Chemische Charakterisierung und Spurenanalytik
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Mechanochemistry is a fast and efficient method applicable for the synthesis of new organic, metal-organic, and inorganic compounds. The direct monitoring of milling reactions is still challenging. The underlying reaction mechanisms often remain unclear. In the last years, we have established a tandem in situ approach for investigating mechanochemical reactions using time-resolved in situ XRD coupled with Raman spectroscopy. A further development is the in situ coupling of synchrotron XRD, Raman spectroscopy, and thermography allowing the observation of mechanochemical reactions in real time. [5] Information on the crystalline, molecular, and temperature state of the materials during grinding could be collected. The chemical composition of the reaction mixture was found to be directly correlated with changes in the temperature profile of the reaction. Furthermore, the presented setup allows the detection of crystalline, amorphous, eutectic as well as liquid intermediates. Based on these data, metastable polymorphs of cocrystals and coordination polymorphs could be isolated and struc-turally characterized. A multi-step diffusion mechanism was identified for most systems. Crystalline phases were obtained intermediately, suggesting that the synthesis is following Ostwald’s rules of stages. The resulting deeper kinetic and thermodynamic understanding of milling processes is the key for future optimization of mechanochemical syntheses.
MALDI time-of-flight mass spectrometry (MALDI-TOF MS) has become a widely used tool for the classification of biological samples. The complex chemical composition of pollen grains leads to highly specific, fingerprint-like mass spectra, with respect to the pollen species. Beyond the species-specific composition, the variances in pollen chemistry can be hierarchically structured, including the level of different populations, of environmental conditions or different genotypes. We demonstrate here the sensitivity of MALDI-TOF MS regarding the adaption of the chemical composition of three Poaceae (grass) pollen for different populations of parent plants by analyzing the mass spectra with partial least squares discriminant analysis (PLS-DA) and principal component analysis (PCA). Thereby, variances in species, population and specific growth conditions of the plants were observed simultaneously. In particular, the chemical pattern revealed by the MALDI spectra enabled discrimination of the different populations of one species. Specifically, the role of environmental changes and their effect on the pollen chemistry of three different grass species is discussed. Analysis of the Group formation within the respective populations showed a varying influence of plant genotype on the classification, depending on the species, and permits conclusions regarding the respective rigidity or plasticity towards environmental changes.
Synchrotron radiation sources with their unique properties in terms of intensity, polarization and adjustability offer a wide range of possibilities in materials research. A basic introduction about the creation and special properties of synchrotron radiation will be given. Examples of current work at BAMline, the high-energy measuring facility of the Federal Institute for Materials Research and Testing at the synchrotron BESSY, are used to illustrate the possibilities and limitations of existing measuring methods. It will be shown how the formation of corrosion layers can be tracked, how the abrasion of implants leads to the introduction of heavy metals into the surrounding bone matrix and how the detection of smallest impurities in gold is possible by optimizing the measuring conditions. Finally, an outlook at the hardware and software developments to be expected in the coming years is given.
The comparison required the assignment of the mass fraction of folic acid present as the main component in the comparison sample. Performance in the comparison is representative of a laboratory's measurement capability for the purity assignment of organic compounds of medium structural complexity [molecular weight range 300–500] and high polarity (pKOW < −2).
Methods used by the eighteen participating NMIs or DIs were based on a mass balance (summation of impurities) or qNMR approach, or the combination of data obtained using both methods. The qNMR results tended to give slightly lower values for the content of folic acid, albeit with larger associated uncertainties, compared with the results obtained by mass balance procedures. Possible reasons for this divergence are discussed in the report, without reaching a definitive conclusion as to their origin.
The comparison demonstrates that for a structurally complex polar organic compound containing a high water content and presenting a number of additional analytical challenges, the assignment of the mass fraction content property value of the main component can reasonably be achieved with an associated relative standard uncertainty in the assigned value of 0.5%
The characterization of a catalyst often occurs by averaging over large areas of the catalyst material. On the other hand, optical probing is easily achieved at a resolution at the micrometer scale, specifically in microspectroscopy. Here, using surface-enhanced Raman scattering (SERS) mapping of larger areas with micrometer-sized spots that contain tens to hundreds of supported gold nanoparticles each, the photoinduced dimerization of p-aminothiophenol (PATP) to 4,4′-dimercaptoazobenzene (DMAB) was monitored. The mapping data reveal an inhomogeneous distribution of catalytic activity in the plasmon-catalyzed reaction in spite of a very homogeneous plasmonic enhancement of the optical signals in SERS. The results lead to the conclusion that only a fraction of the nanostructures may be responsible for a high catalytic activity. The high spot-to-spot variation in catalytic activity is also demonstrated for DMAB formation by the plasmon-catalyzed reduction from p-nitrothiophenol (PNTP) and confirms that an improvement of the accuracy and reproducibility in the characterization of catalytic reactions can be achieved by microspectroscopic probing of many positions. Using SERS micromapping during the incubation of PATP, we demonstrate that the reaction occurs during the incubation process and is influenced by different parameters, leading to the conclusion of dimerization in a gold-catalyzed, nonphotochemical reaction as an alternative to the plasmon-catalyzed process. The results have implications for the future characterization of new catalyst materials as well as for optical sensing using plasmonic materials.
Various applications for artificial intelligence in the context of spectroscopy will be presented. in particular, examples from BAMline will be presented. After a short introduction to synchrotron radiation, artificial intelligence algorithms for the quantification of X-ray fluorescence measurement are discussed. In the second example, information retrieval by natural language processing is discussed.
In X-ray fluorescence (XRF), a sample is excited with X-rays, and the resulting characteristic radiation is detected to detect elements quantitatively and qualitatively. Quantification is traditionally done in several steps:
1. Normalization of the data
2. Determination of the existing elements
3. Fit of the measured spectrum
4. Calculation of concentrations with fundamental parameters / MC simulations / standard based
The problem with standard based procedures is the availability of corresponding standards. The problem with the calculations is that the measured intensities for XRF measurements are matrix-dependent. Calculations must, therefore, be performed iteratively (= time consuming) in order to determine the chemical composition.
First experiments with gold samples have shown the feasibility of machine learning based quantification in principle. A large number of compositions were simulated (> 10000) and analyzed with a deep learning network. For first experiments, an ANN (Artificial Neural Network) with 3 hidden layers and 33x33x33 neurons was used. This network learned the mapping of spectra to concentrations using supervised learning by multidimensional regression. The input layer was formed by the normalized spectrum, and the output layer directly yielded the searched values. The applicability for real samples was shown by measurements on certified reference materials.
In this talk I’ll describe the use of artificial neural networks (ANN) for quantifying X-ray fluorescence (XRF) measurements. The main idea of this talk is to give an overview of the process needed to generate a model that can then be applied to a specific problem.
In XRF, a sample is excited with X-rays and the resulting characteristic radiation is detected to determine elements quantitatively and qualitatively. This is traditionally done in several time-consuming steps. I’ll show the possibilities and problems of using a neural network to realise a "one-click" quantification. This includes generating training data using Monte Carlo simulation and augmenting the existing data set with an ANN to generate more data. The search for the optimal hyperparameters, manually and automatically, is also described. For the case presented, we were able to train a network with a mean absolute error of 0.1% by weight for the synthetic data and 0.7% by weight for a set of experimental data obtained with certified reference materials.
In this work, we describe the use of artificial neural networks for the quantification of X-ray fluorescence measurements. The training data were generated using Monte Carlo simulation, which avoided the use of adapted reference materials. The extension of the available data set by means of an ANN to generate additional data was demonstrated. Particular emphasis was put on the comparability of simulated and experimental data and how the influence of deviations can be reduced. The search for the optimal hyperparameter, manual and automatic, is also described. For the presented case, we were able to train a network with a mean absolute error of 0.1 weight percent for the synthetic data and 0.7 weight percent for a set of experimental data obtained with certified reference materials.
Die Probenpräparation ist ein wichtiger Schritt für die Qualität der Massenspektren in MALDI-TOF MS. Es werden Polymerproben, die lösungsmittelbasiert und lösungsmittelfrei präpariert worden sind, verglichen. Dabei werden die Intensitätsverhältnisse von ternären Mischungen von PEG-, PS- und PMMA-Polymeren beachtet.
A set of 59 ancient magical artefacts, mainly made of lead, was selected from the collections of the Staatliche Museen zu Berlin in order to unravel their origins. All the selected artefacts have been studied for their Pb isotope compositions, which covered the whole range of the Mediterranean ore deposits. However, the majority (≈86%) were made of lead matching the small compositional range of the Laurion ore deposits. Only eight out of the 59 artefacts were made of recycled lead or lead from other ore deposits.
Additionally, all but two were approximately dated based on their inscriptions. The lead isotopic composition together with information obtained from the inscriptions, the resulting dating, the context of the find and the known history of each item allowed us to gain more detailed information about the origins of these magical artefacts. The Attic provenance of 36 curse tablets was confirmed, whereas for 11 curse tablets previously classified as non-Attic, the provenance was either confirmed and specified (six artefacts) or changed to Attic (five artefacts). Surprisingly, the majority (six out of eight) of the analysed curse tablets from the Egyptian collection showed a lead isotopic composition closely matching that of Laurion.
A Laurion-like lead isotopic composition was also observed for three of the four analysed oracular tablets from Dodona. Together with the dating information, this points to Laurion as the major and dominant lead source in the Aegean, at least during the fourth–third century B.C. The few curse tablets from earlier than the fourth–third century B.C. point to the use of multiple and thus isotopically more variable lead sources compared with the Roman times.
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.
The vanadium redox flow battery (VRFB) is currently a potential candidate for stationary energy storage. A major challenge is the unintended vanadium transport through the separator, which results in a fade of capacity. To overcome this issue, it is necessary to understand the transport processes in the membrane on a more fundamental level. In this work, the vanadium species distribution in Nafion™ 117 after cyclization was investigated. Two membranes, one from a charged VRFB and another from a discharged VRFB, were analyzed using ultraviolet–visible spectroscopy (UV/VIS) and X-ray absorption near edge structure spectroscopy (XANES). Little difference between the two membranes was recognizable according to the UV/VIS results. In comparison, the XANES results showed that the membrane from the charged VRFB contains more V3+ than VO2+, whereas for the discharged case, more VO2+ is present in the membrane.
Vanadium redoxflow batteries (VRFB)are currently one of the most promising candidates for stationary energys torage.For large scale applications the ion conducting membranes currently in use need to be improved. Ideally,they need to become more cost efficient and selective regarding the vanadium crossover.For a better understanding of the vanadium crossover, the development of reliable analytical methods and procedures, that elucidate uptake and transport of vanadium ions in the membrane, is necessary. First, we present the uptake of V2+,V3+,VO2+, VO2+ and V2O33+ in Nafion™ and in a novel membrane based onpoly(1,1-difluoroethylene)(PVDF). In preliminary discharge/charge experiments the ETFE-based membrane, the precursor of PVDF-based membrane, performed comparable to Nafion™. The methods of choice for speciation are UV/Vis and X-ray absorption near edge structure spectroscopy (XANES). According to the results, V2O33+, formed from VO2+ and VO2+, diffuses also into the membrane. In present models, the diffusion of V2O33+ is neglected. In addition,we study whether reactions could take place inside the membranes’ nanoscopic water body using XANES. Exposing Nafion™ from one site with V3+a nd from the other site with VO2+ realized the experiment. The results verified that VO2+ was formed inside the membrane. However,in present models reactions inside the membrane are neglected, too.
Confocal Micro X-ray fluorescence analysis (μXRF) is a powerful method for the destruction-free investigation of the elemental composition of various samples in three dimensions. Quantitative results rely heavily on the transmission properties of polycapillary optics, used in confocal setups.
Different models for the functional correlation between energy and transmission of a polycapillary half-lens are compared with experimental data, established with a monochromatic confocal laboratory setup [1], as well as Monte-Carlo-Simulations [2]. The effect of the different approaches on quantitative results are compared using well known SRMs, ranging from thick samples to thin layers and structured materials.
Along with this the basic principles for quantitative evaluations of XRF spectra taken with confocal setups are presented, and compared with experimental results.
The electrocatalytic conversion of water into molecular hydrogen and oxygen under the utilization of excess renewable energies, such as wind power, photovoltaics and hydroelectric power is one possible pathway to establish a sustainable hydrogen economy. The obtained hydrogen is either stored and used in a fuel cell or consumed on-site in industrial applications.
Water electrolysis systems (WES) are based on two half cell reactions, such as oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) which both proceed simultaneously. The OER suffers from slow reaction kinetics and thus limits the overall performance.
The most promising compounds in acidic electrolysis are IrO2 and RuO2. Due to their rare abundance and extremely high price a wide use of acidic WES was prevented. Lowering the catalysts noble metal content by mixing iridium with titanium reduces the production costs.
Thin films are produced by dip coating a solution of metal oxide precursors alongside with a polymer template dissolved in ethanol. The obtained samples are subsequently calcined to the remove the template and adjust crystallinity. Finally, an additional iridium deposition step was performed on the outer surface plane area.
Understanding the influence of structural and morphological aspects on the OER-activity is beneficial to further optimize WES. The current presentation will thus give detailed insights to structural aspects obtained by Raman spectroscopy, small- and wide-angle X-ray scattering which are then combined with electrochemical parameters to deduce structure-activity relationships.
This contribution provides an overview of the BAMline synchrotron radiation beamline, which specializes in hard X-ray spectroscopy techniques for materials research. The BAMline offers X-ray absorption spectroscopy (XAS), x-ray fluorescence spectroscopy (XRF), and tomography to study materials' electronic structure, chemical composition, and structure. Key capabilities include standard and dispersive XAS for electronic structure, micro-XRF for elemental mapping, coded aperture imaging, and depth-resolved grazing exit XAS. The BAMline enables in situ characterization during materials synthesis and functions for energy, catalysis, corrosion, biology, and cultural heritage applications.
Ongoing developments like the implementation of machine learning techniques for experiment optimization and data analysis will be discussed. For instance, Bayesian optimization is being used to improve beamline alignment and scanning. An outlook to the future, where the BAMline will continue pioneering dynamic and multi-scale characterization, aided by advanced data science methods, to provide unique insights into materials research, will be given.