.
In this talk an overview about artificial intelligence/machine learning applications @BAMline is given. In the first part, the use of neural networks for the quantification of XRF measurements and the decoding of coded-aperture measurements are shown. Then it is shown how Gaussian processes and Bayesian statistics can be used to achieve an optimal alignment of the set-up and in general for optimization of measurements.
With the development of hybridoma technology, monoclonal antibodies are increasingly important in therapeutic and analytical applications. For recombinant expression in mammalian cells, knowledge of the variable regions of both, heavy (VH) and light (VL) chain, is a necessary prerequisite for generating expression plasmids. Furthermore, cloning antibody sequences including constant regions CH1 to CH3 and CL reduces impact of hybridoma cell loss and associated full natural antibody sequence leakage. Here, we show a cost-effective workflow for amplification of IgG antibody variable regions in combination with advanced methods for full-length cloning of monoclonal antibodies.
Getting more efficient – The use of Bayesian optimization and Gaussian processes at the BAMline
(2022)
For more than 20 years, BAM is operating the BAMline at the synchrotron BESSY II in Berlin Adlershof. During this time, the complexity of the setup and the amount of data generated have multiplied. To increase the effectiveness and in preparation for BESSY III, algorithms from the field of machine learning are increasingly used.
In this paper, several examples in the areas of beamline alignment and measurement time optimization based on Bayesian optimization (BO) with Gaussian processes (GP) are presented. BO is a method for finding the global optimum of a function using a probabilistic model represented by a GP. The advantage of this method is that it can handle high-dimensional problems, does not depend on the initial estimate, and also provides uncertainty estimates.
After a short introduction to BO and GP, the first example is the automatic alignment of our double multilayer monochromator (DMM). To achieve optimal performance, up to three linear and two angular motor positions have to be optimized. To achieve this with a grid scan, at least 100^5 measurement points would be required. Assuming that all positions can be aligned independently, 100*5 points are still necessary. We show that with BO and GP less than 100 points are sufficient to achieve equal or better results.
The second example is the optimization of measurement time in XRF scanning. Here we will show the advantage of the BO GP approach over point-by-point scanning. As can be seen in Fig. 1, the number of points required and thus the measurement time can be reduced by a factor of 50, while the loss in image quality is acceptable. The advantages and limitations of this approach will be discussed.
Gold is one of the seven metals already known in antiquity and was used from time immemorial as a medium of exchange and for the production of jewelry because of its luster and rarity. In addition, it is easy to work and largely resistant to chemical influences. Investigations of gold using synchrotron radiation excited X-ray fluorescence analysis are non-destructive and provide information about the chemical elements present in the sample under investigation. The investigations presented here at BAMline focus on questions such as the origin, manufacturing process, and association of gold findings. The different questions are explained by a number of examples ranging from the Viking treasure from Hiddensee to the Nebra Sky Disk and finds from Egypt. The find from Bernstorf is discussed in detail. A Bayesian treatment of the authenticity is shown.
News from the BAMline
(2022)
Getting more efficient – The use of Bayesian optimization and Gaussian processes at the BAMline
(2022)
For more than 20 years, BAM is operating the BAMline at the synchrotron BESSY II in Berlin Adlershof. During this time, the complexity of the setup and the amount of data generated have multiplied. To increase the effectiveness and in preparation for BESSY III, algorithms from the field of machine learning are increasingly used.
After a short introduction to BO and GP, the first example is the automatic alignment of our double multilayer monochromator (DMM).
The second example is the optimization of measurement time in XRF scanning.
Mechanochemical reactions promise a new direction for environmentally benign preparation of materials, and has been dubbed by IUPAC as one of the 10 chemical innovations that will change our world. Despite this significant promise, very little is known about the mechanisms that drive mechanochemical transformations, posing significant barriers to realizing their full potential. To this end, there is growing need to follow mechanochemical reactions in situ and in real time. We here describe advances in the development and application of XAS methods to monitor material synthesis in real time under mechanochemical conditions. We demonstrate the generality of our approaches by describing mechanochemical syntheses of materials by both vibratory ball milling and by Resonant Acoustic Mixing (RAM), where a time resolution of 1 second is for a whole XAS spectrum was achieved. Moreover, we describe how spectroscopic methods can be coupled to diffraction-based approaches, thereby providing new dimensions in understanding mechanochemical synthesis.
Mechanochemical reactions promise a new direction for environmentally benign preparation of materials, and has been dubbed by IUPAC as one of the 10 chemical innovations that will change our world. Despite this significant promise, very little is known about the mechanisms that drive mechanochemical transformations, posing significant barriers to realizing their full potential. To this end, there is growing need to follow mechanochemical reactions in situ and in real time. We here describe advances in the development and application of XAS methods to monitor material synthesis in real time under mechanochemical conditions. We demonstrate the generality of our approaches by describing mechanochemical syntheses of materials by both vibratory ball milling and by Resonant Acoustic Mixing (RAM), where a time resolution of 1 second is for a whole XAS spectrum was achieved. Moreover, we describe how spectroscopic methods can be coupled to diffraction-based approaches, thereby providing new dimensions in understanding mechanochemical synthesis.
ABID
(2022)
In order to automate the spectral comparison for larger libraries of antibodies, we developed the online software ABID 2.0. This open-source software determines the number of matching peptides in the fingerprint spectra. We propose that publications and other documents critically relying on monoclonal antibodies with unknown amino acid sequences should include at least one antibody fingerprint. By fingerprinting an antibody in question, its identity can be confirmed by comparison with a library spectrum at any time and context.
Time is the most valuable parameter in synchrotron experiments. This is costly and some of the experiments suffer from low efficiency due to low counting statistics. With today's high processing power long experiments are run in a shorter time and increase efficiency. With optimization algorithms time in "counting-hungry" experiments reduced by factor of 10. Our project is to develop a new method to analyze the chemical properties of complex materials non-destructively and efficiently, such as high entropy materials subjected to corrosion processes. A better understanding of the corrosion process will help to develop corrosion-resistant materials and reduce the cost of corrosion damage, which averages around 2.5 trillion USD annually.
The components that are used in structural and in high temperature applications generally face significant challenges with respect to oxidation behaviours and metalworking processes. In most of the cases, harsh environmental conditions lead materials to degrade due to corrosion. To thoroughly investigate the corrosion processes and to determine oxidation states of metal components within the reaction products, we need special analytical tools. Grazing exit X-ray fluorescence (GEXRF) offers a non-destructive way to collect this information in sub-micrometre depth range.
In order to obtain structural information, such as regarding oxidation states or atomic/molecular geometric arrangement, the GEXRF approach can also be combined with the X-ray absorption spectroscopy (XAS) method. The position and energy sensitive detector, with 264x264 pixel detector area, provides information regarding the signal emitted from the sample as a function of the emission angle and thus allows depth-sensitive analysis. Furthermore, the data collected from samples of an incidence energy which can be controlled with a resolution of 0.5 eV provides XANES data to determine oxidation states.
We address the feasibility of our setup and provide a new optimization procedure (Bayesian Optimization and Gaussian Regression) to decrease measuring time. The results settle on a conceptual study on a reference sample (Cr-Oxide layer (300nm) on Cr layer (500nm) on Si wafer).
The components that are used in structural and in high temperature applications generally face significant challenges with respect to oxidation behaviours and metalworking processes. In most of the cases, harsh environmental conditions lead materials to degrade due to corrosion. To thoroughly investigate the corrosion processes and to determine oxidation states of metal components within the reaction products, we need special analytical tools. Grazing exit X-ray fluorescence (GEXRF) offers a non-destructive way to collect this information in sub-micrometre depth range.
In order to obtain structural information, such as regarding oxidation states or atomic/molecular geometric arrangement, the GEXRF approach can also be combined with the X-ray absorption spectroscopy (XAS) method. The position and energy sensitive detector, with 264x264 pixel detector area, provides information regarding the signal emitted from the sample as a function of the emission angle and thus allows depth-sensitive analysis. Furthermore, the data collected from samples of an incidence energy which can be controlled with a resolution of 0.5 eV provides XANES data to determine oxidation states.
We address the feasibility of our setup and provide a new optimization procedure (Bayesian Optimization and Gaussian Regression) to decrease measuring time. The results settle on a conceptual study on a reference sample (Cr-Oxide layer (300nm) on Cr layer (500nm) on Si wafer).
Compositionally complex alloys (CCAs) are a new class of alloys containing at least 5 elements with concentrations between 5 and 35 atomic percent. Due to their adjustable composition, which enables modifications of mechanical properties (such as hardness, strength and ductility etc) and their stability at high temperatures, CCAs have been the focus of various studies [1,2]. Especially the corrosion behavior of CCAs has been a wide research interest.
However, there are only few studies that deals with the degradation process on such materials, which is highly relevant for the safety aspect for future component design. To thoroughly investigate the corrosion processes and to determine oxidation states of metal components within the reaction products, we need special analytical tools. Since the grazing exit X-ray fluorescence (GEXRF) offers a non-destructive way to collect notable information regarding the high temperature oxidation, we consider it as a useful method to investigate how CCAs behave in corrosive environments.
The main idea of grazing geometry is to enhance the fluorescence signal of the surface. This enables highly sensitive surface analyses of thin protective film on surface in sub-micrometer scale [3]. When compared to a conventional CCD-based camera, the advantage and most important feature of the detector system (Color X-Ray Camera (CXC)) is that each pixel is an energy sensitive detector. The position and area sensitive detector, with 264x264 pixel detector area, provides information regarding the signal emitted from the sample as a function of the emission angle and thus allows depth-sensitive analysis. Furthermore, the data collected from samples of an incidence energy which can be controlled with a resolution of 0.5 eV provides XANES data to determine oxidation states.
In this contribution, we address the feasibility of our setup and new optimization procedure (Bayesian Optimization and Gaussian Regression). The results of a conceptual study regarding layer properties of the reference sample (Cr-Oxide layer (300nm) on Cr layer (500nm) on Si wafer) and CrCoNi (Cr-Oxide (>1µm) layer on CrCoNi substrate) medium entropy alloy.
Because of its mobility and ability to investigate exposed surfaces, single-sided (SiS) nuclear magnetic resonance (NMR) technology enables new application fields in geosciences. To test and assess its corresponding potential, we compare longitudinal (T1) and transverse (T2) data measured by SiS NMR with those of conventional geoscientific laboratory NMR. We use reference sandstone samples covering a broad range of pore sizes. Our study demonstrates that the lower signal-to-noise ratio of SiS NMR data generally tends to slightly overestimated widths of relaxation time distributions and consequently pore size distributions. While SiS and conventional NMR produce very similar T1 relaxation data, unbiased SiS NMR results for T2 measurements can only be expected for fine material, i.e. clayey or silty sediments and soils with main relaxation times below 0.05s. This limit is given by the diffusion relaxation rate due to the gradient in the primary magnetic field associated with the SiS NMR. Above that limit, i.e. for coarse material, the relaxation data is strongly attenuated. If considering the diffusion relaxation time of 0.2 s in the numerical data inversion process, the information content >0.2s is blurred over a range larger than that of conventional NMR. However, our results show that principle range and magnitudes of the relaxation time distributions are reconstructed to some extent. Regarding these findings, SiS NMR can be helpful to solve geoscientific issues, e.g. to assess the hydro-mechanical properties of the walls of underground facilities or to provide local soil moisture data sets for calibrating indirect remote techniques on the regional scale. The greatest opportunity provided by the SiS NMR technology is the acquisition of profile relaxation data for rocks with significant bedding structures at the µm scale. With this unique feature, SiS NMR can support the understanding and modeling of hydraulic and diffusional anisotropy behavior of sedimentary rocks.
Graphene quantum dots (GQDs) have attracted increasing attention due to their favorable optical properties and have been widely used, e.g., in the biomedical field. However, the properties related to the chemical structure of GQDs, resulting in solventdependent optical properties, still remain unclear. Herein, we present the synthesis of long-wavelength emitting GQDs with a size of about 3.6 nm via a solvothermal method using oxo-functionalized graphene (oxo-G) and p-phenylenediamine as precursors and their structural and surface chemical analysis by transmission electron and atomic force microscopy (TEM; AFM) as well as Fourier-transform infrared, Raman, and X-ray photoelectron spectroscopy (FTIR; Raman; XPS). Subsequently, the influence of solvent polarity and proticity on the optical properties of the as-prepared GQDs bearing –OH, –NH2, –COOH and pyridine surface groups was investigated. Based on the results of the absorption and fluorescence (FL) studies, a possible luminescence mechanism is proposed. The observed solvent-induced changes in the spectral position of the FL maximum, FL quantum yield, and FL decay kinetics in protic and aprotic solvents of low and high polarity are ascribed to a combination of polarity effects, intramolecular charge transfer (ICT) processes, and hydrogen bonding. Moreover, the potential of GQDs for the optical sensing of trace amount of water was assessed. The results of our systematic spectroscopic study will promote the rational design of GQDs and shed more light on the FL mechanism of carbon based fluorescent nanomaterials.
Monitoring of construction projects plays increasingly important role in the implementation of growing needs and requirements, especially in geologically difficult areas. This particularly concerns tunnelling and special civil engineering projects. The use of fiber optic sensors for structural health monitoring provides significant economic advantages regarding lower life-cycle costs of the civil infrastructure. We present our achievements in the development of distributed polymer optical fiber sensors based on Rayleigh and Brillouin scattering for early damage detection.
In this work, synchrotron X-ray refraction radiography (SXRR) was combined with in-situ heat treatment to monitor microstructure and porosity evolution as a function of temperature. The investigated material was a laser powder bed fusion (LPBF) manufactured AlSi10Mg, where the initial eutectic Si network is known to break down into larger particles with increasing temperature. Such alloy is also prone to thermally induced porosity (TIP). We show that SXRR allows detecting the changes in the Si-phase morphology upon heating, while this is currently possible only using scanning electron microscopy. SXRR also allows observing the growth of pores, usually studied via X-ray computed tomography, but on much smaller fields-of-view. Our results show the great potential of in-situ SXRR as a tool to gain in-depth knowledge of the susceptibility of any material to thermally induced damage and/or microstructure evolution over statistically relevant volumes.
Hybrid optical measurement technique for detection of defects in epitaxially grown 4H-SiC layers
(2022)
Recent developments in power electronics require the use of new wide bandgap compound semiconductor. We demonstrate the use of the ellipsometry and white light interference microscopy to detect defects in epitaxially grown SiC layers on SiC substrates. Such hybrid optical metrology methods can be used to better understand the mechanism of the development of the defects as well as their effects on the material´s optoelectronic properties.
X-ray refraction is an excellent tool for the characterization of the microstructure of materials. However, there are only a few (synchrotron) laboratories in the world that use this technique for material characterisation. Therefore, the seminar will first explain the basic principles of X-ray refraction and the measurement techniques installed at the hard X-ray beamline BAMline at BESSY II (Berlin, Germany). This is followed by examples of investigations on fibre-reinforced plastic composites (CFRP) as well as ceramic (Cordierite, ZrO2-SiO2) and metallic materials (Ti-6Al-4V, Inconel). Some of the investigations were carried out both ex-situ and in-situ under mechanical and thermal load. The results are correlated with the mechanical properties of the materials.
The most profound consequences of the presence of Ca–Mg carbonates (CaCO3–MgCO3) in the Earth’s upper mantle may be to lower the melting temperatures of the mantle and control the melt composition.
Low-degree partial melting of a carbonate-bearing mantle produces CO2-rich, silica-poor melts compositionally imposed by the melting relations of carbonates. Thus, understanding the melting relations in the CaCO3–MgCO3 system facilitates the interpretation of natural carbonate-bearing silicate systems.
We report the melting relations of the CaCO3–MgCO3 system and the partition coefficient of trace elements between carbonates and carbonate melt from experiments at high pressure (6 and 9 GPa) and temperature (1300–1800 ◦C) using a rocking multi-anvil press. In the absence of water, Ca–Mg carbonates are stable along geothermal gradients typical of subducting slabs. Ca–Mg carbonates (∼ Mg0.1–0.9Ca0.9–0.1CO3) partially melt beneath mid-ocean ridges and in plume settings. Ca–Mg carbonates melt incongruently, forming periclase crystals and carbonate melt between 4 and 9 GPa. Furthermore, we show that the rare earth element (REE) signature of Group-I kimberlites, namely strong REE fractionation and depletion of heavy REE relative to the primitive mantle, is resembled by carbonate melt in equilibrium with Ca-bearing magnesite and periclase at 6 and 9 GPa. This suggests that the dolomite–magnesite join of the CaCO3–MgCO3 system might be useful to approximate the REE signature of carbonate-rich melts parental to kimberlites.
One of the most common causes of damage is the ingress of harmful ions into the concrete, which can lead to deterioration processes and affect structural performance. Therefore, the increasingly aging infrastructure is regularly inspected to assess durability. Regular chemical analysis can be useful to determine the extent and evolution of ion ingress and to intervene in a timely manner. This could prove more economical than extensive repairs for major damage, particularly for critical infrastructure. In addition to already established elemental analysis techniques in civil engineering such as potentiometric titration or X-ray fluorescence analysis, laser-induced breakdown spectroscopy (LIBS) can provide further important complementary information and benefits. The possibilities of LIBS are demonstrated using the example of a drill core taken from a parking garage.
Laser Induced Breakdown Spectroscopy – A Tool for Imaging the Chemical Composition of Concrete
(2022)
One of the most common causes of damage is the ingress of harmful ions into the concrete, which can lead to deterioration processes and affect structural performance. Therefore, the increasingly aging infrastructure is regularly inspected to assess durability. Regular chemical analysis can be useful to determine the extent and evolution of ion ingress and to intervene in a timely manner. This could prove more economical than extensive repairs for major damage, particularly for critical infrastructure. In addition to already established elemental analysis techniques in civil engineering such as potentiometric titration or X-ray fluorescence analysis, laser-induced breakdown spectroscopy (LIBS) can provide further important complementary information and benefits. The possibilities of LIBS are demonstrated using the example of a drill core taken from a parking garage.
The availability of high-performance Al alloys in AM is limited due to difficulties in printability, requiring both the development of synergetic material and AM process to mitigate problems such as solidification cracking during laser powder bed fusion (LPBF). The goal of this work was to investigate the failure mechanism in a LPBF 7017 Aluminium alloy + 3 wt% Zr + 0.5 wt% TiC. The processing leads to different categories of Zr-rich inclusions, precipitates and defects.
Back Deposition of Titanium Oxides under Laser Ablation of Titanium: Simulation and Experiment
(2022)
Titanium is widely used in medicine for implants and prostheses, thanks to its high biocompatibility, good mechanical properties, and high corrosion resistance. Pure titanium, however, has low wear resistance and may release metallic titanium into surrounding tissues. Structuring and coating its surface with oxide layers are necessary for high wear resistance and improved biocompatibility. In this work, a combination of theoretical and experimental methods was used to study processes responsible for deposition of titanium oxides during ablation of titanium in air.
The deposition process was modeled via the Navier-Stokes equations that accounted for the material removal and accumulation of the deposit on the ablation surface. The chemical part was based on the equilibrium model embedded into the hydrodynamic code. Simulations showed that the most active zone of production of condensed titanium oxides were at plasma periphery whereas a zone of strong condensation of titanium metal was above the molten pool.
In experiment, a pulsed Yb fiber laser was scanned across a titanium surface. The temperature and composition of the plasma were inferred from plasma emission spectra. The post-ablation surface was analyzed by SEM, TEM, STEM, AFM, and XRD.
The developed model well reproduced the main features of experimental data. It was concluded that the deposition of condensed metal oxides from the plasma is a principal mechanism of formation of nanoporous oxide layer on the metal surface. The method of surface structuring and modification by nanosecond laser ablation can be developed into a useful technology that may find applications in medicine, photonics, and other areas.
Wide-range X-ray scattering datasets and analyses for all samples described in the 2020 publication "Gold and silver dichroic nanocomposite in the quest for 3D printing the Lycurgus cup". These datasets are composed by combining multiple small-angle x-ray scattering and wide-angle x-ray scattering curves into a single dataset. They have been analyzed using McSAS to extract polydispersities and volume fractions. They have been collected using the MOUSE project (instrument and methodology).
Vertebrate bones are made of a nanocomposite consisting of water, mineral and organics. Water helps bone material withstand mechanical stress and participates in sensation of external loads. Water diffusion across vertebrae of medaka (bone material lacking osteocytes) and zebrafish (bone material containing osteocytes) was compared using neutron tomography. Samples were measured both wet and following immersion in deuterated-water (D2O). By quantifying H+ exchange and mutual alignment with X-ray lCT scans, the amount of water expelled from complete vertebra was determined. The findings revealed that anosteocytic bone material is almost twice as amenable to D2O diffusion and H2O exchange, and that unexpectedly, far more water is retained in osteocytic zebrafish bone. Diffusion in osteocytic bones (only 33 % – 39 % water expelled) is therefore restricted as compared to anosteocytic bone (~ 60 % of water expelled), presumably because water flow is confined to the lacunar-canalicular network (LCN) open-pore system. Histology and Raman spectroscopy showed that anosteocytic bone contains less proteoglycans than osteocytic bone. These findings identify a previously unknown functional difference between the two bone materials. Therefore, this study proposes that osteocytic bone retains water, aided by non-collagenous proteins, which contribute to its poroelastic mechano-transduction of water flow confined inside the LCN porosity.
Gold films coated with a graphene sheet are being widely used as sensors for the detection of label-free binding interactions using surface plasmon resonance (SPR). During the preparation of such sensors, it is often essential to subject the sensor chips to a high-temperature treatment in order to ensure a clean graphene surface. However, sensor chips used currently, which often use chromium as an adhesion promoter, cannot be subjected to temperatures above 250 °C, because under such conditions, chromium is found to reorganize and diffuse to the surface, where it is easily oxidized, impairing the quality of SPR spectra. Here we present an optimized preparation strategy involving a three-cycle tempering coupled with chromium (oxide) etching, which allows the graphene-coated SPR chips to be annealed up to 500 °C with little deterioration of the surface morphology. In addition, the treatment delivers a surface that shows a clear enhancement in spectral response together with a good refractive index sensitivity. We demonstrate the applicability of our sensors by studying the kinetics of avidin–biotin binding at different pH repeatedly on the same chip. The possibility to anneal can be exploited to recover the original surface after sensing trials, which allowed us to reuse the sensor for at least six cycles of biomolecule adsorption.