Chemie und Prozesstechnik
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Paper des Monats
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The entire process involving the determination of Cl by molecular emission detection in Laser-Induced Breakdown Spectroscopy (LIBS) is thoroughly studied in this paper. This critical evaluation considers how spectra are normalized, how interferences from other molecular species signals are removed, and how signal integration is applied. Moreover, a data treatment protocol is proposed to achieve reliable and accurate Cl determination from the CaCl molecular spectral signal, not requiring the use of more complex numerical approaches. Calcium chloride dihydrate (CaCl2⋅2H2O) and high purity anhydrite samples (CaSO4) are used to optimize the acquisition conditions and data treatment of CaCl emission signal. Using the developed protocol, calibration curves for Cl, covering the concentration range from 0 μg/g to 60,000 μg/g of Cl, are successfully achieved. Finally, the suitability of the proposed methodology for Cl determination is successfully applied in industrial gypsum waste samples, where the results obtained by LIBS are validated using high-resolution molecular absorption spectroscopy (HR-CS-MAS) and potentiometric titration.
A series of NaYF4:Yb3+/Tm3+@NaYF4:Yb3+/Er3+ nanoparticles doped with Tm3+ and Er3+ were successfully prepared by the solvothermal method. Under 980 nm laser excitation, intense upconversion emission peaks of Tm3+ and Er3+ were observed for all samples. By doping Tm3+ and Er3+ with core–shell partitioning, not only a significant increase in fluorescence intensity could be achieved, but also simultaneous temperature measurements on multiple thermocouple energy levels could be realised. In addition, the temperature sensing performance of different thermocouple energy levels was also investigated, and it was found that the 3 F3 → 3 H6 and 1 G4 → 3 F4 thermocouple energy level pairs of Tm3+ were the best, with maximum absolute sensitivity and maximum relative sensitivity of up to 0.0250 K−1 and 2.155% K−1 respectively, higher than the sensitivity of other thermocouple energy levels. It has a temperature resolution of less than 0.0139 K, which is lower than that of most materials available today. By using this material as a probe to build a fiber optic temperature sensor platform, it was found to have reliable temperature measurement performance.
Additive manufacturing by laser metal deposition (LMD) requires continuous online monitoring to ensure quality of printed parts. Optical emission spectroscopy (OES) is proposed for the online detection of printing defects by monitoring minute variations in the temperature of a printed spot during laser scan. A two-lens optical system is attached to a moving laser head and focused on a molten pool created on a substrate during LMD. The light emitted by the pool is collected by an ultraviolet–visible (UV–vis) spectrometer and processed.
Two metrics are used to monitor variations in the surface temperature: the spectrally integrated emission intensity and correlation coefficient. The variations in the temperature are introduced by artificial defects, shallow grooves, and holes of various widths and diameters carved on a substrate surface. The metrics show sufficient sensitivity for revealing the surface defects, except for the smallest
holes with an under-millimeter diameter. Additionally, numeric simulations are carried out for the detection of emission in the UV–vis and near-infrared (NIR) spectral ranges at various surface temperatures. It is concluded that both the metrics perform better in the NIR range. In general, this work demonstrates that spectrally resolved OES suits well for monitoring surface defects during 3D metal
printing.
Whereas the characterization of nanomaterials using different analytical techniques is often highly automated and standardized, the sample preparation that precedes it causes a bottleneck in nanomaterial analysis as it is performed manually. Usually, this pretreatment depends on the skills and experience of the analysts. Furthermore, adequate reporting of the sample preparation is often missing. In this overview, some solutions for techniques widely used in nano-analytics to overcome this problem are discussed. Two examples of sample preparation optimization by au-tomation are presented, which demonstrate that this approach is leading to increased analytical confidence. Our first example is motivated by the need to exclude human bias and focuses on the development of automation in sample introduction. To this end, a robotic system has been de-veloped, which can prepare stable and homogeneous nanomaterial suspensions amenable to a variety of well-established analytical methods, such as dynamic light scattering (DLS), small-angle X-ray scattering (SAXS), field-flow fractionation (FFF) or single-particle inductively coupled mass spectrometry (sp-ICP-MS). Our second example addresses biological samples, such as cells exposed to nanomaterials, which are still challenging for reliable analysis. An air–liquid interface has been developed for the exposure of biological samples to nanomaterial-containing aerosols. The system exposes transmission electron microscopy (TEM) grids under reproducible conditions, whilst also allowing characterization of aerosol composition with mass spectrometry. Such an approach enables correlative measurements combining biological with physicochemical analysis. These case studies demonstrate that standardization and automation of sample preparation setups, combined with appropriate measurement processes and data reduction are crucial steps towards more reliable and reproducible data.
Colours, nano and surface
(2022)
The basic ideas of colours and pigments are presented. The correlation between nanomaterials and colours are explained. Different methods are presented for investigating nanoparticles and their surface. At the end a case study is presented explaining the importance of coating for the properties of nanoparticles.
Damage detection of reinforced concrete (RC) structures is becoming a more attractive domain due to the safety issues arising in the last few decades. The damage in concrete can be caused by excessive exploitation of the structure or environmental effects. The cracks in concrete can be detected by different nondestructive testing methods. However, the available methods used for this purpose have numerous limitations. The technologies available in the market nowadays have difficulties detecting slowly progressive, locally limited damage. In addition, some of These methods cannot be applied, especially in hard-to-reach areas in the superstructures. In order to avoid these deficiencies, an embedded ultrasonic methodology can be used to detect cracks in RC structures. In this study, the methodology of crack detection supported with the advanced Signal processing algorithm was proposed and verified on RC structures of various types, and cracks occurring between embedded sensors can be detected. Moreover, different pairs of ultrasonic sensors located in the considered structures are used for the analysis of the sensitivity of distance between them. It is shown that the ultrasonic sensors placed in the range of 1.5–2 m can detect cracks, even when the other methods failed to detect changes in the structure. The obtained results confirmed that diffuse ultrasonic sensor methodology is able to monitor real structures more effectively than traditional techniques.
A facile and efficient methodology is described for the solvothermal synthesis of size-tunable, stable, and uniform NiCu core–shell nanoparticles (NPs) for application in catalysis. The diameter of the NPs is tuned in a range from 6 nm to 30 nm and to adjust the Ni:Cu ratio from 30:1 to 1:1. Furthermore, the influence of different reaction parameters on the final NPs is studied. The NPs are structurally characterized by a method combination of transmission electron microscopy, anomalous small-angle X-ray scattering, X-ray absorption fine structure, and X-ray photoelectron spectroscopy. Using these analytical methods, it is possible to elucidate a core–shell–shell structure of all particles and their chemical composition. In all cases, a depletion from the core to the shell is observed, with the core consisting of NiCu alloy, surrounded by an inner Ni-rich shell and an outer NiO shell. The SiO2-supported NiCu core–shell NPs show pronounced selectivity of >99% for CO in the catalytic reduction of CO2 to CO using hydrogen as reactant (reverse water–gas shift reaction) independent of size and Ni:Cu ratio.
Here, we describe an optimized fast and simple extraction method for the determination of per- and polyfluorinated alkyl substances (PFASs) in soils utilizing high resolution-continuum source-graphite furnace molecular absorption spectrometry (HR–CS–GFMAS). To omit the bias of the solid phase extraction (SPE) step commonly used during the analysis of extractable organically bound fluorine (EOF) we optimized a fast and simple SPE-free extraction method. The developed extraction method consists of a liquid-solid extraction using acidified methanol without any additional SPE. Four extraction steps were representative to determine a high proportion of the EOF (>80% of eight extractions). Comparison of the optimized method with and without an additional SPE clean-up step revealed a drastic underestimation of EOF concentrations using SPE. Differences of up to 94% were observed which were not explainable by coextracted inorganic fluoride. Therefore, not only a more accurate but also a more economic as well as ecologic method (bypassing of unnecessary SPE) was developed. The procedural limit of quantification (LOQ) of the developed method was 10.30 μg/kg which was sufficient for quantifying EOF concentrations in all tested samples. For future PFAS monitoring and potential regulative decisions the herein presented optimized extraction method can offer a valuable contribution.
The influence of solvent polarity and surface ligand rigidification on the SWIR emission profile of gold nanoclusters with an anistropic surface was investigated. A strong enhancement of the SWIR emission band at 1200 nm was observed when measuring in different local environments: in solution, in polymer composites, and in solids. SWIR in vivo imaging of mice assisted by deep learning after intravenous administration of these gold nanoclusters provides high definition pseudo-3D views of vascular blood vessels.