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 - Recknagel, Sebastian A1 - Vogel, Kristin T1 - Berechnung und Nutzung von Unsicherheiten zertifizierter Werte von Referenzmaterialien N2 - Referenzmaterialien sind unter anderem ein wichtiges Werkzeug zur Qualitätskontrolle von Messungen bestimmter Merkmalswerte. Dabei ist zu berücksichtigen, dass zertifizierte Merkmalswerte immer eine gewisse Unsicherheit haben. Die Ermittlung dieser Unsicherheitsbeiträge ist Gegenstand des Vortrags. Referenzmaterialien sind gleichzeitig ein wertvolles Werkzeug zur Ermittlung der Unsicherheit von Messverfahren und -Analysen unbekannter Proben. Die Vorgehensweise bei der Ermittlung der Messunsicherheit mit Hilfe eines Referenzmaterials wird beschrieben. T2 - 11. VDI-Fachtagung Messunsicherheit und Prüfprozesse CY - Erfurt, Germany DA - 14.11.2023 KW - Referenzmaterial KW - Messunsicherheit KW - ISO Guide 35 PY - 2023 AN - OPUS4-58946 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Abad Andrade, Carlos Enrique T1 - Data-Driven Spectrochemical Methods for Elemental and Isotopic Analysis N2 - High-resolution optical spectrometers generate spectra containing tens of thousands of data points per sample. Picometre-scale isotope shifts, matrix-induced line broadening, and strong inter-feature correlations render classical peak fitting unreliable. Current analytical challenges, therefore, require rigorous algorithms able to expose latent structure, quantify uncertainty, and remain chemically interpretable. The research program presented in this lecture integrates state-of-the-art spectrochemical instrumentation with mathematically disciplined data models. Principal Component Analysis and Partial Least Squares provide chemically meaningful latent variables, while gradient-boosted decision trees or deep neural networks (ANNDL) capture residual non-linearity without sacrificing traceability. All models are trained on isotope-enriched or synthetically generated spectra and distributed with full validation workflows. T2 - Chemisches Institutskolloquium, Humboldt-Universität zu Berlin CY - Berlin, Germany DA - 21.05.2025 KW - Spectrochemistry KW - Isotopes KW - Machine learning KW - Battery KW - Data fusion PY - 2025 AN - OPUS4-63488 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Abad Andrade, Carlos Enrique T1 - Data-Driven Spectrochemical Sensing for Elemental and Isotopic Analysis—from Energy Systems to Biomedicine N2 - High-resolution optical spectrometers generate spectra containing tens of thousands of data points per sample. Picometre-scale isotope shifts, matrix-induced line broadening, and strong inter-feature correlations render classical peak fitting unreliable. Current analytical challenges, therefore, require rigorous algorithms able to expose latent structure, quantify uncertainty, and remain chemically interpretable. The research program presented in this lecture integrates state-of-the-art spectrochemical instrumentation with mathematically disciplined data models. Principal Component Analysis and Partial Least Squares provide chemically meaningful latent variables, while gradient-boosted decision trees or deep neural networks (ANNDL) capture residual non-linearity without sacrificing traceability. All models are trained on isotope-enriched or synthetically generated spectra and distributed with full validation workflows. Two research areas illustrate this strategy: (1) Isotopic analytics for materials, environment, and medicine. (2) Data-fusion diagnostics for battery ageing and failure. T2 - Temple University: Mechanical Engineering Transformative Science and Technology Engineering Lecture Series CY - Philadelphia, PA, USA DA - 02.10.2025 KW - Isotope KW - Data analysis KW - Machine learning KW - Elemental analysis KW - Battery PY - 2025 AN - OPUS4-64877 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Abad Andrade, Carlos Enrique T1 - Improvement of manufacturing processes of Li-ion batteries by Glow Discharge Optical Emission Spectroscopy N2 - Manufacturing lithium-ion coin cells (LIBs) for scientific research demands reproducibility, precision, and thorough metrology to ensure consistent quality and performance. Glow-discharge optical emission spectroscopy (GD-OES) emerges as a crucial analytical technique in this context, providing detailed insights into elemental composition and material homogeneity [1,2]. This study focuses on using GD-OES to optimize and standardize the manufacturing processes of LIBs, emphasizing metrology and traceability to develop reproducible and high-quality batteries for research purposes. We refined cell production by adjusting key parameters such as cathode doping, electrolyte concentration, and calendar pressing. GD-OES facilitated depth analysis of elemental composition and distribution, which is essential for identifying and maintaining optimal manufacturing conditions. Validation was achieved through electrochemical impedance spectroscopy (EIS), ensuring the quality and consistency of the manufactured batteries. GD-OES analysis revealed critical insights into elemental uniformity and impurities, guiding adjustments significantly improving cell performance and reproducibility. The method proved fast and effective in detecting and correcting variations in the manufacturing process, leading to enhanced battery quality. To understand the aging mechanisms, GD-OES was employed for fluorine depth profiling, which is crucial for studying polymer and electrolyte degradation. We significantly enhanced fluorine detection sensitivity by substituting the argon plasma with a neon/argon mixture, providing a more accurate aging analysis. By demonstrating the versatility and efficacy of GD-OES in optimizing LIB manufacturing processes and gaining deeper insights into aging mechanisms, this research has significant practical implications. It not only advances lab research but also offers tangible industrial benefits, including improved battery quality, extended lifespan, and enhanced performance. By ensuring metrology and traceability, GD-OES contributes to developing a robust method for the reproducible manufacturing of Li-ion coin cells, boosting innovation and sustainability in battery technology. T2 - SciX 2025 CY - Covington, KY, USA DA - 05.10.2025 KW - GD-OES KW - Battery analysis KW - Depth profile KW - Lithium-ion battery PY - 2025 AN - OPUS4-64878 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Abad Andrade, Carlos Enrique T1 - Isotope analysis through the integration of chemometrics into optical spectroscopy N2 - 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. T2 - Analytica Conference CY - Munich, Germany DA - 09.04.2024 KW - Isotopes KW - HR-CS-MAS KW - Chemometrics KW - Lithium KW - Boron KW - Magnesium KW - Nitrogen PY - 2024 AN - OPUS4-59946 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Abad Andrade, Carlos Enrique T1 - Laser spectroscopy methods for calcium isotope analysis N2 - 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. T2 - Seminars Chemical Physics Caltech CY - Pasadena, CA, USA DA - 13.04.2022 KW - Calcium KW - Atomic spectroscopy KW - CaF KW - Calcium monofluoride KW - Carbon cycle KW - Doppler effect KW - Sub-doppler spectroscopy KW - Laser spectroscopy PY - 2022 AN - OPUS4-56499 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Abad Andrade, Carlos Enrique T1 - On developments of continuum source atomic and molecular absorption spectrometry N2 - 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. T2 - Analytica Conference: Bunsen-Kirchhoff-Preis 2022 der Deutsche Arbeitskreis für Analytische Spektroskopie (DAAS) CY - Munich, Germany DA - 23.06.2022 KW - Isotopes KW - Fluorine KW - Halogens KW - Non-metals KW - HR-CS-MAS KW - HR-CS-AAS KW - Bunsen-Kirchhoff-Preis KW - Continuum source atomic absorption spectrometry KW - Zr-Modifier KW - Graphite furnace KW - Lithium PY - 2022 AN - OPUS4-56500 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Abad Andrade, Carlos Enrique T1 - Optical spectrometry for isotope analysis N2 - Isotope analysis plays a critical role in various disciplines, including environmental science, archaeology, and forensic investigations. Traditional methods such as mass spectrometry provide precise isotopic data but often require complex, costly setups and extensive sample preparation. As an alternative, optical spectrometry has emerged as a versatile and less invasive technique. This presentation explores the advancements and applications of optical spectrometry methods in isotope analysis, emphasizing their benefits and challenges. T2 - University of Calgary PHYS 561 - Stable And Radioactive Isotope - Winter 2024 CY - Online meeting DA - 07.03.2024 KW - Isotopes KW - HR-CS-MAS KW - Chemometrics KW - Laser Ablation Molecular Absorption spectrometry KW - LAMIS PY - 2024 AN - OPUS4-59948 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Abad Andrade, Carlos Enrique T1 - The use of reference materials to improve the calibration strategy in glow discharge optical emission spectroscopy with machine learning N2 - 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. T2 - Winter Conference on Plasma Chemistry 2022 CY - Tucson, AZ, USA DA - 17.01.2022 KW - GDOES KW - Machine learning KW - Reference materials KW - Calibration KW - Cooper PY - 2022 AN - OPUS4-56497 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -