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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.
High-resolution absorption isotopic spectrometry as a tool for aging studies of Li-ion batteries
(2022)
Lithium (Li) is the key element in the manufacturing of batteries. Isotopic study of Li may help to identify the causes of battery aging due to isotopic fractionation during charge/discharge cycles.
Isotopic ratio determination is based on monitoring the isotopic components of lithium by their spin-orbit coupling and its isotopic shift of about 15 pm for the 22P←22S electronic transition around 670.788 nm. In this work, we propose improvements to our previous work [1] by using a higher-resolution double echelle modular spectrometer (HR-DEMON II) coupled to a continuum source graphite furnace atomic absorption spectrometer (HR-CS-GF-AAS) for the isotopic analysis of Li.
The data analysis was carried out by using a decision-tree-based ensemble machine learning (ML) algorithm (XGBoost). A set of samples with 6Li isotope amount fractions ranging from 0.0004 to 0.99 mol mol-1 was used for the algorithm's training. Subsequently, the procedure was validated by a set of stock chemicals (Li2CO3, LiNO3, LiCl, and LiOH) and a BAM candidate reference material, a cathode material (NMC111). Finally, the ML model was applied to determine the isotope ratio of geological samples, including anorthosite, granite, soil, rhyolite, nepheline syenite, and basalt and battery samples. These samples were measured as digested without any further purification step.
Improvements in the optical resolution resolve the lithium isotopic components of the atomic spectra. In the studied geological samples, were found δ7Li values between -0.5 and 4.5 ‰ with a precision range of 1 to 2 ‰. In addition, the proposed method was validated with multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS), and these results are comparable and compatible.
In this poster for the SCIX Conference, we apply an analytical procedure based on the monitoring of the lithium isotope through the partially resolved isotope shift in the electronic transition 22P<-22S around wavelength 670.80 nm using high-resolution continuum source atomic absorption spectrometer (HR-CS-AAS) in combination with machine learning (ML) for the determination of Li Isotope ratio analysis.
Chemical and pharmaceutical companies have to find new paths to survive successfully in a changing environment, while also finding more flexible ways of product and process development to bring their products to market more quickly – especially high-quality high-end products like fine chemicals or pharmaceuticals. The potential of digital technologies belongs to these.
A current approach uses flexible and modular chemical production units, which can produce different high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce the time to market of new products. At the same time, we need to move towards knowledge-based production that takes into account all essential equipment, process and control data from plants and laboratories and makes valuable expertise available and transferable. The potential of data from production together with its contextual information is often not yet consistently used today for a comprehensive understanding of production.
By giving examples this paper outlines a possible more holistic approach to digitalisation and the use of machine-based methods in the production of specialty chemicals and pharmaceuticals through the introduction of integrated and networked systems and processes.
Magnesium is a major element in the hydrosphere and biosphere, and it is direct correlated with the carbon cycle. Therefore, the study of its isotopic fractionation in sediments and sea water helps to understand the earth’s climate and global warming. Mg has three stable isotopes, 24Mg, 25Mg and 26Mg, and traditionally isotope amount ratios are measured by mass spectrometric methods. Their drawbacks include the high costs for instruments and their operation, experienced operators and elaborate time-consuming chromatographic sample preparation. Recently, an optical spectrometric method has been proposed as faster and low-cost alternative for the analysis of isotope ratios: high-resolution continuum source graphite furnace molecular absorption spectrometry (HR-CS-GFMAS).
For the determination of Mg isotope ratios in selected rock reference materials, the high-resolution molecular absorption spectrum of in-situ generated MgF molecule was studied applying multivariate analysis and the results compared with MC-ICP-MS. Samples were dissolved by acid digestion and Mg isotopes analyzed with and without matrix extraction. The absorption spectra were recorded for MgF for the electronic transition X 2Σ → B 2Σ+. The MgF spectrum is described as the linear combination of their isotopic components or isotopologues: 24MgF, 25MgF, and 26MgF. The isotope analysis was done by deconvolution of the MgF spectrum by partial least square regression (PLS). A PLS model was built and calibrated with enriched isotope spikes and certified reference materials. Spectra data was preprocessed by a derivate of second order and venetian blinds cross-validation was employed for finding the optimum latent variables. Finally, the model was refined by a genetic algorithm which identified the best subset of variables for a precise and accurate regression. Results are compatible with those obtained by MC-ICP-MS with an accuracy of ± 0.3‰ with uncertainties ranging between 0.02 to 0.6‰. This accuracy and precision discriminate the isotope fractionation in geological samples, and it is suitable for earth’s climate studies.
Society for Applied Spectroscopy (SAS) Atomic Section Student Award.
Magnesium is a major element in the hydrosphere and biosphere and plays important roles in (bio-) geochemical and physiological cycles. Mg has three stable isotopes, 24Mg, 25Mg and 26Mg. It is due to their relatively large mass difference (~8% between) that isotope fractionation leads to slight variations of isotope amount ratios in biological, environmental and geological samples. Traditionally, isotope ratios are measured by mass spectrometric methods. Their drawbacks include the high costs for instruments and their operation, experienced operators and elaborate time-consuming chromatographic sample preparation.
Recently, optical spectrometric methods have been proposed as faster and low-cost alternative for the analysis of isotope ratios of selected elements by means of high-resolution continuum source molecular absorption spectrometry (HR-CS-MAS), and laser ablation molecular isotopic spectrometry (LAMIS).
For the determination of Mg isotope ratios in selected rock reference materials, the molecular spectrum of the in-situ generated MgF and MgO molecules were studied and their results compared with MC-ICP-MS. By HR-CS-MAS, samples were dissolved by acid digestion and Mg isotopes analyzed with and without matrix. The absorption spectrum was recorded for MgF for the electronic transitions X 2Σ → A 2 Πi, and X 2Σ → B 2Σ+. In the case of LAMIS, we investigated the MgF molecule for the electronic transition A 2Πi → X 2Σ, as well as direct analysis by the MgO molecule for the electronic transition A 1Π+ → X 1Σ. The MgF and MgO spectra are described as the linear combination of their isotopic components or isotopologues: 24MgF, 25MgF, and 26MgF for the MgF and 24MgO, 25MgO, and 26MgO for the MgO. The isotope analysis was done by deconvolution of the MgF spectrum by partial least square regression (PLS) calibrated with enriched isotope spikes. Results were accurate with precisions ranging between 0.2 ‰ and 0.8 ‰ (2 SD, n= 10) for HR-CS-GFMAS. No statistically significant differences were observed for samples w/o matrix extraction. On the other hand, LAMIS allows the direct analysis of solid samples with the extended possibility of direct analysis, however the precision is lower due the lack of solid isotopic calibration standards.
Magnesium is a major element in the hydrosphere and biosphere and plays important roles in (bio-) geochemical and physiological cycles. Mg has three stable isotopes, 24Mg, 25Mg and 26Mg. It is due to their relatively large mass difference (~8% between) that isotope fractionation leads to slight variations of isotope amount ratios in biological, environmental and geological samples. Traditionally, isotope amount ratios are measured by mass spectrometric methods. Their drawbacks include the high costs for instruments and their operation, experienced operators and elaborate time-consuming chromatographic sample preparation. Recently, an optical spectrometric method has been proposed as faster and low-cost alternative for the analysis of isotope ratios: high-resolution continuum source graphite furnace molecular absorption spectrometry (HR-CS-GFMAS).
For the determination of Mg isotope ratios in selected rock reference materials, the high-resolution molecular absorption spectrum of in-situ generated MgF molecule was studied applying multivariate analysis and the results compared with MC-ICP-MS. Samples were dissolved by acid digestion and Mg isotopes analyzed with and without matrix. The absorption spectra were recorded for MgF for the electronic transition X 2Σ → B 2Σ+. The MgF spectrum is described as the linear combination of their isotopic components or isotopologues: 24MgF, 25MgF, and 26MgF. The isotope analysis was done by deconvolution of the MgF spectrum by partial least square regression (PLS). A PLS model was built and calibrated with enriched isotope spikes and certified reference materials. Spectra data was preprocessed by a derivate of second order and venetian blinds cross-validation was employed for finding the optimum latent variables. Finally, the model was refined by a genetic algorithm which identified the best subset of variables for a precise and accurate regression. Results are compatible with those obtained by MC-ICP-MS with an accuracy of ± 0.3‰ with uncertainties ranging between 0.02 to 0.6‰.