Batteries

11 pages, 1504 KiB

Open AccessArticle

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

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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37 pages, 4047 KiB

Open AccessReview

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

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)

17 pages, 5360 KiB

Open AccessArticle

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

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 KiB

Open AccessArticle

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

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 KiB

Open AccessReview

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

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 KiB

Open AccessArticle

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

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 KiB

Open AccessArticle

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

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 KiB

Open AccessReview

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

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

(This article belongs to the Special Issue Battery Management and Advanced Energy Storage/Conversion Technologies in Renewable Power Systems: From Batteries to Fuel Cells and Hybrid Solutions)

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12 pages, 4237 KiB

Open AccessArticle

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

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

(This article belongs to the Special Issue High-Performance Secondary Batteries: Recent Processes and Future Challenges)

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16 pages, 5548 KiB

Open AccessArticle

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

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 KiB

Open AccessArticle

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

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 KiB

Open AccessArticle

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

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

(This article belongs to the Special Issue Second Life and Recycling: Perspectives for High-Performance Batteries)

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14 pages, 2852 KiB

Open AccessReview

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

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 KiB

Open AccessReview

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

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 KiB

Open AccessArticle

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

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 KiB

Open AccessReview

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

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

(This article belongs to the Section Battery Materials and Interfaces: Anode, Cathode, Separators and Electrolytes or Others)

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16 pages, 4770 KiB

Open AccessArticle

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

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

(This article belongs to the Special Issue High-Performance Supercapacitors: Preparation and Application—2nd Edition)

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22 pages, 16421 KiB

Open AccessArticle

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

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 KiB

Open AccessArticle

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

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

k

W

, 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

(This article belongs to the Special Issue Recycling and Reuse of End-of-Life Lithium-Ion Batteries: Challenges and Strategies–2nd Edition)

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