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16 pages, 8439 KiB

Open AccessArticle

Apparent Aging during Accelerated Cycling Aging Test of Cylindrical Silicon Containing Li-Ion Cells

by Pablo Morales Torricos, Christian Endisch and Meinert Lewerenz

Batteries 2023, 9(4), 230; https://doi.org/10.3390/batteries9040230 - 18 Apr 2023

Cited by 3 | Viewed by 2264

Accelerated cyclic aging tests are very important for research and industry to quickly characterize lithium-ion cells. However, the accentuation of stress factors and the elimination of rest periods lead to an apparent capacity fade, that can be subsequently recovered during a resting phase. [...] Read more.

Accelerated cyclic aging tests are very important for research and industry to quickly characterize lithium-ion cells. However, the accentuation of stress factors and the elimination of rest periods lead to an apparent capacity fade, that can be subsequently recovered during a resting phase. This effect is attributed to the inhomogeneous lithium distribution in the anode and is observable with differential voltage analysis (DVA). We tested cylindrical 18,650 cells with Li(Ni_xCo_yAl_z)O₂-graphite/silicon chemistry during two cycling and resting phases. The capacity, the pulse resistance, the DVA, and the capacity difference analysis are evaluated for cells cycled at different average SOC and current rates. An apparent capacity loss of up to 12% was reported after 200 FCE for cells cycled under the presence of pressure gradients, while only 1% were at low-pressure gradients. The subsequent recovery was up to 80% of the apparent capacity loss in some cases. The impact of silicon cannot be estimated as it shows no features in the dV/dQ curves. We observe a recovery of apparent resistance increase, which is not reported for cells with pure graphite anodes. Finally, we demonstrate the strong impact of apparent aging for the lifetime prediction based on standard accelerated cyclic aging tests. Full article

(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms, 2nd Edition)

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16 pages, 3701 KiB

Open AccessArticle

Aging of a Lithium-Metal/LFP Cell: Predictive Model and Experimental Validation

by Davide Dessantis, Piera Di Prima, Daniele Versaci, Julia Amici, Carlotta Francia, Silvia Bodoardo and Massimo Santarelli

Batteries 2023, 9(3), 146; https://doi.org/10.3390/batteries9030146 - 24 Feb 2023

Cited by 3 | Viewed by 2907

Abstract

Actual market requirements for storage systems highlight the limits of graphite as an anode for Li-ion batteries. Lithium metal can represent a suitable alternative to graphite due to its high theoretical specific capacity (about 3860 mAh g⁻¹) and low negative redox [...] Read more.

Actual market requirements for storage systems highlight the limits of graphite as an anode for Li-ion batteries. Lithium metal can represent a suitable alternative to graphite due to its high theoretical specific capacity (about 3860 mAh g⁻¹) and low negative redox potential. However, several aging mechanisms, such as dendrite growth, lithium loss and the formation of an unstable SEI, decrease the performances of Li-based batteries. A suitable strategy to better understand and study these mechanisms could be the development of an electrochemical model that forecasts the aging behaviour of a lithium-metal battery. In this work, a P2D aging electrochemical model for an Li-based cell was developed. The main innovation is represented by the combination of two aspects: the substitution of graphite with metallic lithium as an anode and the implementation of SEI growth on the metallic lithium surface. The calibration of the model, based on experimental measurements and the successive validation, led to us obtaining a good accuracy between the simulated and experimental curves. This good accuracy makes the developed P2D aging model a versatile and suitable approach for further investigations on Li-based batteries considering all the aging phenomena involved. Full article

(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms, 2nd Edition)

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20 pages, 5926 KiB

Open AccessArticle

Estimation of Lithium-ion Battery Discharge Capacity by Integrating Optimized Explainable-AI and Stacked LSTM Model

by Vinay Vakharia, Milind Shah, Pranav Nair, Himanshu Borade, Pankaj Sahlot and Vishal Wankhede

Batteries 2023, 9(2), 125; https://doi.org/10.3390/batteries9020125 - 09 Feb 2023

Cited by 31 | Viewed by 3699

Abstract

Accurate lithium-ion battery state of health evaluation is crucial for correctly operating and managing battery-based energy storage systems. Experimental determination is problematic in these applications since standard functioning is necessary. Machine learning techniques enable accurate and effective data-driven predictions in such situations. In [...] Read more.

Accurate lithium-ion battery state of health evaluation is crucial for correctly operating and managing battery-based energy storage systems. Experimental determination is problematic in these applications since standard functioning is necessary. Machine learning techniques enable accurate and effective data-driven predictions in such situations. In the present paper, an optimized explainable artificial intelligence (Ex-AI) model is proposed to predict the discharge capacity of the battery. In the initial stage, three deep learning (DL) models, stacked long short-term memory networks (stacked LSTMs), gated recurrent unit (GRU) networks, and stacked recurrent neural networks (SRNNs) were developed based on the training of six input features. Ex-AI was applied to identify the relevant features and further optimize Ex-AI operating parameters, and the jellyfish metaheuristic optimization technique was considered. The results reveal that discharge capacity was better predicted when the jellyfish-Ex-AI model was applied. A very low RMSE of 0.04, MAE of 0.60, and MAPE of 0.03 were observed with the Stacked-LSTM model, demonstrating our proposed methodology’s utility. Full article

(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms, 2nd Edition)

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22 pages, 5346 KiB

Open AccessArticle

Comprehensive Degradation Analysis of NCA Li-Ion Batteries via Methods of Electrochemical Characterisation for Various Stress-Inducing Scenarios

by Martin Kemeny, Peter Ondrejka and Miroslav Mikolasek

Batteries 2023, 9(1), 33; https://doi.org/10.3390/batteries9010033 - 01 Jan 2023

Cited by 3 | Viewed by 4738

Abstract

Lithium-ion (Li-ion) batteries with Ni-based cathodes are leading storage technology in the fields of electric vehicles and power-grid applications. NCA (LiNiCoAlO₂) batteries are known for their troublesome degradation tendencies, and this susceptibility to degradation raises questions regarding the safety of their [...] Read more.

Lithium-ion (Li-ion) batteries with Ni-based cathodes are leading storage technology in the fields of electric vehicles and power-grid applications. NCA (LiNiCoAlO₂) batteries are known for their troublesome degradation tendencies, and this susceptibility to degradation raises questions regarding the safety of their usage. Hence, it is of vital importance to analyse the degradation of NCA batteries via methods which are applicable to onboard systems, so that the changes in the battery’s state of health can be addressed accordingly. For this purpose, it is crucial to study batteries stressed by various conditions which might induce degradation of different origins or magnitudes. Methods such as electrochemical impedance spectroscopy (EIS), galvanostatic intermittent titration technique (GITT), and incremental capacity analysis (ICA) have been used in battery research for years, however, there is a lack of published studies which would analyse the degradation of NCA batteries by simultaneous usage of these methods, which is essential for a comprehensive and confirmatory understanding of battery degradation. This study intends to fill this research gap by analysing the degradation of NCA batteries via simultaneous usage of EIS, GITT, and ICA methods for common stress-inducing operating conditions (over-charge, over-discharge, and high-current charging). Full article

(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms, 2nd Edition)

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17 pages, 3743 KiB

Open AccessArticle

Development of an Innovative Procedure for Lithium Plating Limitation and Characterization of 18650 Cycle Aged Cells for DCFC Automotive Applications

by Matteo Dotoli, Emanuele Milo, Mattia Giuliano, Arianna Tiozzo, Marcello Baricco, Carlo Nervi, Massimiliano Ercole and Mauro Francesco Sgroi

Batteries 2022, 8(8), 88; https://doi.org/10.3390/batteries8080088 - 14 Aug 2022

Cited by 4 | Viewed by 2911

Abstract

Since lithium-ion batteries seem to be the most eligible technology to store energy for e-mobility applications, it is fundamental to focus attention on kilometric ranges and charging times. The optimization of the charging step can provide the appropriate tradeoff between time saving and [...] Read more.

Since lithium-ion batteries seem to be the most eligible technology to store energy for e-mobility applications, it is fundamental to focus attention on kilometric ranges and charging times. The optimization of the charging step can provide the appropriate tradeoff between time saving and preserving cell performance over the life cycle. The implementation of new multistage constant current profiles and related performances after 1000 cycles are presented and compared with respect to a reference profile. A physicochemical (SEM, XRD, particle size analysis, etc.) and electrochemical (incremental capacity analysis, internal resistance measurements) characterization of the aged cells is shown and their possible implementation on board is discussed. Full article

(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms, 2nd Edition)

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18 pages, 2664 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Influence of the Ambient Storage of LiNi_0.8Mn_0.1Co_0.1O₂ Powder and Electrodes on the Electrochemical Performance in Li-ion Technology

by Iratxe de Meatza, Imanol Landa-Medrano, Susan Sananes-Israel, Aitor Eguia-Barrio, Oleksandr Bondarchuk, Silvia Lijó-Pando, Iker Boyano, Verónica Palomares, Teófilo Rojo, Hans-Jürgen Grande and Idoia Urdampilleta

Batteries 2022, 8(8), 79; https://doi.org/10.3390/batteries8080079 - 28 Jul 2022

Cited by 2 | Viewed by 3577

Abstract

Nickel-rich LiNi_0.8Mn_0.1Co_0.1O₂ (NMC811) is one of the most promising Li-ion battery cathode materials and has attracted the interest of the automotive industry. Nevertheless, storage conditions can affect its properties and performance. In this work, both NMC811 [...] Read more.

Nickel-rich LiNi_0.8Mn_0.1Co_0.1O₂ (NMC811) is one of the most promising Li-ion battery cathode materials and has attracted the interest of the automotive industry. Nevertheless, storage conditions can affect its properties and performance. In this work, both NMC811 powder and electrodes were storage-aged for one year under room conditions. The aged powder was used to prepare electrodes, and the performance of these two aged samples was compared with reference fresh NMC811 electrodes in full Li-ion coin cells using graphite as a negative electrode. The cells were subjected to electrochemical as well as ante- and postmortem characterization. The performance of the electrodes from aged NM811 was beyond expectations: the cycling performance was high, and the power capability was the highest among the samples analyzed. Materials characterization revealed modifications in the crystal structure and the surface layer of the NMC811 during the storage and electrode processing steps. Differences between aged and fresh electrodes were explained by the formation of a resistive layer at the surface of the former. However, the ageing of NMC811 powder was significantly mitigated during the electrode processing step. These novel results are of interest to cell manufacturers for the widespread implementation of NMC811 as a state-of-the-art cathode material in Li-ion batteries. Full article

(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms, 2nd Edition)

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22 pages, 7973 KiB

Open AccessArticle

Method for In-Operando Contamination of Lithium Ion Batteries for Prediction of Impurity-Induced Non-Obvious Cell Damage

by Patrick Höschele, Simon Franz Heindl, Bernd Schneider, Wolfgang Sinz and Christian Ellersdorfer

Batteries 2022, 8(4), 35; https://doi.org/10.3390/batteries8040035 - 14 Apr 2022

Cited by 1 | Viewed by 3213

Abstract

The safety of lithium-ion batteries within electrified vehicles plays an important role. Hazards can arise from contaminated batteries resulting from non-obvious damages or insufficient production processes. A systematic examination requires experimental methods to provoke a defined contamination. Two prerequisites were required: First, the [...] Read more.

The safety of lithium-ion batteries within electrified vehicles plays an important role. Hazards can arise from contaminated batteries resulting from non-obvious damages or insufficient production processes. A systematic examination requires experimental methods to provoke a defined contamination. Two prerequisites were required: First, the extent and type of contamination should be determinable to exclude randomness. Second, specimens should work properly before the contamination, enabling realistic behavior. In this study, two experimental methods were developed to allow for the first time a controlled and reproducible application of water or oxygen into 11 single-layer full cells (Li₄Ti₅O₁₂/LiCoO₂) used as specimens during electrical cycling. Electrochemical impedance spectroscopy was used to continuously monitor the specimens and to fit the parameters of an equivalent circuit model (ECM). For the first time, these parameters were used to calibrate a machine-learning algorithm which was able to predict the contamination state. A decision tree was calibrated with the ECM parameters of eight specimens (training data) and was validated by predicting the contamination state of the three remaining specimens (test data). The prediction quality proved the usability of classification algorithms to monitor for contaminations or non-obvious battery damage after manufacturing and during use. It can be an integral part of battery management systems that increases vehicle safety. Full article

(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms, 2nd Edition)

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21 pages, 4042 KiB

Open AccessArticle

The Battery Life Estimation of a Battery under Different Stress Conditions

by Natascia Andrenacci, Francesco Vellucci and Vincenzo Sglavo

Batteries 2021, 7(4), 88; https://doi.org/10.3390/batteries7040088 - 18 Dec 2021

Cited by 9 | Viewed by 5297

Abstract

The prediction of capacity degradation, and more generally of the behaviors related to battery aging, is useful in the design and use phases of a battery to help improve the efficiency and reliability of energy systems. In this paper, a stochastic model for [...] Read more.

The prediction of capacity degradation, and more generally of the behaviors related to battery aging, is useful in the design and use phases of a battery to help improve the efficiency and reliability of energy systems. In this paper, a stochastic model for the prediction of battery cell degradation is presented. The proposed model takes its cue from an approach based on Markov chains, although it is not comparable to a Markov process, as the transition probabilities vary with the number of cycles that the cell has performed. The proposed model can reproduce the abrupt decrease in the capacity that occurs near the end of life condition (80% of the nominal value of the capacity) for the cells analyzed. Furthermore, we illustrate the ability of this model to predict the capacity trend for a lithium-ion cell with nickel manganese cobalt (NMC) at the cathode and graphite at the anode, subjected to a life cycle in which there are different aging factors, using the results obtained for cells subjected to single aging factors. Full article

(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms, 2nd Edition)

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18 pages, 4459 KiB

Open AccessEditor’s ChoiceArticle

Identification of Degradation Mechanisms by Post-Mortem Analysis for High Power and High Energy Commercial Li-Ion Cells after Electric Vehicle Aging

by Pierre Kuntz, Olivier Raccurt, Philippe Azaïs, Karsten Richter, Thomas Waldmann, Margret Wohlfahrt-Mehrens, Michel Bardet, Anton Buzlukov and Sylvie Genies

Batteries 2021, 7(3), 48; https://doi.org/10.3390/batteries7030048 - 16 Jul 2021

Cited by 19 | Viewed by 6548

Abstract

Driven by the rise of the electric automotive industry, the Li-ion battery market is in strong expansion. This technology does not only fulfill the requirements of electric mobility, but is also found in most portable electric devices. Even though Li-ion batteries are known [...] Read more.

Driven by the rise of the electric automotive industry, the Li-ion battery market is in strong expansion. This technology does not only fulfill the requirements of electric mobility, but is also found in most portable electric devices. Even though Li-ion batteries are known for their numerous advantages, they undergo serious performance degradation during their aging, and more particularly when used in specific conditions such as at low temperature or high charging current rates. Depending on the operational conditions, different aging mechanisms are favored and can induce physical and chemical modifications of the internal components, leading to performance decay. In this article, the identification of the degradation mechanisms was carried out thanks to an in-depth ante- and post mortem study on three high power and high energy commercial 18,650 cells. Li-ion cells were aged using a battery electric vehicle (BEV) aging profile at −20 °C, 0 °C, 25 °C, and 45 °C in accordance with the international standard IEC 62-660, and in calendar aging mode at 45 °C and SOC 100%. Internal components recovered from fresh and aged cells were investigated through different electrochemical (half-coin cell), chemical (EDX, GD-OES, NMR), and topological (SEM) characterization techniques. The influence of power and energy cells’ internal design and Si content in the negative electrode on cell aging has been highlighted vis-à-vis the capacity and power fade. Full article

(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms, 2nd Edition)

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13 pages, 3161 KiB

Open AccessEditor’s ChoiceArticle

Detection of Lithium Plating in Li-Ion Cell Anodes Using Realistic Automotive Fast-Charge Profiles

by Matteo Dotoli, Emanuele Milo, Mattia Giuliano, Riccardo Rocca, Carlo Nervi, Marcello Baricco, Massimiliano Ercole and Mauro Francesco Sgroi

Batteries 2021, 7(3), 46; https://doi.org/10.3390/batteries7030046 - 07 Jul 2021

Cited by 13 | Viewed by 6407

Abstract

The widespread use of electric vehicles is nowadays limited by the “range anxiety” of the customers. The drivers’ main concerns are related to the kilometric range of the vehicle and to the charging time. An optimized fast-charge profile can help to decrease the [...] Read more.

The widespread use of electric vehicles is nowadays limited by the “range anxiety” of the customers. The drivers’ main concerns are related to the kilometric range of the vehicle and to the charging time. An optimized fast-charge profile can help to decrease the charging time, without degrading the cell performance and reducing the cycle life. One of the main reasons for battery capacity fade is linked to the Lithium plating phenomenon. This work investigates two methodologies, i.e., three-electrode cell measurement and internal resistance evolution during charging, for detecting the Lithium plating conditions. From this preliminary analysis, it was possible to develop new Multi-Stage Constant-Current profiles, designed to improve the performance in terms of charging time and cells capacity retention with respect to a reference profile. Four new profiles were tested and compared to a reference. The results coming from the new profiles demonstrate a simultaneous improvement in terms of charging time and cycling life, showing the reliability of the implemented methodology in preventing Lithium plating. Full article

(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms, 2nd Edition)

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13 pages, 34487 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

An ASIC-Based Miniaturized System for Online Multi-Measurand Monitoring of Lithium-Ion Batteries

by Giuseppe Manfredini, Andrea Ria, Paolo Bruschi, Luca Gerevini, Michele Vitelli, Mario Molinara and Massimo Piotto

Batteries 2021, 7(3), 45; https://doi.org/10.3390/batteries7030045 - 05 Jul 2021

Cited by 11 | Viewed by 4559

Abstract

To better asses the ageing and to reduce the hazards involved in the use of Lithium-Ion Batteries, multi-measurand monitoring units and strategies are urged. In this paper, a Cell Management Unit, based on the SENSIPLUS chip, a recently introduced multichannel, multi-mode sensor interface, [...] Read more.

To better asses the ageing and to reduce the hazards involved in the use of Lithium-Ion Batteries, multi-measurand monitoring units and strategies are urged. In this paper, a Cell Management Unit, based on the SENSIPLUS chip, a recently introduced multichannel, multi-mode sensor interface, is described. SENSIPLUS is a single System on a Chip combined with a reduced number of external components, resulting in a highly miniaturized device, built on 20 × 8 mm² printed circuit board. Thanks to SENSIPLUS’ versatility, the proposed system is capable of performing direct measurements (EIS, cell voltage) on the cell it is applied to, and reading different kinds of sensors. The SENSIPLUS versatile digital communication interface, combined with a digital isolator, enable connection of several devices to a single bus for parallel monitoring a large number of cells connected in series. Experiments performed by connecting the proposed system to a commercial Lithium-Ion Battery and to capacitive and resistive sensors are described. In particular, the capability of measuring the cell internal impedance with a resolution of 120 μΩ is demonstrated. Full article

(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms, 2nd Edition)

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11 pages, 1299 KiB

Open AccessArticle

Thermal Conductivity in Aged Li-Ion Cells under Various Compression Conditions and State-of-Charge

by Georgi Kovachev, Andrea Astner, Gregor Gstrein, Luigi Aiello, Johann Hemmer, Wolfgang Sinz and Christian Ellersdorfer

Batteries 2021, 7(3), 42; https://doi.org/10.3390/batteries7030042 - 25 Jun 2021

Cited by 15 | Viewed by 5037

Abstract

Thermal conductivity (TC) is a parameter, which significantly influences the spatial temperature gradients of lithium ion batteries in operative or abuse conditions. It affects the dissipation of the generated heat by the cell during normal operation or during thermal runaway propagation from one [...] Read more.

Thermal conductivity (TC) is a parameter, which significantly influences the spatial temperature gradients of lithium ion batteries in operative or abuse conditions. It affects the dissipation of the generated heat by the cell during normal operation or during thermal runaway propagation from one cell to the next after an external short circuit. Hence, the thermal conductivity is a parameter of great importance, which concurs to assess the safety of a Li-ion battery. In this work, an already validated, non-destructive measurement procedure was adopted for the determination of the evolution of the through-plane thermal conductivity of 41 Ah commercially available Li-ion pouch cells (LiNiMnCoO₂-LiMn₂O₄/Graphite) as function of battery lifetime and state of charge (SOC). Results show a negative parabolic behaviour of the thermal conductivity over the battery SOC-range. In addition, an average decrease of TC in thickness direction of around 4% and 23% was measured for cells cycled at 60 °C with and without compression, respectively. It was shown that pretension force during cycling reduces battery degradation and thus minimises the effect of ageing on the thermal parameter deterioration. Nevertheless, this study highlights the need of adjustment of the battery pack cooling system due to the deterioration of thermal conductivity after certain battery lifetime with the aim of reducing the risk of battery overheating after certain product life. Full article

(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms, 2nd Edition)

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Review

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23 pages, 7713 KiB

Open AccessEditor’s ChoiceReview

Recent Health Diagnosis Methods for Lithium-Ion Batteries

by Yaqi Li, Jia Guo, Kjeld Pedersen, Leonid Gurevich and Daniel-Ioan Stroe

Batteries 2022, 8(7), 72; https://doi.org/10.3390/batteries8070072 - 15 Jul 2022

Cited by 7 | Viewed by 4121

Abstract

Lithium-ion batteries have good performance and environmentally friendly characteristics, so they have great potential. However, lithium-ion batteries will age to varying degrees during use, and the process is irreversible. There are many aging mechanisms of lithium batteries. In order to better verify the [...] Read more.

Lithium-ion batteries have good performance and environmentally friendly characteristics, so they have great potential. However, lithium-ion batteries will age to varying degrees during use, and the process is irreversible. There are many aging mechanisms of lithium batteries. In order to better verify the internal changes of lithium batteries when they are aging, post-mortem analysis has been greatly developed. In this article, we summarized the electrical properties analysis and post-mortem analysis of lithium batteries developed in recent years and compared the advantages of varieties of both destructive and non-destructive methods, for example, open-circuit-voltage curve-based analysis, scanning electron microscopy, transmission electron microscopy, atomic force microscopy, X-ray photoelectron spectroscopy and X-ray diffraction. On this basis, new ideas could be proposed for predicting and diagnosing the aging degree of lithium batteries, at the same time, further implementation of these technologies will support battery life control strategies and battery design. Full article

(This article belongs to the Special Issue Lithium-Ion Batteries Aging Mechanisms, 2nd Edition)

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