6 Materialchemie
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The mechanism of action of zirconium permanent modifiers on graphite surfaces was investigated in order to understand its influence on the analytical signal in atomic and molecular absorption spectrometry (AAS/MAS). For this, the molecule formation of CaF was studied, which is used for the indirect analytical determination of fluorine in high-resolution continuum source graphite furnace molecular absorption spectrometry (HR-CS-GFMAS). The kinetics of this reaction was established by monitoring its molecular spectrum at different atomisation temperatures. An Arrhenius plot showed a pseudo-first order reaction with respect to fluorine (n = 1). An intermediate state was isolated, and its structure was elucidated by spectroscopic methods: scanning electron microscopy with energy dispersive X-ray spectroscopy (SEMEDX), X-ray photoelectron spectroscopy (XPS), X-ray absorption spectroscopy (XANES and EXAFS), and Raman microspectroscopy. We propose here a mechanism, where ZrO2 acts as a heterogeneous catalyst: after a pyrolytic step, an intermediate state of ZrO(OCaF) is activated, and at higher temperatures, CaF(g) is released from the zirconium-coated graphite surface. No evidence of the formation of zirconium carbide was found. Consequently, as the CaF formation is catalysed by a heterogeneous catalyst, surface modifications with ZrO2 nanoparticles and ZrO xerogels were investigated in order to increase the surface area. Their influence was evaluated in the molecule formation of CaF, CaCl, CaBr, and CaI. Graphite furnace modification with zirconium oxide nanoparticles proves to be the best choice for fluorine analysis with a signal enhancement of more than eleven times with respect a non-coated graphite furnace. However, the influence of zirconium modifications in the analytical signals of Cl, and I is lower than the F signals or even negative in case of the Br. Understanding zirconium modifiers as heterogeneous catalysts offers a new perspective to AAS and MAS, and reveals the potential of surface analytical methods for development of improved permanent modifiers and graphite furnace coatings.
We present a workflow for obtaining fully trained artificial neural networks that can perform automatic particle segmentations of agglomerated, non-spherical nanoparticles from scanning electron microscopy images “from scratch”, without the need for large training data sets of manually annotated images. The whole process only requires about 15 minutes of hands-on time by a user and can typically be finished within less than 12 hours when training on a single graphics card (GPU). After training, SEM image analysis can be carried out by the artificial neural network within seconds. This is achieved by using unsupervised learning for most of the training dataset generation, making heavy use of generative adversarial networks and especially unpaired image-to-image translation via cycle-consistent adversarial networks. We compare the segmentation masks obtained with our suggested workflow qualitatively and quantitatively to state-of-the-art methods using various metrics. Finally, we used the segmentation masks for automatically extracting particle size distributions from the SEM images of TiO2 particles, which were in excellent agreement with particle size distributions obtained manually but could be obtained in a fraction of the time.
Counterfeiting of goods has serious economic implications worldwide and can be a threat to human health and safety. Upconversion nanoparticles (UCNPs)are ideal candidates for optical encoding of various materials. Particles with tailor-made emission patterns can be used as anti-counterfeiting markers and luminophores in security inks and to track material flows. Microenvironment-specific changes in the emission properties of the UCNP tags can be used to study, signal, and sense changes of physico-chemical parameters in different environments, e.g., building
materials.
Safety is a key parameter for the design and construction of buildings. The most widely used construction material to date is concrete that consists of about 15-20 wt.-% cement, which is responsible for the main concrete properties, i.e., strength and durability. Despite many standards regulating the quality of cement, at present, there exists no viable method to track the cement life cycle “from cradle to grave”. This led to an increasing interest in simple and robust methods for studying the processes and changes occurring during the life cycle of cement. In this context, we explored the applicability of fluorescence measurements which can be performed with relatively inexpensive and miniaturized instrumentation yet require robust optical probes which survive the harsh cement environment. Therefore, we developed a platform of lanthanide-based upconversion nanoparticles (UCNPs), consisting of a NaYF4 matrix doped with Yb3+ and Er3+ with sizes between 20 nm and 55 nm, which show characteristic multi-color emission patterns, composed of narrow bands of varying intensity in the ultraviolet, visible, near-infrared, and short-wave spectral region and examined their potential for cement probing and the non-invasive monitoring of the hydration processes occurring during cement formation.
UCNPs of different size and chemical composition were synthesized via a thermal decomposition approach under inert conditions. The tailor-made design of different emission patterns was achieved by tuning particle size and morphology, material composition, and particle surface chemistry in upscaleable syntheses. For cement probing, different types of UCNPs were added to cement and the evolution of the UCNP emission pattern was used to probe in-situ changes of physico-chemical parameters in the cementitious environment during hydration, utilizing a simple and portable custom-designed optical setup. The observed changes in the UCNP emission patterns are characteristic for a given particle size, surface chemistry, and cement composition. In addition to fluorescence measurements, conventional isothermal heat flow calorimetry was used to study the influence of UCNP addition on cement hydration kinetics. Subsequently, both sets of measurements were correlated. Our results underline the potential of our optical approach ad UCNPs for the non-invasive probing of cementitious systems and cement hydration. This can be also exploited for cutting-edge applications of construction materials such as 3D concrete printing.
The transformation of a base-catalyzed, mechano-assisted Knoevenagel condensation of mono-fluorinated benzaldehyde derivatives (p-, m-, o-benzaldehyde) with malonodinitrile was investigated in situ and in real time. Upon milling, the para-substituted product was found to crystallize initially into two different polymorphic forms, depending on the quantity of catalyst used. For low catalyst concentrations, a mechanically metastable phase (monoclinic) was initially formed, converting to the mechanically stable phase (triclinic) upon further grinding. Instead, higher catalyst concentrations crystallize directly as the triclinic product. Inclusion of catalyst in the final product, as evidenced by mass spectrometric analysis, suggests this complex polymorphic pathway may be due to seeding effects. Multivariate analysis for the in situ Raman spectra supports this complex formation pathway, and offers a new approach to monitoring multi-phase reactions during ball milling.
Multi-principal element alloys (MPEAs) are gaining interest in corrosion and electrocatalysis research due to their electrochemical stability across a broad pH range and the design flexibility they offer. Using the equimolar CrCoNi alloy, we observe significant metal dissolution in a corrosive electrolyte (0.1 M NaCl, pH 2) concurrently with the oxygen evolution reaction (OER) in the transpassive region despite the absence of hysteresis in polarization curves or other obvious corrosion indicators. We present a characterization scheme to delineate the contribution of OER and alloy dissolution, using scanning electrochemical microscopy (SECM) for OER-onset detection, and quantitative chemical analysis with inductively coupled-mass spectrometry (ICP-MS) and ultraviolet visible light (UV-Vis) spectroscopy to elucidate metal dissolution processes. In-situ electrochemical atomic force microscopy (EC-AFM) revealed that the transpassive metal dissolution on CrCoNi is dominated by intergranular corrosion. These results have significant implications for the stability of MPEAs in corrosion systems, emphasizing the necessity of analytically determining metal ions released from MPEA electrodes into the electrolyte when evaluating Faradaic efficiencies of OER catalysts. The release of transition metal ions not only reduces the Faradaic efficiency of electrolyzers but may also cause poisoning and degradation of membranes in electrochemical reactors.
For years there have been more and more reports on the presence of drugs in the aquatic environment. Due to the demographic change, the consumption of pharmaceuticals has risen sharply. After taking the drugs, they are partly metabolized in the human body. However, the metabolism is not complete so that both the metabolites and non-metabolized amounts of the parent compounds are excreted. These compounds reach the waste water and afterwards the sewage treatment plants. In sewage treatment plants transformation products can be formed by the oxidative conditions during wastewater treatment processes. The transformation products may have a higher toxicity than the actual environmental pollutants and are often only partly removed during the waste water treatment. Since a lot of these compounds are still unknown, the transformation products are not detected by target analysis used in sewage treatment plants and are often released undetected in the aquatic ecosystems. The released substances may be subject to additional transformation processes in the environment. Pharmaceuticals produced in high amounts can be already detected in the μg/L range in water bodies worldwide.
Metformin and its major transformation product guanylurea are one of the main representatives. Metformin is the drug of choice for treating type 2 diabetes. The drug therapy for diabetes mellitus has increased significantly in recent years. In the year 2015 1500 tons of metformin were prescribed in Germany (for statutory insured persons). Metformin is not metabolized in the human body and is excreted unchanged therefore concentrations between 57 μg/L and 129 μg/L are found in German waste water treatment plants influents.
In this work the transformation of the antidiabetic drug metformin is investigated. The degradation of metformin is initialize by commercial water treatment techniques like UV-radiation or noncommercial techniques like heterogenous photocatalysis based on titanium dioxide. The degradation of metformin and resulting transformation products are analyzed by LC-MS/MS and LC-HRMS.
Core-shell (CS) particles have been increasingly used for a wide range of applications due to their unique properties by merging individual characteristics of the core and the shell materials. The functionality of the designed particles is strongly influenced by their surface roughness. Quantitative evaluation of the roughness of CS microparticles is, however, a challenging task for Scanning Electron Microscopy (SEM).
The SEM images contain two-dimensional (2D) information providing contour roughness data only from the projection of the particle in the horizontal plane. This study presents a practical procedure to achieve more information by tilting the sample holder, hence allowing images of different areas of a single particle to be recorded at different orientations under the same view angle. From the analysis of these images, quasi three-dimensional (3D) information is obtained.
Three types of home-made particles were investigated: i) bare polystyrene (PS) particles, ii) PS particles decorated with a first magnetic iron oxide (Fe3O4) nanoparticle shell forming CS microbeads, iii) PS/Fe3O4 particles closed with a second silica (SiO2) shell forming core-shell-shell (CSS) microbeads. A series images of a single particle were taken with stepwise tilted sample holder up to 10° by an SEM with high-resolution and surface sensitive SE-InLens® mode.
A reliable analysis tool has been developed by a script in Python to analyze SEM images automatically and to evaluate profile roughness quantitatively, for individual core-shell microparticles. Image analysis consists of segmentation of the images, identifying contour and the centre of the particle, and extracting the root mean squared roughness value (RMS-RQ) of the contour profile from the particle projection within a few seconds.
The variation in roughness from batch-to-batch was determined with the purpose to set the method as a routine quality check procedure. Flow cytometry measurements provided complementary data. Measurement uncertainties associated to various particle orientations were also estimated.
In this contribution different ways are explored with the aim to generate suitable training data for ‘non-ideal’ samples using various approaches, e.g., computer-generated images or unsupervised learning algorithms such as generative adversarial networks (GANs). We used these data to train simple CNNs to produce segmentation masks of SEM images and tested the trained networks on real SEM images of complex nanoparticle samples. The novel use of CNN for the automated analysis of the size of nanoparticles of complex shape and with a high degree of agglomeration has proved to be a promising tool for the evaluation of particle size distribution on a large number of constituent particles. Further development and validation of the preliminary model, respectively larger training and validation data sets are necessary.
In this contribution different ways are explored with the aim to generate suitable training data for ‘non-ideal’ samples using various approaches, e.g., computer-generated images or unsupervised learning algorithms such as generative adversarial networks (GANs). We used these data to train simple CNNs to produce segmentation masks of SEM images and tested the trained networks on real SEM images of complex nanoparticle samples. The novel use of CNN for the automated analysis of the size of nanoparticles of complex shape and with a high degree of agglomeration has proved to be a promising tool for the evaluation of particle size distribution on a large number of constituent particles. Further development and validation of the preliminary model, respectively larger training and validation data sets are necessary.
Welcome to the poster Towards Determination of Surface Roughness from a SEM Image, a contribution from BAM in Berlin, Germany. This work is part of the MamaLoCA project, which aims to develop a biosensor for the detection of mycotoxins in cereals. Biosensors come in a great variety, one of which makes use of microscopic beads produced by homogenous coating of polystyrene microspheres. The beads are functionalized by decorating them with bioreceptors – in our case antibodies – which then specifically react with the analyte – in our case mycotoxins – and emit an electrical or optical signal. The functionalization of the beads depends on the surface roughness because this determines the amount and orientation of binders. In other words, the surface roughness affects the accessibility to the binding sites and influences device sensitivity, hence its quantitative determination is an important step in evaluating the quality of the biosensor in general.
The presented solution to the problem of the estimation of surface roughness relies in the repetitive characteristics on the surface of the beads. A SEM image of the bead shows a raspberry like microparticle with a variation of grayscale values, which arise from the secondary electron yield. The principle of the measurement measures the variation of grayscale values along a circumference of a circle centred in the centre of the particle and with an arbitrary radius. The grayscale value variation along the given circumference gives the so-called z-modulation or the lateral profile. By performing Fast Fourier Transform on this profile we obtain the power spectrum as a function of the spatial frequencies through which the grayscales vary. The maximal value for spatial frequency then reveals the most common feature along one given circumference. Surface roughness then is the feature frequency in the spatial domain. This calculation is repeated for several concentric circles with different radii over the particle.
The results for the same particle but recorded at two different accelerating voltages show that the applied method has a potential to reveal the roughness. Interpretation of results from an SE InLens SEM image obtained using 3 kV shows that surface roughness is about 21 nm, which is in a good agreement with an alternative method given in a different presentation. The results from the 10 kV are underestimated due to the loss of surface sensitivity on the SE InLens detection at high voltages.
In conclusion, this method shows promise in determining quantitatively the surface roughness from a single SEM image and its validation is being sought using 3D SEM images and AFM methods.
Tour de table - BAM
(2021)
Thermo-Desorption Gas Chromatography-Mass Spectrometry (TD-GC-MS) was used to investigate the thermal degradation of two different polyurethanes (PU). PU samples were heated at different heating rates and the desorbed products were collected in a cold injection system and thereafter submitted to GC-MS. Prospects and limitations of the detection and quantification of semi-volatile degradation products were investigated. A temperature dependent PU depolymerization was
found at temperatures above 200 °C proved by an increasing release of 1,4-butanediol and methylene diphenyl diisocyanate (MDI) representing the main building blocks of both polymers. Their release was monitored quantitatively based on external calibration with authentic compounds. Size Exclusion Chromatography (SEC) of the residues obtained after thermodesorption confirmed the initial competitive degradation mechanism indicating an equilibrium of crosslinking and depolymerization as previously suggested. Matrix-Assisted Laser Desorption Ionization (MALDI) mass spectrometry of SEC fractions of thermally degraded PUs provided additional hints on degradation mechanism.
BAM is currently building up a platform of novel nanoRMs relying on iron oxide nanoparticles of different shape, size and surface chemistry. Iron oxide was chosen as a core material because of its relevance to the material and life sciences.
As a first candidate of this series, we present cubic iron oxide nanoparticles with a nominal edge length of 8 nm. These particles were synthesized by thermal decomposition of iron oleate in high boiling organic solvents adapting well-known literature procedures. After dilution to a concentration suitable for electron microscopy (TEM and SEM) as well as for small-angle X-ray scattering (SAXS) measurements, the candidate nanoRM was bottled and assessed for homogeneity and stability by both methods following the guidelines of ISO 17034 and ISO Guide 35.
The particle sizes obtained by both STEM-in-SEM and TEM are in excellent agreement with a minimum Feret of 8.3 nm ± 0.7 nm. The aspect ratio (AR) of the iron oxide cubes were extracted from the images as the ratio of minimum Feret to Feret resulting in an AR of 1.18 for TEM to 1.25 for SEM. Alternatively, a rectangular bounding box was fitted originating from the minimum Feret and the longest distance through the particle in perpendicular direction. This led to AR values of 1.05 for TEM and 1.12 for SEM, respectively. The results confirm the almost ideal cubic shape.
The Dark Side of Science
(2019)
The Joint Summer School of the two Marie Skłodowska-Curie Innovative Training Networks (ITN) “BioCapture” and “GlycoImaging”, funded by the EU within the Horizon 2020 framework programme, which are both devoted to the development of new methods for cancer biomarker and cancer cell detection, will take place at the Adlershof Campus of BAM. 19 Early stage researchers of both projects will convene, discuss their own science and plan future collaborative research. Training in scientific writing (instructor: Luita Spangler, Free University of Berlin), an employability workshop (Antti Kapanen, University of Applied Sciences Berlin) and first contacts with the “dark side of science” (Brian R. Pauw, BAM) will complement the programme of the summer school.
This work presents the determination of the corrosion characteristics of CrCoNi (medium entropy alloy) and CrMnFeCoNi (high entropy alloy) in 0.1 M NaCl and 0.1 M H2SO4. The morphology and chemical composition of the oxide layers formed on CrCoNi and CrMnFeCoNi were comparatively analyzed by scanning Kelvin probe microscopy (SKPFM) and scanning electron microscopy (SEM) and supported with chemical analysis by means of inductively coupled plasma mass spectrometry (ICP-MS) and X-Ray photoelectron spectroscopy (XPS). The analysis of the 3p core level peaks showed that the oxide layer (native and after anodic passivation) on CrCoNi consisted mainly of Cr oxides, while the oxide layer on CrMnFeCoNi was primarily composed of a mixture of Cr and Fe oxides. In addition, XPS was utilized to assess the oxide layer thicknesses. These results were compared to the thicknesses obtained by means of electrochemical impedance spectroscopy (EIS), with both approaches yielding values up to about 4 nm depending on the electrolyte and the alloy. Cyclic polarization measurements indicated superior corrosion resistance of CrCoNi in both aqueous environments compared to CrMnFeCoNi, as well as to AISI 304 stainless steel.
Zeolitic imidazolate framework (ZIF) hybrid fluorescent nanoparticles and ZIF antibody conjugates have been synthesized, characterized, and employed in lateral-flow immunoassay (LFIA). The bright fluorescence of the conjugates and the possibility to tailor their mobility gives a huge potential for diagnostic assays. An enzyme-linked immunosorbent assay (ELISA) with horseradish peroxidase (HRP) as label, proved the integrity, stability, and dispersibility of the antibody conjugates, LC-MS/MS provided evidence that a covalent link was established between these metal-organic frameworks and lysine residues in IgG antibodies.