Analytische Chemie
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Lithium exists in two stable isotopes, 6Li and 7Li. The ratio of these in every ore varies depending on the geological history of the sample, thus providing a tool for fingerprinting the distinct origin of Li containing samples. Determination of the exact isotope ratio for e.g. designation of provenance today relies on expensive and bulky instrumentation such as multi `collector inductively coupled plasma mass spectrometry` (MC-ICP-MS). These instruments, however, are known to bear pitfalls in the characterization of particular elements including Lithium. BAM recently developed two alternative analytical devices for this task, solely relying on inexpensive optical spectroscopy in combination with state-of-the-art multivariate data analysis such as Machine learning algorithms. Both techniques have been comprehensively studied using certified reference materials and comparing the results to MC-ICP-MS results and could be shown to result in comparable figures of merit, paving the way for a more general accessibility to provenance determination instrumentation. The results also pave the way towards even further simplification of the laboratory infrastructure demands and to further include additional elements into the isotopic fingerprinting methodology.
An alternative method for lithium isotope amount ratio analysis based on a combination of high-resolution atomic absorption spectrometry and spectral data analysis by machine learning (ML) is proposed herein. It is based on the well-known 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 the state-of-the-art high-resolution continuum source graphite furnace atomic absorption spectrometry. 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, previously determined by a multicollector inductively coupled plasma mass spectrometer (MC-ICP-MS). The calibration ML model was validated with two certified reference materials (LSVEC and IRMM-016). The procedure was applied toward the isotope amount ratio determination of a set of stock chemicals (Li2CO3, LiNO3, LiCl, and LiOH) and a BAM candidate reference material NMC111 (LiNi1/3Mn1/3Co1/3O2), a Li-battery cathode material. The results of 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, as demonstrated for samples ranging from approximately −3 to +15‰. To assess its suitability to technical applications, the NMC111 cathode candidate reference material was analyzed using high-resolution continuum source atomic absorption spectrometry with and without matrix purification. The results obtained were metrologically compatible with each other.
The therapeutic dose of lithium (Li) compounds, which are widely used for the treatment of psychiatric and hematologic disorders, is close to its toxic level; therefore, drug monitoring protocols are mandatory. Herein, we propose a fast, simple, and low-cost analytical procedure for the traceable determination of Li concentration in human serum, based on the monitoring of the Li isotope dilution through the partially resolved isotope shift in its electronic transition around 670.80 nm using a commercially available high-resolution continuum source graphite furnace atomic absorption spectrometer. With this technique, serum samples only require acidic digestion before analysis. The procedure requires three measurements—an enriched 6Li spike, a mixture of a certified standard solution and spike, and a mixture of the sample and spike with a nominal 7Li/6Li ratio of 0.82. Lanthanum has been used as an internal spectral standard for wavelength correction. The 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. Both the spectral constants and the correlation between isotope ratio and relative band intensity have been experimentally obtained using commercially available materials enriched with Li isotopes. The Li characteristic mass (mc) obtained corresponds to 0.6 pg. The procedure has been validated using five human serum certified reference materials. The results are metrologically comparable and compatible to the certified values. The measurement uncertainties are comparable to those obtained by the more complex and expensive technique, isotope dilution mass spectrometry.
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.
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.
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.
Lithium (Li), Boron (B), Nitrogen (N), Magnesium (Mg), and Calcium (Ca) are pivotal elements across various spheres such as the hydrosphere, biosphere, and lithosphere, significantly impacting (bio-) geochemical and physiological processes. These elements exhibit stable isotopes with substantial roles in geological, environmental, and biological studies. The traditional method for measuring isotope amount ratios has been through mass spectrometry, which, despite its accuracy, comes with high operational costs, the need for skilled operators, and time-consuming sample preparation processes.
Combining optical spectroscopy with chemometrics introduces an innovative, cost-effective approach by the hand of high-resolution continuum source atomic and molecular absorption spectrometry (HR-CS-AAS and HR-CS-MAS) for the analysis of isotope ratios in Li, B, N, Mg, and Ca. By analyzing the atomic or molecular absorption spectrum of the in-situ generated cloud of atoms of diatomic molecules (e.g., Li, BH, NO, MgF, CaF) during the electronic transition from the fundamental state, this method allows for the rapid determination of isotope ratios directly from sample solutions without the need for complex sample preparation.
For each element, the respective atomic or molecule's absorption spectrum was deconvoluted into its isotopic components using partial least squares regression or machine learning algorithms. Robust calibration models were developed, calibrated with enriched isotope, and validated against certified reference materials. Spectral data underwent preprocessing to optimize the modeling to determine the optimal number of latent variables.
The findings showcase that this optical spectrometric method yields results that agree with those obtained via inductively coupled plasma mass spectrometry (ICP-MS), offering a promising, cost-effective, and rapid alternative for isotope analysis with precisions as low as ± 0.2‰. This approach is a significant advancement in analytical chemistry, providing a new way to study isotope variations in biological, environmental, and geological samples.
What does GD-OES reveal about the aging and manufacturing processes of lithium-ion batteries?
(2024)
Glow-Discharge Optical Emission Spectroscopy (GD-OES), a powerful analytical technique, sheds light on the two critical aspects of lithium-ion batteries (LIBs): manufacturing and aging 1, 2. We optimized cell production in manufacturing by adjusting parameters, including cathode doping, electrolyte concentration, and pressing force. GD-OES provided in-depth elemental composition and homogeneity analysis, which is crucial for identifying optimal manufacturing conditions. These findings were validated by electrochemical impedance spectroscopy, confirming the quality of the manufactured batteries.
Shifting the focus to aging, we use GD-OES for fluorine depth profiling, a key element in understanding polymer and electrolyte degradation. However, fluorine presents analytical challenges. We addressed this by substituting argon with a neon:argon mixture, which significantly enhanced fluorine detection sensitivity. This advancement not only improves accuracy but also holds the potential to guide sustainable and cost-efficient manufacturing strategies.
Through its versatility, GD-OES has proven to be a powerful tool for not only optimizing LIB manufacturing processes but also gaining deeper insights into their aging mechanisms. This research extends beyond academic interest, offering tangible benefits for the industry by translating into improved battery quality, extended lifespan, and overall performance.