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Batteries, Volume 11, Issue 8 (August 2025) – 36 articles

Cover Story (view full-size image): Lithium metal is a promising anode for next-generation batteries, but its processing is challenging due to high reactivity and poor machinability. This study investigates laser cutting as a non-contact alternative to mechanical separation, comparing nanosecond and picosecond pulse durations. Analysis of cutting-edge quality, heat-affected zones, and melt formation shows that shorter pulses reduce thermal damage and improve electrode integrity. Electrochemical tests in symmetric Li|Li cells reveal that laser-cut anodes outperform mechanically separated ones, exhibiting improved cycling stability despite locally inactive lithium. These results highlight optimized laser processing as a key step toward reliable lithium metal anodes for solid-state batteries. View this paper
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18 pages, 3297 KB  
Article
A Framework for Anomaly Cell Detection in Energy Storage Systems Based on Daily Operating Voltage and Capacity Increment Curves
by Wanchen Liu, Zhihao Zhang, Zekai Zhao and Wenjie Zhang
Batteries 2025, 11(8), 316; https://doi.org/10.3390/batteries11080316 - 20 Aug 2025
Viewed by 538
Abstract
This paper proposes a novel unsupervised multi-model fusion framework for robust cell-level anomaly detection in grid-scale battery energy storage systems (BESSs). Addressing the complex nonlinearity and prevalent data quality issues (e.g., asynchronous sensors, sampling anomalies) in historical operational data, the framework synergistically integrates [...] Read more.
This paper proposes a novel unsupervised multi-model fusion framework for robust cell-level anomaly detection in grid-scale battery energy storage systems (BESSs). Addressing the complex nonlinearity and prevalent data quality issues (e.g., asynchronous sensors, sampling anomalies) in historical operational data, the framework synergistically integrates three complementary techniques: isolation forests for efficient feature screening and dimensionality reduction; LSTM autoencoders to capture the long-term temporal dependencies in normal behavior; and a functional principal component analysis–Mahalanobis distance (FPCA-MD) for statistically rigorous anomaly validation. The fully automated workflow pioneers the combined application of feature screening, temporal modeling, and functional data validation for cell-level diagnostics. Key contributions include (1) maintaining a high detection accuracy despite asynchronous or faulty sensor data; (2) leveraging multi-dimensional operational features beyond traditional voltage curves, optimizing the utilization of historical data through tight integration of the battery characteristics with anomaly signatures; and (3) achieving enhanced performance and robustness via the complementary fusion of diverse algorithms. Comprehensive experimental results demonstrate the framework’s effectiveness in accurately identifying cells exhibiting various anomaly patterns (e.g., noise interference, performance degradation, cluster outliers) while significantly reducing the leakage and misdetection rates inherent in single-algorithm approaches, as validated by the probability scores from the fusion output. Full article
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31 pages, 7431 KB  
Review
Breaking the Polarization Bottleneck: Innovative Pathways to High-Performance Metal–Air Batteries
by Biao Ma, Deling Hong, Xiangfeng Wei and Jiehua Liu
Batteries 2025, 11(8), 315; https://doi.org/10.3390/batteries11080315 - 19 Aug 2025
Viewed by 929
Abstract
Metal–air batteries have excellent theoretical energy density and economic advantages through abundant anode materials and open cathode structures. However, the actual energy efficiency of metal–air batteries is much lower than the theoretical value due to the effect of polarization voltage during battery operation, [...] Read more.
Metal–air batteries have excellent theoretical energy density and economic advantages through abundant anode materials and open cathode structures. However, the actual energy efficiency of metal–air batteries is much lower than the theoretical value due to the effect of polarization voltage during battery operation, limiting the power output and thus hindering their practical application. This review systematically dissects the origins of polarization: slow oxygen reduction/evolution reaction (ORR/OER) kinetics, interfacial resistance, and mass transfer bottlenecks. We highlight cutting-edge strategies to mitigate polarization, including atomic-level engineering of air cathodes (e.g., single-atom catalysts, low Pt catalysts), biomass-derived 3D porous electrodes, and electrolyte innovations (additives to inhibit corrosion, solid-state electrolytes to improve stability). In addition, breakthroughs in metal–H2O2 battery design using concentrated liquid oxygen sources are discussed. Together, these advances alleviate the battery polarization bottleneck and pave the way for practical applications of metal–air batteries in electric vehicles, drones, and deep-sea devices. Full article
(This article belongs to the Special Issue Batteries: 10th Anniversary)
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18 pages, 13041 KB  
Article
Experimental Testing and Modeling of Li-Ion Battery Performance Based on IEC 62660-1 Standard
by Zoi Voltsi and Costas Elmasides
Batteries 2025, 11(8), 314; https://doi.org/10.3390/batteries11080314 - 17 Aug 2025
Cited by 1 | Viewed by 981
Abstract
The adoption of sustainable and environmentally friendly solutions is becoming crucial across several sectors, particularly in transportation. As part of this transition, the transport industry has turned its attention to electric vehicle (EV) development and the deployment of electric batteries. This study provides [...] Read more.
The adoption of sustainable and environmentally friendly solutions is becoming crucial across several sectors, particularly in transportation. As part of this transition, the transport industry has turned its attention to electric vehicle (EV) development and the deployment of electric batteries. This study provides a comprehensive analysis of the performance of EV batteries, integrating both experimental measurements and simulations. The experimental section involved a series of tests conducted on real batteries under various operating conditions, focusing on different charging and discharging rates. Additionally, the IEC 62660-1 standard was applied, to evaluate their performance under realistic usage scenarios. Moreover, a theoretical model was developed in order to simulate the batteries’ behavior and replicate the observed experimental data. A comparison between the simulation outputs and experimental data was conducted, demonstrating the accuracy of the model. This work provides valuable insights into the performance of EV batteries and lays the foundation for optimization in future applications. Full article
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21 pages, 3124 KB  
Article
Systematic Characterization of Lithium-Ion Cells for Electric Mobility and Grid Storage: A Case Study on Samsung INR21700-50G
by Saroj Paudel, Jiangfeng Zhang, Beshah Ayalew and Rajendra Singh
Batteries 2025, 11(8), 313; https://doi.org/10.3390/batteries11080313 - 16 Aug 2025
Viewed by 526
Abstract
Accurate parametric modeling of lithium-ion batteries is essential for battery management system (BMS) design in electric vehicles and broader energy storage applications, enabling reliable state estimation and effective thermal control under diverse operating conditions. This study presents a detailed characterization of lithium-ion cells [...] Read more.
Accurate parametric modeling of lithium-ion batteries is essential for battery management system (BMS) design in electric vehicles and broader energy storage applications, enabling reliable state estimation and effective thermal control under diverse operating conditions. This study presents a detailed characterization of lithium-ion cells to support advanced BMS in electric vehicles and stationary storage. A second-order equivalent circuit model is developed to capture instantaneous and dynamic voltage behavior, with parameters extracted through Hybrid Pulse Power Characterization over a broad range of temperatures (−10 °C to 45 °C) and state-of-charge levels. The method includes multi-duration pulse testing and separates ohmic and transient responses using two resistor–capacitor branches, with parameters tied to physical processes like charge transfer and diffusion. A weakly coupled electro-thermal model is presented to support real-time BMS applications, enabling accurate voltage, temperature, and heat generation prediction. This study also evaluates open-circuit voltage and direct current internal resistance across pulse durations, leading to power capability maps (“fish charts”) that capture discharge and regenerative performance across SOC and temperature. The analysis highlights performance asymmetries between charging and discharging and confirms model accuracy through curve fitting across test conditions. These contributions enhance model realism, thermal control, and power estimation for real-world lithium-ion battery applications. Full article
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24 pages, 6274 KB  
Article
Accurate Prediction of Voltage and Temperature for a Sodium-Ion Pouch Cell Using an Electro-Thermal Coupling Model
by Hekun Zhang, Zhendong Zhang, Yelin Deng and Jianxu Yu
Batteries 2025, 11(8), 312; https://doi.org/10.3390/batteries11080312 - 16 Aug 2025
Cited by 1 | Viewed by 637
Abstract
Due to their advantages, such as abundant raw material reserves, excellent thermal stability, and superior low-temperature performance, sodium-ion batteries (SIBs) exhibit significant potential for future applications in energy storage and electric vehicles. Therefore, in this study, a commercial pouch-type SIB with sodium iron [...] Read more.
Due to their advantages, such as abundant raw material reserves, excellent thermal stability, and superior low-temperature performance, sodium-ion batteries (SIBs) exhibit significant potential for future applications in energy storage and electric vehicles. Therefore, in this study, a commercial pouch-type SIB with sodium iron sulfate cathode material was investigated. Firstly, a second-order RC equivalent circuit model was established through parameter identification using multi-rate hybrid pulse power characterization (M-HPPC) tests at various temperatures. Then, both the specific heat capacity and entropy coefficient of the sodium-ion battery were measured through experiments. Building upon this, an electro-thermal coupling model was developed by incorporating a lumped-parameter thermal model that accounts for the heat generation of the tabs. Finally, the prediction performance of this model was validated through discharge tests under different temperature conditions. The results demonstrate that the proposed electro-thermal coupling model can achieve the simultaneous prediction of both temperature and voltage, providing valuable references for the future development of thermal management systems for SIBs. Full article
(This article belongs to the Special Issue Batteries: 10th Anniversary)
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14 pages, 8711 KB  
Article
Intrinsic Thermal Stability of Li-Rich Mn-Based Cathodes Enabling Safe High-Energy Lithium-Ion Batteries
by Zhaoqiang Pei, Shaobo Feng, Zhibo Han, Zihua Wang, Chengshan Xu, Xiangming He, Li Wang, Yu Wang and Xuning Feng
Batteries 2025, 11(8), 311; https://doi.org/10.3390/batteries11080311 - 15 Aug 2025
Viewed by 658
Abstract
Lithium-rich manganese-based oxides (LMR) are promising next-generation cathode materials due to their high capacity and low cost, but safety remains a critical bottleneck restricting the practical application of high-energy-density cathodes. However, the safety level of LMR batteries and the thermal failure mechanism of [...] Read more.
Lithium-rich manganese-based oxides (LMR) are promising next-generation cathode materials due to their high capacity and low cost, but safety remains a critical bottleneck restricting the practical application of high-energy-density cathodes. However, the safety level of LMR batteries and the thermal failure mechanism of the cathode are still poorly understood, especially when compared with traditional high-energy nickel-rich (Ni-rich) cathodes. Here, we investigate the LMR cell’s thermal runaway behavior and the thermal failure mechanism of the cathode. Compared to a Ni-rich cell, Accelerating Rate Calorimetry (ARC) shows the LMR pouch cell exhibits a 62.7 °C higher thermal runaway trigger temperature (T2) and 270.3 °C lower maximum temperature (T3). These results indicate that the cell utilizing a higher-energy-density LMR cathode presents significantly lower thermal runaway risks and hazards. The results of differential scanning calorimetry–thermogravimetry–mass spectrometry (DSC-TG-MS) and in situ heating X-ray diffraction (XRD) indicate that the LMR cathode has superior thermal stability compared with the Ni-rich cathode, with cathode oxygen released at higher temperatures and lower rates, which is beneficial for delaying and mitigating the exothermic reaction inside the battery. This study demonstrates that simultaneously enhancing cathode energy density and battery safety is achievable, and these findings provide theoretical guidance for the design of next-generation high-energy and high-safety battery systems. Full article
(This article belongs to the Special Issue Thermal Management System for Lithium-Ion Batteries: 2nd Edition)
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18 pages, 4380 KB  
Article
Exploring the Potential of Green Synthesized Sr0.8Ce0.2Fe0.8Co0.2O3 Using Orange and Lemon Extracts for Hybrid Supercapacitor Applications
by Asmara Fazal, M. Javaid Iqbal, Mohsin Ali Raza, Badriah S. Almutairi, Hesham M. H. Zakaly, Naureen Akhtar, Muneeb Irshad and Saira Riaz
Batteries 2025, 11(8), 310; https://doi.org/10.3390/batteries11080310 - 15 Aug 2025
Viewed by 576
Abstract
Supercapacitors are required to store energy from renewable resources to ensure a pollutant-free environment. To further encourage its study, researchers are interested in introducing green methods to produce electrode materials. Green synthesis is an innovative and emerging field because plant extracts are the [...] Read more.
Supercapacitors are required to store energy from renewable resources to ensure a pollutant-free environment. To further encourage its study, researchers are interested in introducing green methods to produce electrode materials. Green synthesis is an innovative and emerging field because plant extracts are the best substitute for toxic chemicals. They are considered eco-friendly and cost-effective. In this work, two plant extracts, orange juice (ORJ) and lemon juice (LMJ), are used to synthesize the Sr0.8Ce0.2Fe0.8Co0.2O3 perovskite using the auto-combustion method. The electrochemical performance of Sr0.8Ce0.2Fe0.8Co0.2O3 made from LMJ and ORJ is compared to check their effectiveness. LMJ proved to be a better reducing agent than ORJ with a higher specific capacity of 300 C/g (544 F/g) at 1 A/g current density due to increased oxygen vacancies and surface area. These findings show that green-synthesized perovskites can be utilized in high-performance hybrid supercapacitor devices. Full article
(This article belongs to the Section Supercapacitors)
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21 pages, 2683 KB  
Article
Referential Integrity Framework for Lithium Battery Characterization and State of Charge Estimation
by Amel Benmouna, Mohamed Becherif, Mohamed Ahmed Ebrahim, Mohamed Toufik Benchouia, Tahir Cetin Akinci, Miroslav Penchev, Alfredo Martinez-Morales and Arun S. K. Raju
Batteries 2025, 11(8), 309; https://doi.org/10.3390/batteries11080309 - 14 Aug 2025
Cited by 1 | Viewed by 493
Abstract
The global rise of electric vehicles (EVs) is reshaping the automotive industry, driven by a 25% increase in EV sales in 2024 and mounting regulatory pressure from European countries aiming to phase out thermal and hybrid vehicle production. In this context, the development [...] Read more.
The global rise of electric vehicles (EVs) is reshaping the automotive industry, driven by a 25% increase in EV sales in 2024 and mounting regulatory pressure from European countries aiming to phase out thermal and hybrid vehicle production. In this context, the development of advanced battery technologies has become a critical priority. However, progress in electrochemical storage systems remains limited due to persistent technological barriers such as gaps in data, inadequate modeling tools, and difficulties in system integration, such as thermal management and interface instability. Safety concerns like thermal runaway and the lack of long-term performance data also hinder large-scale adoption. This study presents an in-depth analysis of lithium–ion (Li–ion) batteries, with a particular focus on evaluating their charging and discharging behaviors. To facilitate this, a series of automated experiments was conducted using a custom-built test bench equipped with MATLAB (2024b) programming and dSPACE data acquisition cards, enabling precise current and voltage measurements. The acquired data were analyzed to derive mathematical models that capture the operational characteristics of Li–ion batteries. Furthermore, various state-of-charge (SoC) estimation techniques were investigated to enhance battery efficiency and improve range management in EVs. This paper contributes to the advancement of energy storage technologies and supports global ecological goals by proposing safer and more efficient solutions for the electric mobility sector. Full article
(This article belongs to the Special Issue Advances in Battery Electric Vehicles—2nd Edition)
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11 pages, 1962 KB  
Article
Cu-Substituted Na3V2(PO4)3/C Composites as High-Rate, Long-Cycle Cathodes for Sodium-Ion Batteries
by Hyeon-Jun Choi, Yu Gyeong Kim, Su Hwan Jeong, Sang Jun Lee, Young Hwa Jung and Joo-Hyung Kim
Batteries 2025, 11(8), 308; https://doi.org/10.3390/batteries11080308 - 11 Aug 2025
Viewed by 597
Abstract
The advancement of high-performance sodium-ion batteries (SIBs) necessitates cathode materials that exhibit both structural robustness and long-term electrochemical stability. Na3V2(PO4)3 (NVP), with its NASICON-type framework, is a promising candidate; however, its inherently low electronic conductivity restricts [...] Read more.
The advancement of high-performance sodium-ion batteries (SIBs) necessitates cathode materials that exhibit both structural robustness and long-term electrochemical stability. Na3V2(PO4)3 (NVP), with its NASICON-type framework, is a promising candidate; however, its inherently low electronic conductivity restricts full capacity utilization. In this study, carbon-coated and Cu-substituted Na3V2(PO4)3 (NVCP) composites were synthesized via a solid-state reaction using agarose as a carbon source. Structural and morphological analyses confirmed the successful incorporation of Cu2+ ions into the rhombohedral lattice without disrupting the crystal structure and the formation of uniform conductive carbon layers. The substitution of Cu2+ induced increased carbon disorder and partial oxidation of V3+ to V4+, contributing to enhanced electronic conductivity. Consequently, NVCP exhibited excellent long-term cycling performance, maintaining over 99% of its initial capacity after 500 cycles at 0.5 C. Furthermore, the electrode demonstrated outstanding high-rate capabilities, with a capacity recovery of 97.98% after cycling at 20 C and returning to lower current densities. These findings demonstrate that Cu substitution combined with carbon coating synergistically enhances structural integrity and Na+ transport, offering an effective approach to engineer high-performance cathodes for next-generation SIBs. Full article
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28 pages, 1374 KB  
Article
A Circuital Equivalent for Supercapacitors Accurate Simulation in Power Electronics Systems
by Catalina Rus-Casas, Carlos Andrés Ramos-Paja, Sergio Ignacio Serna-Garcés, Carlos Gilabert-Torres and Juan Domingo Aguilar-Peña
Batteries 2025, 11(8), 307; https://doi.org/10.3390/batteries11080307 - 9 Aug 2025
Viewed by 451
Abstract
The effective integration of energy storage systems is paramount for the widespread deployment of renewable energy technologies. Selection of a specific storage system is typically dictated by the primary challenge it aims to mitigate, such as intermittency, grid stability, or power quality. The [...] Read more.
The effective integration of energy storage systems is paramount for the widespread deployment of renewable energy technologies. Selection of a specific storage system is typically dictated by the primary challenge it aims to mitigate, such as intermittency, grid stability, or power quality. The optimization of overall system efficiency and longevity is increasingly achieved through hybrid storage systems that integrate supercapacitors into their designs. This research introduces a novel circuital equivalent for a commercial supercapacitor, optimized for precise simulations within the frequency range of power electronics applications. A key distinction of this circuital equivalent lies in its rigorous foundation: its comprehensive characterization across a broad frequency spectrum, specifically from 0.01 Hz to 300 kHz, employing a commercial frequency response analyzer. This precise circuital representation offers substantial utility in simulation, analysis, and design of high-frequency circuits, particularly for switched-power converter design and control. It enables the anticipation of undesirable phenomena, such as significant voltage ripple and operational instability. This predictive capability is crucial for experimental preparation, facilitating the proactive integration of necessary filters and protective measures within sensing circuits, thereby underscoring its value prior to physical implementation. In addition, the developed circuital equivalent exhibits broad compatibility, allowing seamless implementation within commercial circuit simulators. Finally, the proposed methodology was illustrated with a commercial supercapacitor, but it can be applied to other supercapacitor types or manufacturers. Full article
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13 pages, 10178 KB  
Article
Luffa-like Interconnective Porous Nanofiber with Anchored Co/CoCr2O4 Hybrid Nanoparticles for Zinc–Air Batteries
by Guoqiang Jin, Bin Liu, Yan Liu, Xueting Zhang, Dapeng Cao and Xiuling Zhang
Batteries 2025, 11(8), 306; https://doi.org/10.3390/batteries11080306 - 8 Aug 2025
Viewed by 739
Abstract
The development of robust oxygen reduction reaction (ORR) catalyst with fast kinetics and good durability is significant for rechargeable zinc–air batteries (ZABs) but still remains a great challenge. Herein, inspired by the chain-like interconnective porous structure of plant luffa, an ORR catalyst of [...] Read more.
The development of robust oxygen reduction reaction (ORR) catalyst with fast kinetics and good durability is significant for rechargeable zinc–air batteries (ZABs) but still remains a great challenge. Herein, inspired by the chain-like interconnective porous structure of plant luffa, an ORR catalyst of Co/CoCr2O4@ IPCF is fabricated, with Co and CoCr2O4 hybrid nanoparticles (NPs) embedding into interconnective porous carbon nanofibers (IPCF). Contributing to CoCr2O4 NPs stabilized Co active sites, the resulting ZABs assembled with Co/CoCr2O4@IPCF as an air cathode catalyst delivering sustainable cycling stability of 550 h, surpassing that of Co@IPCF based on ZABs (215 h). Also, the Co/CoCr2O4@IPCF has a high ORR performance with a half-wave potential (E1/2) of 0.866 V in alkaline medium. The cycling stability originates from the IPCF carrier and the synergistic effect of Co NPs and CoCr2O4 NPs. The chain-like interconnective porous structure of the fibers provides more active sites and facilitates mass transfer to avoid the accumulation of OH and the exposure of H2O2, while the CoCr2O4 NPs can serve as a regulator for stabilizing the Co NPs electrochemical performance. Full article
(This article belongs to the Special Issue Novel Materials for Rechargeable Batteries)
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11 pages, 1504 KB  
Article
Nano-Alloy FeSb Wrapped in Three-Dimensional Honeycomb Carbon for High-Performance Lithium-Ion Batteries
by Nanjun Jia, Xinming Nie, Jianwei Li and Wei Qin
Batteries 2025, 11(8), 305; https://doi.org/10.3390/batteries11080305 - 8 Aug 2025
Viewed by 470
Abstract
Sb-based anodes have great potential in lithium-ion batteries because of their relatively high theoretical capacities. However, in general, their volume changes (>150%) during charge and discharge process have a significant impact, which affects their electrochemical performances. In this paper, nano-alloy FeSb wrapped in [...] Read more.
Sb-based anodes have great potential in lithium-ion batteries because of their relatively high theoretical capacities. However, in general, their volume changes (>150%) during charge and discharge process have a significant impact, which affects their electrochemical performances. In this paper, nano-alloy FeSb wrapped in three-dimensional honeycomb graphite carbon (FeSb@C) was prepared by the freeze-drying method using sodium chloride as a template. The three-dimensional carbon can buffer the volume change in the reaction process, increasing the contact area between the electrode and electrolyte. Furthermore, the addition of metallic iron also increases the overall specific capacity and improves its electrochemical performance. As the anode of a lithium-ion battery, the optimized FeSb@C shows excellent electrochemical performance with a specific capacity of 193.0 mAh g−1 at a high current density of 5 A g−1, and a reversible capacity of 607.8 mAh g−1 after 600 cycles of 1 A g−1. It provides an effective strategy for preparing high-performance lithium-ion batteries anode materials. Full article
(This article belongs to the Special Issue Batteries: 10th Anniversary)
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35 pages, 3497 KB  
Review
Recent Advances in Dendrite Suppression Strategies for Solid-State Lithium Batteries: From Interface Engineering to Material Innovations
by Abniel Machín, Francisco Díaz, María C. Cotto, José Ducongé and Francisco Márquez
Batteries 2025, 11(8), 304; https://doi.org/10.3390/batteries11080304 - 8 Aug 2025
Viewed by 2497
Abstract
Solid-state lithium batteries (SSLBs) have emerged as a promising alternative to conventional lithium-ion systems due to their superior safety profile, higher energy density, and potential compatibility with lithium metal anodes. However, a major challenge hindering their widespread deployment is the formation and growth [...] Read more.
Solid-state lithium batteries (SSLBs) have emerged as a promising alternative to conventional lithium-ion systems due to their superior safety profile, higher energy density, and potential compatibility with lithium metal anodes. However, a major challenge hindering their widespread deployment is the formation and growth of lithium dendrites, which compromise both performance and safety. This review provides a comprehensive and structured overview of recent advances in dendrite suppression strategies, with special emphasis on the role played by the nature of the solid electrolyte. In particular, we examine suppression mechanisms and material innovations within the three main classes of solid electrolytes: sulfide-based, oxide-based, and polymer-based systems. Each electrolyte class presents distinct advantages and challenges in relation to dendrite behavior. Sulfide electrolytes, known for their high ionic conductivity and good interfacial wettability, suffer from poor mechanical strength and chemical instability. Oxide electrolytes exhibit excellent electrochemical stability and mechanical rigidity but often face high interfacial resistance. Polymer electrolytes, while mechanically flexible and easy to process, generally have lower ionic conductivity and limited thermal stability. This review discusses how these intrinsic properties influence dendrite nucleation and propagation, including the role of interfacial stress, grain boundaries, void formation, and electrochemical heterogeneity. To mitigate dendrite formation, we explore a variety of strategies including interfacial engineering (e.g., the use of artificial interlayers, surface coatings, and chemical additives), mechanical reinforcement (e.g., incorporation of nanostructured or gradient architectures, pressure modulation, and self-healing materials), and modifications of the solid electrolyte and electrode structure. Additionally, we highlight the critical role of advanced characterization techniques—such as in situ electron microscopy, synchrotron-based X-ray diffraction, vibrational spectroscopy, and nuclear magnetic resonance (NMR)—for elucidating dendrite formation mechanisms and evaluating the effectiveness of suppression strategies in real time. By integrating recent experimental and theoretical insights across multiple disciplines, this review identifies key limitations in current approaches and outlines emerging research directions. These include the design of multifunctional interphases, hybrid electrolytes, and real-time diagnostic tools aimed at enabling the development of reliable, scalable, and dendrite-free SSLBs suitable for practical applications in next-generation energy storage. Full article
(This article belongs to the Special Issue Advances in Solid Electrolytes and Solid-State Batteries)
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17 pages, 5360 KB  
Article
Experimental and Numerical Study of the Impact of Pressure During the Pyrolysis of Diethyl Carbonate and Ethyl Methyl Carbonate
by Claire M. Grégoire, Eric L. Petersen and Olivier Mathieu
Batteries 2025, 11(8), 303; https://doi.org/10.3390/batteries11080303 - 8 Aug 2025
Viewed by 456
Abstract
During a thermal runaway, Lithium-ion battery cells are subjected to a large increase in temperature, which will vaporize and potentially thermally degrade their liquid electrolyte. The formation of gas in the battery cell will increase the pressure until the flammable gases vent and [...] Read more.
During a thermal runaway, Lithium-ion battery cells are subjected to a large increase in temperature, which will vaporize and potentially thermally degrade their liquid electrolyte. The formation of gas in the battery cell will increase the pressure until the flammable gases vent and potentially lead to a fire incident. While the pyrolysis chemistry of the electrolyte components has been studied near atmospheric pressure, the effect of pressure has not been investigated. This study was undertaken to better understand the effect of pressure on the thermal dissociation of two common linear electrolyte components, diethyl carbonate (DEC) and ethyl methyl carbonate (EMC). The pyrolysis of DEC and EMC was studied in the gas phase, in 99.75% He/Ar, and was carried out at high temperatures and for pressures near 5.5 atm. The time-resolved CO formation was measured using a quantum cascade laser, providing a unique experimental dataset. A detailed chemical kinetics analysis was performed to understand the effect of pressure on DEC and EMC, with CO time-history results obtained in similar conditions at near-atmospheric pressure for DEC and EMC serving as baselines for comparison. Numerical predictions using detailed chemical kinetics mechanisms from the literature were carried out, and reaction pathways at different pressures were highlighted to emphasize the effect of pressure on the pyrolysis chemistry. Full article
(This article belongs to the Special Issue Battery Thermal Performance and Management: Advances and Challenges)
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21 pages, 2537 KB  
Article
State of Health Prediction of Lithium-Ion Batteries Based on Dual-Time-Scale Self-Supervised Learning
by Yuqi Li, Longyun Kang, Xuemei Wang, Di Xie and Shoumo Wang
Batteries 2025, 11(8), 302; https://doi.org/10.3390/batteries11080302 - 8 Aug 2025
Viewed by 725
Abstract
Accurate estimation of the state of health (SOH) of lithium-ion batteries confronts two critical challenges: the extreme scarcity of labeled data in large-scale operational datasets and the mismatch between existing methods (relying on full charging–discharging conditions) and shallow charging–discharging conditions prevalent in real-world [...] Read more.
Accurate estimation of the state of health (SOH) of lithium-ion batteries confronts two critical challenges: the extreme scarcity of labeled data in large-scale operational datasets and the mismatch between existing methods (relying on full charging–discharging conditions) and shallow charging–discharging conditions prevalent in real-world scenarios. To address these challenges, this study proposes a self-supervised learning framework for SOH estimation. The framework employs a dual-time-scale collaborative pre-training approach via masked voltage sequence reconstruction and interval capacity prediction tasks, enabling automatic extraction of cross-time-scale aging features from unlabeled data. Innovatively, it integrates domain knowledge into the attention mechanism and incorporates time-varying factors into positional encoding, significantly enhancing the capability to extract battery aging features. The proposed method is validated on two datasets. For the standard dataset, using only 10% labeled data, it achieves an average RMSE of 0.491% for NCA battery estimation and 0.804% for transfer estimation between NCA and NCM. For the shallow-cycle dataset, it achieves an average RMSE of 1.300% with only 2% labeled data. By synergistically leveraging massive unlabeled data and extremely sparse labeled samples (2–10% labeling rate), this framework reduces the labeling burden for battery health monitoring by 90–98%, offering an industrial-grade solution with near-zero labeling dependency. Full article
(This article belongs to the Topic Advanced Electric Vehicle Technology, 3rd Edition)
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36 pages, 13501 KB  
Review
Research Progress on Risk Prevention and Control Technology for Lithium-Ion Battery Energy Storage Power Stations: A Review
by Weihang Pan
Batteries 2025, 11(8), 301; https://doi.org/10.3390/batteries11080301 - 6 Aug 2025
Viewed by 905
Abstract
Amidst the background of accelerated global energy transition, the safety risk of lithium-ion battery energy storage systems, especially the fire hazard, has become a key bottleneck hindering their large-scale application, and there is an urgent need to build a systematic prevention and control [...] Read more.
Amidst the background of accelerated global energy transition, the safety risk of lithium-ion battery energy storage systems, especially the fire hazard, has become a key bottleneck hindering their large-scale application, and there is an urgent need to build a systematic prevention and control program. This paper focuses on the fire characteristics and thermal runaway mechanism of lithium-ion battery energy storage power stations, analyzing the current situation of their risk prevention and control technology across the dimensions of monitoring and early warning technology, thermal management technology, and fire protection technology, and comparing and analyzing the characteristics of each technology from multiple angles. Building on this analysis, this paper summarizes the limitations of the existing technologies and puts forward prospective development paths, including the development of multi-parameter coupled monitoring and warning technology, integrated and intelligent thermal management technology, clean and efficient extinguishing agents, and dynamic fire suppression strategies, aiming to provide solid theoretical support and technical guidance for the precise risk prevention and control of lithium-ion battery storage power stations. Full article
(This article belongs to the Special Issue Advanced Battery Safety Technologies: From Materials to Systems)
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16 pages, 2886 KB  
Article
Incremental Capacity-Based Variable Capacitor Battery Model for Effective Description of Charge and Discharge Behavior
by Ngoc-Thao Pham, Sungoh Kwon and Sung-Jin Choi
Batteries 2025, 11(8), 300; https://doi.org/10.3390/batteries11080300 - 5 Aug 2025
Viewed by 444
Abstract
Determining charge and discharge behavior is essential for optimizing charging strategies and evaluating balancing algorithms in battery energy storage systems and electric vehicles. Conventionally, a sequence of circuit simulations or tedious hardware tests is required to evaluate the performance of the balancing algorithm. [...] Read more.
Determining charge and discharge behavior is essential for optimizing charging strategies and evaluating balancing algorithms in battery energy storage systems and electric vehicles. Conventionally, a sequence of circuit simulations or tedious hardware tests is required to evaluate the performance of the balancing algorithm. To mitigate these problems, this paper proposes a variable capacitor model that can be easily built from the incremental capacity curve. This model provides a direct and insightful R-C time constant method for the charge/discharge time calculation. After validating the model accuracy by experimental results based on the cylindrical lithium-ion cell test, a switched-capacitor active balancing and a passive cell balancing circuit are implemented to further verify the effectiveness of the proposed model in calculating the cell balancing time within 2% error. Full article
(This article belongs to the Special Issue Batteries: 10th Anniversary)
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19 pages, 2626 KB  
Article
Process–Structure–Property Correlations in Twin-Screw Extrusion of Graphitic Negative Electrode Pastes for Lithium Ion Batteries Focusing on Kneading Concentrations
by Kristina Borzutzki, Markus Börner, Olga Fromm, Uta Rodehorst and Martin Winter
Batteries 2025, 11(8), 299; https://doi.org/10.3390/batteries11080299 - 5 Aug 2025
Viewed by 982
Abstract
A continuous mixing process with a twin-screw extruder was investigated for graphite-based negative electrode pastes for high-power applications. In the extrusion-based mixing process, the first kneading concentration is one of the key processing parameters for systematic optimization of relevant electrode paste properties like [...] Read more.
A continuous mixing process with a twin-screw extruder was investigated for graphite-based negative electrode pastes for high-power applications. In the extrusion-based mixing process, the first kneading concentration is one of the key processing parameters for systematic optimization of relevant electrode paste properties like viscosity and particle size distribution. For different active materials at a constant electrode paste composition, a clear correlation of increasing kneading concentration with decreasing viscosity can be observed up to a certain reversal point, initiating a change in the trend and the rheological behavior, thus indicating a process limit. The fundamental effects causing this change and the associated impact on materials and battery performance were evaluated by applying further analytical methods and electrochemical characterization. It is revealed that the change in viscosity is associated with enhanced de-agglomeration of the carbon black additive and with partial particle grinding of the active material and thus a partial change in the interlayer distance of graphene layers and, correspondingly, the electrochemical behavior of the active material. Beyond this, correlations between processing parameters and product properties are presented. Furthermore, indicators are suggested with which monitoring of the machine parameters enables the detection of changes in the electrode paste characteristics. Full article
(This article belongs to the Special Issue Batteries: 10th Anniversary)
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51 pages, 4099 KB  
Review
Artificial Intelligence and Digital Twin Technologies for Intelligent Lithium-Ion Battery Management Systems: A Comprehensive Review of State Estimation, Lifecycle Optimization, and Cloud-Edge Integration
by Seyed Saeed Madani, Yasmin Shabeer, Michael Fowler, Satyam Panchal, Hicham Chaoui, Saad Mekhilef, Shi Xue Dou and Khay See
Batteries 2025, 11(8), 298; https://doi.org/10.3390/batteries11080298 - 5 Aug 2025
Cited by 1 | Viewed by 2510
Abstract
The rapid growth of electric vehicles (EVs) and new energy systems has put lithium-ion batteries at the center of the clean energy change. Nevertheless, to achieve the best battery performance, safety, and sustainability in many changing circumstances, major innovations are needed in Battery [...] Read more.
The rapid growth of electric vehicles (EVs) and new energy systems has put lithium-ion batteries at the center of the clean energy change. Nevertheless, to achieve the best battery performance, safety, and sustainability in many changing circumstances, major innovations are needed in Battery Management Systems (BMS). This review paper explores how artificial intelligence (AI) and digital twin (DT) technologies can be integrated to enable the intelligent BMS of the future. It investigates how powerful data approaches such as deep learning, ensembles, and models that rely on physics improve the accuracy of predicting state of charge (SOC), state of health (SOH), and remaining useful life (RUL). Additionally, the paper reviews progress in AI features for cooling, fast charging, fault detection, and intelligible AI models. Working together, cloud and edge computing technology with DTs means better diagnostics, predictive support, and improved management for any use of EVs, stored energy, and recycling. The review underlines recent successes in AI-driven material research, renewable battery production, and plans for used systems, along with new problems in cybersecurity, combining data and mass rollout. We spotlight important research themes, existing problems, and future drawbacks following careful analysis of different up-to-date approaches and systems. Uniting physical modeling with AI-based analytics on cloud-edge-DT platforms supports the development of tough, intelligent, and ecologically responsible batteries that line up with future mobility and wider use of renewable energy. Full article
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12 pages, 4237 KB  
Article
Ultra-Stable Anode-Free Na Metal Batteries Enabled by Al2O3-Functionalized Separators
by Han Wang, Yiheng Zhao, Jiaqi Huang, Lu Wang, Canglong Li and Yuejiao Chen
Batteries 2025, 11(8), 297; https://doi.org/10.3390/batteries11080297 - 4 Aug 2025
Viewed by 714
Abstract
The development of anode-free sodium metal batteries (AFSMBs) offers a promising pathway to achieve ultrahigh energy density and cost efficiency inherent to conventional sodium ion/metal batteries. However, irreversible Na plating/stripping and dendritic growth remain critical barriers. Herein, we demonstrate that separator engineering is [...] Read more.
The development of anode-free sodium metal batteries (AFSMBs) offers a promising pathway to achieve ultrahigh energy density and cost efficiency inherent to conventional sodium ion/metal batteries. However, irreversible Na plating/stripping and dendritic growth remain critical barriers. Herein, we demonstrate that separator engineering is a pivotal strategy for stabilizing AFSMBs. Through systematic evaluation of four separators—2500 separator (PP), 2325 separator (PP/PE/PP), glass fiber (GF), and an Al2O3-coated PE membrane, we reveal that the Al2O3-coated separator uniquely enables exceptional interfacial kinetics and morphological control. Na||Na symmetric cells with Al2O3 coated separator exhibit ultralow polarization (4.5 mV) and the highest exchange current density (1.77 × 10−2 mA cm−2), while the anode-free AlC-NFPP full cells retain 91.6% capacity after 150 cycles at 2C. Specifically, the Al2O3 coating homogenizes Na+ flux, promotes dense and planar Na deposition, and facilitates near-complete stripping with minimal “dead Na”. This work establishes ceramic-functionalized separators as essential enablers of practical high-energy AFSMBs. Full article
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16 pages, 5548 KB  
Article
A State-of-Charge-Frequency Control Strategy for Grid-Forming Battery Energy Storage Systems in Black Start
by Yunuo Yuan and Yongheng Yang
Batteries 2025, 11(8), 296; https://doi.org/10.3390/batteries11080296 - 4 Aug 2025
Viewed by 749
Abstract
As the penetration of intermittent renewable energy sources continues to increase, ensuring reliable power system and frequency stability is of importance. Battery energy storage systems (BESSs) have emerged as an important solution to mitigate these challenges by providing essential grid support services. In [...] Read more.
As the penetration of intermittent renewable energy sources continues to increase, ensuring reliable power system and frequency stability is of importance. Battery energy storage systems (BESSs) have emerged as an important solution to mitigate these challenges by providing essential grid support services. In this context, a state-of-charge (SOC)-frequency control strategy for grid-forming BESSs is proposed to enhance their role in stabilizing grid frequency and improving overall system performance. In the system, the DC-link capacitor is regulated to maintain the angular frequency through a matching control scheme, emulating the characteristics of the rotor dynamics of a synchronous generator (SG). Thereby, the active power control is implemented in the control of the DC/DC converter to further regulate the grid frequency. More specifically, the relationship between the active power and the frequency is established through the SOC of the battery. In addition, owing to the inevitable presence of differential operators in the control loop, a high-gain observer (HGO) is employed, and the corresponding parameter design of the proposed method is elaborated. The proposed strategy simultaneously achieves frequency regulation and implicit energy management by autonomously balancing power output with available battery capacity, demonstrating a novel dual benefit for sustainable grid operation. To verify the effectiveness of the proposed control strategy, a 0.5-Hz frequency change and a 10% power change are carried out through simulations and also on a hardware-in-the-loop (HIL) platform. Full article
(This article belongs to the Section Battery Modelling, Simulation, Management and Application)
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15 pages, 1832 KB  
Article
PyBEP: An Open-Source Tool for Electrode Potential Determination from Battery OCV Measurements
by Jon Pišek, Tomaž Katrašnik and Klemen Zelič
Batteries 2025, 11(8), 295; https://doi.org/10.3390/batteries11080295 - 4 Aug 2025
Viewed by 721
Abstract
This paper introduces PyBEP, a Python-based tool for the automated and optimized selection of open-circuit potential (OCP) curves and calculation of stoichiometric cycling ranges for lithium-ion battery electrodes based on open-circuit voltage (OCV) measurements. Thereby, it overcomes key challenges in traditional approaches, which [...] Read more.
This paper introduces PyBEP, a Python-based tool for the automated and optimized selection of open-circuit potential (OCP) curves and calculation of stoichiometric cycling ranges for lithium-ion battery electrodes based on open-circuit voltage (OCV) measurements. Thereby, it overcomes key challenges in traditional approaches, which are often time-intensive and susceptible to errors due to manual curve digitization, data inconsistency, and coding complexities. The originality of PyBEP arises from the systematic integration of automated electrode chemistry identification, quality-controlled database usage, refinement of the results using incremental capacity methodology, and simultaneous optimization of multiple electrode parameters. The PyBEP database leverages high-quality, curated OCP data and employs differential evolution optimization for precise OCP determination. Validation against literature data and experimental results confirms the robustness and accuracy of PyBEP, consistently achieving precision of 10 mV or better. PyBEP also offers features like electrode chemical composition identification and quality enhancement of measurement data, further extending the battery modeling functionalities without the need for battery disassembly. PyBEP is open-source and accessible on GitHub, providing a streamlined, accurate resource for the battery research community, making PyBEP a unique and directly applicable toolkit for electrochemical researchers and engineers. Full article
(This article belongs to the Section Battery Modelling, Simulation, Management and Application)
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26 pages, 1085 KB  
Article
Evaluating Sustainable Battery Recycling Technologies Using a Fuzzy Multi-Criteria Decision-Making Approach
by Chia-Nan Wang, Nhat-Luong Nhieu and Yen-Hui Wang
Batteries 2025, 11(8), 294; https://doi.org/10.3390/batteries11080294 - 4 Aug 2025
Viewed by 610
Abstract
The exponential growth of lithium-ion battery consumption has amplified the urgency of identifying sustainable and economically viable recycling solutions. This study proposes an integrated decision-making framework based on the T-Spherical Fuzzy Einstein Interaction Aggregator DEMATEL-CoCoSo approach to comprehensively evaluate and rank battery recycling [...] Read more.
The exponential growth of lithium-ion battery consumption has amplified the urgency of identifying sustainable and economically viable recycling solutions. This study proposes an integrated decision-making framework based on the T-Spherical Fuzzy Einstein Interaction Aggregator DEMATEL-CoCoSo approach to comprehensively evaluate and rank battery recycling technologies under uncertainty. Ten key evaluation criteria—encompassing environmental, economic, and technological dimensions—were identified through expert consultation and literature synthesis. The T-Spherical Fuzzy DEMATEL method was first applied to analyze the causal interdependencies among criteria and determine their relative weights, revealing that environmental drivers such as energy consumption, greenhouse gas emissions, and waste generation exert the most systemic influence. Subsequently, six recycling alternatives were assessed and ranked using the CoCoSo method enhanced by Einstein-based aggregation, which captured the complex interactions present in the experts’ evaluations and assessments. Results indicate that Direct Recycling is the most favorable option, followed by the Hydrometallurgical and Bioleaching methods, while Pyrometallurgical Recycling ranked lowest due to its high energy demands and environmental burden. The proposed hybrid model effectively handles linguistic uncertainty, expert variability, and interdependent evaluation structures, offering a robust decision-support tool for sustainable technology selection in the circular battery economy. The framework is adaptable to other domains requiring structured expert-based evaluations under fuzzy environments. Full article
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14 pages, 2852 KB  
Review
Review of Quasi-Solid Aqueous Zinc Batteries: A Bibliometric Analysis
by Zhongxiu Liu, Xiaoou Zhou, Tongyuan Shen, Miaomiao Yu, Liping Zhu, Guiyin Xu and Meifang Zhu
Batteries 2025, 11(8), 293; https://doi.org/10.3390/batteries11080293 - 3 Aug 2025
Viewed by 622
Abstract
Quasi-solid aqueous zinc batteries (QSAZBs) have wide applications in the energy storage field due to their advantages of high safety, cost-effectiveness, and eco-friendliness. Despite prolific research output in the field of QSAZBs, existing reviews predominantly focus on experimental advancements, with limited synthesis of [...] Read more.
Quasi-solid aqueous zinc batteries (QSAZBs) have wide applications in the energy storage field due to their advantages of high safety, cost-effectiveness, and eco-friendliness. Despite prolific research output in the field of QSAZBs, existing reviews predominantly focus on experimental advancements, with limited synthesis of global research trends, interdisciplinary connections, or knowledge gaps. Herein, we review the research on QSAZBs via bibliometric analysis using the VOSviewer software (version 1.6.20). First, the data from qualitatively evaluated publications on QSAZBs from 2016 and 2024 are integrated. In addition, the annual trends, leading countries/regions and their international collaborations, institutional research and patent distribution, and important keyword cluster analyses in QSAZB research are evaluated. The results reveal that China dominates in terms of publication output (71.16% of total papers), and Singapore exhibits the highest citation impact (103.2 citations/paper). International collaboration networks indicate the central role of China, with strong ties to Singapore, the USA, and Australia. Keyword clustering indicates core research priorities: cathode materials (MnO2 and V2O5), quasi-solid electrolyte optimization (hydrogels and graphene composites), and interfacial stability mechanisms. By mapping global trends and interdisciplinary linkages, this work provides insights to accelerate QSAZBs’ transition from laboratory breakthroughs to grid-scale and wearable applications. Full article
(This article belongs to the Special Issue Battery Interface: Analysis & Design)
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23 pages, 3040 KB  
Review
All-Solid-State Anode-Free Sodium Batteries: Challenges and Prospects
by Alexander M. Skundin and Tatiana L. Kulova
Batteries 2025, 11(8), 292; https://doi.org/10.3390/batteries11080292 - 2 Aug 2025
Viewed by 1377
Abstract
All-solid-state anode-free sodium batteries present a special and especially important kind of energy storage device. Unfortunately, the industrial production of such batteries has been absent up to now, although the prospects of their development seem to be rather optimistic. The present mini review [...] Read more.
All-solid-state anode-free sodium batteries present a special and especially important kind of energy storage device. Unfortunately, the industrial production of such batteries has been absent up to now, although the prospects of their development seem to be rather optimistic. The present mini review considers the fundamental advantages of all-solid-state anode-free sodium batteries as well as challenges in their creation. The advantages of all-solid-state anode-free sodium batteries reveal themselves when comparing them with ordinary sodium-ion batteries, sodium metal batteries, sodium batteries with liquid electrolyte, and their lithium counterparts. Full article
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15 pages, 3882 KB  
Article
Performance of Low-Cost Energy Dense Mixed Material MnO2-Cu2O Cathodes for Commercially Scalable Aqueous Zinc Batteries
by Gautam G. Yadav, Malesa Sammy, Jungsang Cho, Megan N. Booth, Michael Nyce, Jinchao Huang, Timothy N. Lambert, Damon E. Turney, Xia Wei and Sanjoy Banerjee
Batteries 2025, 11(8), 291; https://doi.org/10.3390/batteries11080291 - 1 Aug 2025
Viewed by 518
Abstract
Zinc (Zn)-based batteries have attracted significant interest for applications ranging from electric bikes to grid storage because of its advantageous properties like high abundance, non-toxicity and low-cost. Zn offers a high theoretical capacity of two electrons per atom, resulting in 820 mAh/g, making [...] Read more.
Zinc (Zn)-based batteries have attracted significant interest for applications ranging from electric bikes to grid storage because of its advantageous properties like high abundance, non-toxicity and low-cost. Zn offers a high theoretical capacity of two electrons per atom, resulting in 820 mAh/g, making it a promising anode material for the development of highly energy dense batteries. However, the advancement of Zn-based battery systems is hindered by the limited availability of cathode materials that simultaneously offer high theoretical capacity, long-term cycling stability, and affordability. In this work, we present a new mixed material cathode system, comprising of a mixture of manganese dioxide (MnO2) and copper oxide (Cu2O) as active materials, that delivers a high theoretical capacity of ~280 mAh/g (MnO2 + Cu2O active material) (based on the combined mass of MnO2 and Cu2O) and supports stable cycling for >200 cycles at 1C. We further demonstrate the scalability of this novel cathode system by increasing the electrode size and capacity, highlighting its potential for practical and commercial applications. Full article
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125 pages, 50190 KB  
Review
Sulfurized Polyacrylonitrile for Rechargeable Batteries: A Comprehensive Review
by Mufeng Wei
Batteries 2025, 11(8), 290; https://doi.org/10.3390/batteries11080290 - 1 Aug 2025
Viewed by 1071
Abstract
This paper presents a comprehensive review of research on sulfurized polyacrylonitrile (SPAN) for rechargeable batteries which was firstly reported by Jiulin Wang in July 2002. Spanning over two decades (2002–2025), this review cites over 600 publications, covering various aspects of SPAN-based battery systems. [...] Read more.
This paper presents a comprehensive review of research on sulfurized polyacrylonitrile (SPAN) for rechargeable batteries which was firstly reported by Jiulin Wang in July 2002. Spanning over two decades (2002–2025), this review cites over 600 publications, covering various aspects of SPAN-based battery systems. These include SPAN chemical structure, structural evolution during synthesis, redox reaction mechanism, synthetic conditions, cathode, electrolyte, binder, current collector, separator, anode, SPAN as additive, SPAN as anode, and high-energy SPAN cathodes. As this field continues to advance rapidly and garners significant interest, this review aims to provide researchers with a thorough and in-depth overview of the progress made over the past 23 years. Additionally, it highlights emerging trends and outlines future directions for SPAN research and its practical applications in energy storage technologies. Full article
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16 pages, 4770 KB  
Article
Developing a CeS2/ZnS Quantum Dot Composite Nanomaterial as a High-Performance Cathode Material for Supercapacitor
by Shan-Diao Xu, Li-Cheng Wu, Muhammad Adil, Lin-Feng Sheng, Zi-Yue Zhao, Kui Xu and Xin Chen
Batteries 2025, 11(8), 289; https://doi.org/10.3390/batteries11080289 - 1 Aug 2025
Viewed by 480
Abstract
To develop high-performance electrode materials for supercapacitors, in this paper, a heterostructured composite material of cerium sulfide and zinc sulfide quantum dots (CeS2/ZnS QD) was successfully prepared by hydrothermal method. Characterization through scanning electron microscopy (SEM), X-ray diffraction (XRD), and transmission [...] Read more.
To develop high-performance electrode materials for supercapacitors, in this paper, a heterostructured composite material of cerium sulfide and zinc sulfide quantum dots (CeS2/ZnS QD) was successfully prepared by hydrothermal method. Characterization through scanning electron microscopy (SEM), X-ray diffraction (XRD), and transmission electron microscopy (TEM) showed that ZnS QD nanoparticles were uniformly composited with CeS2, effectively increasing the active sites surface area and shortening the ion diffusion path. Electrochemical tests show that the specific capacitance of this composite material reaches 2054 F/g at a current density of 1 A/g (specific capacity of about 256 mAh/g), significantly outperforming the specific capacitance of pure CeS2 787 F/g at 1 A/g (specific capacity 98 mAh/g). The asymmetric supercapacitor (ASC) assembled with CeS2/ZnS QD and activated carbon (AC) retained 84% capacitance after 10,000 charge–discharge cycles. Benefited from the synergistic effect between CeS2 and ZnS QDs, the significantly improved electrochemical performance of the composite material suggests a promising strategy for designing rare-earth and QD-based advanced energy storage materials. Full article
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22 pages, 16421 KB  
Article
Deep Neural Network with Anomaly Detection for Single-Cycle Battery Lifetime Prediction
by Junghwan Lee, Longda Wang, Hoseok Jung, Bukyu Lim, Dael Kim, Jiaxin Liu and Jong Lim
Batteries 2025, 11(8), 288; https://doi.org/10.3390/batteries11080288 - 30 Jul 2025
Viewed by 981
Abstract
Large-scale battery datasets often contain anomalous data due to sensor noise, communication errors, and operational inconsistencies, which degrade the accuracy of data-driven prognostics. However, many existing studies overlook the impact of such anomalies or apply filtering heuristically without rigorous benchmarking, which can potentially [...] Read more.
Large-scale battery datasets often contain anomalous data due to sensor noise, communication errors, and operational inconsistencies, which degrade the accuracy of data-driven prognostics. However, many existing studies overlook the impact of such anomalies or apply filtering heuristically without rigorous benchmarking, which can potentially introduce biases into training and evaluation pipelines. This study presents a deep learning framework that integrates autoencoder-based anomaly detection with a residual neural network (ResNet) to achieve state-of-the-art prediction of remaining useful life at the cycle level using only a single-cycle input. The framework systematically filters out anomalous samples using multiple variants of convolutional and sequence-to-sequence autoencoders, thereby enhancing data integrity before optimizing and training the ResNet-based models. Benchmarking against existing deep learning approaches demonstrates a significant performance improvement, with the best model achieving a mean absolute percentage error of 2.85% and a root mean square error of 40.87 cycles, surpassing prior studies. These results indicate that autoencoder-based anomaly filtering significantly enhances prediction accuracy, reinforcing the importance of systematic anomaly detection in battery prognostics. The proposed method provides a scalable and interpretable solution for intelligent battery management in electric vehicles and energy storage systems. Full article
(This article belongs to the Special Issue Machine Learning for Advanced Battery Systems)
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16 pages, 3383 KB  
Article
Thermal and Electrical Design Considerations for a Flexible Energy Storage System Utilizing Second-Life Electric Vehicle Batteries
by Rouven Christen, Simon Nigsch, Clemens Mathis and Martin Stöck
Batteries 2025, 11(8), 287; https://doi.org/10.3390/batteries11080287 - 26 Jul 2025
Viewed by 536
Abstract
The transition to electric mobility has significantly increased the demand for lithium-ion batteries, raising concerns about their end-of-life management. Therefore, this study presents the design, development and first implementation steps of a stationary energy storage system utilizing second-life electric vehicle (EV) batteries. These [...] Read more.
The transition to electric mobility has significantly increased the demand for lithium-ion batteries, raising concerns about their end-of-life management. Therefore, this study presents the design, development and first implementation steps of a stationary energy storage system utilizing second-life electric vehicle (EV) batteries. These batteries, no longer suitable for traction applications due to a reduced state of health (SoH) below 80%, retain sufficient capacity for less demanding stationary applications. The proposed system is designed to be flexible and scalable, serving both research and commercial purposes. Key challenges include heterogeneous battery characteristics, safety considerations due to increased internal resistance and battery aging, and the need for flexible power electronics. An optimized dual active bridge (DAB) converter topology is introduced to connect several batteries in parallel and to ensure efficient bidirectional power flow over a wide voltage range. A first prototype, rated at 50 kW, has been built and tested in the laboratory. This study contributes to sustainable energy storage solutions by extending battery life cycles, reducing waste, and promoting economic viability for industrial partners. Full article
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