Статті в журналах: "Lithium quantification"

1

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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2

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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3

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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4

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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5

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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6

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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7

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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8

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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9

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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10

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.

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11

Suryanarayanan, R. "Quantification of Carbamazepine in Tablets by Powder X-ray Diffractometry." Advances in X-ray Analysis 34 (1990): 417–27. http://dx.doi.org/10.1154/s0376030800014737.

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AbstractA powder x-ray diffraction technique has been developed for the quantification of carbamazepine in tablets. The other tablet ingredients were microcrystalline cellulose, starch, stearic acid and silicon dioxide. The tablets were ground in a ball mill and the powder mixed with lithium fluoride (20% w/w) which was the internal standard. Five lines of carbamazepine with d-spacings of 3.38, 3.34, 3.28, 3.26 and 3.23 Å and the 2.01 Å line of lithium fluoride were used for the quantitative analysis. A plot of the intensity ratio (sum of the intensities of the lines of carbamazepine/intensity of die lithium fluoride line) as a function of the weight fraction of carbamazepine in the tablets resulted in a straight line. Using this standard curve, the carbamazepine content in “unknown” tablets was determined and ranged between 98.6 and 101.6% of the actual drug content. The coefficient of variation in the determinations ranged between 0.28 and 2.1%.

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12

Tanim, Tanvir R., Eric J. Dufek, Charles C. Dickerson, and Sean M. Wood. "Electrochemical Quantification of Lithium Plating: Challenges and Considerations." Journal of The Electrochemical Society 166, no. 12 (2019): A2689—A2696. http://dx.doi.org/10.1149/2.1581912jes.

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13

Bai, Miao, Chao Lyu, Dazhi Yang, and Gareth Hinds. "Quantification of Lithium Plating in Lithium-Ion Batteries Based on Impedance Spectrum and Artificial Neural Network." Batteries 9, no. 7 (July 1, 2023): 350. http://dx.doi.org/10.3390/batteries9070350.

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Accurate evaluation of the health status of lithium-ion batteries must be deemed as of great significance, insofar as the utility and safety of batteries are of concern. Lithium plating, in particular, is notoriously known to be a chemical reaction that can cause deterioration in, or even fatal hazards to, the health of lithium-ion batteries. Electrochemical impedance spectroscopy (EIS), which has distinct advantages such as being fast and non-destructive over its competitors, suffices in detecting lithium plating and thus has been attracting increasing attention in the field of battery management, but its ability of assessing quantitatively the degree of lithium plating remains largely unexplored hitherto. On this point, this work seeks to narrow that gap by proposing an EIS-based method that can quantify the degree of lithium plating. The core conception is to eventually circumvent the reliance on state-of-health measurement, and use instead the impedance spectrum to acquire an estimate on battery capacity loss. To do so, the effects of solid electrolyte interphase formation and lithium plating on battery capacity must be first decoupled, so that the mass of lithium plating can be quantified. Then, based on an impedance spectrum measurement, the parameters of the fractional equivalent circuit model (ECM) of the battery can be identified. These fractional ECM parameters are received as inputs by an artificial neural network, which is tasked with establishing a correspondence between the model parameters and the mass of lithium plating. The empirical part of the work revolves around the data collected from an aging experiment, and the validity of the proposed method is truthfully attested by dismantling the batteries, which is otherwise not needed during the actual uptake of the method.

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14

Xu, Hanying, Ce Han, Wenting Li, Huiyu Li, and Xinping Qiu. "Quantification of lithium dendrite and solid electrolyte interphase (SEI) in lithium-ion batteries." Journal of Power Sources 529 (May 2022): 231219. http://dx.doi.org/10.1016/j.jpowsour.2022.231219.

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15

Petzl, Mathias, and Michael A. Danzer. "Nondestructive detection, characterization, and quantification of lithium plating in commercial lithium-ion batteries." Journal of Power Sources 254 (May 2014): 80–87. http://dx.doi.org/10.1016/j.jpowsour.2013.12.060.

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16

Zhou, Hongyao, Haodong Liu, Xing Xing, Zijun Wang, Sicen Yu, Gabriel M. Veith, and Ping Liu. "Quantification of the ion transport mechanism in protective polymer coatings on lithium metal anodes." Chemical Science 12, no. 20 (2021): 7023–32. http://dx.doi.org/10.1039/d0sc06651f.

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Protective Polymer Coatings (PPCs) protect lithium metal anodes in rechargeable batteries to stabilize the Li/electrolyte interface and to extend the cycle life by reducing parasitic reactions and improving the lithium deposition morphology.

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17

Rifai, Kheireddine, Marc Constantin, Adnan Yilmaz, Lütfü Ç. Özcan, François R. Doucet, and Nawfel Azami. "Quantification of Lithium and Mineralogical Mapping in Crushed Ore Samples Using Laser Induced Breakdown Spectroscopy." Minerals 12, no. 2 (February 16, 2022): 253. http://dx.doi.org/10.3390/min12020253.

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This article reports on the quantification of lithium and mineralogical mapping in crushed lithium ore by laser-induced breakdown spectroscopy (LIBS) using two different calibration methods. Thirty crushed ore samples from a pegmatite lithium deposit were used in this study. Representative samples containing the abundant minerals were taken from these crushed ores and mixed with resin to make polished disks. These disks were first analyzed by TIMA (TESCAN Integrated Mineral Analyzer) and then by a LIBS ECORE analyzer to determine the minerals. Afterwards, each of the thirty crushed ore samples (<10 mm) were poured into rectangular containers and analyzed by the ECORE analyzer, then mineral mapping was produced on the scanned surfaces using the mineral library established on the polished sections. For the first method the lithium concentrations were inferred from the empirical mineral chemistry formula, whereas the second one consisted of building a conventional calibration curve with the crushed material to predict the lithium concentration in unknown crushed materials.

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18

Md Said and Mohd Tohir. "Prediction of Lithium-ion Battery Thermal Runaway Propagation for Large Scale Applications Fire Hazard Quantification." Processes 7, no. 10 (October 5, 2019): 703. http://dx.doi.org/10.3390/pr7100703.

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The high capacity and voltage properties demonstrated by lithium-ion batteries render them as the preferred energy carrier in portable electronic devices. The application of the lithium-ion batteries which previously circulating and contained around small-scale electronics is now expanding into large scale emerging markets such as electromobility and stationary energy storage. Therefore, the understanding of the risk involved is imperative. Thermal runaway is the most common failure mode of lithium-ion battery which may lead to safety incidents. Transport process of immense amounts of heat released during thermal runaway of lithium-ion battery to neighboring batteries in a module can lead to cascade failure of the whole energy storage system. In this work, a model is developed to predict the propagation of lithium-ion battery in a module for large scale applications. For this purpose, kinetic of material thermal decomposition is combined with heat transfer modelling. The simulation is built based on chemical kinetics at component level of a singular cell and energy balance that accounts for conductive and convective heat transfer.

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19

Paul, Partha P., Vivek Thampy, Chuntian Cao, Hans-Georg Steinrück, Tanvir R. Tanim, Alison R. Dunlop, Eric J. Dufek, et al. "Quantification of heterogeneous, irreversible lithium plating in extreme fast charging of lithium-ion batteries." Energy & Environmental Science 14, no. 9 (2021): 4979–88. http://dx.doi.org/10.1039/d1ee01216a.

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20

Wilken, A., V. Kraft, S. Girod, M. Winter, and S. Nowak. "A fluoride-selective electrode (Fse) for the quantification of fluoride in lithium-ion battery (Lib) electrolytes." Analytical Methods 8, no. 38 (2016): 6932–40. http://dx.doi.org/10.1039/c6ay02264b.

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21

Huang, Ming, and Bo Lan. "Quantifying Tortuosity in Porous Lithium-Ion Battery Materials Using Ultrasound." ECS Meeting Abstracts MA2022-02, no. 6 (October 9, 2022): 591. http://dx.doi.org/10.1149/ma2022-026591mtgabs.

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Active electrode materials in lithium-ion batteries are porous. These materials are composed of a solid frame containing interconnected pores/channels, in which mass transport follows a tortuous pathway. Tortuosity is defined as the ratio of the average tortuous pathway to the projected straight path, and is a particularly important parameter indicating the diffusivity and conductivity properties of porous battery materials; so quantifying tortuosity is highly desirable to safeguard battery performance. Existing quantification methods are mostly based on impedance and polarisation measurements from specially-fabricated cells and numerical diffusion simulations using the microstructural tomographic images of porous materials. These methods, however, are generally cumbersome and barely applicable to in-production measurement. Here we report a novel alternative quantification method based on ultrasonic Biot waves in porous materials. This method utilises the fundamental fact that in a porous material with a rigid frame (which the electrode sheets are when immersed in the air), the slow Biot wave only travels in the liquid/gaseous phase, through the same tortuous pathway that the diffusion of ions and electrons happens in a finished battery. To achieve the quantification, we first develop a physical model relating the propagation of ultrasonic Biot waves to the tortuosity of porous battery materials. Based on this physical model, we then propose an inversion method to infer tortuosity from ultrasonic readings. The readings are acquired using air-coupled ultrasonic transducers in a non-destructive fashion, thus enabling real-time tortuosity quantification. This ultrasonic method measures the average tortuosity in a range of ~20 mm across the testing material, and can easily scan over a sheet to provide spatially resolved information. With these exciting features, the proposed method could offer a next-generation tortuosity quantification tool for quality control of porous battery material productions and a better understanding of battery performance.

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22

Sheikh, Mahsa, Meha Qassem, Iasonas F. Triantis, and Panicos A. Kyriacou. "Advances in Therapeutic Monitoring of Lithium in the Management of Bipolar Disorder." Sensors 22, no. 3 (January 19, 2022): 736. http://dx.doi.org/10.3390/s22030736.

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Since the mid-20th century, lithium continues to be prescribed as a first-line mood stabilizer for the management of bipolar disorder (BD). However, lithium has a very narrow therapeutic index, and it is crucial to carefully monitor lithium plasma levels as concentrations greater than 1.2 mmol/L are potentially toxic and can be fatal. The quantification of lithium in clinical laboratories is performed by atomic absorption spectrometry, flame emission photometry, or conventional ion-selective electrodes. All these techniques are cumbersome and require frequent blood tests with consequent discomfort which results in patients evading treatment. Furthermore, the current techniques for lithium monitoring require highly qualified personnel and expensive equipment; hence, it is crucial to develop low-cost and easy-to-use devices for decentralized monitoring of lithium. The current paper seeks to review the pertinent literature rigorously and critically with a focus on different lithium-monitoring techniques which could lead towards the development of automatic and point-of-care analytical devices for lithium determination.

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23

Danani, Chandan, H. L. Swami, Paritosh Chaudhuri, A. Mutzke, R. Schneider, and Manoj Warrier. "Multi-model quantification of defects in irradiated lithium titanate." Fusion Engineering and Design 140 (March 2019): 92–96. http://dx.doi.org/10.1016/j.fusengdes.2019.02.006.

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24

Li, Na, Zhichao Chu, Chenchen Liu, Shuai Fu, Jinbao Fan, Le Yang, Yikun Wu, Wei-Li Song, Hao-Sen Chen, and Shuqiang Jiao. "Quantification of lithium deposition under mechano-electrochemical coupling effect." Journal of Power Sources 594 (February 2024): 233979. http://dx.doi.org/10.1016/j.jpowsour.2023.233979.

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25

Schultz, Carola, Sven Vedder, Benjamin Streipert, Martin Winter, and Sascha Nowak. "Quantitative investigation of the decomposition of organic lithium ion battery electrolytes with LC-MS/MS." RSC Advances 7, no. 45 (2017): 27853–62. http://dx.doi.org/10.1039/c7ra03839a.

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A novel high performance liquid chromatography hyphenated to tandem mass spectrometry method for the separation and quantification of components from common organic carbonate-based electrolyte systems in lithium ion batteries was developed.

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26

Oberti, Roberta, Fernando Cá mara, Luisa Ottolini, and José Maria Caballero. "Lithium in amphiboles: detection, quantification, and incorporation mechanisms in the compositional space bridging sodic and BLi-amphiboles." European Journal of Mineralogy 15, no. 2 (March 31, 2003): 309–19. http://dx.doi.org/10.1127/0935-1221/2003/0015-0309.

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27

Menzel, Jennifer, Hannah Schultz, Vadim Kraft, Juan Pablo Badillo, Martin Winter, and Sascha Nowak. "Quantification of ionic organo(fluoro)phosphates in decomposed lithium battery electrolytes." RSC Advances 7, no. 62 (2017): 39314–24. http://dx.doi.org/10.1039/c7ra07486g.

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28

Kim, Sangwook, Zonggen Yi, Tanvir R. Tanim, Ross R. Kunz, Eric J. Dufek, Kevin L. Gering, Peter J. Weddle, Kandler Smith, and Bor-Rong Chen. "Physics-Based Methods and Tools for Rapid Classification, Quantification, and Forecasting of Lithium-Ion Battery Aging Modes and Life." ECS Meeting Abstracts MA2022-02, no. 3 (October 9, 2022): 351. http://dx.doi.org/10.1149/ma2022-023351mtgabs.

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Physics-based methods and tools for rapid classification, quantification, and forecasting of lithium-ion battery aging modes and life Sangwook Kim,1 Zonggen Yi,1 Ross R. Kunz,1 Eric J. Dufek,1 Tanvir Tanim,1 Kevin L. Gering1, Bor-Rong Chen,1 Peter Weddle, 2 Kandler Smith, 2 1 Energy and Environmental Science and Technology, Idaho National Laboratory, Idaho Falls, Idaho 83415 USA 2 Center for Energy Conversion & Storage Systems, National Renewable Energy Laboratory, Golden, CO 80401, USA 242nd ECS Meeting, Atlanta, GA, Oct. 9 - 13, 2022 Symposium: A03 – Lithium Ion Batteries Lithium-ion batteries play a central role in powering electric vehicles, stationary energy storage systems, and consumer electronics. Lately, machine learning and deep learning (DL) has been successfully used to gain insights into battery degradation during battery operation and predict lifetime in battery research and development community. Fast and robust classification and quantification of battery aging (e.g., Loss of Lithium Inventory (LLI) and Loss of active Material (LAM)) and accurate long-term forecasting of battery life enable more proactive planning of battery management and preemptive actions of modified operating conditions to achieve safe operations and prolong battery life. Here, we present the development of Incremental Capacity (IC)-DL framework for fast charging conditions as a diagnostic tool for aging mode classification and quantification (Figure 1). The classification and quantification of dominant battery aging modes is conducted using a synthetic-data-based DL modeling framework. Over 6000 initial conditions and 26,000 different aging conditions are generated using IC model to train DL. We applied trained DL classification and quantification algorithm to 22 Gr/NMC532 pouch cells with a different loading and charging protocol tested up to 600 cycles. Besides the analysis of reference performance test data at C/20, cycle-by-cycle data at higher C-rate is analyzed. This IC-DL framework as a diagnostic tool is also used in different battery chemistries, such as Gr/NMC811and LTO/LMO. IC-DL framework enables unique, rapid identification and quantification of the dominant aging modes at different C-rates in different battery chemistries. Additionally, a prognostic tool, Sigmoidal Rate Expression (SRE)-type mathematics are employed to evaluate the capacity loss and aging mode (i.e., LLI). SREs are robust engines that contain three variables that capture the thermodynamic and kinetic “thumbprint” of the mechanism progression within the context of a batch reactor scenario [1].We show two different methods by which SRE parameters can be early assessed based on quantified values from IC-DL framework; (1) extrapolative techniques using specialized functions to determine SRE parameter convergence and (2) a technique based on deep learning and Monte Carlo framework. Overall results from both methods confirm that we can predict capacity loss and LLI at the end of test (i.e., 600 cycles) within 1-2% absolute error using three weeks of testing data (or 125 cycles). We believe the IC-DL framework combined with SRE-base prognostics will reduce lithium-ion batteries development cycle as well as shorten the turnover time for validation, fulfilling the demands of rapidly growing battery market. References K. Gering, Electrochimica Acta, 228(20), 636-651 (2017) Figure 1

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Weitzel, Karl-Michael, Johanna Schepp, Jona Schuch, Jan Philipp Hofmann, and Stefan Adams. "On the Description of Electrode Materials Based on the Quantification of Ionic and Electronic Work Functions." ECS Meeting Abstracts MA2023-02, no. 2 (December 22, 2023): 187. http://dx.doi.org/10.1149/ma2023-022187mtgabs.

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During decharging of a lithium ion battery (LIB) electrons are transferred from the cathode material to the outer circuit and lithium ions are transferred into the electrolyte. Here, the energy required to take electrons and lithium ions out of two prototypical cathode materials, LixFePO4 and LixMn2O4 is investigated as a function of the state of lithiation, x [1]. Ionic work functions are measured by thermionic emission, electronic work functions are measured either by thermionic emission or by photoelectron spectroscopy. The work functions measured vary significantly with x for LixFePO4 with moderate, low-dimensional ionic and electronic conductivities but rather little for cubic LixMn2O4 with ca. three orders of magnitude higher ionic and electronic conductivities [2]. The experimental data are supported and rationalized by static energy-landscape calculations and molecular dynamics simulations of the Lithium migration as a function of Lithium content and electric field strength [1]. This study provides new insight into the role of ionic contributions to the energy balance in LIBs. Current efforts are aimed at a complete energetic description of LIBs as previously discussed for LiCoO2 [3]. [1] J. Schepp, J. Schuch, J.P. Hofmann, S. Adams, K.-M. Weitzel, to be published [2] M. Park, X. Zhang, M. Chung, G.B. Less, A.M. Sastry, A review of conduction phenomena in Li-ion batteries, Journal of Power Sources 195 (2010) 7904–7929. [3] S. Schuld, R. Hausbrand, M. Fingerle, W. Jaegermann, K.-M. Weitzel, Experimental Studies on Work Functions of Li+ Ions and Electrons in the Battery Electrode Material LiCoO2 A Thermodynamic Cycle Combining Ionic and Electronic Structure, Adv. Energy Mater. 8 (2018) 1703411.

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Ciampolillo, Maria Vittoria, Annamaria Zaltron, Marco Bazzan, Nicola Argiolas, and Cinzia Sada. "Quantification of Iron (Fe) in Lithium Niobate by Optical Absorption." Applied Spectroscopy 65, no. 2 (February 2011): 216–20. http://dx.doi.org/10.1366/10-06015.

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Liu, Danny X., Jinghui Wang, Ke Pan, Jie Qiu, Marcello Canova, Lei R. Cao, and Anne C. Co. "In Situ Quantification and Visualization of Lithium Transport with Neutrons." Angewandte Chemie International Edition 53, no. 36 (July 14, 2014): 9498–502. http://dx.doi.org/10.1002/anie.201404197.

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Liu, Danny X., Jinghui Wang, Ke Pan, Jie Qiu, Marcello Canova, Lei R. Cao, and Anne C. Co. "In Situ Quantification and Visualization of Lithium Transport with Neutrons." Angewandte Chemie 126, no. 36 (July 14, 2014): 9652–56. http://dx.doi.org/10.1002/ange.201404197.

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McShane, Eric J., Andrew M. Colclasure, David Emory Brown, Zachary M. Konz, Kandler Smith, and Bryan D. McCloskey. "Quantification of Inactive Lithium, Solid Carbonate Species, and Lithium Acetylide on Graphite Electrodes after Fast Charging." ECS Meeting Abstracts MA2020-02, no. 3 (November 23, 2020): 542. http://dx.doi.org/10.1149/ma2020-023542mtgabs.

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Xia, C., C. Y. Kwok, and L. F. Nazar. "A high-energy-density lithium-oxygen battery based on a reversible four-electron conversion to lithium oxide." Science 361, no. 6404 (August 23, 2018): 777–81. http://dx.doi.org/10.1126/science.aas9343.

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Lithium-oxygen (Li-O2) batteries have attracted much attention owing to the high theoretical energy density afforded by the two-electron reduction of O2 to lithium peroxide (Li2O2). We report an inorganic-electrolyte Li-O2 cell that cycles at an elevated temperature via highly reversible four-electron redox to form crystalline lithium oxide (Li2O). It relies on a bifunctional metal oxide host that catalyzes O–O bond cleavage on discharge, yielding a high capacity of 11 milliampere-hours per square centimeter, and O2 evolution on charge with very low overpotential. Online mass spectrometry and chemical quantification confirm that oxidation of Li2O involves transfer of exactly 4 e–/O2. This work shows that Li-O2 electrochemistry is not intrinsically limited once problems of electrolyte, superoxide, and cathode host are overcome and that coulombic efficiency close to 100% can be achieved.

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Möller, Sören, Takahiro Satoh, Yasuyuki Ishii, Britta Teßmer, Rayan Guerdelli, Tomihiro Kamiya, Kazuhisa Fujita, et al. "Absolute Local Quantification of Li as Function of State-of-Charge in All-Solid-State Li Batteries via 2D MeV Ion-Beam Analysis." Batteries 7, no. 2 (June 20, 2021): 41. http://dx.doi.org/10.3390/batteries7020041.

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Direct observation of the lithiation and de-lithiation in lithium batteries on the component and microstructural scale is still difficult. This work presents recent advances in MeV ion-beam analysis, enabling quantitative contact-free analysis of the spatially-resolved lithium content and state-of-charge (SoC) in all-solid-state lithium batteries via 3 MeV proton-based characteristic x-ray and gamma-ray emission analysis. The analysis is demonstrated on cross-sections of ceramic and polymer all-solid-state cells with LLZO and MEEP/LIBOB solid electrolytes. Different SoC are measured ex-situ and one polymer-based operando cell is charged at 333 K during analysis. The data unambiguously show the migration of lithium upon charging. Quantitative lithium concentrations are obtained by taking the physical and material aspects of the mixed cathodes into account. This quantitative lithium determination as a function of SoC gives insight into irreversible degradation phenomena of all-solid-state batteries during the first cycles and locations of immobile lithium. The determined SoC matches the electrochemical characterization within uncertainties. The presented analysis method thus opens up a completely new access to the state-of-charge of battery cells not depending on electrochemical measurements. Automated beam scanning and data-analysis algorithms enable a 2D quantitative Li and SoC mapping on the µm-scale, not accessible with other methods.

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Zanini, Leonardo, Annamaria Zaltron, Enrico Turato, Riccardo Zamboni, and Cinzia Sada. "Opto-Microfluidic Integration of the Bradford Protein Assay in Lithium Niobate Lab-on-a-Chip." Sensors 22, no. 3 (February 2, 2022): 1144. http://dx.doi.org/10.3390/s22031144.

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This paper deals with the quantification of proteins by implementing the Bradford protein assay method in a portable opto-microfluidic platform for protein concentrations lower than 1.4 mg/mL. Absorbance is measured by way of optical waveguides integrated to a cross-junction microfluidic circuit on a single lithium niobate substrate. A new protocol is proposed to perform the protein quantification based on the high correlation of the light absorbance at 595 nm, as commonly used in the Bradford method, with the one achieved at 633 nm with a cheap commercially available diode laser. This protocol demonstrates the possibility to quantify proteins by using nL volumes, 1000 times less than the standard technique such as paper-analytical devices. Moreover, it shows a limit of quantification of at least 0.12 mg/mL, which is four times lower than the last literature, as well as a better accuracy (98%). The protein quantification is obtained either by using one single microfluidic droplet as well by performing statistical analysis over ensembles of several thousands of droplets in less than 1 min. The proposed methodology presents the further advantage that the protein solutions can be reused for other investigations and the same pertains to the opto-microfluidic platform.

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Otten, Abigail, Kelly Nieto, and Amy L. Prieto. "Coupling Quantification of Pulverization with Galvanostatic Cycling of Bulk Film Alloy-Type Anodes." ECS Meeting Abstracts MA2022-02, no. 29 (October 9, 2022): 2587. http://dx.doi.org/10.1149/ma2022-02292587mtgabs.

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Alloy-type anodes, such as metallic antimony, demonstrate promise as alternative electrode materials for lithium-ion battery systems due to their high theoretical capacity of 660 mAh/g. However, antimony undergoes anisotropic volume expansion and multiple crystallographic phase transformations upon lithiation and delithiation, which often leads to fracture. This fracture can result in loss of electrical contact and poor cycling stability. These pulverization phenomena are often observed, primarily during delithiation, but are not quantified in terms of physical bulk material lost. To quantify the mass, size, volume, and density of pulverized regions in a bulk antimony film in a lithium system, we have developed a cell that enables the use of optical microscopy to capture videos of lithiation and delithiation. Using ImageJ and MATLAB® scripts developed for analysis, we have begun to quantify the amount of material lost as a function of deposition parameters.

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Imaz, M. L., L. Garcia-Esteve, M. Torra, D. Soy, K. Langohr, and R. Martin-Santos. "Lithium placental passage at delivery: an observational study." European Psychiatry 65, S1 (June 2022): S401—S402. http://dx.doi.org/10.1192/j.eurpsy.2022.1017.

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Introduction Lithium is used as a first-line treatment for bipolar disorder during perinatal period. Dosing of lithium can be challenging as a result of pharmacokinetic changes in renal physiology. Frequent monitoring of lithium blood levels during pregnancy is recommended in order remain within the therapeutic window (0.5 to 1.2 mEq/L). Lower neonatal lithium blood level (<0.64 mEq/L) at time of delivery reduces the risk of lithium side effects in the neonate. Objectives The aim of the present study was to quantify the rate of lithium placental passage in real word. Methods We included a total of 68 mother-infant pairs for which a lithium measurement was performed intrapartum. Lithium serum concentrations were determined by means of an AVL 9180 electrolyte analyzer. The limit of quantification (LoQ) was 0.20 mEq/L and detection limit was 0.10 mEq/L. Pearson analyse was performer to assess the correlation between mother and umbilical cord lithium serum concentrations. Results The mean of umbilical cord serum concentration at delivery was 0.57 mEq/L (SD=0.26, range 0,20-1,42). The mean infant-mother lithium ratio at delivery for the 68 pairs was 1.12 (SD=0.24) across a wide range of maternal concentrations (range 0.14-1,40 mEq/L). There was a strong positive correlation between maternal and umbilical cord lithium blood levels (Peearson correlation coefficient 0.948, p<0.001). Conclusions Lithium demostrates complete placental passage. This finding is consistent with the results of others studies (Newport 2005; Molenaar 2021). Disclosure No significant relationships.

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Meng, Shirley. "Si Anode for All Solid State Batteries." ECS Meeting Abstracts MA2022-02, no. 3 (October 9, 2022): 249. http://dx.doi.org/10.1149/ma2022-023249mtgabs.

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The development of silicon anodes for lithium-ion batteries has been largely impeded by poor interfacial stability against liquid electrolytes. I will show how to enable the operation of a 99.9 weight % microsilicon anode by using the interface passivating properties of sulfide solid electrolytes. Advanced interface and bulk characterization, and quantification of interfacial components, showed that such an approach eliminates continuous interfacial growth and irreversible lithium losses. Microsilicon full cells were assembled and found to achieve high areal current density, wide operating temperature range, and high areal loadings for the different cells. The promising performance can be attributed to both the desirable interfacial property between microsilicon and sulfide electrolytes and the distinctive chemomechanical behavior of the lithium-silicon alloy. I will also discuss a few exciting future directions for nanosilicon with solid state electrolytes.

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Scharpmann, Philippa, Robert Leonhardt, Tim Tichter, Anita Schmidt, and Jonas Krug von Nidda. "In-Situ Quantification of the Ageing Dynamics in Lithium-Ion Cells up to Failure-Near Conditions." ECS Meeting Abstracts MA2023-02, no. 3 (December 22, 2023): 449. http://dx.doi.org/10.1149/ma2023-023449mtgabs.

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Implementing end-of-life (EOL) lithium-ion batteries from automotive applications in stationary energy storages is of utmost relevance for a sustainable handling of scarce resources. Beneficial from an economic and ecological perspective, such second-life applications urgently require a guarantee for safe operation. Unlike the state of health (SOH), defined by classical performance indicators such as capacity and voltage, the state of safety (SOS) of an aged battery cannot be assessed straightforward. Its determination requires a plethora of cells to be tested which is a particular challenge for new technologies with limited access to EOL batteries. For providing cells with a defined SOH at a reasonable timescale, we herein propose a novel method of greatly accelerating the ageing process of lithium-ion batteries. In a preliminary test series, lithium-ion NMC pouch cells are exposed to incrementally increasing temperatures, current rates and/or states of charge (SOC), until thermal runaway is induced. In this manner, the critical state in proximity to cell failure is spotted for individual and combined stress parameters. Based on this knowledge, cell-specific test parameters for heavily accelerated ageing are developed. In this protocol, electrical abuse conditions are defined by over/under charging and high current rates. Typically, the cells are cycled utilizing a depth of discharge above 100 %. The accelerated aging dynamics under these critical conditions are monitored by systematic capacity, open circuit voltage and electrochemical impedance spectroscopy (EIS) measurements. This enables a comparative assessment of the electrical behaviour, following conventional vs. heavily accelerated ageing. Such knowledge will in turn help to define the threshold to which cyclic ageing can be accelerated without changing the characteristic degradation mechanisms of lithium-ion batteries.

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Hsieh, Yi-Chen, Marco Leißing, Sascha Nowak, Bing-Joe Hwang, Martin Winter, and Gunther Brunklaus. "Quantification of Dead Lithium via In Situ Nuclear Magnetic Resonance Spectroscopy." Cell Reports Physical Science 1, no. 8 (August 2020): 100139. http://dx.doi.org/10.1016/j.xcrp.2020.100139.

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Bianconi, M., N. Argiolas, M. Bazzan, G. G. Bentini, A. Cerutti, M. Chiarini, G. Pennestrì, P. Mazzoldi, and C. Sada. "Quantification of nuclear damage in high energy ion implanted lithium niobate." Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 257, no. 1-2 (April 2007): 597–600. http://dx.doi.org/10.1016/j.nimb.2007.01.046.

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Dumaresq, Nicolas, Raynald Gauvin, and Karim Zaghib. "Low-Voltage STEM-Eels Quantification for Lithium Ion Battery Material Characterization." ECS Meeting Abstracts MA2020-01, no. 4 (May 1, 2020): 525. http://dx.doi.org/10.1149/ma2020-014525mtgabs.

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Imaz, M. L., M. Torra, D. Soy, K. Langorh, L. Garcia-Esteve, and R. Martin-Santos. "Lithium placental passage at delivery and neonatal outcomes: A retrospective observational study." European Psychiatry 64, S1 (April 2021): S203. http://dx.doi.org/10.1192/j.eurpsy.2021.540.

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Introduction Lithium is an effective mood stabilizer and is widely used as a first-line treatment for bipolar disorder in the perinatal period. Several guidelines have provided clinical advice on dosing strategy (dose reduction versus stop lithium) in the peripartum period to minimize the risk of neonatal complications. An association has been observed between high neonatal lithium concentrations (> 0.64 mEq/L) and lower 1-min Apgar scores, longer hospital stays, and central nervous system and neuromuscular complications.ObjectivesTo quantify the rate of lithium placental passage at delivery. To assess any association between plasma concentration of lithium at delivery and neonatal outcome.Methods In this retrospective observational cohort study, we included women treated with llithium at least in late pregnancy. Maternal (MB) and umbilical cord (UC) lithium blood level measurement were collected at delivery. Lithium serum concentrations were determined by means of an AVL 9180 electrolyte analyzer. The limit of quantification (LoQ) was 0.20 mEq/L and detection limit was 0.10 mEq/L. From the medical records, we extracted information on neonatal outcomes (preterm birth, birth weight, Apgar scores, pH-values, and admision to NICU) and complications categoriced by organ system: respiratory, circulatory, hematological, gastro-intestinal, metabolic, neurological, and immune system (infections).ResultsUmbilical cord and maternal lithium blood levels were strongly correlated: mean (SD) range UC/MR ratio 1.15 (0.24). Umbilical cord lithium levels ranged between 0.20 to 1.42 mEq/L. We observed no associations between umbilical cord lithium blood levels at delivery and neonatal outcomes.ConclusionsIn our study, newborns tolerated well a wide range of lithemias, between 0.20 and 1.42 mEq/L.

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Zhu, Changlian, Cuicui Xie, Kai Zhou, and Klas Blomgren. "Lithium treatment reduced microglia activation and inflammation after irradiation to the immature brain (P6256)." Journal of Immunology 190, no. 1_Supplement (May 1, 2013): 115.24. http://dx.doi.org/10.4049/jimmunol.190.supp.115.24.

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Abstract To evaluate the effects of lithium on microglia activation and inflammation after irradiation to the immature brain, male rat pups were injected 2 mmol/kg lithium chloride i.p. on postnatal day 7 (P7), additional lithium injections, 1 mmol/kg, were administered at 24 h intervals. Pups were subjected to whole brain 6Gy irradiation on P11. The pups were sacrificed at 6h and 24h after IR. Microglia scattered in the brain can be detected by counting their numbers, their size, engulfment of cell debris or by the production of cytokines and chemokines. Microglia were stained using the marker Iba-1, revealing the presence of these cells throughout the brain under normal conditions, and apparently higher numbers and bigger sizes after IR, particularly in areas where cell death occurred. Quantification of Iba-1+ cells in the GCL of DG showed a significant increase after IR, but with a lower increase in the lithium-treated brains. The concentration of MCP-1, IL-1α, IL-1β, GRO/KC in the hippocampus were increased significantly at 6h after IR compared with non-irradiation control. Lithium treatment significantly inhibited the increase. There was no significantly difference with these cytokines/chemokines at 24h after IR between lithium and vehicle treated group. These data indicate that lithium can specifically reduce inflammation through GSK3-beta inhibition or modified microglia activation.

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Pöllmann, Herbert, and Uwe König. "Monitoring of Lithium Contents in Lithium Ores and Concentrate-Assessment Using X-ray Diffraction (XRD)." Minerals 11, no. 10 (September 28, 2021): 1058. http://dx.doi.org/10.3390/min11101058.

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Lithium plays an increasing role in battery applications, but is also used in ceramics and other chemical applications. Therefore, a higher demand can be expected for the coming years. Lithium occurs in nature mainly in different mineralizations but also in large salt lakes in dry areas. As lithium cannot normally be analyzed using XRF-techniques (XRF = X-ray Fluorescence), the element must be analyzed by time consuming wet chemical treatment techniques. This paper concentrates on XRD techniques for the quantitative analysis of lithium minerals and the resulting recalculation using additional statistical methods of the lithium contents. Many lithium containing ores and concentrates are rather simple in mineralogical composition and are often based on binary mineral assemblages. Using these compositions in binary and ternary mixtures of lithium minerals, such as spodumene, amblygonite, lepidolite, zinnwaldite, petalite and triphylite, a quantification of mineral content can be made. The recalculation of lithium content from quantitative mineralogical analysis leads to a fast and reliable lithium determination in the ores and concentrates. The techniques used for the characterization were quantitative mineralogy by the Rietveld method for determining the quantitative mineral compositions and statistical calculations using additional methods such as partial least square regression (PLSR) and cluster analysis methods to predict additional parameters, like quality, of the samples. The statistical calculations and calibration techniques makes it especially possible to quantify reliable and fast. Samples and concentrates from different lithium deposits and occurrences around the world were used for these investigations. Using the proposed XRD method, detection limits of less than 1% of mineral and, therefore down to 0.1% lithium oxide, can be reached. Case studies from a hard rock lithium deposit will demonstrate the value of mineralogical monitoring during mining and the different processing steps. Additional, more complex considerations for the analysis of lithium samples from salt lake brines are included and will be discussed.

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Surgiewicz, Jolanta. "Lithium hydride. Determination in workplaces air." Podstawy i Metody Oceny Środowiska Pracy 33, no. 3(93) (September 10, 2017): 151–60. http://dx.doi.org/10.5604/01.3001.0010.4342.

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Lithium hydride is a solid, unstable substance. It reacts violently with water to produce strong liquor (LiOH) and hydrogen. It may self-ignite. It is used in the metallurgical, pharmaceutical, ceramic and chemical industries. Lithium hydride is strongly toxic. It is irritating and corrosive to the to the skin, damaging the mucous membranes of the respiratory tract. May cause eye burns and loss of vision. Harmful to the digestive tract, nervous system and kidneys. Exposure limit values for lithium hydride is NDS – 0.025 mg/ m3. The aim of the study was the amendment of the method for determining concentrations of lithium hydride in the air at workplaces in the range of 1/10 to 2 NDS values, in accordance with the requirements of Standard No. EN 482. The developed method for determining involves: collect of lithium hydride contained in the air on a membrane filter, mineralization of the filter using concentrated nitric acid, and the determination lithium in the solution prepared for analysis by atomic absorption spectrometry with lean flame air-acetylene ( F-AAS). This method enables the determination of lithium in concentration range of 0.05  3.50 g/ml. The lithium calibration curve obtained is characterized by correlation coefficient R2 = 1.0000. The detection limit of lithium (LOD) is 2 ng/ml, and the limit of quantification (LOQ) is 5 ng/ml. Determined coefficient of recovery is 1.00. The developed method enables the determination of lithium hydride in workplaces air in the concentration range of 0.0008  0.056 mg/m3 (for a 720 l air sample) which represents 0.03  2.24 NDS. The method of determining of lithium hydride has been recorded as an analytical procedure (appendix).

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Furtmair, Michael, Anika Wolters, Sanja Simic, Markus Thannhuber, Günther Ruhl, and Michael Sternad. "Tracing the Powerfade: Location and Quantification of the Fluoridic Solid Electrolyte Interphase on Graphite Anodes." ECS Meeting Abstracts MA2023-01, no. 7 (August 28, 2023): 2860. http://dx.doi.org/10.1149/ma2023-0172860mtgabs.

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Due to the conversion of the global energy supply from carbon emitting to renewable sources, there is the need for energy storage systems being efficient at high energy- and power densities. Many requirements are fulfilled best by Lithium-Ion Batteries (LIBs), so this technology is successfully part of battery-electric vehicles, cordless power tools and portable electronic devices. The ongoing improvement of anode- and cathode materials, together with adapted electrolytes [1] led to excellent advances in power- and energy densities. However, the increasing amount of total energy per cell underlines the importance of monitoring the cell’s health parameters (e.g. capacity fades, coulombic efficiencies, AC-and DC-impedances) in order to ensure safety and expand the lifetime [2, 3]. The Solid Electrolyte Interphase (SEI) represents a main source for cell impedances [4] and was in the case of LiPF6-based electrolytes found to be best analytically accessible by the quantitative determination of its unsolvable, fluoridic fractions (LiF) using ion-exchange chromatography [5]. During this work, long term cycling tests (T = 25, 40, 60 °C, 2 C charging) of industrial 3 Ah-21700-cells with graphite anode (figure a), NMC 811 cathode and LiPF6-based electrolyte were performed (figure b). Subsequently, after defined cycling steps (10, 250, 500, 750 cycles) the cells were opened, post-mortem analysis (SEM, EDX, “broad ion beam”- (BIB) preparation) together with the drawing of anode/separators samples for the later fluoride determination took place. The samples were cleaned from LiPF6 (washing with DEC) and dried under glovebox conditions (Ar, < 0.5 ppm H2O). With the aim to quantify the SEI layer 1) in the anode bulk and 2) adhering to or inside the separator to trace reversible Li-plating, anode/separators samples were eluted separately with deionized water and the fluoride-concentration of the solutions was determined by ion-exchange chromatography (figure c - f). SEI fractions, like inorganic carbonates, alkyl carbonates, oxides, etc., were investigated using X-ray photoelectron spectroscopy (XPS) along a depth profile (figure g) using Ar-ion sputtering [6, 7]. The results elaborated within this study point out a strong correlation in between the amount of fluoridic SEI and the DC-impedance rise during cycling, especially at elevated temperatures (40, 60 °C). At 25 °C different ageing mechanisms are obvious: In comparison lower fluoride concentrations together with substantial DC impedance gains suggest the temporary and superficial occurrence of reversible Li-plating, blocking important Li-ion paths via the electrolyte (e.g. anode surface pores, separator pores [8, 9]) by residual products of their SEI-films. Reference s [1] Eshetu, G. G.; Zhang, H.; Judez, X.; Adenusi, H.; Armand, M.; Passerini, S.; Figgemeier, E., Production of high-energy Li-ion batteries comprising silicon-containing anodes and insertion-type cathodes. Nat Commun 2021, 12, (1), 5459. [2] Sternad, M.; Cifrain, M.; Watzenig, D.; Brasseur, G.; Winter, M., Condition monitoring of Lithium-Ion Batteries for electric and hybrid electric vehicles. e & i Elektrotechnik und Informationstechnik 2009, 126, (5), 186-193. [3] Furtmair, M.; Wolters, A.; Kühnel, F.; Thannhuber, M.; Sötz, V.; Sternad, M., The Impact of Fast-Charging on Cell Ageing of Industrial High-Power Lithium-Ion Batteries. In IMLB 2022, Sydney, Australia, 2022. [4] Aurbach, D.; Markovsky, B.; Rodkin, A.; Cojocaru, M.; Levi, E.; Kim, H.-J., An analysis of rechargeable lithium-ion batteries after prolonged cycling. Electrochimica Acta 2002, 47, (12), 1899-1911. [5] Uitz, M.; Sternad, M.; Breuer, S.; Täubert, C.; Traußnig, T.; Hennige, V.; Hanzu, I.; Wilkening, M., Aging of Tesla's 18650 Lithium-Ion Cells: Correlating Solid-Electrolyte-Interphase Evolution with Fading in Capacity and Power. Journal of The Electrochemical Society 2017, 164, (14), A3503-A3510. [6] Shutthanandan, V.; Nandasiri, M.; Zheng, J.; Engelhard, M. H.; Xu, W.; Thevuthasan, S.; Murugesan, V., Applications of XPS in the characterization of Battery materials. Journal of Electron Spectroscopy and Related Phenomena 2019, 231, 2-10. [7] Zhu, Y.; Pande, V.; Li, L.; Wen, B.; Pan, M. S.; Wang, D.; Ma, Z. F.; Viswanathan, V.; Chiang, Y. M., Design principles for self-forming interfaces enabling stable lithium-metal anodes. Proc Natl Acad Sci U S A 2020, 117, (44), 27195-27203. [8] Lagadec, M. F.; Ebner, M.; Zahn, R.; Wood, V., Communication—Technique for Visualization and Quantification of Lithium-Ion Battery Separator Microstructure. Journal of The Electrochemical Society 2016, 163, (6), A992-A994. [9] Zier, M.; Scheiba, F.; Oswald, S.; Thomas, J.; Goers, D.; Scherer, T.; Klose, M.; Ehrenberg, H.; Eckert, J., Lithium dendrite and solid electrolyte interphase investigation using OsO4. Journal of Power Sources 2014, 266, 198-207. Acknowledgment The authors wish to thank H. Schröttner (Institute of Electron Microscopy and Nanoanalysis, Graz University of Technology) for preferential access to preparation and examination equipment. Figure 1

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Yang, Xiao-Guang, Shanhai Ge, Teng Liu, Yongjun Leng, and Chao-Yang Wang. "A look into the voltage plateau signal for detection and quantification of lithium plating in lithium-ion cells." Journal of Power Sources 395 (August 2018): 251–61. http://dx.doi.org/10.1016/j.jpowsour.2018.05.073.

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50

Imaz, M. L., M. Torra, D. Soy, K. Langorh, L. Garcia-Esteve, and R. Martin-Santos. "Infant exposure to lithium through breast milk." European Psychiatry 64, S1 (April 2021): S180. http://dx.doi.org/10.1192/j.eurpsy.2021.477.

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IntroductionWomen who take lithium during pregnancy and continue after delivery may opt to breastfeed, formula feed, or mix these options.ObjectivesTo evaluate the neonatal lithium plasma concentrations and nursing infant outcomes based on these three feeding trajectories.MethodsWe followed 24 women with bipolar disorder on lithium monotherapy during late pregnancy and postpartum (8 per trajectory). Lithium serum concentrations were determined by an AVL 9180 electrolyte analyser with a 0.10 mEq/L detection limit and a 0.20 mEq/L limit of quantification (LoQ).ResultsThe mean ratio of lithium concentration in the umbilical cord to maternal serum being 1.12 (0.17). We used the Turnbull estimator for interval-censored data to estimate the probability that the LoQ was reached as a function of time. The median times to LoQ was 6–8, 7–8, and 53–60 days for formula, mixed, and breastfeeding, respectively. Generalised log-rank testing indicated that the median times to LoQ differed by feeding trajectory (p = 0.037). Multivariate analysis confirmed that the differences remained after adjusting for serum lithium concentrations at birth (formula, p = 0.015; mixed, p = 0.012). We did not found any acute observable growth or developmental delays in any of the neonates/infants.ConclusionsLithium did not accumulate in the infant under either exclusive or mixed-breastfeeding. Lithium concentrations declined in all trayectories. The time needed to reach the LoQ was much longer for those breastfeeding exclusively. Lithium transfer via breastmilk is much less than via the placenta. We did not found any acute observable growth or developmental delays in any infant during follow-up.DisclosureNo significant relationships.

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