Ionics最新文献

{"title":"Parameter estimation of a temperature-dependent double-exponential SOH model for battery management systems","authors":"Dongqi Han,&nbsp;Jin Li","doi":"10.1007/s11581-026-07296-3","DOIUrl":"10.1007/s11581-026-07296-3","url":null,"abstract":"<div><p>Accurate estimation of the State of Health (SOH) is critical for ensuring the reliability and safety of lithium-ion battery management systems. While traditional power-law models are widely used, they often struggle to capture multi-stage degradation characteristics and accelerated aging behavior under varying thermal conditions. This study proposes a temperature-dependent double-exponential model (TDM) for SOH estimation. Unlike single-exponential or power-law approaches, the dual-exponential structure is able to describe both the stable solid electrolyte interphase (SEI) growth phase and the accelerated degradation stage associated with active material loss. To account for thermal effects, an Arrhenius-based temperature compensation term is incorporated into the exponential decay rates. A hierarchical two-stage identification algorithm is then developed, in which the linear parameters are updated by least squares and the nonlinear parameters are estimated by gradient-based iterations. Experimental results show that the proposed TDM improves fitting and prediction accuracy compared with conventional models in the considered validation cases. On the real NASA battery aging dataset, the proposed TDM achieves an RMSE of 0.0170, an MAE of 0.0140, and a MAPE of <span>(1.95%)</span>.</p></div>","PeriodicalId":599,"journal":{"name":"Ionics","volume":"32 9","pages":"9271 - 9284"},"PeriodicalIF":3.4,"publicationDate":"2026-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A statistical study on electrolyte additives of aqueous zinc-ion batteries","authors":"Xiaonan Liu,&nbsp;Chunhui Xie,&nbsp;Jinlong Zhang,&nbsp;Jun Huang,&nbsp;Yunqi Li","doi":"10.1007/s11581-026-07312-6","DOIUrl":"10.1007/s11581-026-07312-6","url":null,"abstract":"<div><p>Electrolyte additives for aqueous zinc-ion batteries (AZIBs) are critical to optimizing the trade-off between two core performance metrics, charge-discharge cycling lifetime (CT) and ionic conductivity (<i>σ</i>). Additives have been mechanistically understood through 6 functional categories in the regulation of Zn²⁺ solvation/desolvation, the Zn anode and its interphase, raising the necessity to clarify their complex chemical – functional – performance relationships. A collection of 56 organic additives were clustered into 9 groups according to Tanimoto distance based on chemical similarity, allocated into the 6 functional categories, and projected onto a (CT, <i>σ</i>) joint performance space. Additives that fall into the upper boundaries were identified, then contributions from their inherent molecular descriptors and interactions with water and Zn²⁺ were explored. Accounting for the distribution in chemical similarity and functional mechanisms, additives with favored molecular descriptors were screened that could simultaneously enhance <i>σ</i> and prolong CT. Among them, methyl diethylphosphonoacetate served as experimental validation and provided a <i>σ</i> of 57.3mS·cm^− 1 (200.3% improvement) and a CT of 2300.0 h at 1.0 mA·cm^− 2, a 1383.9% improvement against the control. The majority of relationships are conserved when extending to a larger collection of 94 additives, from organic molecules to inorganic salts, ionic liquids, and metal-cations. This tentative statistical study may provide useful references to design and prepare high-performance AZIBs with high power density and long cycle lifetimes.</p><h3>Graphical Abstract</h3><div><figure><div><div><picture><source><img></source></picture></div><div><p>(8.25*4.45 cm) We performed a statistical study by systematically analyzing the potential relationships among the chemical structures, functional mechanisms, and performance of reported electrolyte additives for aqueous zinc-ion batteries. Based on exploratory clustering and descriptor analysis, we identified preliminary quantum-chemical feature ranges that may help prioritize candidate additives capable of improving ionic conductivity and cycling stability. This framework provides preliminary trend-based references for organizing literature-reported additive data and screening representative candidate additives for further validation.</p></div></div></figure></div></div>","PeriodicalId":599,"journal":{"name":"Ionics","volume":"32 9","pages":"9241 - 9250"},"PeriodicalIF":3.4,"publicationDate":"2026-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-world state of charge estimation for electric vehicle batteries using interpretable physics-informed neural networks","authors":"Rongpu Huang,&nbsp;Chunxiang Zhu,&nbsp;Xingkai Zhou,&nbsp;Changcheng Sun,&nbsp;Zhou Hong","doi":"10.1007/s11581-026-07304-6","DOIUrl":"10.1007/s11581-026-07304-6","url":null,"abstract":"<div><p>Accurate State of Charge (SOC) estimation holds considerable significance for battery management yet remains challenging due to complex electrochemical dynamics and sensing noise. To address the limitations of fixed-parameter equivalent circuit models (ECM) and the interpretability issues of black-box data-driven methods, this paper proposes a robust hybrid framework coupling a Physics-Informed Neural Network (PINN) with an Adaptive Extended Kalman Filter (AEKF). Contrasting with loosely integrated approaches, a differentiable Multi-Layer Perceptron (MLP) is embedded into the ECM topology to model the nonlinear Open-Circuit Voltage (OCV) relationship. Through a physics-constrained training strategy, the framework can simultaneously identify physically consistent circuit parameters and learn the OCV-SOC curve from dynamic data, eliminating the necessity for offline OCV calibration. Furthermore, the learned differentiable model is employed as the state evolution function for the AEKF, where the MLP’s analytical gradient is directly utilized for system linearization. An adaptive noise covariance update mechanism is further incorporated to compensate for model mismatches. Validations on real-world datasets demonstrated that the proposed method delivered a Mean Absolute Error (MAE) below 1% and outperformed existing physics-guided learning approaches in terms of accuracy and robustness against temperature variations and aging.</p></div>","PeriodicalId":599,"journal":{"name":"Ionics","volume":"32 9","pages":"9251 - 9269"},"PeriodicalIF":3.4,"publicationDate":"2026-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-noble metal catalysis for environmental benign energy: Ni-Co nanoferrites for high-rate hydrogen generation","authors":"Fatima Zohra Benkrifa,&nbsp;Fatiha Abdelmalek,&nbsp;Khelifa Sabri,&nbsp;Aykut Caglar,&nbsp;Hilal Kivrak,&nbsp;Ahmed Addou","doi":"10.1007/s11581-026-07308-2","DOIUrl":"10.1007/s11581-026-07308-2","url":null,"abstract":"<div><p>Sustainable and cost-effective catalytic systems are essential for the environmental viability of hydrogen energy technologies. This study addresses this challenge by designing a series of non-noble Ni_1−xCo_xFe₂O₄ (x = 0–1) spinel nano catalysts via an energy-efficient sol-gel route for hydrogen production through sodium borohydride (NaBH₄) methanolysis. Structural and spectroscopic characterization by XRD, SEM/EDS, FTIR, and Raman confirmed the formation of phase-pure cubic spinels across the entire composition range. Rietveld refinement revealed a systematic lattice contraction with increasing Ni²⁺ content, consistent with Vegard’s law, while vibrational analyses evidenced cation redistribution within the Fd-3 m spinel framework. Catalytic screening identified Ni0.75Co0.25Fe2O4 as the optimal composition, delivering a high hydrogen generation rate of 31 699 mL·min− 1·gcat−1 under mild conditions. This superior activity is attributed to a strong Ni/Co synergistic effect, reflected in a low apparent activation energy of 14.49 kJ·mol− 1. Kinetic evaluation using the Eyring approach yielded activation parameters (ΔH = 11.85 kJ·mol− 1, ΔS = -199.81 J·mol− 1·K− 1), indicating an associative surface reaction mechanism. Temperature-programmed analyses (H2-TPR, O2-TPO, NH3-TPD) further showed that the optimal catalyst possesses accessible redox couples and a favourable distribution of acid sites, lowering energetic barriers for BH₄⁻ activation. The catalyst demonstrated excellent durability, retaining 96% of its initial activity over five consecutive cycles. This work establishes Ni_0.75Co_0.25Fe₂O₄ as a high-performance, sustainable, and reusable catalyst for chemical hydrogen storage, aligning with green chemistry principles and contributing to environmentally benign energy solutions.</p></div>","PeriodicalId":599,"journal":{"name":"Ionics","volume":"32 9","pages":"9197 - 9227"},"PeriodicalIF":3.4,"publicationDate":"2026-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of different carbon sources and carbon contents on the electrochemical properties of Li3V2(PO4)3","authors":"Zhihong He,&nbsp;Huanqiao Song,&nbsp;Xiayu Wu,&nbsp;Qihang Zou,&nbsp;Mingsheng Luo","doi":"10.1007/s11581-026-07299-0","DOIUrl":"10.1007/s11581-026-07299-0","url":null,"abstract":"<div><p>This paper presents the successful synthesis of Li₃V₂(PO₄)₃ (LVP)/C samples with different carbon sources and carbon contents by introducing metal-organic framework (MOF)-derived carbon, glucose-derived carbon, and sucrose-derived carbon during the sol-gel process. The effects of carbon source and carbon content on the properties of LVP are systematically investigated. The results show that LVP-10 (containing 10 wt% MOF-derived carbon) exhibits the best lithium storage performance. The initial discharge capacity of LVP-10 reaches 180.1 mAh g^− 1 at 0.1 C and remains the highest among all samples even at 5 C. The capacity retention after 100 cycles at 0.1 C is also the highest among the studied electrodes. Furthermore, electrochemical impedance spectroscopy reveals that LVP-10 exhibits the lowest charge transfer resistance (91.93 Ω) and the highest lithium-ion diffusion coefficient (6.22 × 10^− 17 cm²·s^− 1). It is concluded that the outstanding electrochemical performance of LVP-10 arises from the synergistic effects of its inferior LVP crystallinity, along with the graphitic carbon and graphitic-N incorporated within the porous MOF-derived carbon framework. The inferior crystallinity of LVP enhances the pseudocapacitive contribution to lithium storage, while the graphitic carbon and graphitic-N significantly improve the electronic conductivity of the composite. This study provides valuable insights into the design and synthesis of high-performance Li₃V₂(PO₄)₃ cathode materials.</p></div>","PeriodicalId":599,"journal":{"name":"Ionics","volume":"32 9","pages":"9229 - 9240"},"PeriodicalIF":3.4,"publicationDate":"2026-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal electrothermal modeling and predictive thermal regulation of solid-state batteries under high-altitude eVTOL operating conditions using deep transformer networks","authors":"Natrayan Lakshmaiya","doi":"10.1007/s11581-026-07291-8","DOIUrl":"10.1007/s11581-026-07291-8","url":null,"abstract":"<div><p>Efficient thermal management of solid-state batteries is a critical challenge in high-altitude eVTOL systems, where reduced air density limits convective cooling and increases the risk of thermal imbalance and degradation. Current methods such as traditional machine learning (ML) models like XGBoost and deep learning (DL) models such as CNN-BiLSTM often fail to simultaneously capture spatial thermal variations across individual cells and long-term degradation dynamics, leading to poor predictive performance and delayed thermal regulation. To address these limitations, a novel physics-aware spatiotemporal predictive framework is proposed, integrating a Convolutional Autoencoder (CAE) for compact spatial thermal representation with a Hierarchical Thermal Dynamics Transformer (HTDT) for degradation-aware temporal forecasting. The proposed framework incorporates physics-inspired electro-thermal proxy variables, including estimated current and Joule heat generation, to improve degradation-sensitive learning and interpretability. The framework does not explicitly solve electrochemical governing equations or implement PINN-based constraints. The model incorporates physics-inspired electro-thermal features, including estimated charging current and Joule heat generation, to enhance electro-thermal modeling fidelity while maintaining data-driven adaptability. The framework is implemented in Python using TensorFlow and PyTorch and evaluated on a high-resolution dataset of solid-state battery cycles capturing thermal, voltage, and resistance dynamics. Comparative results demonstrate superior predictive performance, achieving an RMSE of 0.125 °C, MAE of 0.092 °C, and R² of 0.985, representing an approximate 30–50% improvement over baseline models. Ablation studies further confirm the contribution of latent spatial embeddings and physics-guided attention mechanisms. The predictive thermal regulation layer enables real-time adjustment of discharge current and operational load to prevent hotspot formation. Unlike existing approaches that treat thermal prediction and degradation modeling independently, the proposed framework uniquely integrates physics-informed features with hierarchical spatiotemporal learning and predictive thermal regulation, enabling accurate and proactive thermal management under high-altitude conditions.</p></div>","PeriodicalId":599,"journal":{"name":"Ionics","volume":"32 9","pages":"9129 - 9158"},"PeriodicalIF":3.4,"publicationDate":"2026-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temperature-influenced synthesis of copper cobaltite electrodes for high-performance and sustainable asymmetric supercapacitor applications","authors":"Priyanka Kumaravel,&nbsp;SK Krishna,&nbsp;D Navaneethan,&nbsp;S Radhakrishnan,&nbsp;K Kavitha","doi":"10.1007/s11581-026-07297-2","DOIUrl":"10.1007/s11581-026-07297-2","url":null,"abstract":"<div><p>Transition metal oxides (TMOs) are widely regarded as potential electrode material for high-performance supercapacitors. In this study, CuCo₂O₄ was synthesised by a facile solvothermal route using ethanol as green solvent. A systematic study was conducted to assess the impact of solvothermal temperature on the morphological and electrochemical performance of CuCo₂O₄. The variation in solvothermal temperature resulted in the formation of distinct morphologies, such as microspheres at 120˚C, urchin-like structures at 150˚C, and flower-like architectures at 180˚C, as confirmed by FE-SEM and HR-TEM analyses. Among the synthesized samples, the material prepared at 150˚C (denoted as C-5) with urchin-like morphology exhibited the highest specific surface area of about 75.5 m²g^− 1. The electrochemical measurements also revealed that CuCo₂O₄(C-5) exhibits a maximum specific capacitance of 1133 F g^− 1 at a current density of 1 A g^− 1 and a capacitance retention of 82% after 8000 cycles in a three-electrode setup. The fabricated CuCo₂O₄(C-5)@NF // AC@NF-ASC device delivers a C_sp value of 156 F g^− 1 at 1 A g^− 1, retaining 80% initial capacitance over 8000 cycles. The device also exhibited a high energy density of 76 Wh kg^− 1 at a power density of 2040 W kg^− 1. In addition, the ASC device was powered a red LED, demonstrating its practical applicability for energy storage applications.</p></div>","PeriodicalId":599,"journal":{"name":"Ionics","volume":"32 8","pages":"7875 - 7893"},"PeriodicalIF":3.4,"publicationDate":"2026-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148652325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Selective electrochemical oxidation of piperonol by bi-phase electrolysis","authors":"M. Thairiyaraja,&nbsp;M. S. Viswaksenan,&nbsp;M. Ilayaraja,&nbsp;R. Jagatheesan,&nbsp;Paulraj Arunkumar","doi":"10.1007/s11581-026-07285-6","DOIUrl":"10.1007/s11581-026-07285-6","url":null,"abstract":"<div><p>A bi-phase electrochemical method for the selective oxidation of piperonol to piperonaldehyde has been developed using an undivided cell equipped with carbon (C) and stainless steel (SS) electrodes. The reaction proceeds in an aqueous NaNO₃ electrolyte with a catalytic amount of H₂SO₄ under mild conditions, affording piperonaldehyde in 78% yield with excellent current efficiency. Systematic optimization of electrolysis parameters revealed key factors governing selectivity and efficiency. This operationally simple, scalable process demonstrates a sustainable approach to aldehyde synthesis via electrocatalysis, highlighting its potential for industrial application in fine chemical production.</p></div>","PeriodicalId":599,"journal":{"name":"Ionics","volume":"32 9","pages":"9189 - 9195"},"PeriodicalIF":3.4,"publicationDate":"2026-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Carbon coating enhances electrochemical performance of LiNi0.8Mn0.2O2 assisted by dopamine hydrochloride","authors":"An Ding,&nbsp;Yitong Li,&nbsp;Lei Zhao,&nbsp;Yongtao Tan,&nbsp;Hailong Wang","doi":"10.1007/s11581-026-07293-6","DOIUrl":"10.1007/s11581-026-07293-6","url":null,"abstract":"<div><p>Due to their ultrahigh specific energy density, Ni-rich cobalt-free layered oxides are regarded as promising cathode materials for next-generation lithium-ion batteries (LIBs). However, as the nickel content increases, serious structural degradation during the cycling process can lead to a rapid decrease in capacity. This work aims to prepare a carbon layer coating on the surface of LiNi_0.8Mn_0.2O₂ cathode by dopamine hydrochloride using solid-state sintering method. The crystal structure, micro-morphology and electrochemical performance have been studied. This surface carbon coating strategy effectively suppresses the generation of surface side reactions on material particles, improves the electrochemical performance of the cathode in comparison with the original material NM. The optimized sample (NM@NC-0.2) shows a high specific capacity of 205.1 mAh g^− 1 at 0.5 C, along with a capacity retention of 93% after 100 cycles under the same current density. In situ EIS showed that this modification method significantly reduced the electrochemical impedance of the cathode surface, further enhancing the electron/Li⁺ diffusion ability.</p></div>","PeriodicalId":599,"journal":{"name":"Ionics","volume":"32 8","pages":"7863 - 7873"},"PeriodicalIF":3.4,"publicationDate":"2026-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148652394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient degradation of tetracycline over Fe doped NaTO3 via H2O2 activation and photocatalysis","authors":"Ameha Gebrewold,&nbsp;Haoyu Wang,&nbsp;Yan Guo,&nbsp;Hongru Han,&nbsp;Yuefa Jia","doi":"10.1007/s11581-026-07298-1","DOIUrl":"10.1007/s11581-026-07298-1","url":null,"abstract":"<div><p>In this study, Fe doped NaTaO₃ (Fe-NTO) catalysts were synthesized via a one-step hydrothermal reaction process, and the influence of Fe doping on their photo-Fenton catalytic efficiency in tetracycline hydrochloride (TCH) removal was examined under UV light illumination. It was observed that Fe doping can effectively enhance UV light absorption, accelerate charge transfer, as well as promote H₂O₂ activation. As expected, the incorporation of Fe into NTO significantly improved its photo-Fenton catalytic activity. The degradation rate of the optimized 1% Fe-NTO catalyst (35.35%) was 2.46 times that of pure NTO. The active species including •OH, •O₂⁻ and h⁺ play major roles for TCH photo-Fenton decomposition. The present work offers a feasible strategy to improve the catalytic activity of NaTaO₃ based catalysts for photo-Fenton decomposition of organic pollutants in wastewater.</p></div>","PeriodicalId":599,"journal":{"name":"Ionics","volume":"32 9","pages":"9177 - 9188"},"PeriodicalIF":3.4,"publicationDate":"2026-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}