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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.
Besides conventional scanning X-ray fluorescence imaging at synchrotron sources, full-field X-ray fluorescence (FF-XRF) imaging techniques that do not implicitly require spatial scanning of the sample have become available. FF-XRF has become achievable thanks to the development of a new type of energy dispersive CCD-based 2D detector, also referred to as a 'color X-ray camera (CXC)' or 'SLcam'. We report on different imaging schemes for biological samples using FF-XRF imaging: (a) 2D 'zoom' imaging with pinhole optics using the 'camera obscura' principle; (b) 2D 'fixed magnification' imaging using magnifying polycapillary optics; and (c) 3D-FF-XRF imaging using an X-ray sheet beam or computed tomography (CT). The different FF-XRF imaging modes are illustrated using the crustacean Daphnia magna, a model organism for investigating the effects of metals on organism/ecosystem health, and foraminifera, a class of amoeboid protist. Detailed analytical characterization of the set-up is performed through analyzing various reference materials in order to determine limits of detection (LODs) and sensitivities. Experiments were performed using the BAMline at the BESSY synchrotron (Berlin, Germany) and using the P06 Hard X-ray Microprobe at the PETRAIII synchrotron (Hamburg, Germany).
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.
To better study the impact of nanoparticles on both in vitro and in vivo models, tissue distribution and cellular doses need to be described more closely. Here silver nanoparticles were visualized in alveolar macrophages by means of synchrotron radiation micro X-ray fluorescence spectroscopy (SR-μXRF) with high spatial resolution of 3 × 3 μm2. For the spatial allocation of silver signals to cells and tissue structures, additional elemental labeling was carried out by staining with eosin, which binds to protein and can be detected as bromine signal with SR-μXRF. The method was compatible with immunostaining of macrophage antigens. We found that the silver distribution obtained with SR-μXRF was largely congruent with distribution maps from a subsequent laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) of the same tissue sites. The study shows a predominant, though not exclusive uptake of silver into alveolar macrophages in the rat lung, which can be modeled by a similar uptake in cultured alveolar macrophages. Advantages and limitations of the different strategies for measuring nanoparticle uptake at the single cell level are discussed.
X-ray fluorescence imaging is a well-established tool in materials characterization. In this work, we present the adaption of coded aperture imaging to full-field X-ray fluorescence imaging at the synchrotron. Coded aperture imaging has its origins in astrophysics, and has several advantages: Coded apertures are relatively easy to fabricate, achromatic, allow a high photon throughput, and high angular acceptance. Coded aperture imaging is a two-step-process, consisting of the measurement process and a reconstruction step. Different programs have been written, for the raytracing/forward projection and the reconstruction. Experiments with coded aperture in combination with a Color X-ray Camera and an energy-dispersive area detector, have been conducted at the BAMline. Measured samples were successfully reconstructed, and gave a 9.1-fold increase in count rate compared to a polycapillary optic.
Quantitative Analysis and 2D/3D Elemental Imaging of Cocoa Beans Using X‑ray Fluorescence Techniques
(2023)
As an important raw material for the confectionery industry, the cocoa bean (Theobroma cacao L.) has to meet certain legal requirements in terms of food safety and maximum contaminant levels in order to enter the cocoa market. Understanding the enrichment and distribution of essential minerals but also toxic metals is of utmost importance for improving the nutritional quality of this economically important raw food material. We present three X-ray fluorescence (XRF) techniques for elemental bio-imaging of intact cocoa beans and one additional XRF technique for quantitative analysis of cocoa pellets. The interrelation of all the methods presented gives a detailed picture of the content and 3D-resolved distribution of elements in complete cocoa beans for the first time.
Imaging with X-rays is a challenging field, due to the optical properties of X-rays. The fabrication of appropriate optics is usually expensive and requires an elaborate manufacturing process. One simpler and less expensive possibility of imaging high energy radiation is coded aperture imaging, a technique well established in astrophysics and also used in nuclear medicine or radiation detection, e.g., for nuclear decommissioning. Our aim is to adapt coded aperture imaging for X-ray fluorescence spectroscopy in the nearfield. In this work we show theoretical considerations and preliminary simulations of Image formation through a coded aperture and three different reconstruction methods to prepare the experiments. We used a new mask based on an inverted modified uniformly redundant array (MURA) that could be used for the construction of a decoding mask for all investigated geometrical arrangements.
The most commonly used reconstruction method, convoluting the detected image with a Decoding mask, does not always deliver satisfactory results. This is more noticeable for small distances between the object, mask and detector. Hence, we developed two new reconstruction methods, one based on iterative algebraic optimization and another one based on a genetic algorithm. Both show good performance even in those cases where the convolution method fails. This provides a basis for further investigations of the ideal parameters for near field coded aperture imaging and refinements of the algorithms. We performed first measurements with a coded aperture at the BAMline at BESSY II and could successfully reconstruct a test object from the obtained recorded images.
The present study investigates early stages of ZIF-8 crystallization up to 5 minutes post mixing of precursor solutions. Dispersive X-ray Absorption Spectroscopy (DXAS) provides a refined understanding of the evolution of the coordination environment during ZIF-8 crystallization. Linear Combination Fiting (LCF) suggests tetrakis(1-methylimidazole)zinc2+ to be a suitable and stable mononuclear structure analogue for some early stage ZIF-8 intermediates. Our results pave the way for more detailed studies on physico-chemical aspects of ZIF-8 crystallization to better control tailoring ZIF-8 materials for specific applications.
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.