Academic literature on the topic 'Lithium quantification'
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Journal articles on the topic "Lithium quantification"
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Paul, Partha P., Vivek Thampy, Chuntian Cao, Hans-Georg Steinrück, Tanvir R. Tanim, Alison R. Dunlop, Eric J. Dufek, et al. "Correction: Quantification of heterogeneous, irreversible lithium plating in extreme fast charging of lithium-ion batteries." Energy & Environmental Science 14, no. 9 (2021): 5097. http://dx.doi.org/10.1039/d1ee90049h.
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Correction for ‘Quantification of heterogeneous, irreversible lithium plating in extreme fast charging of lithium-ion batteries’ by Partha P. Paul et al., Energy Environ. Sci., 2021, DOI: 10.1039/d1ee01216a.
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Vikrant, K. S. N., Eric McShane, Andrew M. Colclasure, Bryan D. McCloskey, and Srikanth Allu. "Quantification of Dead Lithium on Graphite Anode under Fast Charging Conditions." Journal of The Electrochemical Society 169, no. 4 (April 1, 2022): 040520. http://dx.doi.org/10.1149/1945-7111/ac61d3.
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A series of computational and experimental studies were conducted to understand the onset of lithium plating and subsequent quantification of dead lithium on graphite electrodes in the design of fast charging batteries. The experiments include titration and relaxation studies for detecting initiation of lithium metal plating for various SOC and C-rates, which are compared against the thermodynamically consistent phase field computational results. The collaborative study on “model graphite electrode” with 2.18 mAh cm−2 nominal capacity at 25 °C demonstrates: (1) the macroscopic voltage response during relaxation studies indicate the reintercalation of plated lithium into the graphite anode; (2) for SOC below 60% and low C–Rates, there is no dead lithium; (3) for SOC between 60% to 80%, and C-Rates in the range of 4C–6C show dead lithium both in experiments and simulations.; (4) at 100% SOC and 4C–6C rates, large amounts of dead lithium are observed. The study presented here allows us to evaluate the effects of the physical properties of the electrochemical system on plating and stripping kinetics and the amount of dead lithium on graphite electrodes, which determines the cell capacity loss under fast charge.
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Zhou, Hanwei, Conner Fear, Tapesh Joshi, Judith Jeevarajan, and Partha P. Mukherjee. "Interplay of Lithium Plating Quantification on Thermal Safety Characteristics of Lithium-Ion Batteries." ECS Meeting Abstracts MA2022-02, no. 3 (October 9, 2022): 349. http://dx.doi.org/10.1149/ma2022-023349mtgabs.
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Adverse lithium plating is a significant side reaction during the fast charging of lithium-ion (Li-ion) batteries when the Li-ion flux exceeds the intercalation or diffusion limits of graphite electrodes. Accurate quantification of lithium plating has always been a tough challenge given the severe defects of online detection methods such as coulombic efficiency and voltage relaxation plateau, making the mathematical correlation between cell-level thermal safety hazards and quantitative lithium plating events still a bottleneck problem. In this study, we apply a three-electrode (3E) Li-ion cell configuration and the accelerating rate calorimeter (ARC) to comprehensively investigate the interplay of unfavorable lithium plating on thermal runaway characteristics of Li-ion batteries. Lithium plating is introduced by cycling 3E Li-ion cells at low temperatures and quantified by analyzing potential-based plating energy, coulombic inefficiency, internal resistance, and voltage relaxation plateau. Surface microscopic characterization is carried out on graphite electrodes to reveal the morphologies and chemical states of lithium deposition. ARC experiments are implemented at full-cell and partial-cell scales to fundamentally understand the effects and contributions of thermally unstable lithium plating to the overall safety performance of Li-ion cell chemistries.
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Kraft, Vadim, Waldemar Weber, Benjamin Streipert, Ralf Wagner, Carola Schultz, Martin Winter, and Sascha Nowak. "Qualitative and quantitative investigation of organophosphates in an electrochemically and thermally treated lithium hexafluorophosphate-based lithium ion battery electrolyte by a developed liquid chromatography-tandem quadrupole mass spectrometry method." RSC Advances 6, no. 1 (2016): 8–17. http://dx.doi.org/10.1039/c5ra23624j.
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The work focused on the development of a new liquid chromatography-tandem quadrupole mass spectrometry method for the identification and quantification of organophosphates in lithium hexafluorophosphate-based lithium ion battery electrolytes.
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Dagger, Tim, Jonas Henschel, Babak Rad, Constantin Lürenbaum, Falko M. Schappacher, Martin Winter, and Sascha Nowak. "Investigating the lithium ion battery electrolyte additive tris (2,2,2-trifluoroethyl) phosphite by gas chromatography with a flame ionization detector (GC-FID)." RSC Advances 7, no. 84 (2017): 53048–55. http://dx.doi.org/10.1039/c7ra09476k.
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The quantification of lithium ion battery electrolyte additives like flame retardants is both important and challenging. Here, different analytical methods were applied to investigate detection phenomena when applying GC-FID for the quantification.
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Rangarajan, Sobana P., Yevgen Barsukov, and Partha P. Mukherjee. "In operando signature and quantification of lithium plating." Journal of Materials Chemistry A 7, no. 36 (2019): 20683–95. http://dx.doi.org/10.1039/c9ta07314k.
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Portillo, F. E., J. A. Liendo, A. C. González, D. D. Caussyn, N. R. Fletcher, O. A. Momotyuk, B. T. Roeder, et al. "Light element quantification by lithium elastic scattering." Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 305 (June 2013): 16–21. http://dx.doi.org/10.1016/j.nimb.2013.04.049.
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Kpetemey, Amen, Sanonka Tchegueni, Magnoudéwa Bassaï Bodjona, Koffi Agbégnigan Degbe, Koffi Kili, Gado Tchangbedji, and Rachid Idouhli. "Quantification of Recoverable Components of Spent Lithium-Ion Batteries." Oriental Journal Of Chemistry 39, no. 4 (August 30, 2023): 925–32. http://dx.doi.org/10.13005/ojc/390414.
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Recovering spent lithium-ion batteries can help protect the environment and generate added value. The aim of this work is to characterize the various parts of these spent lithium-ion batteries for subsequent recovery of the precious metal elements. The batteries were collected, electrically discharged and dismantled, and the various components quantified. The cathode powder obtained after basic leaching was characterized by ICP and XRD. The batteries consist of steel (21.10%) and plastic shells, the anode (24.40%), the electrolyte-soaked separator and the cathode (35.86%). The anode consists of graphite deposited on a copper foil representing 15.15% of its weight, and the cathode of aluminum foil (3.93%) and lithium cobalt oxide. Physico-chemical characterization of the cathode powder yielded CoO (65.30%), Li2O (5.39%), MnO (15.78%) and NiO (2.17%). At the end of this study, we note the presence of precious metals, on which our subsequent recovery work will focus.
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Bao, Wurigumula, and Ying Shirley Meng. "(Invited) Development and Application of Titration Gas Chromatography in Elucidating the Behavior of Anode in Lithium Batteries." ECS Meeting Abstracts MA2023-01, no. 2 (August 28, 2023): 633. http://dx.doi.org/10.1149/ma2023-012633mtgabs.
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The accelerated transition to renewable energy systems worldwide has triggered increasing interest in energy storage technologies, especially in lithium batteries. Accurate diagnosis and understanding of the batteries degradation mechanism are essential. Titration Gas Chromatography (TGC) has been developed to quantitively understand the anode. The inactive Li in the cycled anode can be categorized into two kinds: 1) trapped Li0 (such as trapped lithiated graphite (LixC6), Li0, and lithium silicon alloy (LixSi)) and 2) solid electrolyte interphase (SEI) Li+. Noted that only trapped Li0 can react with the protic solvent to generate the hydrogen (H2), while SEI (Li+) does not1. Therefore, the H2 gas quantification can be correlated to the trapped Li0 as the foundation mechanism of TGC. With the optimal solvent selection, we successfully applied TGC to investigated: 1) the degradation behavior of Si-based anode materials2, 3; 2) corrosion effects on electrochemically deposited Li metal anode4; 3) the cycling behavior of Gr anode; 4) Li inventory quantification in practical Li metal battery5. We demonstrate the various application of TGC techniques in quantitatively examining the Li inventory changes of the anode. Beyond that, the results can provide unique insights into identifying the critical bottlenecks that facilitate battery performance development. References: Fang, C.; Li, J.; Zhang, M.; Zhang, Y.; Yang, F.; Lee, J. Z.; Lee, M. H.; Alvarado, J.; Schroeder, M. A.; Yang, Y.; Lu, B.; Williams, N.; Ceja, M.; Yang, L.; Cai, M.; Gu, J.; Xu, K.; Wang, X.; Meng, Y. S., Quantifying inactive lithium in lithium metal batteries. Nature 2019, 572 (7770), 511-515. Bao, W.; Fang, C.; Cheng, D.; Zhang, Y.; Lu, B.; Tan, D. H.; Shimizu, R.; Sreenarayanan, B.; Bai, S.; Li, W., Quantifying lithium loss in amorphous silicon thin-film anodes via titration-gas chromatography. Cell Reports Physical Science 2021, 2 (10), 100597. Sreenarayanan, B.; Tan, D. H.; Bai, S.; Li, W.; Bao, W.; Meng, Y. S., Quantification of lithium inventory loss in micro silicon anode via titration-gas chromatography. Journal of Power Sources 2022, 531, 231327. Lu, B.; Li, W.; Cheng, D.; Bhamwala, B.; Ceja, M.; Bao, W.; Fang, C.; Meng, Y. S., Suppressing chemical corrosions of lithium metal anodes. Advanced Energy Materials 2022, 2202012. Deng, W.; Yin, X.; Bao, W.; Zhou, X.; Hu, Z.; He, B.; Qiu, B.; Meng, Y. S.; Liu, Z., Quantification of reversible and irreversible lithium in practical lithium-metal batteries. Nature Energy 2022, 7 (11), 1031-1041.
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Konz, Zachary M., Brendan M. Wirtz, Andrew M. Colclasure, Ankit Verma, Matthew J. Crafton, Tzu-Yang Huang, and Bryan D. McCloskey. "High-Throughput Lithium Plating Quantification for Fast Charging Battery Design." ECS Meeting Abstracts MA2023-01, no. 2 (August 28, 2023): 503. http://dx.doi.org/10.1149/ma2023-012503mtgabs.
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Fast charging of most commercial lithium-ion batteries is limited due to fear of lithium plating on the graphite anode, which is difficult to detect and poses significant safety risk. Here we demonstrate the power of simple, accessible, and high-throughput cycling techniques to quantify irreversible Li plating spanning data from over 100 cells. We first demonstrate a protocol for Li|Graphite half-cells to observe the effects of energy density, charge rate, temperature, and State-of-Charge (SOC) on lithium plating and provide an interpretable empirical equation for predicting the plating onset SOC. We then design a method to quantify in-situ Li plating for commercially relevant Graphite|LiNi0.5Mn0.3Co0.2O2 (NMC) cells and compare with results from the experimentally convenient Li|Graphite configuration. Ex-situ mass spectrometry titration is used to validate the in-situ analysis methods. This work showcases innovative testing methods and data processing that enable rapid battery engineering.
Dissertations / Theses on the topic "Lithium quantification"
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Larvaron, Benjamin. "Modeling battery health degradation with uncertainty quantification." Electronic Thesis or Diss., Université de Lorraine, 2024. http://www.theses.fr/2024LORR0028.
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Face au changement climatique, des mesures importantes doivent être prise pour décarboner l’économie. Cela inclus une transformation des secteurs du transport et de la production d’énergie. Ces transformations augmentent l’utilisation d’énergie électrique et posent la question du stockage notamment grâce aux batteries Lithium-ion. Dans cette thèse nous nous intéressons à la modélisation de la dégradation de la santé des batteries. Afin de quantifier les risques associés aux garantis de performance, les incertitudes doivent être prise en compte. La dégradation est un phénomène complexe mettant en jeux différents mécanismes physiques en interaction. Celle-ci va varier selon le type de batterie ou de conditions d’utilisation. Nous avons tout d’abord considéré le problème de la dégradation temporelle à une condition expérimentale de référence, par une approche « data-driven » par processus gaussiens. Cette approche présente l’avantage de permettre l’apprentissage de modèles complexes tout en incluant une quantification des incertitudes. Partant de l’état de l’art, nous avons proposé une adaptation de la régression par processus gaussien. Par un design de noyaux adapté le modèle permet de prendre explicitement en compte la variabilité de performance entre les batteries. Cependant, la régression par processus Gaussien repose généralement sur une hypothèse de stationnarité, trop restrictive pour prendre en compte l’évolution de l’incertitude au cours du temps. Nous avons donc exploité le cadre plus général de la régression par processus gaussiens chaînés, reposant sur l’inférence variationnelle. Avec un choix adapté de fonction de vraisemblance, ce cadre permet d’ajuster un modèle non paramétrique de l’évolution de la variabilité entre batteries, améliorant significativement la quantification des incertitudes. Cela produit un modèle satisfaisant aux cycles observés mais se généralise mal pour prédire l’évolution future de la dégradation avec des comportements incohérents d’un point de vue physique. En particulier, la monotonie et la concavité des courbes de dégradations ne sont pas toujours respectées. Nous avons proposé une approche, pour inclure ces contraintes dans la régression par processus gaussiens chaînés. Cela nous a ainsi permis d’améliorer les prévisions à un horizon de plusieurs centaines de cycles, permettant potentiellement de réduire le temps de test nécessaire des batteries, source de coûts importants pour les manufacturiers. Nous avons ensuite élargi le problème afin de prendre en compte l’effet des conditions expérimentales sur la dégradation des batteries. Nous avons tout d’abord tenté d’adapter les méthodes à base de processus gaussien en incluant les facteurs expérimentaux comme variables explicatives. Cette approche a fourni des résultats intéressants dans des cas de conditions avec des dégradations similaires. Cependant pour des conditions plus complexes les résultats deviennent incohérents avec les connaissances physiques et ne sont plus exploitables. Nous avons donc proposé une autre approche, en deux temps, séparant l’évolution temporelle de l’effet des facteurs. Dans un premier temps l’évolution temporelle est modélisée par les méthodes par processus gaussien précédentes. Le second temps, plus complexe, utilise les résultats de l’étape précédente, des distributions gaussiennes, pour apprendre un modèle des conditions expérimentales. Cela nécessite une approche de régression sur données complexes. Nous proposons l’utilisation des barycentres conditionnels de Wasserstein, bien adapté au cas des distributions. Deux modèles sont introduits. Le premier, utilisant le cadre de la régression structurée, permet d’inclure un modèle physique de la dégradation. Le second, utilisant la régression Fréchet, permet d’améliorer les résultats en interpolant les conditions expérimentales et en permettant la prise en compte de plusieurs facteurs expérimentauxWith the acceleration of climate change, significant measures must be taken to decarbonize the economy. This includes a transformation of the transportation and energy production sectors. These changes increase the use of electrical energy and raise the need for storage, particularly through Lithium-ion batteries.In this thesis, we focus on modeling battery health degradation. To quantify the risks associated with performance guarantees, uncertainties must be taken into account. Degradation is a complex phenomenon involving various interacting physical mechanisms. It varies depending on the battery type and usage conditions. We first addressed the issue of the temporal degradation under a reference experimental condition using a data-driven approach based on Gaussian processes. This approach allows for learning complex models while incorporating uncertainty quantification. Building upon the state-of-the art, we proposed an adaptation of Gaussian process regression. By designing appropriate kernels, the model explicitly considers performance variability among batteries. However, Gaussian process regression generally relies on a stationarity assumption, which is too restrictive to account for uncertainty evolution over time. Therefore, we have leveraged the broader framework of chained Gaussian process regression, based on variational inference. With a suitable choice of likelihood function, this framework allows for adjusting a non-parametric model of the evolution of the variability among batteries, significantly improving uncertainty quantification. While this approach yields a model that fits observed cycles well, it does not generalize effectively to predict future degradation with consistent physical behaviors. Specifically, monotonicity and concavity of degradation curves are not always preserved. To address this, we proposed an approach to incorporate these constraints into chained Gaussian process regression. As a result, we have enhanced predictions over several hundred cycles, potentially reducing the necessary battery testing time—a significant cost for manufacturers. We then expanded the problem to account for the effect of experimental conditions on battery degradation. Initially, we attempted to adapt Gaussian process-based methods by including experimental factors as additional explanatory variables. This approach yielded interesting results in cases with similar degradation conditions. However, for more complex settings, the results became inconsistent with physical knowledge and were no longer usable. As a result, we proposed an alternative two-step approach, separating the temporal evolution from the effect of factors. In the first step, temporal evolution was modeled using the previously mentioned Gaussian process methods. The second, more complex step utilized the results from the previous stage—Gaussian distributions—to learn a model of experimental conditions. This required a regression approach for complex data. We suggest using Wasserstein conditional barycenters, which are well-suited for distribution cases. Two models were introduced. The first model, within the structured regression framework, incorporates a physical degradation model. The second model, using Fréchet regression, improves results by interpolating experimental conditions and accounting for multiple experimental factors
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Schweizer, Pia. "Analyse et quantification du lithium par le développement d'un dispositif innovant de spectrométrie et microanalyse X." Electronic Thesis or Diss., Sorbonne université, 2024. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2024SORUS207.pdf.
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L'analyse quantitative du lithium est aujourd'hui possible, mais repose sur l'usage de techniques destructives. Une analyse quantitative locale non-destructive est encore difficile à mettre en œuvre par les méthodes spectroscopiques classiques de laboratoire. Cette thèse vise à développer un dispositif innovant de quantification du lithium par microsonde électronique. L'implémentation d'une multicouche périodique et de fenêtres de séparation ultra fines dans un spectromètre de la microsonde de Castaing a permis la spectrométrie dans la gamme des très faibles énergies de photons X et ainsi la mesure du lithium. Malgré les difficultés qui compliquent fortement l'analyse, principalement liées aux spécificités de l'instrumentation et aux divers phénomènes physiques tels que le faible rendement de fluorescence du lithium et la forte absorption des photons caractéristiques dans l'échantillon, des premiers résultats quantitatifs ont pu être obtenus pour différents matériaux avec des fractions massiques en lithium comprises entre 4 % et 9 %. Ces résultats conduisent à des limites de détection inférieures à un pourcent. Différentes approches de quantification basées sur une mesure avec des témoins réels et sur des simulations Monte Carlo pour créer des témoins virtuels ont été mises en place. De plus, la mesure expérimentale des coefficients d'atténuation des photons dans la gamme des très faibles énergies a permis d'apporter des précisions aux bases de données existantes pour différents éléments, contribuant ainsi à l'amélioration de la précision des résultats. Malgré les défis persistants, ces travaux ouvrent la voie à de nouvelles avancées dans la quantification du lithium par microsonde électronique et constituent une première étape importante pour un futur développement de cette techniqueQuantitative analysis of lithium is feasible today, but relies on the use of destructive techniques. Local non-destructive quantitative analysis remains challenging using traditional laboratory spectroscopic methods. The aim of this thesis is to develop an innovative device for lithium quantification using electron probe microanalysis. By implementing a periodic multilayer and ultra-thin separation windows into the spectrometer of a Castaing microprobe, spectroscopy in the extreme low photon energy range, including Li K measurement was possible. Despite the significant analytical challenges, mainly linked to the specificities of the instrumentation and to various physical phenomena such as low lithium fluorescence yield and strong absorption of the characteristic photons in the sample, quantitative results were obtained for different materials with lithium mass fractions ranging from 4 % to 9 % and detection limits lower than one percent. Two different quantification approaches based on measurement with real standards and Monte Carlo simulations to create virtual standards were employed. In addition, experimental measurement of photon attenuation coefficients in the ultra-soft X-ray range provided precision to existing databases for different elements, helping to improve the accuracy of results. Despite persistent challenges, this work paves the way for further advances in lithium quantification by electron probe microanalysis and represents an important first step towards future development of this technique
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Xiong, Bao Kou. "Quantification des gaz générés lors du fonctionnement d'une batterie Li-ion : effet des conditions opératoires et rôle de l'électrolyte." Thesis, Tours, 2018. http://www.theses.fr/2018TOUR4003/document.
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Le fonctionnement des batteries lithium-ion, qu’il soit normal ou dans des conditions abusives, est accompagné d’une génération de gaz en particulier lors des premiers cycles. Celle-ci est intrinsèque au dispositif et est soumise à de nombreux paramètres tels que les matériaux d’électrodes utilisés, l’électrolyte ou encore les conditions opératoires. Cette génération de gaz est délétère : elle conduit à l’augmentation de la pression interne des batteries et pose donc des problèmes de sécurité. Cette étude vise à quantifier les volumes de gaz générés et à comprendre les mécanismes liés à la surpression dans les batteries. A cet effet, le format de batterie « pouch cell » a été adopté tout au long de ce travail de thèse. L’électrolyte choisi est le mélange EC:PC:3DMC + 1 mol.L-1 LiPF6. La première partie de ce travail est dédiée à la mise au point d’un protocole expérimental basé sur (i) l’analyse des matériaux d’électrodes (NMC, LFP, Gr, et LTO), (ii) la solubilité de gaz (O2, H2) comparées à (CO2, CH4) par PVT, et (iii) la quantification des volumes de gaz générés durant le cyclage en pouch cell, corrélée aux performances électrochimiques. Une analyse préalable en demi-piles et en dispositifs complets Gr//NMC et LTO//LFP a également été réalisée afin d’anticiper les performances attendues en pouch cells. Une analyse critique des données (de la littérature et de nos mesures) a permis de définir une procédure optimisée pour obtenir des résultats reproductibles et comparables lors des mesures de volume en pouch cells. La seconde partie de cette thèse consiste en la quantification du volume de gaz produit au cours du cyclage des pouch cells Gr//NMC, Gr//LFP, LTO//LFP et LTO//NMC. Ainsi, les tensions de fin de charge, l’effet du sel et de la température ont été discutés pour dégager les paramètres déterminants dans la génération de gaz en particulier lors de la formation de la SEI. Enfin, une analyse de la composition du gaz récupéré a été effectué par GC-MS et FTIR. A partir de résultats obtenus, des mécanismes ont été proposés et discutésThe functioning of lithium-ion batteries, may it be under normal use or under abusive conditions, is accompanied by gas generation, especially during the first cycles. This extent of gas generation is dependent on the choice of electrode materials, the electrolyte, and the operating conditions. This gas generation is detrimental: the build-up of pressure leads to the over-pressure in the battery, raising serious concerns. This study is aimed at understanding the fundamental mechanisms governing these reactions. To do so, the « pouch cell » configuration was adopted throughout this thesis. The electrolyte we worked on is the mixture EC:PC:3DMC + 1 mol.L-1 LiPF6. The first chapter of this work is dedicated to development of an experimental protocol based on (i) the analysis of the electrodes materials (NMC, LFP, Gr and LTO), (ii) the gas solubilities (O2, H2) compared to (CO2, CH4) by PVT method, and (iii) the quantification of the volume of generated gases during the cycling of pouch cells which was correlated to the electrochemical performances. A preliminary analysis of half-cells and full cells Gr//NMC and LTO//LFP were also conducted to foresee the performances of the pouch cells. A critical analysis of data taken from the literature and from our own experiments enabled the optimization of a proper procedure to get reproducible and comparable results. The second part of this thesis consists in the quantification of the volume of gases generated during the cycling of Gr//NMC, Gr//LFP, LTO//LFP and LTO//NMC pouch cells. In that respect, the voltages of the end of charge and the effect of salt and of temperature were discussed to figure out the essential parameters in the gas generation and in particular during the formation of SEI. Lastly, a compositional analysis of gases was performed using GC-MS and FTIR. Based on those results, a mechanism is proposed and discussed herein
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Zhang, Yuanci. "Performance and ageing quantification of electrochemical energy storage elements for aeronautical usage." Thesis, Bordeaux, 2019. http://www.theses.fr/2019BORD0029/document.
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Dans un contexte de progression du stockage d’énergie sous forme électrochimique dans les transports, notamment dans l’aéronautique, les problématiques de performance, de fiabilité, de sureté de fonctionnement et de durée de vie du stockeur sont essentielles pour utilisateurs. Cette thèse se focalise ces voltes pour l’avion plus électrique. Les technologies étudiées correspondent à des éléments commerciaux de dernière génération de type Lithium-ion (NMC/graphite+SiO, NCA/graphite, LFP/graphite, NMC/LTO), Lithium-Soufre (Li-S), supercondensateur et hybride (LiC). Une première partie de ce manuscrit s’attache à la quantification des performances des différents éléments dans l’environnement aéronautique [-20°C, 55°C] et pour l’usage aéronautique. Un modèle comportemental de type électro-thermique est développé et validé. La seconde partie est consacrée à la quantification du vieillissement des différents éléments. Les résultats de vieillissement calendaire et en cyclage actif sont présentés ainsi que ceux des tests abusifs. Une méthode d’estimation de l’état de santé (SOH) des éléments basés sur l’analyse de la capacité incrémentale (ICA) est proposée. Enfin, l’évaluation de la robustesse des éléments de stockage lors de tests de vieillissement accéléré avec un profil spécifique à l’usage aéronautique est proposé. Les modèles de vieillissement et la méthode d'estimation de SOH proposés précédemment sont utilisés ici pour évaluer l'impact de la température sur la vitesse de dégradation et pour estimer le SOH des cellules vieillies à l’aide de ce profil aéronautiqueIn the context of progress in the electrochemical energy storage systems in the transport field, especially in the aeronautics, the issues of performance, reliability, safety and robustness of these elements are essential for users. This thesis is focused on these issues for the more electric aircraft. The technologies studied correspond to the latest generation commercial elements of Lithium-ion batteries (NMC/ graphite + SiO, NCA/graphite, LFP/graphite, NMC/LTO), Lithium-Sulfur (Li-S), Supercapacitor and Lithium-ion capacitors. The first part of this manuscript is dedicated to the performance quantification of the different electrochemical energy storage elements in aeronautical environment [-20°C, 55°C] and usage. An efficient and accurate electro-thermal model is developed and validated. The second part is devoted to the calendar and power cycling ageings as well as to the presentation of abuse testing results. A State Of Health (SOH) estimation based on incremental capacity analysis method is proposed. Finally, the robustness of the storage elements during accelerated ageing tests with a specific profile for the aeronautical usage is evaluated. The ageing models and SOH estimation methods proposed in the previous sections are used here to evaluate the impact of temperature on the degradation rate and to estimate the SOH of the cells with this aeronautical profile
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Stout, Jacques. "Spectroscopie et Imagerie RMN multi-noyaux à très haut champ magnétique." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLS312/document.
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Le trouble bipolaire est un trouble de l'humeur récurrent affectant de 1 à 3% de la population adulte à travers le monde et ayant une comorbidité importante avec une hausse du taux de suicides, l'abus de drogues et d'autres troubles médicaux. Ce trouble semble avoir plusieurs liens avec la schizophrénie et une vulnérabilité au trouble est souvent héréditaire dans une famille. Même si les causes biologiques n'ont pas encore été établies, de nombreuses anomalies dans le système limbique sous-cortical et la zone préfrontal ont été observés.Depuis sa découverte il y a plus d'un demi-siècle, une prise de sels de Lithium a été le traitement le plus fiable, mais l'action biochimique du Lithium sur le cerveau et le pourquoi de l'efficacité du traitement reste un mystère. Afin de pouvoir mieux comprendre cet effet, nous avons développé des séquences d'imagerie du Lithium-7 via résonance magnétique à 7 et 17 Tesla afin de pouvoir établir sa distribution et concentration cérébrale. Spécifiquement, j'ai travaillé sur le développement et la validation des méthodes d'acquisition, de reconstruction et de quantification de notre protocole. Ces méthodes ont d'abord été appliqués afin d'étudier la distribution cérébrale du Lithium sur des cerveaux de rats ex-vivo. Ces rats étés traités pendant 28 jours avec du Li2CO3, sacrifiés et leurs têtes fixés avec du PFA. En utilisant une antenne surfacique double canaux 1H/7Li fait maison, une acquisition 7Li Turbo Spin echo et une méthode de remplacement par fantôme pour la quantification, nous avons pu mesurer les cartes de concentration du Lithium. Les concentrations moyennes obtenus dans des régions d’intérêt prédéfinis ont été mesurés afin de les comparer avec les résultats obtenus par spectrométrie de masse.Après cette étude préclinique qui a permis de valider notre approche, un protocole similaire fut créé pour une étude in-vivo 7Li d'imagerie par résonance magnétique chez des patients bipolaires euthymiques sur un scanner 7T. Ces individus ont tous suivis un traitement régulier de Lithium. Pour cette étude, nous avons utilisé une séquence Steady State Free Precession à TE ultra-court et avec un échantillonnage du k-space non-cartésien. Un pipeline de quantification et d'analyse similaire à celle utilisé pour notre étude préclinique fut appliqué pour cette étude, avec l'ajout d'une étape de correction pour les inhomogénéités de B0. Après avoir fait une analyse statistique au niveau de toute la cohorte par régions d'intérêt, il a été observé que l'hippocampe gauche, une part majeur du système limbique associé au trouble bipolaire à de multiples occasions, possède systématiquement une haute concentration de Lithium. Finalement, la méthode de quantification fut modifiée en quantification bi-compartimentale afin de prendre en compte les différences dans les taux de relaxation du Lithium dans le CSF et dans le parenchyme du cerveau. Cette méthode fut appliqué afin de pouvoir quantifier le Lithium à 7T dans un sous-groupe des patients bipolaires et radicalement réduire les différences initialement observés entre les séquences SSFP et bSSFPBipolar disorder is a chronic affective disorder affecting 1 to 3% of the adult population worldwide and has a high level of comorbidity with suicide rates, substance abuse and other harmful conditions. The disorder has possible ties to schizophrenia and has been observed to have a strong genetic component. The exact biological underpinnings have not been firmly established, however abnormalities in limbic subcortical and prefrontal areas have been observed.Ever since its discovery more than half a century ago, a daily intake of Lithium salts has arguably become the most reliable treatment of the disorder, despite us possessing little to no understanding of its biochemical action. In order to shed some light on the effect of Lithium in the brain, we have developed Lithium-7 MR imaging at 7 and 17 Tesla in order to assess its cerebral concentration and distribution. Specifically, I worked on developing and validating several acquisition, reconstruction and quantification methods dedicated to 7Li MRI and MRS. Those methods were first applied to study ex vivo the cerebral distribution of lithium in rats. These rats were pretreated for 28 days with Li2CO3, sacrificed and their head fixated with PFA. Using a home-made 1H/7Li radiofrequency surface coil and a 7Li Turbo Spin echo acquisition and a modified phantom replacement method for quantification, we were able to measure Li concentration maps. Regional Li concentration values were then compared with those obtained with mass spectrometry.After this preclinical proof-of-concept study, an in vivo 7Li MRI protocol was designed to map the cerebral Li concentration in euthymic bipolar subjects at 7T. These individuals all followed a regular lithium treatment. For this study, we chose to use an ultra-short echo-time Steady State Free Precession sequence with non-Cartesian k-space sampling. A quantification and analysis pipeline similar to the one used for our preclinical study was applied for this study, with the addition of a correction step for B0 inhomogeneities. After conducting a statistical analysis at the cohort level, it was assessed that the left hippocampus, a major part of the limbic system that has been associated with BD on multiple occasions, exhibited systematically a high level of lithium. Finally, I developed a quantification method accounting for the different relaxation times of 7Li in the CSF and in the brain parenchyma. This method was applied to image lithium at 7T in a subset of bipolar patients reducing drastically the differences initially observed between the SSFP and bSSFP sequences
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Wetjen, Morten [Verfasser], Hubert A. [Akademischer Betreuer] Gasteiger, Bastian [Gutachter] Märkisch, Andreas [Gutachter] Hintennach, and Hubert A. [Gutachter] Gasteiger. "Studies on the Differentiation and Quantification of Degradation Phenomena in Silicon-Graphite Anodes for Lithium-Ion Batteries / Morten Wetjen ; Gutachter: Bastian Märkisch, Andreas Hintennach, Hubert A. Gasteiger ; Betreuer: Hubert A. Gasteiger." München : Universitätsbibliothek der TU München, 2018. http://d-nb.info/1191897168/34.
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Mertens, Andreas, Shicheng Yu, Deniz C. Gunduz, Hermann Tempel, Roland Schierholz, Hans Kungl, Josef Granwehr, and Rüdiger-A. Eichel. "Impedance-Spectroscopic Quantification of High Bulk Ionic Conductivity in Li1.3Al0.3Ti1.7(PO4)3 Solid Electrolyte." 2017. https://ul.qucosa.de/id/qucosa%3A31608.
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Evans, Adrian A. "On the importance of blind testing in archaeological science: the example from lithic functional studies." 2014. http://hdl.handle.net/10454/9838.
Full textAbstract:
YesBlind-testing is an important tool that should be used by all analytical fields as an approach for validating method. Several fields do this well outside of archaeological science. It is unfortunate that many applied methods do not have a strong underpinning built on, what should be considered necessary, blind-testing. Historically lithic microwear analysis has been subjected to such testing, the results of which stirred considerable debate. However, putting this aside, it is argued here that the tests have not been adequately exploited. Too much attention has been focused on basic results and the implications of those rather than using the tests as a powerful tool to improve the method. Here the tests are revisited and reviewed in a new light. This approach is used to highlight specific areas of methodological weakness that can be targeted by developmental research. It illustrates the value in having a large dataset of consistently designed blind-tests in method evaluation and suggests that fields such as lithic microwear analysis would greatly benefit from such testing. Opportunity is also taken to discuss recent developments in quantitative methods within lithic functional studies and how such techniques might integrate with current practices.
Books on the topic "Lithium quantification"
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St-Onge, Véronique A. Quantification of hippocampal damage in the lithium-pilocarpine model of epilepsy using different post-seizure drugs and behavioral correlates. Sudbury, Ont: Laurentian University, 2006.
Find full textBook chapters on the topic "Lithium quantification"
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Stemp, W. James, and Danielle A. Macdonald. "Chapter 5. Diversity and Lithic Microwear: Quantification, Classification, and Standardization." In Defining and Measuring Diversity in Archaeology, 97–124. Berghahn Books, 2022. http://dx.doi.org/10.1515/9781800734302-008.
Full textConference papers on the topic "Lithium quantification"
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Guibert, Alexandre, Álvaro Díaz-Flores, Anirban Chaudhuri, and H. Alicia Kim. "Multifidelity Uncertainty Quantification in Battery Performance for eVTOL Flights Under Material and Loading Uncertainties." In Vertical Flight Society 80th Annual Forum & Technology Display, 1–8. The Vertical Flight Society, 2024. http://dx.doi.org/10.4050/f-0080-2024-1167.
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This study addresses safety concerns within the rapidly evolving Electric Vertical Takeoff and Landing (eVTOL) aircraft domain, focusing on efficient tools to quantify uncertainties in lithium-ion battery behavior - a critical aspect of eVTOL. One major issue with quantifying uncertainty is the prohibitive computational cost associated with many queries of an expensive-to-evaluate computational model. This work employs three physics-based battery models models of varying fidelity and cost to estimate the mean and the variance of the selected quantities of interest through a multifidelity method to reduce the computation cost. By combining information from multiple cheaper, lower-fidelity models through the Multifidelity Monte Carlo method, we significantly reduce the number of high-fidelity samples required for a prescribed mean-squared error, consequently reducing computational costs down to a tractable level. The proposed methodology is applied to estimate the mean and the variance of the battery temperature and voltage, accounting for uncertainties in flight conditions and materials. The first example focuses on a 580-second flight and is benchmarked against a standard Monte Carlo sampling technique. Results indicate a notable fourfold speed-up using the Multifidelity Monte Carlo method compared to the standard Monte Carlo method for the same mean-squared error for the voltage estimate. To showcase the method's generality, the multifidelity method is then applied to a longer flight of 3580 seconds for estimating the mean and the variance and utilizing these statistics to approximately estimate the probability of the flight completion. This demonstrates the adaptability of the methodology to various power profiles and considered uncertainties, with potential extensions to any battery chemistry. In conclusion, the presented multifidelity method offers a robust approach to enhance eVTOL safety by efficiently estimating uncertainties in battery behavior.
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Orcioni, Simone, and Massimo Conti. "Uncertainty Quantification of Lithium-Ion Batteries with Polynomial Chaos." In 2020 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2020. http://dx.doi.org/10.1109/iscas45731.2020.9180515.
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Liu, Datong, Yue Luo, Limeng Guo, and Yu Peng. "Uncertainty quantification of fusion prognostics for lithium-ion battery remaining useful life estimation." In 2013 IEEE Conference on Prognostics and Health Management (PHM). IEEE, 2013. http://dx.doi.org/10.1109/icphm.2013.6621441.
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Zhang, Weiqi, Yuhang Du, Yuchen Song, Datong Liu, and Yu Peng. "Uncertainty Quantification Based Health Diagnosis for Lithium-Ion Batteries Under Different Operating Conditions." In 2023 IEEE 16th International Conference on Electronic Measurement & Instruments (ICEMI). IEEE, 2023. http://dx.doi.org/10.1109/icemi59194.2023.10270214.
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ChiuHuang, Cheng-Kai, Chuanzhen Zhou, and Hsiao-Ying Shadow Huang. "Exploring Lithium-Ion Intensity and Distribution via a Time-of-Flight Secondary Ion Mass Spectroscopy." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-63013.
Full textAbstract:
For high rate-capability and low cost lithium-ion batteries, the prevention of capacity loss is one of major challenges facing by lithium-ion batteries today. During electrochemical processes, lithium ions diffuse from and insert into battery electrodes accompanied with the phase transformation, where ionic diffusivity and concentration are keys to the resultant battery capacity. In the current study, we first compare voltage vs. capacity curves at different C-rates (1C, 2C, 6C, 10C). Second, lithium-ion distributions and intensity are quantified via the Time-of-Flight Secondary Ion Mass Spectroscopy (ToF-SIMS). The result shows that voltage vs. capacity relations are C-rate dependent and larger hystereses are observed in the higher C-rate samples. Detailed quantification of lithium-ion intensity for the 1C sample is conducted. It is observed that lithium-ions are distributed uniformly inside the electrode. Therefore, the current study provides a qualitative and quantitative data to better understand C-rate dependent phenomenon of LiFePO4 battery cells.
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Pastor-Fernandez, Carlos, W. Dhammika Widanage, James Marco, Miguel-Angel Gama-Valdez, and Gael H. Chouchelamane. "Identification and quantification of ageing mechanisms in Lithium-ion batteries using the EIS technique." In 2016 IEEE Transportation Electrification Conference and Expo (ITEC). IEEE, 2016. http://dx.doi.org/10.1109/itec.2016.7520198.
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Weber, Ross M., Robert Spragg, Kenneth Hoffmann, and Simona Onori. "Process noise quantification in Kalman filters with application to electrochemical Lithium-ion battery state estimation." In 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE). IEEE, 2019. http://dx.doi.org/10.1109/isie.2019.8781525.
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Ke, Yuqi, Ruomei Zhou, Rong Zhu, and Weiwen Peng. "State of Health Estimation of Lithium Ion Battery with Uncertainty Quantification Based on Bayesian Deep Learning." In 2021 3rd International Conference on System Reliability and Safety Engineering (SRSE). IEEE, 2021. http://dx.doi.org/10.1109/srse54209.2021.00009.
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Mendoza, Sergio, Ji Liu, Partha Mishra, and Hosam K. Fathy. "Statistical Quantification of Least-Squares Battery State of Charge Estimation Errors." In ASME 2016 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/dscc2016-9750.
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This paper derives analytic expressions for both the mean and variance of battery state of charge (SOC) estimation error, assuming a least squares estimation law. The paper examines three sources of estimation error, namely: (i) voltage measurement errors (both bias and noise), (ii) current measurement bias, and (iii) mismatch between the order of the battery model used for estimation and the true order of the battery’s dynamics. There is already a rich literature on quantifying battery SOC estimation errors for different estimator designs. The novelty of this paper stems from its extensive examination of both the expected SOC estimation bias and noise, for a least squares estimation algorithm, in the presence of three different fundamental sources of these estimation errors. We show, both analytically and using Monte Carlo simulation, that under reasonable operating conditions, the expected bias in SOC estimation for lithium-ion batteries is dominant compared to the expected estimation variance. This leads to the important insight that quantifying SOC estimation variance using Fisher information furnishes overly optimistic predictions of achievable SOC estimation accuracy.
Reports on the topic "Lithium quantification"
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Orendorff, Christopher J., Joshua Lamb, Leigh Anna Marie Steele, Scott Wilmer Spangler, and Jill Louise Langendorf. Quantification of Lithium-ion Cell Thermal Runaway Energetics. Office of Scientific and Technical Information (OSTI), January 2016. http://dx.doi.org/10.2172/1236109.
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