TY - CONF A1 - Maiwald, Michael T1 - Integrated and networked systems and processes – A perspective for digital transformation of our chemical and pharmaceutical production N2 - 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. T2 - GDCh Science Forum 2021 - GDCh Wissenschaftsforum 2021 CY - Online meeting DA - 29.08.2021 KW - Process analytical technology KW - Online NMR spectroscopy KW - Process industry KW - Industry 4.0 KW - Digital transformation KW - Autonomous chemistry PY - 2021 AN - OPUS4-53171 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Abad Andrade, Carlos Enrique T1 - Applications of atomic absorption spectrometry for lithium isotope analysis N2 - 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. T2 - Colloquium Spectroscopicum Internationale XLII (CSI XLII) CY - Gijón, Spain DA - 30.05.2022 KW - Lithium KW - HR-CS-AAS KW - Chemometrics KW - Atomic spectrometry PY - 2022 AN - OPUS4-56498 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Morcillo, Dalia T1 - What we need to know about lithium isotopes in batteries N2 - Flash talk presentation about the relevance of lithium in our lives and its influence on the battery aging process. T2 - Make and Measure Conference SALSA CY - Berlin, Germany DA - 15.09.2022 KW - Lithium isotope KW - Battery KW - Spectroscopy PY - 2022 AN - OPUS4-56360 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Morcillo, Dalia T1 - High-resolution absorption isotopic spectrometry as a tool for aging studies of Li-ion batteries N2 - 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. T2 - Caltech-BAM Meeting CY - Online meeting DA - 10.08.2022 KW - Lithium isotope KW - Machine learning KW - Battery KW - High-resolution absorption isotopic spectrometry PY - 2022 AN - OPUS4-56380 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -