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Batteries, Volume 11, Issue 8 (August 2025) – 28 articles

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11 pages, 1962 KiB  
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
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 KiB  
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 110
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 KiB  
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 166
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 KiB  
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 199
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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37 pages, 3497 KiB  
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 346
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 KiB  
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 174
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  
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 168
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  
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 345
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  
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 236
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  
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 284
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  
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
Viewed by 737
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 KiB  
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 382
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 KiB  
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 313
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  
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 303
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  
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 354
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 KiB  
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 314
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  
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 461
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  
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 265
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  
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 358
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 KiB  
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 270
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 KiB  
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 591
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  
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 336
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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18 pages, 5066 KiB  
Article
Influence of Pulse Duration on Cutting-Edge Quality and Electrochemical Performance of Lithium Metal Anodes
by Lars O. Schmidt, Houssin Wehbe, Sven Hartwig and Maja W. Kandula
Batteries 2025, 11(8), 286; https://doi.org/10.3390/batteries11080286 - 26 Jul 2025
Viewed by 342
Abstract
Lithium metal is a promising anode material for next-generation batteries due to its high specific capacity and low density. However, conventional mechanical processing methods are unsuitable due to lithium’s high reactivity and adhesion. Laser cutting offers a non-contact alternative, but photothermal effects can [...] Read more.
Lithium metal is a promising anode material for next-generation batteries due to its high specific capacity and low density. However, conventional mechanical processing methods are unsuitable due to lithium’s high reactivity and adhesion. Laser cutting offers a non-contact alternative, but photothermal effects can negatively impact the cutting quality and electrochemical performance. This study investigates the influence of pulse duration on the cutting-edge characteristics and electrochemical behavior of laser-cut 20 µm lithium metal on 10 µm copper foils using nanosecond and picosecond laser systems. It was demonstrated that shorter pulse durations significantly reduce the heat-affected zone (HAZ), resulting in improved cutting quality. Electrochemical tests in symmetric Li|Li cells revealed that laser-cut electrodes exhibit enhanced cycling stability compared with mechanically separated anodes, despite the presence of localized dead lithium “reservoirs”. While the overall pulse duration did not show a direct impact on ionic resistance, the characteristics of the cutting edge, particularly the extent of the HAZ, were found to influence the electrochemical performance. Full article
(This article belongs to the Section Battery Processing, Manufacturing and Recycling)
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18 pages, 16988 KiB  
Article
Deploying Virtual Quality Gates in a Pilot-Scale Lithium-Ion Battery Assembly Line
by Xukuan Xu, Simon Stier, Andreas Gronbach and Michael Moeckel
Batteries 2025, 11(8), 285; https://doi.org/10.3390/batteries11080285 - 25 Jul 2025
Viewed by 295
Abstract
Pilot production is a critical transitional phase in the process of new product development or manufacturing, aiming at ensuring that products are thoroughly validated and optimized before entering full-scale production. During this stage, a key challenge is how to leverage limited resources to [...] Read more.
Pilot production is a critical transitional phase in the process of new product development or manufacturing, aiming at ensuring that products are thoroughly validated and optimized before entering full-scale production. During this stage, a key challenge is how to leverage limited resources to build data infrastructure and conduct data analysis to establish and verify quality control. This paper presents the implementation of a cyber–physical system (CPS) for a lithium battery pilot assembly line. A machine learning-based predictive model was employed to establish quality control mechanisms. Process knowledge-guided data analysis was utilized to build a quality prediction model based on the collected battery data. The model-centric concept of ‘virtual quality’ enables early quality judgment during production, which allows for flexible quality control and the determination of optimal process parameters, thereby reducing production costs and minimizing energy consumption during manufacturing. Full article
(This article belongs to the Section Battery Processing, Manufacturing and Recycling)
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13 pages, 5204 KiB  
Article
Spontaneous Formation of a Zincphilic Ag Interphase for Dendrite-Free and Corrosion-Resistant Zinc Metal Anodes
by Neng Yu, Qingpu Zeng, Yiming Fu, Hanbin Li, Jiating Li, Rui Wang, Longlong Meng, Hao Wu, Zhuyao Li, Kai Guo and Lei Wang
Batteries 2025, 11(8), 284; https://doi.org/10.3390/batteries11080284 - 24 Jul 2025
Viewed by 378
Abstract
The remarkable advantages of zinc anodes render aqueous zinc-ion batteries (ZIBs) a highly promising energy storage solution. Nevertheless, the uncontrolled growth of zinc dendrites and side reactions pose significant obstacles to the practical application of ZIBs. To address these issues, a straightforward strategy [...] Read more.
The remarkable advantages of zinc anodes render aqueous zinc-ion batteries (ZIBs) a highly promising energy storage solution. Nevertheless, the uncontrolled growth of zinc dendrites and side reactions pose significant obstacles to the practical application of ZIBs. To address these issues, a straightforward strategy has been proposed, involving the addition of a minute quantity of AgNO3 to the electrolyte to stabilize zinc anodes. This additive spontaneously forms a hierarchically porous Ag interphase on the zinc anodes, which is characterized by its zinc-affinitive nature. The interphase offers abundant zinc nucleation sites and accommodation space, leading to uniform zinc plating/stripping and enhanced kinetics of zinc deposition/dissolution. Moreover, the chemically inert Ag interphase effectively curtails side reactions by isolating water molecules. Consequently, the incorporation of AgNO3 enables zinc anodes to undergo cycling for extended periods, such as over 4000 h at a current density of 0.5 mA/cm2 with a capacity of 0.5 mAh/cm2, and for 450 h at 2 mA/cm2 with a capacity of 2 mAh/cm2. Full zinc-ion cells equipped with this additive not only demonstrate increased specific capacities but also exhibit significantly improved cycle stability. This research presents a cost-effective and practical approach for the development of reliable zinc anodes for ZIBs. Full article
(This article belongs to the Special Issue Flexible and Wearable Energy Storage Devices)
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23 pages, 13580 KiB  
Article
Enabling Smart Grid Resilience with Deep Learning-Based Battery Health Prediction in EV Fleets
by Muhammed Cavus and Margaret Bell
Batteries 2025, 11(8), 283; https://doi.org/10.3390/batteries11080283 - 24 Jul 2025
Viewed by 327
Abstract
The widespread integration of electric vehicles (EVs) into smart grid infrastructures necessitates intelligent and robust battery health diagnostics to ensure system resilience and performance longevity. While numerous studies have addressed the estimation of State of Health (SOH) and the prediction of remaining useful [...] Read more.
The widespread integration of electric vehicles (EVs) into smart grid infrastructures necessitates intelligent and robust battery health diagnostics to ensure system resilience and performance longevity. While numerous studies have addressed the estimation of State of Health (SOH) and the prediction of remaining useful life (RUL) using machine and deep learning, most existing models fail to capture both short-term degradation trends and long-range contextual dependencies jointly. In this study, we introduce V2G-HealthNet, a novel hybrid deep learning framework that uniquely combines Long Short-Term Memory (LSTM) networks with Transformer-based attention mechanisms to model battery degradation under dynamic vehicle-to-grid (V2G) scenarios. Unlike prior approaches that treat SOH estimation in isolation, our method directly links health prediction to operational decisions by enabling SOH-informed adaptive load scheduling and predictive maintenance across EV fleets. Trained on over 3400 proxy charge-discharge cycles derived from 1 million telemetry samples, V2G-HealthNet achieved state-of-the-art performance (SOH RMSE: 0.015, MAE: 0.012, R2: 0.97), outperforming leading baselines including XGBoost and Random Forest. For RUL prediction, the model maintained an MAE of 0.42 cycles over a five-cycle horizon. Importantly, deployment simulations revealed that V2G-HealthNet triggered maintenance alerts at least three cycles ahead of critical degradation thresholds and redistributed high-load tasks away from ageing batteries—capabilities not demonstrated in previous works. These findings establish V2G-HealthNet as a deployable, health-aware control layer for smart city electrification strategies. Full article
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24 pages, 738 KiB  
Review
Photocuring in Lithium-Ion Battery Fabrication: Advances Towards Integrated Manufacturing
by Zihao Li, Yanlong Li, Mengting Chen, Weishan Li and Xiaoming Wei
Batteries 2025, 11(8), 282; https://doi.org/10.3390/batteries11080282 - 23 Jul 2025
Viewed by 441
Abstract
Photocuring, including photopolymerization and photocrosslinking, has emerged as a transformative manufacturing paradigm that enables the precise, rapid, and customizable fabrication of advanced battery components. This review first introduces the principles of photocuring and vat photopolymerization and their unique advantages of high process efficiency, [...] Read more.
Photocuring, including photopolymerization and photocrosslinking, has emerged as a transformative manufacturing paradigm that enables the precise, rapid, and customizable fabrication of advanced battery components. This review first introduces the principles of photocuring and vat photopolymerization and their unique advantages of high process efficiency, non-contact fabrication, ambient-temperature processing, and robust interlayer bonding. It then systematically summarizes photocured battery components, involving electrolytes, membranes, anodes, and cathodes, highlighting their design strategies. This review examines the impact of photocured materials on the battery’s properties, such as its conductivity, lithium-ion transference number, and mechanical strength, while examining how vat-photopolymerization-derived 3D architectures optimize ion transport and electrode–electrolyte integration. Finally, it discusses current challenges and future directions for photocuring-based battery manufacturing, emphasizing the need for specialized energy storage resins and scalable processes to bridge lab-scale innovations with industrial applications. Full article
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15 pages, 2830 KiB  
Article
Predictive Framework for Lithium Plating Risk in Fast-Charging Lithium-Ion Batteries: Linking Kinetics, Thermal Activation, and Energy Loss
by Junais Habeeb Mokkath
Batteries 2025, 11(8), 281; https://doi.org/10.3390/batteries11080281 - 22 Jul 2025
Viewed by 424
Abstract
Fast charging accelerates lithium-ion battery operation but increases the risk of lithium (Li) plating—a process that undermines efficiency, longevity, and safety. Here, we introduce a predictive modeling framework that captures the onset and severity of Li plating under practical fast-charging conditions. By integrating [...] Read more.
Fast charging accelerates lithium-ion battery operation but increases the risk of lithium (Li) plating—a process that undermines efficiency, longevity, and safety. Here, we introduce a predictive modeling framework that captures the onset and severity of Li plating under practical fast-charging conditions. By integrating an empirically parameterized SOC threshold model with time-dependent kinetic simulations and Arrhenius based thermal analysis, we delineate operating regimes prone to irreversible Li accumulation. The framework distinguishes reversible and irreversible plating fractions, quantifies energy losses, and identifies a critical activation energy (0.25 eV) associated with surface-limited deposition. Visualizations in the form of severity maps and voltage-zone risk classifications enable direct application to battery management systems. This approach bridges electrochemical degradation modeling with real-time charge protocol design, offering a practical tool for safe, high-performance battery operation. Full article
(This article belongs to the Section Battery Modelling, Simulation, Management and Application)
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