Article
Chemistry, Physical
Mohammad A. Hoque, Petteri Nurmi, Arjun Kumar, Samu Varjonen, Junehwa Song, Michael G. Pecht, Sasu Tarkoma
Summary: The paper uses a public dataset to characterize battery internal resistance behavior; develops battery health prediction models for different operating conditions based on internal resistance dynamics; and demonstrates that instantaneous voltage drops due to multiple pulse discharge loads can characterize battery heterogeneity.
JOURNAL OF POWER SOURCES
(2021)
Article
Energy & Fuels
Anci Chen, Weige Zhang, Caiping Zhang, Zhihao Wang, Xinyuan Fan
Summary: A novel on-board Al-Cu ISC detection method free from dependence on voltage sampling frequency is proposed, which extracts and converts signals to continuously indicate the occurrence of Al-Cu ISC.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Multidisciplinary Sciences
T. M. M. Heenan, I. Mombrini, A. Llewellyn, S. Checchia, C. Tan, M. J. Johnson, A. Jnawali, G. Garbarino, R. Jervis, D. J. L. Brett, M. Di Michiel, P. R. Shearing
Summary: This study characterizes the temperature and mechanical strain of high-rate lithium-ion batteries using advanced synchrotron XRD methods. The results show that the discharge time and optimization strategy significantly affect the internal temperature of the battery under the same current. The temperature rise is caused by heat accumulation, which is influenced by the charging protocol and battery degradation.
Article
Chemistry, Physical
Jonas A. Braun, Rene Behmann, David Schmider, Wolfgang G. Bessler
Summary: Accurately diagnosing the SOC and SOH of batteries is crucial for battery users and manufacturers. This study presents a new algorithm that uses battery voltage as input for a voltage-controlled model to accurately estimate SOC and SOH. The algorithm is self-calibrating, robust against cell aging, allows SOH estimation from arbitrary load profiles, and is numerically simpler than state-of-the-art model-based methods.
JOURNAL OF POWER SOURCES
(2022)
Article
Energy & Fuels
Jialong Liu, Qiangling Duan, Kaixuan Qi, Yujun Liu, Jinhua Sun, Zhirong Wang, Qingsong Wang
Summary: This study investigates the aging mechanisms and state of health prediction of lithium-ion batteries throughout their lifespan. Battery capacity fading is divided into three stages: stable fading, fast fading, and repetition between capacity increase and decrease. Incremental capacity analysis and electrochemical impedance spectroscopy are used to study relevant aging mechanisms. In the first stage, aging mechanisms include loss of lithium and active material at both electrodes. In the second stage, aging mechanisms are loss of lithium and active material at the negative electrode. In the third stage, the loss of lithium is recovered to increase capacity. Finally, a back propagation neural network optimized by genetic algorithm is used to predict the state of health of lithium-ion batteries, including cycle life, second-life use, and residual capacity.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Green & Sustainable Science & Technology
Bo Yang, Yucun Qian, Qiang Li, Qian Chen, Jiyang Wu, Enbo Luo, Rui Xie, Ruyi Zheng, Yunfeng Yan, Shi Su, Jingbo Wang
Summary: The rapid development of lithium-ion battery technology has led to its widespread use in electric vehicles, aerospace, and mobile electronics. Accurate estimation of the state of health of lithium-ion batteries is a challenging task, and previous reviews have had deficiencies in classification, summary, and evaluation of estimation methods. This comprehensive review investigates and discusses 190 relevant studies, providing a thorough analysis of different perspectives on the definition of state of health, representative battery models, commonly used evaluation criteria, and explicit estimation schemes. The review also addresses the main problems and challenges in state of health estimation, proposes future development trends, and summarizes essential public datasets. Overall, this review offers valuable guidance for researchers and engineers working on state of health estimation and promotes further development in this field.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Article
Chemistry, Analytical
Shirui Feng, Anchen Wang, Jing Cai, Hongfu Zuo, Ying Zhang
Summary: This paper proposes a multi-source information fusion method based on the Gaussian mixture model and Bayesian inference distance for assessing the health status of vehicle batteries. The method accurately evaluates the state of the battery and reduces safety hazards during normal operation of electric vehicles.
Article
Energy & Fuels
Yuanyuan Li, Daniel-Ioan Stroe, Yuhua Cheng, Hanmin Sheng, Xin Sui, Remus Teodorescu
Summary: This study extracts health indicators from battery current, voltage, and temperature data based on laboratory measured experimental data to improve the accuracy in battery health estimation. Grey relation analysis quantifies the correlation between health indicators and battery capacity degradation, showing that most health indicators are closely related to battery heath, with correlation degree values mostly above 90%.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Energy & Fuels
Edoardo Locorotondo, Vincenzo Cultrera, Luca Pugi, Lorenzo Berzi, Marco Pierini, Giovanni Lutzemberger
Summary: This paper introduces a new diagnostic method for detecting battery state of health (SOH) using fast impedance measurements, achieved by applying a broad current signal excitation on the battery. Experimental results demonstrate the method's accuracy and potential as a solution for real-time diagnostic of battery SOH.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Energy & Fuels
Tae -Won Noh, Dong Hwan Kim, Byoung Kuk Lee
Summary: In this study, a novel online state-of-health (SOH) estimation algorithm for electric vehicles (EVs) is proposed based on the compression ratio of open circuit voltage (OCV)-to-charged capacity curve. The proposed algorithm estimates the degraded capacity at every sampling time during the driving operation through a first-order low-pass filter, which does not require complex mathematical tools and numerous offline data.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Bowen Yang, Dafang Wang, Bi Zhang, Shiqin Chen, Xu Sun, Tao Wang
Summary: Based on microscopic morphological changes, this paper proposes the evolving agglomerate fracture and growing SEI film as key factors driving the aging of lithium-ion batteries. The aging and impedance changes are represented by the fracture expansion of secondary particles and thickness growth of the SEI layer, resulting in an impedance model capable of approximating the electrochemical impedance spectrum. The parameters related to the state of health (SOH), such as fracture depth and SEI film thickness, exhibit correlation with morphological development, providing a convenient method for estimating the SOH of LIB.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Thermodynamics
Feiyu Xiao, Bobin Xing, Lingzhao Kong, Yong Xia
Summary: Recent technical advances are crucial for the development of electric vehicles, but there are still technical bottlenecks in the application of lithium-ion batteries, including how to detect mechanical deformation-induced short circuits and fires. This study proposes an approach based on electrochemical impedance spectroscopy to diagnose early internal mechanical damage of large-format LIBs.
Article
Energy & Fuels
Hanmin Sheng, Yuan Zhou, Libing Bai, Lei Shi
Summary: The data-driven approach is a hot topic in battery state of health (SOH) estimation. In existing research, a portable model is needed to deal with different battery objects and their characteristics. To address this, a novel cross-manifold transfer learning method is proposed, which achieves SOH estimation with a small amount of target data by embedding relevant information from related tasks.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Lingfeng Fan, Ping Wang, Ze Cheng
Summary: This paper introduces a remaining capacity prediction technique for lithium-ion batteries based on partial charging curve and health feature fusion, with a battery aging model established by Gaussian process regression. The reliability and accuracy of the proposed method are validated on six battery data sets from NASA and the University of Oxford.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Energy & Fuels
Simone Barcellona, Silvia Colnago, Giovanni Dotelli, Saverio Latorrata, Luigi Piegari
Summary: This study analyzes the relationship between internal resistance of lithium batteries and temperature, state of charge, and aging. The proposed mathematical model is validated through experimental tests and a chemical interpretation of the observed phenomena is provided.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Automation & Control Systems
Johannes Mueller, Michael Buchholz
Summary: Subjective Logic (SL) is a powerful extension of classical probability theory that excels in handling small sample sizes and statistical uncertainty, but has received limited attention in the field of automation. This work introduces a new urn model intuition to connect SL with the Polya urn scheme, demonstrating the application of SL-based reliability estimation in automation, specifically in the domain of connected automated driving.
AT-AUTOMATISIERUNGSTECHNIK
(2021)
Article
Energy & Fuels
Sebastian Menner, Jochen Siehr, Michael Buchholz
Summary: This study combines advantages of both approaches by simulating a large-format pouch cell segmented by a suitable parallel connection of smaller cells, investigating the influence of uneven heat distributions on local cell currents. A linear relationship between the current distribution and the temperature gradient across the cell was found, especially more significant at lower temperatures. The findings from the parallel connection can be transferred to the large-size cell, allowing for modeling correlations without extensive material parameters.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Instruments & Instrumentation
Christian Kinzig, Markus Horn, Martin Lauer, Michael Buchholz, Christoph Stiller, Klaus Dietmayer
Summary: This article describes the procedure for calibrating the full sensor setup of a modular autonomous driving platform, including camera, lidar, and radar sensors. The steps outlined in the article lead to an accurate calibration of the complete vehicle.
TM-TECHNISCHES MESSEN
(2022)
Article
Engineering, Electrical & Electronic
Michael Buchholz, Johannes Mueller, Martin Herrmann, Jan Strohbeck, Benjamin Voelz, Matthias Maier, Jonas Paczia, Oliver Stein, Hubert Rehborn, Ruediger-Walter Henn
IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE
(2022)
Article
Engineering, Civil
Johannes Mueller, Jan Strohbeck, Martin Herrmann, Michael Buchholz
Summary: Motion planning at urban intersections is a major challenge in urban automated driving, and this work addresses it with a sampling-based optimization approach. An optimal control problem is formulated to optimize for low risk and high passenger comfort, providing safety guarantees using a risk model that combines set-based methods and probabilistic approaches.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Proceedings Paper
Automation & Control Systems
Jan Strohbeck, Johannes Mueller, Martin Herrmann, Michael Buchholz
Summary: This paper presents a method that combines deep neural networks with Gaussian processes to predict future paths of vehicles or pedestrians. The proposed method generates predicted paths with uncertainty information, which can be used for risk calculation and predictive distribution evaluation in planning algorithms.
2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
(2022)
Proceedings Paper
Automation & Control Systems
Max Bastian Mertens, Johannes Muller, Michael Buchholz
Summary: This paper proposes a new maneuver planning system for cooperative connected vehicles in mixed traffic at unsignalized intersections to improve traffic efficiency. The system utilizes probabilistic multi-modal prediction and an optimization algorithm to find the best maneuvers, suitable for unsignalized intersections in urban areas.
2022 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV)
(2022)
Proceedings Paper
Automation & Control Systems
Matti Henning, Michael Buchholz, Klaus Dietmayer
Summary: Advancements in environment perception for automated agents have led to an increase in sensor data, requiring more computational resources for real-time processing. The concept of situation-awareness, which identifies relevant data based on the agents' situation, has gained research interest and is expected to become even more important in the future. This study extends the application of situation-aware environment perception to the decentralized automation architecture of the UNICARagil project and successfully reduces power consumption by 36.2% through post-processing with real-world data.
2022 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV)
(2022)
Proceedings Paper
Automation & Control Systems
Marvin Klimke, Benjamin Voelz, Michael Buchholz
Summary: This study proposes leveraging machine learning algorithms to optimize traffic flow at urban intersections by jointly planning for multiple vehicles, addressing congestion issues at urban intersections.
2022 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Thomas Griebel, Johannes Mueller, Paul Geisler, Charlotte Hermann, Martin Herrmann, Michael Buchholz, Klaus Dietmayer
Summary: This article introduces a self-assessment method for single-object tracking in clutter, based on Kalman filtering and subjective logic. It can monitor multiple aspects of reliability and significantly improve the reliability checking.
2022 25TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION 2022)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Martin Herrmann, Tim Luchterhand, Charlotte Hermann, Thomas Wodtko, Jan Strohbeck, Michael Buchholz
Summary: This article introduces a product multi-sensor generalized labeled multi-Bernoulli filter for centralized and distributed multi-sensor systems. The filter simplifies the NP-hard multidimensional k-best assignment problem in the multi-sensor multi-object update through the implementation of the Bayes parallel combination rule. By allowing for efficient, parallelizable, and distributed calculation, the filter demonstrates excellent performance. The article also corrects an oversight in the original publication and provides a mathematically clean derivation and implementation details of the filter.
2022 25TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION 2022)
(2022)
Proceedings Paper
Engineering, Aerospace
Sebastian Menner, Michael Buchholz
Summary: Knowledge of local temperature-dependent current distributions is important for battery management systems to ensure optimal operation. However, measuring current for all cells in a battery pack is not feasible, and common model-based methods are too complex for real-time application on simple computing hardware. To address this, we propose an extended model that provides reliable results for load profiles with high discharge current. We use subspace identification methods to determine this model, which is user-friendly, robust, and purely data-based. Comparing two different algorithms, both show promising results. The parameterization of this extended model is still based on few measurements, making it easy to determine, and it has low memory requirements and can meet real-time requirements on simple control units.
2022 IEEE/AIAA TRANSPORTATION ELECTRIFICATION CONFERENCE AND ELECTRIC AIRCRAFT TECHNOLOGIES SYMPOSIUM (ITEC+EATS 2022)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Thomas Griebel, Dominik Authaler, Markus Horn, Matti Henning, Michael Buchholz, Klaus Dietmayer
Summary: Radar is a critical sensor type for autonomous driving due to its robustness, but it can be affected by ghost targets or clutter, leading to errors in object detection. This study presents an approach utilizing PointNets to detect anomalous radar targets, with modifications to the PointNet architecture and development of a novel grouping variant for multi-form grouping. Evaluation on a real-world dataset in urban scenarios demonstrates promising results in detecting anomalous radar targets.
2021 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC)
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Markus Schoen, Michael Buchholz, Klaus Dietmayer
Summary: MGNet is a multi-task framework for monocular geometric scene understanding, combining panoptic segmentation and self-supervised monocular depth estimation. The model is designed for low latency and real-time inference on a single consumer-grade GPU, producing dense 3D point clouds with instance-aware semantic labels. It demonstrates competitive performance on popular autonomous driving benchmarks Cityscapes and KITTI.
2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021)
(2021)
Proceedings Paper
Engineering, Electrical & Electronic
Sebastian Menner, Michael Buchholz
Summary: The paper investigates the current distribution of parallelly connected pouch cells under inhomogeneous temperature distributions and develops a simplified model based on temperature data for calculating the current distribution, without the need for knowledge of difficult-to-determine cell parameters. The model is compared with a classic electric circuit model approach in simulations, demonstrating good results for real driving cycle applications.
2021 IEEE VEHICLE POWER AND PROPULSION CONFERENCE (VPPC)
(2021)
Article
Chemistry, Physical
Tianyu Chen, Zhibin Lu, Guangjin Zeng, Yongmin Xie, Jie Xiao, Zhifeng Xu
Summary: The study introduces a high-performance LSGM electrolyte-supported tubular DC-SOFC stack for portable applications, which shows great potential in developing into high-performing, efficient, and environmentally friendly portable power sources for distributed applications.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Wenbin Tong, Yili Chen, Shijie Gong, Shaokun Zhu, Jie Tian, Jiaqian Qin, Wenyong Chen, Shuanghong Chen
Summary: In this study, a three-dimensional porous NiO interface layer with enhanced anode dynamics is fabricated, forming a Schottky contact with the zinc substrate, allowing rapid and uniform zinc plating both inside and below the interface layer. The resulting NiO@Zn exhibits exceptional stability and high capacity retention.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Yafeng Bai, Kaidi Li, Liying Wang, Yang Gao, Xuesong Li, Xijia Yang, Wei Lu
Summary: In this study, a flexible zinc ion supercapacitor with gel electrolytes, porous alpha-MnO2@reduced graphene oxide cathode, and activated carbon/carbon cloth anode was developed. The device exhibits excellent electrochemical performance and stability, even at low temperatures, with a high cycle retention rate after 5000 cycles.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Anmol Jnawali, Matt D. R. Kok, Francesco Iacoviello, Daniel J. L. Brett, Paul R. Shearing
Summary: This article presents the results of a systematic study on the electrochemical performance and mechanical changes in two types of commercial batteries with different anode chemistry. The study reveals that the swelling of anode layers in batteries with silicon-based components causes deformations in the jelly roll structure, but the presence of a small percentage of silicon does not significantly impact the cycling performance of the cells within the relevant state-of-health range for electric vehicles (EVs). The research suggests that there is room for improving the cell capacities by increasing the silicon loading in composite anodes to meet the increasing demands on EVs.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Yohandys A. Zulueta, My Phuong Pham-Ho, Minh Tho Nguyen
Summary: Advanced atomistic simulations were used to study ion transport in the Na- and K-doped lithium disilicate Li2Si2O5. The results showed that Na and K doping significantly enhanced Li ion diffusion and conduction in the material.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Zongying Han, Hui Dong, Yanru Yang, Hao Yu, Zhibin Yang
Summary: An efficient phase inversion-impregnation approach is developed to fabricate BaO-decorated Ni8 mol% YSZ anode-supported tubular solid oxide fuel cells (SOFCs) with anti-coking properties. BaO nanoislands are successfully introduced inside the Ni-YSZ anode, leading to higher peak power densities and improved stability in methane fuel. Density functional theory calculations suggest that the loading of BaO nanoislands facilitates carbon elimination by capturing and dissociating H2O molecules to generate OH.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Suresh Mamidi, Dan Na, Baeksang Yoon, Henu Sharma, Anil D. Pathak, Kisor Kumar Sahu, Dae Young Lee, Cheul-Ro Lee, Inseok Seo
Summary: Li-CO2 batteries, which utilize CO2 and have a high energy density, are hindered in practical applications due to slow kinetics and safety hazards. This study introduces a stable and highly conductive ceramic-based solid electrolyte and a metal-organic framework catalyst to improve the safety and performance of Li-CO2 batteries. The optimized Li-CO2 cell shows outstanding specific capacity and cycle life, and the post-cycling analysis reveals the degradation mechanism of the electrodes. First-principles calculations based on density functional theory are also performed to understand the interactions between the catalyst and the host electrode. This research demonstrates the potential of MOF cathode catalyst for stable operation in Li-CO2 batteries.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Ganghua Xiang, Zhihuan Qiu, Huilong Fei, Zhigang Liu, Shuangfeng Yin, Yuen Wu
Summary: In this study, a CeFeOx-supported Pt single atoms and subnanometric clusters catalyst was developed, which exhibits enhanced catalytic activity and stability for the preferential oxidation of CO in H2-rich stream through synergistic effect.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Dimitrios Chatzogiannakis, Marcus Fehse, Maria Angeles Cabanero, Natalia Romano, Ashley Black, Damien Saurel, M. Rosa Palacin, Montse Casas-Cabanas
Summary: By coupling electrochemical testing to operando synchrotron based X-ray absorption and powder diffraction experiments, blended positive electrodes consisting of LiMn2O4 spinel (LMO) and layered LiNi0.5Mn0.3Co0.2O2 (NMC) were studied to understand their redox mechanism. It was found that blending NMC with LMO can enhance energy density at high rates, with the blend containing 25% LMO showing the best performance. Testing with a special electrochemical setup revealed that the effective current load on each blend component can vary significantly from the nominal rate and also changes with SoC. Operando studies allowed monitoring of the oxidation state evolution and changes in crystal structure, in line with the expected behavior of individual components considering their electrochemical current loads.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Chiara Cementon, Daniel Dewar, Thrinathreddy Ramireddy, Michael Brennan, Alexey M. Glushenkov
Summary: This Perspective discusses the specific power and power density of lithium-ion capacitors, highlighting the fact that their power characteristics are often underestimated. Through analysis, it is found that lithium-ion capacitors can usually achieve power densities superior to electrochemical supercapacitors, making them excellent alternatives to supercapacitors.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Weihao Wang, Hao Yu, Li Ma, Youquan Zhang, Yuejiao Chen, Libao Chen, Guichao Kuang, Liangjun Zhou, Weifeng Wei
Summary: This study achieved an improved electrolyte with excellent low-temperature and high-voltage performance by regulating the Li+ solvation structure and highly concentrating it. The electrolyte exhibited outstanding oxidation potential and high ionic conductivity under low temperature and high voltage conditions, providing a promising approach for the practical application of high-voltage LIBs.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Martin Bures, Dan Gotz, Jiri Charvat, Milos Svoboda, Jaromir Pocedic, Juraj Kosek, Alexandr Zubov, Petr Mazur
Summary: Vanadium redox flow battery is a promising energy storage solution with long-term durability, non-flammability, and high overall efficiency. Researchers have developed a mathematical model to simulate the charge-discharge cycling of the battery, and found that hydraulic connection of electrolyte tanks is the most effective strategy to reduce capacity losses, achieving a 69% reduction.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
M. Rodriguez-Gomez, J. Campo, A. Orera, F. de La Fuente, J. Valenciano, H. Fricke, D. S. Hussey, Y. Chen, D. Yu, K. An, A. Larrea
Summary: In this study, we analysed the operando performance of industrial lead cells using neutron diffraction experiments. The experiments revealed the evolution of different phases in the positive electrode, showed significant inhomogeneity of phase distribution inside the electrode, and estimated the energy efficiency of the cells.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Jiawei Liu, Chenpeng Wang, Yue Yao, Hao Ye, Yinglong Liu, Yingli Liu, Xiaoru Xu, Zhicong Chen, Huazheng Yang, Gang Wu, Libin Lei, Chao Wang, Bo Liang
Summary: The study focuses on utilizing double conductive Ni-pads as anode collectors in micro-tubular solid oxide fuel cells. The simulation results show excellent performance and stability of DCNPs, and also highlight the potential applications in various fields.
JOURNAL OF POWER SOURCES
(2024)
Article
Chemistry, Physical
Yang Wang, Kangjie Zhou, Lang Cui, Jiabing Mei, Shengnan Li, Le Li, Wei Fan, Longsheng Zhang, Tianxi Liu
Summary: This study presents a polyimide sandwiched separator (s-PIF) for improving the cycling stability of Li-metal batteries. The s-PIF separator exhibits superior mechanical property, electrolyte adsorption/retention and ion conductivity, and enables dendrite-free Li plating/stripping process.
JOURNAL OF POWER SOURCES
(2024)