Batteries

22 pages, 10243 KB

Open AccessArticle

A Novel Empirical Degradation-Guided Transformer–GRU Network for Predicting Battery Capacity Degradation

by Xiandao Lei, Chenyu Liu, Zeping Chen, Jin Fang, Shanshan Guo and Caiping Zhang

Batteries 2026, 12(3), 85; https://doi.org/10.3390/batteries12030085 (registering DOI) - 2 Mar 2026

Battery ageing is inevitable during operation, leading not only to performance degradation but to potential safety concerns. Consequently, accurate prediction of the state of health (SOH) of lithium-ion batteries is crucial for ensuring their safety and reliability. This study proposed a novel hybrid [...] Read more.

Battery ageing is inevitable during operation, leading not only to performance degradation but to potential safety concerns. Consequently, accurate prediction of the state of health (SOH) of lithium-ion batteries is crucial for ensuring their safety and reliability. This study proposed a novel hybrid neural network architecture that integrates a transformer module, an empirical degradation (ED) model, and a gated recurrent unit (GRU). The transformer module enhances the global representation of the feature sequence, while the ED model comprehensively considers the impact of temperature on the rate of battery capacity degradation, compensating the un-interpretability of the transformer architecture in predicting SOH. In addition, pseudo-incremental capacity curves have been obtained using charging fragments from multi-stage constant current fast charging, which solves the issue of extracting mechanism features under fast charging conditions. Experimental results demonstrate that, across a wide temperature range, the model maintains a low average RMSE between 0.43% and 0.59% for prediction horizons of 4 to 128 cycles. Specifically, the average RMSE is 0.87% at −5 °C and 0.37% between 25 °C and 55 °C. Compared to standalone data-driven models, the proposed hybrid architecture reduces prediction error by approximately 50% at 25 °C, exhibiting superior predictive performance and robustness. Full article

(This article belongs to the Special Issue Battery Management Systems Based on Electrochemical Impedance Spectroscopy)

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26 pages, 12290 KB

Open AccessArticle

State of Charge Estimation Method for Lithium-Ion Batteries Based on Online Parameter Identification and QPSO-AUKF

by Hai Guo, Zhaohui Li, Haoze Xue and Jing Luo

Batteries 2026, 12(3), 84; https://doi.org/10.3390/batteries12030084 (registering DOI) - 1 Mar 2026

Abstract

Accurate estimation of the state of charge (SOC) is essential for the safe and efficient operation of lithium-ion batteries. Conventional Adaptive Unscented Kalman Filter (AUKF) methods often exhibit limited accuracy, primarily due to the empirical selection of process and measurement noise covariance matrices. [...] Read more.

Accurate estimation of the state of charge (SOC) is essential for the safe and efficient operation of lithium-ion batteries. Conventional Adaptive Unscented Kalman Filter (AUKF) methods often exhibit limited accuracy, primarily due to the empirical selection of process and measurement noise covariance matrices. To overcome this limitation, this study proposes a QPSO-AUKF algorithm based on a second-order RC equivalent circuit model, which integrates Quantum-behaved Particle Swarm Optimization (QPSO) with online parameter identification. In this approach, the QPSO algorithm optimizes the noise covariance matrices, which are subsequently used within the AUKF framework for SOC estimation. MATLAB R2020a simulations conducted on the Maryland and Wisconsin datasets demonstrate that the QPSO-AUKF reduces the root mean square error (RMSE) by more than 60% compared with the conventional AUKF, indicating a significant improvement in SOC estimation accuracy. Full article

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15 pages, 2034 KB

Open AccessArticle

State of Health Estimation of Lithium-Ion Batteries Based on Voltage Data Segment Hybrid Model

by Zhenhan Zou, Xiangyang Xia, Chaofeng Zhang, Jiahui Yue, Boyan Xia and Caibo Zhou

Batteries 2026, 12(3), 83; https://doi.org/10.3390/batteries12030083 (registering DOI) - 28 Feb 2026

Abstract

The health state estimation of lithium-ion batteries are the essential issues for the safety of energy storage stations. The important indicators often focus on the battery capacity and internal resistance. However, the measurement of capacity requires a complete charge/discharge cycle, and the measurement [...] Read more.

The health state estimation of lithium-ion batteries are the essential issues for the safety of energy storage stations. The important indicators often focus on the battery capacity and internal resistance. However, the measurement of capacity requires a complete charge/discharge cycle, and the measurement of internal resistance requires additional equipment. To solve the above problems, based on the voltage segment under the constant-current discharge condition of lithium-ion battery, this paper takes the sharp voltage drop of the initial discharge segment as a new healthy factor. Furthermore, facing the possibility that the new healthy factor data is polluted by noise, this factor data is reconstructed to reduce noise through multi-order Bezier curve. Subsequently, an empirical degradation hybrid model is constructed with the number of cycles. On this basis, the battery healthy state is defined by voltage segment and a new healthy state estimation model is proposed. The feasibility and effectiveness of the proposed degradation model and estimation model are verified by the aging data published by NASA and experimental platform. Full article

(This article belongs to the Special Issue 10th Anniversary of Batteries: Battery Health, Aging and Degradation Mechanisms)

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19 pages, 5093 KB

Open AccessArticle

Improvement of Cycling Stability of Core–Shell Structured Ni-Rich NMC Cathodes by Using a Tungsten Oxide Stabilization Interlayer

by Bilal Tasdemir, Svitlana Krüger, Pinank Sohagiya, Apurba Ray and Bilge Saruhan

Batteries 2026, 12(3), 82; https://doi.org/10.3390/batteries12030082 - 27 Feb 2026

Abstract

The growing demand for higher-energy lithium-ion batteries, encompassing consumer electronics, stationary grid storage, and electric mobility to specialized sectors like aerospace, medical devices, and industrial robotics, requires cathode materials that offer higher capacity while remaining cost-effective. This trend has intensified the development of [...] Read more.

The growing demand for higher-energy lithium-ion batteries, encompassing consumer electronics, stationary grid storage, and electric mobility to specialized sectors like aerospace, medical devices, and industrial robotics, requires cathode materials that offer higher capacity while remaining cost-effective. This trend has intensified the development of nickel-rich LiNi_1−x−yMn_xCo_yO₂ (NMC) systems. However, high-Ni NMCs such as LiNi_0.9Mn_0.05Co_0.05O₂ (NMC90) suffer from limited thermal and cycling stability. Core–shell architectures using LiNi_0.6Mn_0.2Co_0.2O₂ (NMC622) as a shell can partially alleviate these drawbacks, but structural degradation caused by interdiffusion between the core and shell persists as a major challenge. This study investigates whether a tungsten oxide interlayer can act as a protective barrier that suppresses interdiffusion, stabilizes the crystal structure, and improves long-term electrochemical performance. In this work, NMC cathode powders were synthesized via a one-pot oxalate co-precipitation route, followed by structural characterization using X-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and ion scattering spectroscopy (ISS). Electrochemical performance, including capacity retention, cycling stability, and internal resistance, was evaluated through galvanostatic charge–discharge (GCD) testing and electrochemical impedance spectroscopy (EIS). The core–shell configuration delivered higher specific discharge capacity compared to the individually synthesized core-only and shell-only reference materials, and the incorporation of a tungsten oxide interlayer resulted in a twofold increase in cycle life. These results demonstrate that tungsten oxide effectively enhances cycling stability by inhibiting core–shell interdiffusion, offering a promising pathway toward more durable high-Ni NMC cathodes. Full article

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

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20 pages, 1673 KB

Open AccessArticle

A Model for State-of-Health, Swelling and Out-of-Plane Stress Evolution in Lithium-Ion Batteries

by Marios Mantelos, Peter Gudmundson and Artem Kulachenko

Batteries 2026, 12(3), 81; https://doi.org/10.3390/batteries12030081 - 26 Feb 2026

Abstract

Module- and pack-level mechanical design of lithium-ion batteries in electric vehicles is a primary driver of swelling-induced stack pressure and spatially varying ageing. Current practice remains largely empirical or data-driven and configuration-specific, limiting the ability to predict how design changes translate into local [...] Read more.

Module- and pack-level mechanical design of lithium-ion batteries in electric vehicles is a primary driver of swelling-induced stack pressure and spatially varying ageing. Current practice remains largely empirical or data-driven and configuration-specific, limiting the ability to predict how design changes translate into local pressure heterogeneity and state-of-health (SOH) loss. This motivates a compact chemo-mechanical model that maps packaging boundary conditions to pressure, swelling, and SOH evolution with few interpretable parameters. This study introduces finite-element-ready constitutive laws that couple reversible and irreversible swelling to SOH and through-thickness pressure, covering three boundary cases reported in literature: constant pressure, thickness clamp after an initial preload, and flexible support. Parameters are identified from different published datasets, and the model is validated against independent constraint scenarios. Good quantitative agreement is shown with averaged RMSE of 1.16% for SOH and 0.16 [MPa] for pressure evolution. Variance-based sensitivity analysis shows SOH uncertainty dominated by the damage-law parameters of the proposed constitutive relationship, whereas pressure evolution is primarily controlled by irreversible swelling and the non-linear through-thickness stiffness, indicating calibration priorities for engineering design studies. The framework is intended for fast comparative analyses of individual cells under a controlled environment. Further extensions, including SOC-dependent mechanics, refined hysteresis, temperature, and C-rate variations require dedicated datasets and are left for future work. Full article

(This article belongs to the Special Issue Batteries: 10th Anniversary)

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26 pages, 1132 KB

Open AccessArticle

Structure–Property Relationships of Recycled Lithium-Ion Battery Cathodes: Microstructure Optimization Using Virtual Materials Testing

by Lukas Fuchs, Philipp Rieder, Donal P. Finegan, Francois Usseglio-Viretta, Jeffery Allen, Melissa Popeil, Orkun Furat and Volker Schmidt

Batteries 2026, 12(3), 80; https://doi.org/10.3390/batteries12030080 - 26 Feb 2026

Abstract

The increasing demand for sustainable battery technologies requires effective recycling strategies for end-of-life lithium-ion battery cathodes. In this study, virtual materials testing, a well-established framework for modeling conventionally manufactured NMC-based cathodes, is applied to partially recycled cathodes. To this end, virtual cathodes consisting [...] Read more.

The increasing demand for sustainable battery technologies requires effective recycling strategies for end-of-life lithium-ion battery cathodes. In this study, virtual materials testing, a well-established framework for modeling conventionally manufactured NMC-based cathodes, is applied to partially recycled cathodes. To this end, virtual cathodes consisting of mixtures of pristine and recycled NMC particles are utilized to systematically analyze structure–property relationships depending on mixing ratios and different spatial arrangement strategies. For this purpose, a stochastic 3D model is developed that is capable of generating virtual cathodes with arbitrary volume fractions of active materials and mixing ratios of pristine and recycled NMC particles. Particularly, the stochastic 3D model can mimic the different size distributions of pristine and recycled particles that are observed in image data. Additionally, the model allows the structuring of pristine and recycled NMC either uniformly mixed or layer-wise arranged, mimicking single- and dual-layer cathodes. Subsequently, a systematic computational analysis is conducted to assess the influence of increasing active material ratios of recycled particles, ranging from 0 % to 100 %, while maintaining a constant overall active material volume fraction. The impact of particle mixing on cathode performance is evaluated by examining transport-relevant geometrical descriptors and effective properties, such as geodesic tortuosity, specific surface area, and tortuosity factor. Full article

(This article belongs to the Special Issue 10th Anniversary of Batteries: Second-Life Applications and Recycling of Li-Ion Batteries)

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35 pages, 12319 KB

Open AccessReview

A Comprehensive Review on the Rapid Development of Silicon/MXene Nanocomposites for Lithium-Ion Battery Applications

by Narasimharao Kitchamsetti, Sungwook Mhin and HyukSu Han

Batteries 2026, 12(3), 79; https://doi.org/10.3390/batteries12030079 - 24 Feb 2026

Abstract

Silicon (Si) has attracted extensive attention as a promising anode material for next-generation lithium-ion batteries (LIBs) due to its ultra-high theoretical capacity, low lithiation potential, and economic advantages. However, drastic volume expansion during cycling and slow reaction kinetics severely compromise its structural stability [...] Read more.

Silicon (Si) has attracted extensive attention as a promising anode material for next-generation lithium-ion batteries (LIBs) due to its ultra-high theoretical capacity, low lithiation potential, and economic advantages. However, drastic volume expansion during cycling and slow reaction kinetics severely compromise its structural stability and practical application. Recently, two-dimensional (2D) MXenes have been explored as effective functional components in Si-based electrodes because of their excellent electrical conductivity, high specific surface area, adjustable surface terminations, and mechanical robustness. When integrated with Si, MXenes serve as conductive matrices that alleviate volumetric stress, enhance charge transport, and accelerate electron/ion diffusion. Consequently, Si/MXene nanocomposites (NCs) exhibit significantly improved lithium (Li) storage performance. This review outlines recent advances in Si/MXene NCs, covering fabrication strategies, structural engineering, and various configurations, including particulate materials, three-dimensional (3D) architectures, films, and fibrous systems, and establishes the relationship between structural design and electrochemical behavior. Remaining challenges and prospective research directions are also discussed to guide the development of high-energy-density LIB anodes. Full article

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30 pages, 3492 KB

Open AccessArticle

Multi-Objective Optimization of CPCM–Liquid Cooling Hybrid Thermal Management Systems for Lithium-Ion Batteries via NSGA-II Optimized Artificial Neural Networks

by Qianqian Xin, Xu Zhang, Tianqi Yang, Hengyun Zhang and Jinsheng Xiao

Batteries 2026, 12(3), 78; https://doi.org/10.3390/batteries12030078 - 24 Feb 2026

Abstract

Considering the synergistic optimization design of battery thermal safety and system economy in extreme environments, a hybrid lithium-ion battery thermal management system (BTMS) employing composite phase change material (CPCM) with liquid cooling is proposed by comparing four BTMSs of pure air cooling, pure [...] Read more.

Considering the synergistic optimization design of battery thermal safety and system economy in extreme environments, a hybrid lithium-ion battery thermal management system (BTMS) employing composite phase change material (CPCM) with liquid cooling is proposed by comparing four BTMSs of pure air cooling, pure CPCM, pure liquid cooling, and the hybrid cooling using CPCM and liquid cooling. The proposed hybrid cooling system demonstrates the capability to maintain the maximum battery temperature at 45.27 °C under extreme operating conditions, including elevated ambient temperatures of 40 °C combined with 5C discharge rate. Notably, this thermal regulation performance is achieved without requiring additional power input, highlighting the energy-efficient design of the system. Further, to address the critical challenge of thermal runaway prevention under summer extreme temperature up to 50 °C, an artificial neural network (ANN) model is established for the hybrid cooling, integrated with the non-dominated sorting genetic algorithm II (NSGA-II) algorithm, leading to the maximum temperature controlled at 48.68 °C and minimum system power consumption of 158 W, achieving a 12.1% reduction in thermal fluctuation amplitude and a 5.9% reduction in power consumption compared to initial design and optimal solutions, respectively. The proposed BTMS introduces the NSGA-II-ANN model for multi-objective collaborative optimization to solve the contradiction between thermal safety and energy consumption under extreme working conditions, enhancing the safety measures of power batteries and economic viability for electric vehicles. Full article

(This article belongs to the Special Issue Thermal Management System for Lithium-Ion Batteries: 2nd Edition)

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15 pages, 1353 KB

Open AccessArticle

Battery State-of-Health Estimation with Embedded Impedance Spectrum Features Under Multiple Battery Chemistry and Temperature Conditions

by Yue Xiang, Dikshit Chauhan and Dipti Srinivasan

Batteries 2026, 12(2), 77; https://doi.org/10.3390/batteries12020077 - 20 Feb 2026

Abstract

The transition to clean energy and electrification of transportation requires accurate, real-time monitoring of the state of health (SoH) of lithium-ion batteries, which serve as critical components for energy storage. Conventional SoH estimation methods typically rely on fixed statistical feature extraction, have poor [...] Read more.

The transition to clean energy and electrification of transportation requires accurate, real-time monitoring of the state of health (SoH) of lithium-ion batteries, which serve as critical components for energy storage. Conventional SoH estimation methods typically rely on fixed statistical feature extraction, have poor generalization ability, and are unsuitable for multiple battery chemistry and temperature conditions. In this work, we propose a deep learning framework based on a transformer encoder and XGBoost to extract ageing-related electrochemical impedance spectroscopy (EIS) features, capturing low-, mid-, and high-frequency ageing characteristics, directly from daily operation profiles for capacity estimation. The approach requires only current, voltage, and temperature time-series data, making it suitable for edge deployment without the need for explicit EIS measurements. Validation on a dataset with two battery chemistries and three temperature conditions yields a root-mean-square error of 0.16% to 0.20% in capacity estimation. These results establish the feasibility of accurate SoH estimation during multiple operation of battery energy storage systems and electric vehicles. Full article

(This article belongs to the Special Issue Battery Management Systems Based on Electrochemical Impedance Spectroscopy)

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48 pages, 5396 KB

Open AccessReview

Neural Architectures and Learning Strategies for State-of-Health Estimation of Lithium-Ion Batteries: A Critical Review

by Tai Duc Le, Jin-Hyeok Park and Moo-Yeon Lee

Batteries 2026, 12(2), 76; https://doi.org/10.3390/batteries12020076 - 19 Feb 2026

Abstract

Accurate state-of-health (SOH) estimation is a cornerstone of safe, reliable, and cost-effective operation of lithium-ion batteries (LIBs) in electric vehicles and energy storage systems. In recent years, rapid advances in artificial intelligence technology have led to the widespread adoption of neural-network-based SOH estimation [...] Read more.

Accurate state-of-health (SOH) estimation is a cornerstone of safe, reliable, and cost-effective operation of lithium-ion batteries (LIBs) in electric vehicles and energy storage systems. In recent years, rapid advances in artificial intelligence technology have led to the widespread adoption of neural-network-based SOH estimation methods, offering strong nonlinear modeling capability and improved adaptability compared with traditional model-based approaches. However, the growing diversity of neural architectures and learning strategies has led to fragmented development and inconsistent evaluation, hindering their practical deployment. This paper presents a critical and systematic review of the most recent representative studies on neural-network-based SOH estimation for LIBs between 2024 and 2025. A unified taxonomy is introduced to distinguish neural architectures from learning strategies. The neural architectures include artificial neural networks, convolutional and recurrent networks, attention-based models, Transformers, and physics-informed neural networks. The learning strategies encompass transfer learning, physics-constrained/physics-informed learning, robustness-oriented training and efficiency-aware design. The reviewed methods are analyzed in terms of modeling capability, generalization across operating conditions and chemistries, data efficiency, interpretability and deployability within battery management systems. Key challenges including nonlinear degradation, degradation diversity, data scarcity, and limited observability are critically examined. The roles of architecture-strategy co-design in addressing these issues are highlighted. Finally, open research directions and practical recommendations are discussed to guide the development of reliable, scalable and physically consistent SOH estimation frameworks. This review provides a structured reference for researchers and practitioners seeking to advance data-driven battery health monitoring toward real-world applications. Full article

(This article belongs to the Special Issue Artificial Intelligence-Based State-of-Health Estimation of Lithium-Ion Batteries: 3rd Edition)

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24 pages, 5042 KB

Open AccessArticle

Novel Anodic Material Sourced from Biomass Based on Amorphous Carbon Doped with Aluminum as an Efficient Alternative for Next-Generation Lithium-Ion Batteries

by Alifhers Mestra, Silvio Ceballos, Sergio Conejeros, Jaime Llanos, Karem Gallardo and Jonathan Cisterna

Batteries 2026, 12(2), 75; https://doi.org/10.3390/batteries12020075 - 18 Feb 2026

Abstract

This article focuses on the synthesis and characterization of an amorphous carbon derived from spent coffee grounds converted into a porous amorphous carbon (Cp₁) by carbonization up to 900 °C and subsequently combined with aluminum via mechanochemical treatment to obtain the [...] Read more.

This article focuses on the synthesis and characterization of an amorphous carbon derived from spent coffee grounds converted into a porous amorphous carbon (Cp₁) by carbonization up to 900 °C and subsequently combined with aluminum via mechanochemical treatment to obtain the composite Al@Cp₁. Powder X-Ray diffraction, Raman spectroscopy, and X-Ray photoelectron spectroscopy indicate turbostratic carbon domains (ID/IG ≈ 1.04) and an Al–O/Al–OH surface layer (Al₂O₃/Al(OH)₃) with a minor metallic Al contribution. Electrochemical performance in Li half-cells was evaluated by cyclic voltammetry, galvanostatic cycling, rate capability tests, and electrochemical impedance spectroscopy. At 0.02 A g⁻¹, Al@Cp₁ delivers 212.1 mAh g⁻¹, compared with 83.0 mAh g⁻¹ for Cp₁, with an initial coulombic efficiency of ~44%. Across increasing current densities, Al@Cp₁ retains higher reversible capacities than Cp₁ and shows stable cycling over extended tests (>160 cycles). Impedance analysis indicates a reduced interfacial/charge transfer resistance after electrode conditioning, consistent with interfacial stabilization by the Al-containing surface layer. These results demonstrate a simple, scalable route to upgrade coffee waste carbon into a higher-performance lithium-ion battery anode through mechanochemical interfacial engineering. Full article

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50 pages, 3749 KB

Open AccessReview

A Review of Nail Penetration and Thermal Abuse Tests of Lithium-Ion Batteries and Their Emission Characterization

by Ananthu Shibu Nair, Xiao-Yu Wu, Prodip K. Das and Michael Fowler

Batteries 2026, 12(2), 74; https://doi.org/10.3390/batteries12020074 - 18 Feb 2026

Abstract

Lithium-ion batteries (LIBs) are pivotal in electric vehicles (EVs), grid storage, and portable electronics, but their high energy density introduces safety risks, particularly thermal runaway (TR). TR can lead to fires, explosions, and hazardous emissions, posing severe health and environmental threats. Experimental investigation [...] Read more.

Lithium-ion batteries (LIBs) are pivotal in electric vehicles (EVs), grid storage, and portable electronics, but their high energy density introduces safety risks, particularly thermal runaway (TR). TR can lead to fires, explosions, and hazardous emissions, posing severe health and environmental threats. Experimental investigation of TR commonly relies on abuse testing methods, among which mechanical abuse via nail penetration (NP) and thermal abuse (TA) are widely used to simulate crash-induced and heat-driven failure scenarios, respectively. This review provides a comprehensive and comparative synthesis of NP and TA testing methodologies, examining how variations in test configuration, cell parameters (capacity, state of charge, and chemistry), and environmental conditions influence TR behavior and emission characteristics. Particular emphasis is placed on comparing reported emission profiles from NP- and TA-triggered TR events, including CO₂, CO, HF, hydrocarbons, and solvent vapors, and identifying the methodological origins of discrepancies across studies. By systematically linking emission variability to gas collection methods, analytical techniques, and data normalization approaches, this review highlights key limitations in current testing standards related to emission characterization. Finally, recommendations are offered for harmonizing abuse testing protocols and improving experimental design to enhance reproducibility, enabling meaningful cross-study comparison, and supporting safer deployment of LIBs in high-risk applications such as EVs and grid-scale energy storage. Full article

(This article belongs to the Special Issue Battery Management in Electric Vehicles: Current Status and Future Trends: 3rd Edition)

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20 pages, 4009 KB

Open AccessFeature PaperArticle

Strategies for Enhancing Battery Life Under Fast Charging: Insights from NMC-Based Cell Cycling

by Saiful Islam, Pete Barnes, Bumjun Park, Bianca Yi Wen Mak, Michael C. Evans, Eric J. Dufek and Tanvir R. Tanim

Batteries 2026, 12(2), 73; https://doi.org/10.3390/batteries12020073 - 17 Feb 2026

Abstract

Fast charging improves the usability of consumer electronics and electric vehicles (EVs) by reducing range anxiety and downtime but accelerates battery degradation and raises safety concerns. Optimizing operational conditions during fast-charging is critical to mitigating aging and ensuring safety. This study evaluated multilayer [...] Read more.

Fast charging improves the usability of consumer electronics and electric vehicles (EVs) by reducing range anxiety and downtime but accelerates battery degradation and raises safety concerns. Optimizing operational conditions during fast-charging is critical to mitigating aging and ensuring safety. This study evaluated multilayer Gr/NMC811 cells under various conditions, including depths of discharge (DODs of 68%, 84%, and 100%), upper charge cutoff voltages (4.1–4.2 V), and post-charge rest periods (2–30 min), using a 20 min fast charging protocol for up to 500 cycles (up to 150,000 miles of EV use assuming 3.3 mi/kWh vehicle level energy efficiency). Surprisingly, higher DODs under fast charging improved battery life and performance compared to lower DODs. Reducing the upper charge cut-off voltage helped mitigate degradation. A brief 2 min rest period after charging further reduced aging effects. The primary aging modes were loss of lithium inventory and cathode active material. Although minor lithium plating was observed within 500 cycles, it did not affect performance significantly. These findings suggest that, with optimized conditions, cells can sustain hundreds of fast charge cycles—equivalent to over 100,000 miles of EV use—without significant adverse effects on performance or longevity. Full article

(This article belongs to the Section Battery Performance, Ageing, Reliability and Safety)

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21 pages, 9542 KB

Open AccessArticle

Architectural Evolution and Advanced Joining Techniques in High-Energy-Density Cylindrical Li-Ion Cells

by Masilamani Chelladurai Asirvatham, Puritut Nakhanivej, Vincent A. Perry-French, Ehman F. Altaf, Melanie J. Loveridge, Tanveerkhan S. Pathan and James D. McLaggan

Batteries 2026, 12(2), 72; https://doi.org/10.3390/batteries12020072 - 17 Feb 2026

Abstract

This study presents a comparative analysis of cylindrical lithium-ion cell architectures, tracing the evolution from the conventional tabbed design (18650/21700) to the large-format 4680 cell with its tabless current collectors. This architectural shift is driven by the imperative to minimise internal ohmic resistance [...] Read more.

This study presents a comparative analysis of cylindrical lithium-ion cell architectures, tracing the evolution from the conventional tabbed design (18650/21700) to the large-format 4680 cell with its tabless current collectors. This architectural shift is driven by the imperative to minimise internal ohmic resistance and enhance thermal management in high-power automotive battery applications. Forensic investigation reveals that the 4680 design replaces localised, high-resistance tab connections with a distributed, low-impedance interface, necessitating the adoption of advanced manufacturing techniques, including long ultrasonic torsional welding and highly controlled high-power density laser welding. Crucially, the welding of external aluminium busbars to the cell relies on sophisticated microstructural engineering, particularly for the challenging dissimilar Aluminium-Steel (Al-Steel) anode weld. This weld format employs a spiral laser path to limit the formation of brittle aluminium-iron (Al-Fe) intermetallic compounds (IMCs), leveraging the steel cell casing’s nickel plating to promote a more ductile Al-Fe-Ni phase for improved joint reliability. Furthermore, the 4680 cell incorporates a significantly thicker casing (≈0.54 to 0.7 mm) for enhanced mechanical strength. In conclusion, the 4680 cell achieves superior performance through robust mechanical design and advanced welding processes that prioritise microstructurally sound, low-resistance interfaces. Full article

(This article belongs to the Section Battery Processing, Manufacturing and Recycling)

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15 pages, 1569 KB

Open AccessArticle

Accelerated Electrochemical Impedance Spectroscopy of LFP Modules Using Gradient-Based Sensitivity and D-Optimal Selection

by Isabel Aguilar, Ekaitz Zulueta, Unai Fernandez and Javier Olarte

Batteries 2026, 12(2), 71; https://doi.org/10.3390/batteries12020071 - 16 Feb 2026

Abstract

Efficient and accurate characterization of lithium-ion battery packs is critical for both first-life applications and second-life reuse. Electrochemical Impedance Spectroscopy (EIS) provides detailed insight into internal electrochemical processes, but full-spectrum measurements are time-consuming, especially at low frequencies. This work presents a methodology combining [...] Read more.

Efficient and accurate characterization of lithium-ion battery packs is critical for both first-life applications and second-life reuse. Electrochemical Impedance Spectroscopy (EIS) provides detailed insight into internal electrochemical processes, but full-spectrum measurements are time-consuming, especially at low frequencies. This work presents a methodology combining cell-level equivalent circuit modeling, integrated gradients sensitivity analysis, and D-optimal frequency selection to reduce the number of measurement points while preserving parameter identifiability. Individual 16s5p LFP cells were characterized using full-spectrum EIS at 10 °C, and the resulting equivalent circuit models were scaled to the pack level. Integrated gradients were used to quantify the frequency-dependent influence of each parameter on the real and imaginary parts of the impedance, identifying the regions containing the most information. Using the per-frequency Jacobian and the Fisher Information Matrix, a D-optimal frequency selection was performed to demonstrate that a reduced set of measurements is sufficient to estimate key parameters reliably. The results show that variations in parameters due to aging are accurately captured using the reduced frequency set, validating the approach for fast, accurate, and traceable characterization at the pack level. The proposed methodology highlights a systematic strategy for frequency selection, enabling faster EIS measurements, maintaining sensitivity to aging and degradation mechanisms, and supporting standardized and sustainable evaluation of lithium-ion batteries. Full article

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19 pages, 6909 KB

Open AccessArticle

Glycolic Acid-Induced Surface Reconstruction and In Situ Carbon Coating for High-Electrochemical-Performance Lithium-Rich Manganese-Based Cathodes

by Xichen Yang, Jie Miao, Yongchao Chen, Yaoxun Fang, Hao Wang and Gongchang Peng

Batteries 2026, 12(2), 70; https://doi.org/10.3390/batteries12020070 - 15 Feb 2026

Abstract

Lithium-rich manganese-based cathode materials (LRMs, Li_1.2Mn_0.54Ni_0.13Co_0.13O₂) are promising prospects for subsequent-generation lithium-ion batteries owing to their elevated operating voltage, large specific capacity, and affordability. Nonetheless, their actual implementation is significantly impeded by irreversible [...] Read more.

Lithium-rich manganese-based cathode materials (LRMs, Li_1.2Mn_0.54Ni_0.13Co_0.13O₂) are promising prospects for subsequent-generation lithium-ion batteries owing to their elevated operating voltage, large specific capacity, and affordability. Nonetheless, their actual implementation is significantly impeded by irreversible lattice-oxygen redox reactions, surface structural disorder, and interfacial phase collapse, leading to low initial Coulombic efficiency (ICE), inadequate rate capability, and sluggish Li⁺ transport. Herein, we report a simple and mild glycolic acid-assisted surface-engineering strategy to enhance the electrochemical performance of LRM. Glycolic acid treatment induces controlled H⁺/Li⁺ ion exchange at the particle surface and anchors surface transition metals through the formation of transition metals (TM)–OH and TM–O–C=O bonds. Subsequent calcination constructs an in situ carbon layer-spinel-layered heterostructure, accompanied by the generation of coupled anionic and cationic vacancies. This reconstructed surface provides fast Li⁺ diffusion pathways and stabilized ion-transport channels, while the dual-vacancy configuration enhances lattice-oxygen reversibility and suppresses structural disorder. Consequently, the modified LRM delivers a high initial discharge capacity of 285.3 mAh⋅g⁻¹ with an ICE of 89.9%, while maintaining 81% capacity retention after 100 cycles. Notably, it exhibits a significantly suppressed voltage decay of only 1.7 mV/cycle at 3C, markedly outperforming the pristine LRM. Density Functional Theory (DFT) calculations reveal that the surface-modified sample possesses enhanced electronic conductivity, as evidenced by the improved Density of States (DOS), and achieves superior structural stability through increased binding energies. This environmentally benign surface-engineering strategy offers a practical and efficient route toward the industrial application of LRM. Full article

(This article belongs to the Special Issue Toward Next-Generation Rechargeable Lithium-Ion Batteries: Current Status and Future Prospects—2nd Edition)

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23 pages, 6544 KB

Open AccessArticle

Electrochemical Stability of Passive Films on β-TiZrNbTa Alloys in Seawater-Based Electrolytes: Influence of Fluoride, pH, and Scan Rate

by Manal A. El Sayed, Ibrahim H. Elshamy, Sami M. Alharbi and Magdy A. M. Ibrahim

Batteries 2026, 12(2), 69; https://doi.org/10.3390/batteries12020069 - 15 Feb 2026

Abstract

The corrosion behavior and passive-film stability of a β-TiZrNbTa (β-TZNT) alloy were investigated in artificial seawater (ASW), focusing on the effects of pH, temperature, immersion time, fluoride ion concentration, and potential scan rate. In addition to electrochemical methods such as open-circuit potential (OCP), [...] Read more.

The corrosion behavior and passive-film stability of a β-TiZrNbTa (β-TZNT) alloy were investigated in artificial seawater (ASW), focusing on the effects of pH, temperature, immersion time, fluoride ion concentration, and potential scan rate. In addition to electrochemical methods such as open-circuit potential (OCP), potentiodynamic polarization (PDP), and electrochemical impedance spectroscopy (EIS), scanning electron microscopy (SEM) and X-ray diffraction (XRD) were employed for surface characterization. The establishment of a stable and efficient passive layer enriched in Zr-, Nb-, and Ta-oxides was responsible for the β-TZNT alloy’s superior corrosion resistance in fluoride-free ASW when compared to commercially pure titanium. Reduced passive-film resistance resulted from corrosion kinetics being greatly accelerated by decreasing the pH and increasing the temperature. The presence of fluoride ions strongly affected the passivity of the alloy due to the chemical dissolution of TiO₂ through the formation of soluble fluoride complexes, resulting in an increase in the corrosion current densities by more than one order of magnitude. A bilayer passive structure with a compact inner barrier layer and a porous outer layer was identified by EIS analysis. The stability of this structure gradually decreased with increasing fluoride concentration and acidity. Over time, passive-film degradation was dominant in fluoride-free seawater, whereas prolonged exposure in fluoride-containing media promoted partial re-passivation. Overall, these results highlight the potential and limitations of the β-TZNT alloy for marine and offshore applications by offering new mechanistic insights into the synergistic effects of fluoride ions and environmental factors on corrosion performance. Full article

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24 pages, 2132 KB

Open AccessArticle

Toward Sustainable Anode Materials: LCA of Natural Graphite Processing in Québec

by Gary Vegh, Sajedi Sarah, Ivan Kantor, Khalil Amine, Muskan Srivastava, Mina Rezayi, Anil Kumar Madikere Raghunatha Reddy and Karim Zaghib

Batteries 2026, 12(2), 68; https://doi.org/10.3390/batteries12020068 - 15 Feb 2026

Abstract

Graphite is a critical mineral used to produce anodes for lithium-ion batteries (LIBs). Battery-grade anode active material (AAM) is derived from natural graphite. As the electric vehicle (EV) market continues to expand across North America, establishing a local AAM supply chain has become [...] Read more.

Graphite is a critical mineral used to produce anodes for lithium-ion batteries (LIBs). Battery-grade anode active material (AAM) is derived from natural graphite. As the electric vehicle (EV) market continues to expand across North America, establishing a local AAM supply chain has become increasingly important. This new supply chain must be sustainable if critical minerals are to replace the internal combustion engine (ICE) powertrain in vehicles. Canada possesses abundant critical mineral resources, including natural graphite, which is mined and processed in the province of Québec. To better understand the environmental implications of this emerging supply chain, a life cycle assessment (LCA) was conducted on a Québec-based graphite mine and processing facility. The results showed that producing one ton of AAM in Québec generates approximately 1.44 tons of CO₂-equivalent (long-term) emissions, significantly lower than the 9.6 tons of CO₂ emitted per ton of graphite produced in China. Natural gas used for purification and coating at the process plant was the largest contributor of CO₂ in this study. Although this LCA in Québec represents a substantial reduction in carbon intensity, further opportunities must be explored to enhance sustainability and strengthen North America’s graphite supply chain. Full article

(This article belongs to the Section Battery Processing, Manufacturing and Recycling)

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24 pages, 17655 KB

Open AccessArticle

Mechanisms of Electrochemical Performance Degradation and Thermal Runaway Risk Evolution in LiFePO₄ Pouch Batteries After Extreme Low-Temperature Storage

by Feng Gao, Desheng Qiang, Yanping Bai, Zongliang Zhai, Yechang Gao, Weixing Lu and Ruixin Jia

Batteries 2026, 12(2), 67; https://doi.org/10.3390/batteries12020067 - 15 Feb 2026

Abstract

This research focuses on the passive behavior changes of 3 Ah pouch LiFePO₄ (LFP) batteries during low-temperature storage, a point often neglected in previous studies. This experiment examines the low-temperature non-operational endurance of fully charged batteries (FCB) at 25 °C, −10 °C, [...] Read more.

This research focuses on the passive behavior changes of 3 Ah pouch LiFePO₄ (LFP) batteries during low-temperature storage, a point often neglected in previous studies. This experiment examines the low-temperature non-operational endurance of fully charged batteries (FCB) at 25 °C, −10 °C, and −35 °C. Battery performance reliability under these conditions is evaluated through capacity retention and internal resistance (IR) analysis. Microstructural changes on the surfaces of thawed battery electrodes are acquired using scanning electron microscopy (SEM) and X-ray diffraction (XRD) techniques. After seven freeze–thaw cycles, the maximum usable capacity is marginally affected. Notably, a pronounced increase in polarization resistance (R_p) has been observed, particularly at −10 °C conditions, with an increase of about 40.57 mΩ. Microstructural analyses reveal that low-temperature storage significantly led to cracking of the electrolyte layer and of the particles in the anode material. Subsequently, at room temperature (RT, 25 °C), external short circuit (ESC) tests were performed on thawed batteries. At 50C, the peak temperatures recorded at the center of the FCB₋₁₀, FCB₂₅, and FCB₋₃₅ batteries are 104.35 °C, 94.67 °C, and 90.56 °C, respectively. The batteries exhibit rupture at approximately 47 s, 60 s, and 70 s during the ESC process. The results show that battery FCB₋₃₅ exhibits a slower temperature rise and delayed physical damage during ESC. Full article

(This article belongs to the Special Issue Thermal Runaway and Thermal Management: Toward Safe and Reliable Batteries)

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