Chemische Charakterisierung und Spurenanalytik
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Paper des Monats
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We investigated the performance of nitrogen microwave inductively coupled atmospheric-pressure plasma mass spectrometry (MICAP-MS) under matrix effects and its applicability to trace element analysis in steels. Influences of different gas flows and ion optics on the matrix tolerance are studied, indicating that nebulizer gas flow has the most significant impact. Optimization of ion optics improves matrix tolerance for light elements due to the reduction of the inelastic collisional scattering effect. With optimized operating conditions, MICAP-MS achieves an internal standard intensity recovery of over 90% at an Fe concentration of 500 mg L−1. Even at an Fe concentration of 1 g L−1, the recovery remains above 80%. Three certified reference materials – non-alloy, low-alloy and high-alloy steel – were analyzed using MICAP-MS. The determined mass concentrations of the trace and minor components show metrological compatibility to the reference values. No significant differences are observed between the results obtained with aqueous and matrix-matched calibration, demonstrating the strong matrix tolerance of MICAP-MS, and its promising applicability to steel analysis.
In this work, we employed glow discharge optical emission spectrometry (GD-OES) depth profiling as a fast and semi-quantitative method to investigate the aluminum (Al) current collector degradation in commercial lithium cobalt oxide (LCO) pouch cells with no Al2O3 pretreatment. After battery aging, a heterogeneous deposit was found on the surface of the cathode. Gray hotspot areas within an extensive pale white region were formed. Consistent with energy dispersive X-ray (EDX) analysis of micro-cross sections milled via targeted focused ion beam (FIB), an Al-containing layer of approximately 3 µm can be observed using GD-OES. We attribute one main cause of this layer is the degradation of the Al current collector. The nonuniform growth of this layer was investigated by performing GD-OES depth profiling at different in-plane positions. We found that the gray area has a higher mass concentration of Al, probably in metallic form, whereas the white area was probably covered more homogeneously with Al2O3, resulting from the inhomogeneous distribution of the pitting positions on the current collector. Compared to FIB-EDX, GD-OES enables a faster and more convenient depth profile analysis, which allows the more productive characterization of lithium-ion batteries (LIBs), and consequently benefits the development of preferable battery materials.
This work aimed to evaluate high-resolution continuum source molecular absorption spectrometry (HR-CS MAS), traditionally used to determine non-metals, for the determination of a new element, metal, vanadium. VO was selected as a target molecule because it is relatively stable and was expected to be spontaneously generated in a flame or a graphite furnace (GF). The high-resolution overview spectra of the molecule were obtained in a wide range of 480–630 nm, and absorption due to the X4Σ−–C4Σ− electronic transition was registered. A unique instrumental setup, comprising a prototype Modular Simultaneous Echelle Spectrograph (MOSES) and a commercial HR-CS MAS apparatus, was applied in the research. Finally, the spectral area centered at 550.6230 nm was selected for analysis. A method was developed to determine V in solutions of catalysts of heavy petroleum oil hydroprocessing using a commercial HR-CS spectrometer in a flame version. Although sensitivity was relatively poor (characteristic concentration 380 mg L−1), an extremely low noise enabled reaching a satisfactory detection limit (20 mg L−1 in solution, i.e. 0.1% m:m in the catalyst). For the first time vanadium was determined using ordinary air-acetylene flame. The obtained results were consistent with the results of atomic absorption spectrometry with N2O-C2H2 flame. Unfortunately, only a small population of VO molecules could have been generated in GF measurements. Furthermore, the observed VO molecules appeared only at unfavorably high temperatures. The work shows the potential of HR-CS MAS as a scientific tool for investigating the mechanism of processes occurring in the GF. This work can inspire other research of new analytes for HR-CS MAS.
Der Bunsen-Kirchhoff-Preis 2022 wurde am 23.06.2022 anlässlich der analytica conference in München an Dr. Carlos Abad verliehen - in Anerkennung seiner exzellenten Entwicklungen im Bereich der continuum source atomic absorption spectrometry (CS-AAS).
Dr. Carlos Abad ist ein herausragender Experte auf dem Gebiet der Atom- und molekularen Absorptionsspektrometrie. insbesondere trug er maßgeblich zur substanziellen Weiterentwicklung von Echelle-Spektrometern für die CS-AAS bei. So gelang es, einen quantitativen Zugang zu Elementen wie Bor, Chlor, Fluor und Schwefel, mittels AAS zu erreichen. Erstmals demonstriert Dr. Carlos Abad am Beispiel eines Zr-Modifier, dass durch die Zeitauflösung der eingesetzten Echelle-Systeme mechanistische Untersuchungen zur Wirkung des Modifiers im Graphitrohrofen möglich sind.
Besonders hervorzuheben sind seine Arbeiten zum Einsatz der CS-AAS für die Analyse von Isotopen, die eine Genauigkeit aufweist, welche an die der Multikollektor-induktiv gekoppelten Plasma-Massenspektrometrie (MC-ICP-MS) heranreicht. Damit ergeben sich völlig neue Einsatzmöglichkeiten für technologisch hochrelevante Applikationen, wie z.B. die Untersuchung der Alterung von Lithium-Batterien oder die Lithium-Analyse in Blutserum.
Calcium isotope analysis can be an important tool for paleoclimate studies of the carbon cycle, as well in carbon capture technology, but its utility is limited by challenges using conventional mass spectrometry. We propose a new fast, precise, and high-throughput technology based on multiple complementary high-resolution spectroscopies analyzed by machine-learning.
An alternative method for lithium isotope analysis by using high-resolution atomic absorption spectrometry (HR-CS-AAS) is proposed herein. This method is based on monitoring the isotope shift of approximately 15 pm for the electronic transition 22P←22S at around the wavelength of 670.8 nm, which can be measured by state-of-the-art HR-CS-AAS. Isotope analysis can be used for (i) the traceable determination of Li concentration and (ii) isotope amount ratio analysis based on a combination of HR-CS-AAS and spectral data analysis by machine learning (ML).
In the first case, the Li spectra are described as the linear superposition of the contributions of the respective isotopes, each consisting of a spin-orbit doublet, which can be expressed as Gaussian components with constant spectral position and width and different relative intensity, reflecting the isotope ratio in the sample. Precision was further improved by using lanthanum as internal spectral standard. The procedure has been validated using human serum-certified reference materials. The results are metrologically comparable and compatible with the certified values.
In the second case, for isotope amount ratio analysis, a scalable tree boosting ML algorithm (XGBoost) was employed and calibrated using a set of samples with 6Li isotope amount fractions ranging from 0.06 to 0.99 mol mol−1. The training ML model was validated with certified reference materials. The procedure was applied to the isotope amount ratio determination of a set of stock chemicals and a BAM candidate reference material NMC111 (LiNi1/3Mn1/3Co1/3O2), a Li-battery cathode material. These determinations were compared with those obtained by MC-ICP-MS and found to be metrologically comparable and compatible. The residual bias was −1.8‰, and the precision obtained ranged from 1.9‰ to 6.2‰. This precision was sufficient to resolve naturally occurring variations. The NMC111 cathode candidate reference material was analyzed using high-resolution continuum source atomic absorption spectrometry with and without matrix purification to assess its suitability for technical applications. The results obtained were metrologically compatible with each other.
Glow discharge optical emission spectroscopy (GD-OES) is a technique for the analysis of solids such as metals, semiconductors, and ceramics. A low-pressure glow discharge plasma is applied in this system, which ‘sputters’ and promotes the sample atoms to a higher energy state. When the atoms return to their ground state, they emit light with characteristic wavelengths, which a spectrometer can detect. Thus, GD-OES combines the advantages of ICP-OES with solid sampling techniques, which enables it to determine the bulk elemental composition and depth profiles. However, direct solid sampling methods such as glow-discharge spectroscopy require reference materials for calibration due to the strong matrix effect.
Reference materials are essential when the accuracy and reliability of measurement results need to be guaranteed to generate confidence in the analysis. These materials are frequently used to determine measurement uncertainty, validate methods, suitability testing, and quality assurance. In addition, they guarantee that measurement results can be compared to recognized reference values. Unfortunately, the availability of certified reference materials suited to calibrate all elements in different matrix materials is limited. Therefore various calibration strategies and the preparation of traceable matrix-matched calibration standards will be discussed.
Machine learning is an essential component of the growing field of data science. Through statistical methods, algorithms are trained to make classifications or predictions, uncovering key insights within data mining projects. Therefore, it was tried in our work to combine GD-OES with machine learning strategies to establish a new and robust calibration model, which can be used to identify the elemental composition and concentration of metals from a single spectrum. For this purpose, copper reference materials from different manufacturers, which contain various impurity elements, were investigated using GD-OES. The obtained spectra information are evaluated with different algorithms (e.g., gradient boosting and artificial neural networks), and the results are compared and discussed in detail.
Isotope analysis is a tool for material research. For example, it may provide information about the provenance of a sample or changes in dynamic systems. Here is presented optical spectroscopy as an analytical alternative to mass spectrometry for isotope quantification based on the isotopic shift of atoms and diatomic molecules.
In this study, we employed nitrogen microwave inductively coupled atmospheric-pressure plasma (MICAP) combined with quadrupole mass spectrometry (MS) and a liquid sample introduction system to analyze heavy metals in soils. The vanadium, cobalt, nickel, zinc, copper, chromium, arsenic, lead, and cadmium contents in seven reference and three environmental soil samples determined using MICAP-MS were within the uncertainty of the reference values, indicating that MICAP-MS is promising for soil analysis similar to the conventional inductively coupled plasma mass spectrometry (ICP-MS) technique. In addition, the limits of detection (LODs) and sensitivity of both techniques using N2 and Ar plasma were of the same order of magnitude. Furthermore, the performance of MICAP-MS under different N2 purity was investigated, and we found that the plasma formation and ionization efficiency were not influenced by the impurities in the gas. A prominent advantage of MICAP-MS is the low operating cost associated with gas consumption. In this work, MICAP-MS used nitrogen, which is cheaper than argon, and consumed 25% less gas than ICP-MS. Using low-purity N2 can further reduce the gas cost, making MICAP-MS more cost effective than ICP-MS. These results suggest that MICAP-MS is a promising alternative to ICP-MS for the analysis of heavy metals in the soil.
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.