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Graphite anode with thick honeycomb architecture and high areal capacity fabricated via FDM 3D printing for lithium-ion batteries 采用FDM 3D打印技术制备了具有厚蜂窝结构和高面容量的锂离子电池石墨阳极
IF 2.4 4区 化学 Q4 ELECTROCHEMISTRY Pub Date : 2025-11-03 DOI: 10.1016/j.ijoes.2025.101219
Qiongzhen Zeng , Zhiyu Huo , Dongdong Wu , Lei Chen , Jinan Zhao
Graphite as the most widely used commercial anode material, has been developed to approach the theoretical upper limit of specific capacity, which possibly unsatisfied market demand in the coming future. To pursuit higher energy density Li-ion batteries (LIBs), a way of increasing anode thickness to improve areal capacity is proposed. 3D printing as an emerging technology, has more potential than traditional slurry-casting method in manufacturing the thick electrodes. Hence, this work employs Fused deposition modeling (FDM) printing and carbonization process to fabricate a thick electrode without current collector, 3D-G, which has honeycomb architecture, high areal mass loading and high areal capacity. With the biggest thickness, 3D-G can present a 16.96 mg cm−2 areal mass loading. The architecture offers surface channel to facilitate electrolyte infiltration and Li-ion diffusion that alleviates the kinetics defect caused by scaling up thickness. With a 0.6 mm electrode thickness and 0.5 mm honeycomb thickness, 3D-G delivered a 1.69 mAh cm−2 remaining capacity and a 2.53 mAh cm−2 average capacity after 100 cycles at a 0.3 mA cm−2. This research reveals the defects of graphite thick electrode and contributes a surface channel strategy to fabricate thick electrodes and optimize the rate and cycle capability.
石墨作为应用最广泛的工业阳极材料,其比容量已接近理论上限,未来可能无法满足市场需求。为了追求更高能量密度的锂离子电池,提出了增加阳极厚度以提高面容量的方法。3D打印作为一种新兴技术,在制造厚电极方面比传统的浆料铸造技术具有更大的潜力。因此,本研究采用熔融沉积建模(FDM)打印和碳化工艺,制备了蜂窝结构、高面质量载荷和高面容量的无集流电极3D-G。在厚度最大的情况下,3D-G的面质量载荷为16.96 mg cm−2。该结构提供了表面通道,以促进电解质的渗透和锂离子的扩散,减轻了因厚度增加而引起的动力学缺陷。3D-G电极厚度为0.6 mm,蜂窝厚度为0.5 mm,在0.3 mA cm−2下循环100次后,剩余容量为1.69 mAh cm−2,平均容量为2.53 mAh cm−2。本研究揭示了石墨厚电极存在的缺陷,为厚电极的制备及速率和循环性能的优化提供了一种表面通道策略。
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引用次数: 0
Combined X-ray computed tomography (X-CT) and electrochemical analysis of electrolyte-regulated stability of Li-metal anodes 联合x射线计算机断层扫描(X-CT)和电化学分析锂金属阳极的电解质调节稳定性
IF 2.4 4区 化学 Q4 ELECTROCHEMISTRY Pub Date : 2025-11-02 DOI: 10.1016/j.ijoes.2025.101224
Renzhi Jiang, Yuncheng Cai, Ningning Dong
Rechargeable Li metal batteries are regarded as a pragmatic solution in the pursuit of cell-level energy densities exceeding 500 Wh kg−1. However, their stable operation remains a formidable challenge, primarily due to the dendritic and heterogeneous Li plating/stripping behavior of the Li metal anode, which is strongly influenced by electrolyte chemistry. Herein, we employ synergetic X-ray computed tomography (X-CT) and electrochemical characterization to examine electrolyte-dependent stabilization of Li metal interfaces and structural integrity. X-CT analysis uncovered Li plating/stripping dynamics and crack propagation in ester-based (ES) and ether-based (ET) electrolytes We reveal that, compared to conventional ES electrolytes, advanced ET electrolytes markedly enhance the homogeneity and densification of Li deposition, effectively suppressing dendrite formation and mitigating electrode structural degradation. This improvement is attributed to the enhanced stability of electrode structure, coupled with accelerated Li+ transport kinetics. With a 50 μm-thick electrode, Li||Li symmetric cells exhibit remarkable longevity, sustaining stable operation for over 1200 h at 1 mA cm−2 and 1 mAh cm−2, and extending to 2000 h at 1 mA cm−2 and 2 mAh cm−2. When applied to practical full cells with a high cathode loading of 4 mAh cm−2 and a 50 μm-thick bare Li electrode, LiNi0.95Mn0.03Co0.02O2 (NMC9532) ||Li cells demonstrate superior capacity retention, 96 % after 100 cycles and 74 % after 200 cycles at 0.3 C, outperforming their counterparts with carbonate-based electrolytes (50 % retention after 200 cycles under identical conditions). This work offers valuable insights into electrolyte-dependent Li plating behavior and the evolution of the electrolyte/electrode interface under practical conditions, paving the way for the development of high-energy-density Li metal batteries.
可充电锂金属电池被认为是追求电池级能量密度超过500 Wh kg−1的实用解决方案。然而,它们的稳定运行仍然是一个艰巨的挑战,主要是由于锂金属阳极的枝晶和非均相镀/剥离行为,这受到电解质化学的强烈影响。在此,我们采用协同x射线计算机断层扫描(X-CT)和电化学表征来检查锂金属界面的电解质依赖稳定性和结构完整性。X-CT分析揭示了酯基(ES)和醚基(ET)电解质中的锂电镀/剥离动力学和裂纹扩展。我们发现,与传统的ES电解质相比,先进的ET电解质显著增强了锂沉积的均匀性和致密性,有效地抑制了枝晶的形成,减轻了电极结构的退化。这种改进归因于电极结构稳定性的增强,以及Li+传输动力学的加速。使用50 μm厚的电极,Li||Li对称电池表现出显著的寿命,在1 mA cm−2和1 mAh cm−2下稳定运行1200 h以上,在1 mA cm−2和2 mAh cm−2下稳定运行2000 h。当应用于具有4 mAh cm−2高阴极负载和50 μm厚裸锂电极的实际全电池时,lini0.95 mn0.03 co0.020 o2 (NMC9532) ||锂电池表现出优异的容量保持率,在0.3 C下循环100次后为96% %,在200次循环后为74% %,优于使用碳酸基电解质的电池(在相同条件下循环200次后为50% %)。这项工作对电解质依赖的锂电镀行为和实际条件下电解质/电极界面的演变提供了有价值的见解,为高能量密度锂金属电池的发展铺平了道路。
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引用次数: 0
Numerical analysis of gas diffusion layer porosity effects on degradation and durability in proton exchange membrane fuel cells 气体扩散层孔隙度对质子交换膜燃料电池降解和耐久性影响的数值分析
IF 2.4 4区 化学 Q4 ELECTROCHEMISTRY Pub Date : 2025-11-01 DOI: 10.1016/j.ijoes.2025.101221
Xin Zhou, Lei Chen
The porosity of the gas diffusion layer (GDL) in proton exchange membrane fuel cells (PEMFCs) exerts a significant impact on water - heat management. However, relatively few studies have been conducted on in-depth degradation quantification and impact analysis. This study innovatively employs a comprehensive numerical model to elucidate the impact of varying GDL porosity on PEMFC degradation mechanisms, including carbon corrosion, platinum (Pt) oxidation, dissolution, and redeposition. Our findings reveal that lower GDL porosity exacerbates carbon corrosion, accelerating Pt oxidation and reducing the electrochemically active surface area (ECSA), with distinct corrosion patterns emerging beneath ribs and flow channels. This work not only provides novel insights into the intricate relationship between GDL porosity and PEMFC durability but also offers a robust framework for optimizing GDL design to enhance fuel cell longevity and performance, marking a significant step forward in the field of fuel cell engineering.
质子交换膜燃料电池(pemfc)内气体扩散层(GDL)的孔隙率对电池的水热管理有重要影响。然而,关于深度降解量化和影响分析的研究相对较少。本研究创新性地采用了一个综合数值模型来阐明不同GDL孔隙度对PEMFC降解机制的影响,包括碳腐蚀、铂(Pt)氧化、溶解和再沉积。研究结果表明,较低的GDL孔隙度加剧了碳腐蚀,加速了Pt氧化,降低了电化学活性表面积(ECSA),在肋和流道下方出现了不同的腐蚀模式。这项工作不仅为GDL孔隙度与PEMFC耐久性之间的复杂关系提供了新的见解,而且为优化GDL设计提供了一个强大的框架,以提高燃料电池的寿命和性能,标志着燃料电池工程领域迈出了重要的一步。
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引用次数: 0
Corrigendum to “Advances in electrochemical methods for the determination of ephedrine: Current status and future trends” [Int. J. Electrochem. Sci. 20 (2025) DOI:10.1016/j.ijoes.2024.100903] “测定麻黄碱电化学方法的进展:现状和未来趋势”的勘误[同]。j . Electrochem。科学通报。20 (2025)DOI:10.1016/ j.j ijoes.2024.100903]
IF 2.4 4区 化学 Q4 ELECTROCHEMISTRY Pub Date : 2025-11-01 DOI: 10.1016/j.ijoes.2025.101197
Mingfan Cai , Wentao Wang
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引用次数: 0
Front Matter1:Full Title Page 封面1:完整的标题页
IF 2.4 4区 化学 Q4 ELECTROCHEMISTRY Pub Date : 2025-11-01 DOI: 10.1016/S1452-3981(25)00309-8
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引用次数: 0
Fabric-integrated supercapacitors as power sources for wearable motion sensors 织物集成超级电容器作为可穿戴运动传感器的电源
IF 2.4 4区 化学 Q4 ELECTROCHEMISTRY Pub Date : 2025-10-31 DOI: 10.1016/j.ijoes.2025.101220
Dongmei Pan
Wearable motion monitoring systems demand power sources that are lightweight, flexible, and mechanically resilient while providing sufficient electrochemical performance under real-world conditions. This review critically surveys recent progress in fabric-integrated supercapacitors, emphasizing their unique suitability for intermittent, high-power operation in wearable electronics. The discussion begins with an evaluation of carbon-based, pseudocapacitive, and hybrid electrode materials, highlighting advances in nanostructuring, heterostructure design, and composite engineering that balance conductivity, capacitance, and durability. Fabrication strategies—including dip-coating, screen printing, wet spinning, and electrodeposition—are compared in terms of scalability, adhesion, and impact on textile comfort, with particular attention to the “scalability gap” that separates laboratory prototypes from manufacturable devices. The role of solid-state and gel polymer electrolytes is analyzed, noting their trade-offs between safety, ionic conductivity, and mechanical stability. Performance benchmarking across diverse material and device architectures reveals impressive power densities and mechanical robustness but also exposes the persistent challenge of low energy density relative to batteries. Case studies demonstrate that while current devices cannot yet serve as sole continuous power sources, their high-rate capabilities and durability position them as effective energy buffers when coupled with harvesting technologies such as thermoelectrics or triboelectrics. By situating these developments within the context of wearable sensor requirements, this review provides a holistic perspective on the state of fabric-integrated supercapacitors and delineates the material, processing, and integration strategies necessary to close the gap toward practical deployment in next-generation e-textiles.
可穿戴式运动监测系统需要轻便、灵活、机械弹性强的电源,同时在实际条件下提供足够的电化学性能。本文综述了织物集成超级电容器的最新进展,强调了其在可穿戴电子产品中间歇性、高功率运行的独特适用性。讨论从碳基、假电容和杂化电极材料的评估开始,重点介绍了纳米结构、异质结构设计和复合材料工程方面的进展,以平衡电导率、电容和耐用性。制造策略——包括浸涂、丝网印刷、湿纺和电沉积——在可扩展性、附着力和对纺织品舒适性的影响方面进行了比较,特别注意将实验室原型与可制造设备分开的“可扩展性差距”。分析了固态和凝胶聚合物电解质的作用,指出了它们在安全性、离子电导率和机械稳定性之间的权衡。不同材料和器件架构的性能基准测试显示了令人印象深刻的功率密度和机械稳健性,但也暴露了相对于电池的低能量密度的持续挑战。案例研究表明,虽然目前的设备还不能作为唯一的连续电源,但当与热电或摩擦电等收集技术相结合时,它们的高速率能力和耐用性使它们成为有效的能量缓冲器。通过将这些发展置于可穿戴传感器需求的背景下,本综述提供了对织物集成超级电容器状态的整体视角,并描述了在下一代电子纺织品中实际部署所需的材料,加工和集成策略。
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引用次数: 0
Bioelectrical impedance vector analysis (BIVA) in sports science: Applications, insights and future directions 生物电阻抗矢量分析(BIVA)在运动科学中的应用、见解和未来方向
IF 2.4 4区 化学 Q4 ELECTROCHEMISTRY Pub Date : 2025-10-31 DOI: 10.1016/j.ijoes.2025.101222
Yuanyuan Liu, Xiaoqin Xu, Aixin Yang
Bioelectrical impedance vector analysis (BIVA) has emerged as a promising bioelectrochemical method to evaluate physiological states and monitor training responses in athletes. This review synthesizes current evidence on BIVA’s applications in four major domains: hydration assessment, body composition and training adaptation, injury monitoring and recovery, and performance profiling. Unlike conventional single-parameter bioimpedance metrics, BIVA integrates resistance and reactance normalized for height to yield phase angle and vector displacement within population tolerance ellipses, enabling a qualitative assessment of cellular integrity and fluid distribution. In hydration monitoring, vectors typically lengthen and migrate upward with fluid loss when assessed serially under standardized conditions; single time-point classification is less sensitive in individuals. We outline practical thresholds for meaningful change using paired vector statistics for groups and reference-change values for individuals, and we summarize evidence from exercise hypohydration and training adaptations. Longitudinal studies indicate that training-induced increases in body cell mass correspond to leftward and shorter vectors, while segmental BIVA enhances resolution for localized muscle groups. Evidence also supports the use of BIVA to detect injury-related tissue alterations, track edema resolution, and guide return-to-play decisions through vector re-alignment toward pre-injury values. Furthermore, correlations between phase angle and performance indices such as VO₂max, muscle power, and neuromuscular efficiency suggest BIVA’s potential to complement performance assessments. However, variability due to electrode placement, skin temperature, posture, and timing relative to exercise underscores the need for standardized protocols and sport-specific reference ellipses. Future integration of multifrequency data and machine learning-driven pattern recognition may strengthen BIVA’s predictive capacity, transforming it from a descriptive biomarker into a decision-support tool for individualized athlete management.
生物电阻抗矢量分析(BIVA)已成为一种很有前途的生物电化学方法来评估运动员的生理状态和监测训练反应。这篇综述综合了目前BIVA在四个主要领域的应用证据:水合作用评估、身体成分和训练适应、损伤监测和恢复以及表现分析。与传统的单参数生物阻抗测量不同,BIVA集成了电阻和电抗的高度归一化,从而在种群容忍椭圆内产生相角和矢量位移,从而能够定性评估细胞完整性和流体分布。在水化监测中,当在标准化条件下连续评估时,载体通常会随着流体损失而延长并向上移动;单时间点分类对个体不太敏感。我们使用成对矢量统计对群体和个人的参考变化值概述了有意义变化的实际阈值,并总结了运动缺水和训练适应的证据。纵向研究表明,训练诱导的体细胞质量增加对应于向左和更短的向量,而节段性BIVA增强了局部肌肉群的分辨率。证据还支持使用BIVA来检测损伤相关的组织改变,跟踪水肿消退,并通过矢量重新对准损伤前值来指导恢复比赛决策。此外,相角与VO₂max、肌肉力量和神经肌肉效率等性能指标之间的相关性表明,BIVA有可能补充性能评估。然而,与运动相关的电极放置、皮肤温度、姿势和时间的可变性强调了标准化方案和运动特定参考省略的必要性。未来多频数据和机器学习驱动的模式识别的整合可能会加强BIVA的预测能力,将其从描述性生物标志物转变为个性化运动员管理的决策支持工具。
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引用次数: 0
Hybrid XGBoost–LSTM model for state-of-health prediction of lithium-ion batteries under different thermal conditions 不同热条件下锂离子电池健康状态预测的XGBoost-LSTM混合模型
IF 2.4 4区 化学 Q4 ELECTROCHEMISTRY Pub Date : 2025-10-30 DOI: 10.1016/j.ijoes.2025.101218
Wajid Khan , Abdul Aziz , Muhammad Zain Yousaf , Feng Renhai , Yunshou Mao , Muhammad Waqas Latif , Wu Tonghao , Baseem Khan , Nkateko Eshias Mabunda , Ahmed Ali
Accurate monitoring of the State of Health (SoH) of lithium-ion batteries is critical for the reliable and safe operation of energy storage systems, particularly in grid-level applications where battery performance directly impacts the stability and efficiency of the grid. Traditional SoH estimation methods face challenges due to the complex and dynamic behavior of batteries, especially under varying thermal conditions. This paper proposes a hybrid machine learning approach that combines XGBoost with Long Short-Term Memory (LSTM) networks to predict the SoH of lithium-ion batteries. The XGBoost component models the relationship between engineered features, while the LSTM network captures the temporal degradation patterns in time-series data. The model is validated across a broad temperature range of 5°C–35°C to account for thermal variability. To rigorously assess generalization, the model is evaluated using ten-fold cross-validation and leave-one-temperature-out (LOTO) analysis, ensuring robustness across unseen conditions. Experimental results demonstrate that the proposed framework outperforms traditional methods, including electrochemical models and support vector machines, in terms of accuracy and robustness, particularly in fluctuating thermal conditions. The model’s interpretability is enhanced through TreeSHAP analysis, providing actionable insights into battery degradation mechanisms. This approach offers a reliable and scalable solution for real-time SoH monitoring, predictive maintenance, and optimal management of energy storage systems.
准确监测锂离子电池的健康状态(SoH)对于储能系统的可靠和安全运行至关重要,特别是在电网级应用中,电池性能直接影响电网的稳定性和效率。由于电池的复杂和动态行为,特别是在不同的热条件下,传统的SoH估算方法面临挑战。本文提出了一种混合机器学习方法,结合XGBoost和长短期记忆(LSTM)网络来预测锂离子电池的SoH。XGBoost组件对工程特征之间的关系进行建模,而LSTM网络则捕获时间序列数据中的时间退化模式。该模型在5°C - 35°C的宽温度范围内进行了验证,以考虑热变化。为了严格评估泛化,模型使用十倍交叉验证和留一个温度(LOTO)分析进行评估,确保在未知条件下的稳健性。实验结果表明,该框架在准确性和鲁棒性方面优于传统方法,包括电化学模型和支持向量机,特别是在波动热条件下。通过TreeSHAP分析,增强了模型的可解释性,为电池退化机制提供了可操作的见解。该方法为实时SoH监测、预测性维护和储能系统的优化管理提供了可靠且可扩展的解决方案。
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引用次数: 0
Recent advances in iron oxide/carbon composite electrodes for high-performance supercapacitors 高性能超级电容器用氧化铁/碳复合电极研究进展
IF 2.4 4区 化学 Q4 ELECTROCHEMISTRY Pub Date : 2025-10-29 DOI: 10.1016/j.ijoes.2025.101217
Jiang Xia , Li Xin , Zhao Dongni
The performance of supercapacitors largely depends on the characteristics of electrode materials. Among various electrode materials, iron oxide has been widely used as an electrode material for supercapacitors. However, iron oxide still has problems of low stability and poor conductivity, which seriously hinders its application as an electrode material for high-performance supercapacitors. To solve these problems, one approach is to use carbon materials with good mechanical and electrical conductivity as the carbon skeleton of composite electrode materials and combine them with iron oxide of different crystal structures to obtain composite supercapacitor electrode materials with excellent electrochemical performance. Based on the introduction of the structure and properties of ferrite compounds, this paper comprehensively reviews the preparation methods of iron-based/carbon composite electrode materials. In addition, based on different micro-space dimensional structures, the research progress of iron-based/carbon composite electrode materials in supercapacitors is summarized, and the problems in their application process are pointed out. This comprehensive summary will help promote the research and development of high-performance supercapacitors based on iron-based electrode materials.
超级电容器的性能在很大程度上取决于电极材料的特性。在各种电极材料中,氧化铁作为超级电容器的电极材料得到了广泛的应用。然而,氧化铁仍然存在稳定性低、导电性差等问题,严重阻碍了其作为高性能超级电容器电极材料的应用。为了解决这些问题,一种方法是使用具有良好机械导电性和导电性的碳材料作为复合电极材料的碳骨架,并与不同晶体结构的氧化铁结合,得到电化学性能优异的复合超级电容器电极材料。在介绍铁氧体化合物结构和性能的基础上,综述了铁基/碳复合电极材料的制备方法。此外,基于不同的微空间尺寸结构,总结了超级电容器中铁基/碳复合电极材料的研究进展,并指出了其应用过程中存在的问题。本文的综合总结将有助于推动基于铁基电极材料的高性能超级电容器的研究与开发。
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引用次数: 0
Optimization of electroplating processes using Kriging-based response surface method (K-RSM) and genetic algorithm (GA) for enhanced surface uniformity of copper 基于kriging响应面法(K-RSM)和遗传算法(GA)优化电镀工艺以提高铜表面均匀性
IF 2.4 4区 化学 Q4 ELECTROCHEMISTRY Pub Date : 2025-10-28 DOI: 10.1016/j.ijoes.2025.101216
Cheng-Tang Pan , Yu-Hsiu Lin , Yi-Hsuan Liu , Ming-Chan Lee
Non-uniform copper surface roughness in semiconductor manufacturing causes false Automated Optical Inspection (AOI) signals, necessitating manual re-inspection and reducing production efficiency. This study aims to optimize electroplating processes to improve surface quality and reduce labor dependence by systematically investigating the effects of critical process parameters. Uniform Design (UD) was employed to establish the experimental framework, examining the influence of current density, production time limitation (Q-Time), and plating thickness on electroplating quality. A Kriging-based Response Surface Method (K-RSM) integrated with Genetic Algorithm (GA) was applied for process optimization, followed by experimental validation. Analysis of Variance (ANOVA) assessed the contribution of each factor to surface uniformity. Results demonstrated that optimal parameters—current density of 9 A/dm², Q-Time of 1 h, and plating thickness of 5.7 μm—achieved 17.48 % improvement in surface roughness uniformity and 23.33 % reduction in manual re-inspection rates after AOI. Current density exhibited the most significant influence on surface quality. The proposed methodology provides a systematic and reproducible approach for electroplating process optimization, effectively enhancing manufacturing reliability while minimizing labor costs in semiconductor production.
半导体制造中铜表面不均匀的粗糙度会导致错误的自动光学检测(AOI)信号,需要人工重新检测,降低生产效率。本研究旨在通过系统研究关键工艺参数的影响,优化电镀工艺,以提高表面质量,减少对劳动力的依赖。采用均匀设计(UD)建立实验框架,考察了电流密度、生产时限(Q-Time)和电镀厚度对电镀质量的影响。将基于kriging的响应面法(K-RSM)与遗传算法(GA)相结合,进行工艺优化,并进行实验验证。方差分析(ANOVA)评估了每个因素对表面均匀性的贡献。结果表明,最优参数为电流密度为9 A/dm²,Q-Time为1 h,电镀厚度为5.7 μm,表面粗糙度均匀性提高17.48% %,AOI后人工复检率降低23.33% %。电流密度对表面质量的影响最为显著。提出的方法为电镀工艺优化提供了一种系统的、可重复的方法,有效地提高了制造可靠性,同时最大限度地降低了半导体生产中的劳动力成本。
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引用次数: 0
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International Journal of Electrochemical Science
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