Journal of energy storage最新文献_第8页

Multi-criteria optimization and assessment of phase-change materials for indirect concentrated solar cookers 间接聚光太阳能炊具相变材料多准则优化与评价

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-02-04 DOI: 10.1016/j.est.2026.120929

Akshay Thakur , Vijay Kumar , Varun Goel

Conventional cooking relies on biomass and fossil fuels that burn inefficiently and emit particulate matter and harmful gases. These emissions create health risks, increase time burdens, and expose households to fuel-price volatility. Solar cooking avoids fuel combustion at the point of use and can reduce household emissions to near zero. However, practical adoption is limited by poor controllability and the inability to cook after sunset. Thermal energy storage using phase change materials (PCMs) addresses this limitation by shifting collected solar heat to off-sun cooking hours.Selecting an appropriate PCM requires more than high latent heat. The material must melt near the cooking setpoint and provide adequate thermal conductivity, cycling stability, chemical compatibility, food safety, acceptable cost, and low environmental impact. This study presents a structured preselection and ranking of candidate PCMs for the thermal energy storage unit of a concentrated indirect solar cooker. Materials are first screened based on melting temperature to match the operating window of the cooker. An entropy-weighted multi-criteria decision-making framework is then applied using TOPSIS, VIKOR, and COPRAS. The evaluation includes thermophysical performance, durability, compatibility, safety, economic feasibility, and sustainability. Robustness is examined through weight-perturbation tests, criterion-omission trials, and normalization checks. The rankings remain stable, with changes limited to mid-ranked materials. TOPSIS and VIKOR identify high-density polyethylene as the leading candidate, while COPRAS favors erythritol due to its strong thermal attributes. To address practical significance, an experiment-anchored thermal validation is conducted. A system-level energy-balance discharge model is calibrated using measured no-PCM and magnesium chloride hexahydrate discharge data. The validated model confirms that the shortlisted PCMs can sustain cooking-relevant temperatures under identical system constraints without altering the decision ranking.Considering thermal performance together with safety, compatibility, cost, and deployability, high-density polyethylene is recommended as the most suitable PCM for the thermal energy storage unit of an indirect concentrated solar cooker.

传统烹饪依赖于生物质和化石燃料，燃烧效率低下，排放颗粒物和有害气体。这些排放造成健康风险，增加时间负担，并使家庭受到燃料价格波动的影响。太阳能烹饪在使用时避免燃料燃烧，可以将家庭排放减少到接近零。然而，实际应用受到可控性差和日落后无法烹饪的限制。使用相变材料（PCMs）的热能储存通过将收集的太阳能转移到非太阳烹饪时间来解决这一限制。选择合适的PCM需要的不仅仅是高潜热。材料必须在烹饪设定值附近熔化，并提供足够的导热性、循环稳定性、化学相容性、食品安全性、可接受的成本和低环境影响。本研究对聚光间接太阳能炊具蓄热单元的候选相变材料进行了结构化的预选和排序。首先根据熔化温度筛选材料，以匹配炊具的操作窗口。然后使用TOPSIS、VIKOR和COPRAS应用熵加权多标准决策框架。评估包括热物理性能、耐久性、兼容性、安全性、经济可行性和可持续性。鲁棒性通过权重扰动试验、标准遗漏试验和归一化检查来检验。排名保持稳定，变化仅限于排名中等的大学。TOPSIS和VIKOR认为高密度聚乙烯是主要的候选材料，而COPRAS则认为赤藓糖醇具有很强的热属性。为了说明实际意义，进行了实验锚定的热验证。使用测量的无pcm和六水合物氯化镁放电数据校准系统级能量平衡放电模型。经过验证的模型证实，入围的pcm可以在相同的系统约束下保持与烹饪相关的温度，而不改变决策排名。考虑到热性能以及安全性、兼容性、成本和可部署性，高密度聚乙烯被推荐为间接聚光太阳能炊具储热单元最合适的PCM。

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引用次数: 0

Numerical study of multi-nozzle inlet structure optimization for immersion cooling systems of large-scale lithium-ion battery pack 大型锂离子电池组浸没冷却系统多喷嘴进口结构优化数值研究

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-02-04 DOI: 10.1016/j.est.2026.120872

Wenhao Shan , Qun He , Ziyang Cao , Zhichao Zhang , Zuoqiang Dai , Lili Zheng , Xichao Li

Liquid immersion cooling for lithium-ion battery has attracted extensive interest due to superior cooling performance. This study proposes multiple-nozzle inlet configurations for immersion cooling system of the large-scale lithium-ion battery pack (90S1P). It is revealed that the multiple-nozzles force the fluid to flow through the gaps between battery cells, contributing to significantly enhanced heat transfer between coolant and battery cells. Wherein, the multi-nozzle inlet on the front of battery pack (CIF) exhibits better comprehensive performance than those on the side (CIS). In the CIF configuration, nozzle-to-battery distance, nozzle diameter and battery row gap significantly influence the temperature rise, temperature difference and pressure drop of system. The corresponding optimal values are determined to be 1 mm, 20 mm, and 10 mm, respectively. In the optimal configuration, the flow rate of 2 L/min and 5 L/min are adopted for discharging at 1C and 3C, respectively, to balance the power consumption, maximum temperature and temperature difference. When the battery pack is discharged at 3C, the temperature rise and temperature difference are only 14.98 °C and 4.96 °C, respectively. The results highlight great potential application of liquid immersion cooling in the field of large-scale energy storage system.

锂离子电池的液体浸没冷却由于其优越的冷却性能而引起了广泛的关注。本研究提出了大型锂离子电池组（90S1P）浸没冷却系统的多喷嘴进口配置。研究表明，多喷嘴迫使流体流过电池单元之间的间隙，从而显著增强了冷却剂与电池单元之间的传热。其中，电池组正面（CIF）的多喷嘴进口综合性能优于侧面（CIS）的多喷嘴进口。在CIF配置下，喷嘴到电池的距离、喷嘴直径和电池排间隙对系统的温升、温差和压降影响显著。确定其最优值分别为1mm、20mm和10mm。在最优配置中，1C和3C放电分别采用2l /min和5l /min的流量，以平衡功耗、最高温度和温差。当电池包在3C放电时，温升仅为14.98℃，温差仅为4.96℃。研究结果表明，液体浸没冷却技术在大型储能系统领域具有巨大的应用潜力。

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引用次数: 0

Multifunctional binder engineering approach toward mechanically adaptive and self-healing poly(benzoxazole aniline)-based flexible supercapacitors 机械自适应和自修复聚苯并恶唑苯胺基柔性超级电容器的多功能粘结剂工程方法

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-02-04 DOI: 10.1016/j.est.2026.120686

Sajida Khan , Tayyaba Bashir , Gul Hassan , Shah Fahad , Ahmad Shuja , Habib Ahmad

The growing demand for wearable and soft electronic systems requires energy storage devices that can deliver electrochemical efficiency while enduring mechanical stress and structural damage. Conducting polymers offers a pathway to such systems, yet their performance is often undermined by poor cycling stability and inadequate electrode cohesion. In this work, poly(benzoxazole aniline) (pBOA), a derivative of polyaniline with enhanced flexibility and stability, was employed as the active material in flexible supercapacitor electrodes. The role of binders was systematically evaluated by comparing conventional insulating types (PVDF, PVP, CMC) with the conductive polymer PEDOT:PSS. Comprehensive electrochemical and self-healing assessments revealed that PEDOT:PSS serves as an active conductive matrix rather than a passive binder. Upon healing, the PEDOT:PSS-based electrode recovered to a series resistance (Rs) of 25.4 Ω, corresponding to ∼35.0%, ∼32.5%, and ∼53.7% lower post-healing Rs compared with PVDF-, CMC-, and PVP-based electrodes, respectively, and remaining ∼6.6% lower than the binder-free device. This superior charge transport translated into an aerial capacitance of 146.3 mF cm⁻², 86% capacity retention after 1000 cycles, and ∼95% post-healing capacitance recovery. These findings reposition the binder from a passive additive to a decisive factor in dictating multifunctional device behavior, highlighting PEDOT:PSS as a dual-role binder–conductor for robust and adaptable energy storage platforms.

对可穿戴和软电子系统日益增长的需求要求储能设备能够在承受机械应力和结构损伤的同时提供电化学效率。导电聚合物为这种系统提供了一条途径，但它们的性能往往受到循环稳定性差和电极凝聚力不足的影响。本研究将聚苯胺的衍生物聚苯并恶唑苯胺（pBOA）作为柔性超级电容器电极的活性材料。通过对传统绝缘材料（PVDF、PVP、CMC）与导电聚合物PEDOT:PSS的对比，系统评价了粘结剂的作用。综合电化学和自修复评估表明，PEDOT:PSS是一种主动导电基质，而不是被动粘合剂。愈合后，基于PEDOT: pss的电极恢复到25.4 Ω的串联电阻（Rs），与基于PVDF、CMC和vpp的电极相比，愈合后的Rs分别降低了~ 35.0%、~ 32.5%和~ 53.7%，比无粘结剂的装置低了~ 6.6%。这种优越的电荷传输转化为146.3 mF cm−2的空中电容，1000次循环后容量保持率为86%，修复后电容恢复率为~ 95%。这些发现将粘结剂从被动添加剂重新定位为决定多功能器件行为的决定性因素，突出了PEDOT:PSS作为强大且适应性强的储能平台的双作用粘结剂-导体。

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引用次数: 0

Rational construction of zeolitic imidazolate framework-derived Co3S4@Ti3C2Tx@NiV-LDH/NF electrodes via core–shell design for efficient supercapacitors 通过核壳设计合理构建高效超级电容器用沸石咪唑酸框架衍生Co3S4@Ti3C2Tx@NiV-LDH/NF电极

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-02-04 DOI: 10.1016/j.est.2026.120828

Kexin Li , Xiang Luo , Gentian Yue , Yueyue Gao , Jinghao Huo , Chen Dong , Furui Tan

To fully exploit the large specific surface area, well-defined porous structure, and outstanding advantages in rate capability and cycling stability of metal-organic frameworks, while overcoming their poor electrical conductivity, we synthesized a layered double hydroxide (LDH)-based composite incorporating metal sulfides and Ti₃C₂T_x MXene. This was realized using a zeolitic imidazolate framework (ZIF-67) as a sacrificial template. The as-prepared ZIF-67 and Ti₃C₂T_x MXene were first anchored onto nickel foam (NF) and subsequently converted into a Co₃S₄@Ti₃C₂T_x/NF heterostructure via a sulfidation process. A Co₃S₄/Ti₃C₂T_x/NiV-LDH composite was then fabricated through a hydrothermal method and employed as a cathode for supercapacitors. Electrochemical characterization revealed that, at a scan rate of 20 mV·s⁻¹, the Co₃S₄@Ti₃C₂T_x@NiV-LDH composite delivered a higher specific capacitance, improved conductivity, and superior cycling stability compared to the pristine ZIF-67/NF, ZIF-67@Ti₃C₂T_x/NF, and Co₃S₄@Ti₃C₂T_x/NF electrodes. Furthermore, an asymmetric supercapacitor assembled with Co₃S₄@Ti₃C₂T_x@NiV-LDH/NF as the positive electrode and activated carbon as the negative electrode achieved a high energy density of 43.56 Wh·kg⁻¹ at a power density of 800 W·kg⁻¹, successfully powering an LED light for 5 min.

为了充分利用金属-有机骨架的比表面积大、多孔结构清晰、速率能力和循环稳定性突出的优点，同时克服其导电性差的缺点，我们合成了一种含金属硫化物和Ti3C2Tx MXene的层状双氢氧化物（LDH）基复合材料。这是通过使用沸石咪唑盐框架（ZIF-67）作为牺牲模板来实现的。制备的ZIF-67和Ti3C2Tx MXene首先被锚定在泡沫镍（NF）上，随后通过硫化过程转化为Co3S4@Ti3C2Tx/NF异质结构。采用水热法制备了Co3S4/Ti3C2Tx/NiV-LDH复合材料，并将其用作超级电容器的阴极材料。电化学表征表明，与ZIF-67/NF、ZIF-67@Ti3C2Tx/NF和Co3S4@Ti3C2Tx/NF电极相比，在20 mV·s−1的扫描速率下，Co3S4@Ti3C2Tx@NiV-LDH复合材料具有更高的比电容、更好的电导率和更好的循环稳定性。此外，以Co3S4@Ti3C2Tx@NiV-LDH/NF为正极，活性炭为负极组装的非对称超级电容器在800 W·kg - 1的功率密度下获得了43.56 Wh·kg - 1的高能量密度，成功地为LED灯供电5 min。

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引用次数: 0

Enhanced pseudo-capacitive behavior of Mn-doped Ag@SrCoO3 composite for efficient supercapacitor energy storage 增强掺锰Ag@SrCoO3复合材料的伪电容性用于高效超级电容器储能

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-02-04 DOI: 10.1016/j.est.2026.120754

Fatemeh Asadi , Jafar Mostafaei , Mohammad Ahangari , Neda Kalantari , Nagihan Delibaş , Ali Çoruh , Elnaz Asghari , Aligholi Niaei

In this study, sol-gel combustion was used to create Mn-doped Ag@SrCoO₃ (Ag@SCM-x, x = 0.0, 0.2, 0.5, 0.8) perovskite composites, which have been then assessed as potential electrode materials for supercapacitor applications. Comprehensive structural, morphological, and electrochemical investigations showed that the concentration of oxygen vacancies and the oxidation states of the transition metals were significantly affected by the addition of Mn to the B-site of the perovskite lattice. The kinetics of ion transport and redox activity were enhanced by these structural modifications. [email protected] outperformed the other produced samples in terms of electrochemical performance, exhibiting a specific capacitance of 950.18 F·g⁻¹ at a current density of 2.0 A·g⁻¹. The combined effects of Mn doping, which improves Co oxidation states and promotes oxygen ion mobility through enriched vacancy channels, are responsible for the enhanced performance. Moreover, the [email protected] electrode exhibited a high stability and could maintain approximately 92.5% of its initial capacitance after 5000 charge-discharge cycles, which implies that the electrode is quite reliable and can be utilized in the next-generation advanced supercapacitors.

在这项研究中，溶胶-凝胶燃烧被用于制造mn掺杂Ag@SrCoO3 （Ag@SCM-x, x = 0.0, 0.2, 0.5, 0.8）钙钛矿复合材料，然后被评估为超级电容器应用的潜在电极材料。综合结构、形态和电化学研究表明，在钙钛矿晶格的b位添加Mn对过渡金属的氧空位浓度和氧化态有显著影响。这些结构修饰增强了离子传输动力学和氧化还原活性。[email protected]在电化学性能方面优于其他生产的样品，在电流密度为2.0 a·g−1时显示出950.18 F·g−1的比电容。Mn掺杂改善了Co的氧化态，并通过丰富的空位通道促进了氧离子的迁移，这是性能增强的原因。此外，[email protected]电极表现出很高的稳定性，在5000次充放电循环后可以保持约92.5%的初始电容，这意味着该电极非常可靠，可以用于下一代先进的超级电容器。

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引用次数: 0

Graphene modified carbon rope for fabricating cable-type lithium-ion batteries with high-rate performance 石墨烯改性碳绳用于制造具有高倍率性能的电缆型锂离子电池

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-02-04 DOI: 10.1016/j.est.2026.120946

Zhanqiang Liu , Zongze Li , Hui Cheng , Chen Luan , Jun Ren , Qiang Shen , Yuhua Guo , Yufeng Tang

In this work, we fabricate a graphene-modified carbon (GC) composite from carbonized cotton rope with graphene grown on its surface. The diameters of the carbonized cotton fibers and the cotton rope are several micrometers and about 0.3 cm, respectively. The GC rope possesses flexible, free-standing characteristics and high conductivity, making it suitable for use as a supporter and current collector to enhance the performance of active materials. For example, the as-prepared Li₄T₅O₁₂/GC (LTO/GC, the content of LTO is 79 wt%) rope and the LiFePO₄/GC (LFP/GC, the content of LFP is 84 wt%) rope demonstrate excellent rate performance of 131 mAh g⁻¹ at 50C (LTO/GC) and 110 mAh g⁻¹ at 20C (LFP/GC), respectively. With the rope-like structure, the LTO/GC anode and the LFP/GC cathode are assembled into a flexible cable-type full battery. The electrochemical testing indicates high performance of the cable-type battery and no significant decrease in performance when the battery is bent.

在这项工作中，我们用炭化棉绳在其表面生长石墨烯制备了石墨烯改性碳（GC）复合材料。炭化棉纤维的直径为几微米，棉绳的直径为0.3厘米左右。GC绳具有灵活、独立的特性和高导电性，适合用作支撑和集流器，以增强活性材料的性能。例如，制备的li4t5012 /GC （LTO/GC， LTO含量为79 wt%）绳和LiFePO4/GC （LFP/GC， LFP含量为84 wt%）绳在50C （LTO/GC）和20C （LFP/GC）下分别表现出131 mAh g−1和110 mAh g−1的优良倍率性能。LTO/GC阳极和LFP/GC阴极采用绳状结构，组装成柔性电缆式全电池。电化学测试表明，电缆型电池性能良好，电池弯曲后性能无明显下降。

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引用次数: 0

Thermodynamic performance investigation of liquid hydrogen storage tanks considering the heat leakage redistribution effect of the wall 考虑壁面热泄漏重分布效应的液氢储罐热力学性能研究

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-02-04 DOI: 10.1016/j.est.2026.120910

Yao He , Zhuoming Yang , Jianjun Ye , Ruyi Ji , Jinwu Liu , Honggang Chen

A non-equilibrium thermodynamic model coupled with the heat leakage redistribution effect in the tank wall (HRW) is introduced to describe the long-period and non-venting storage process of LH₂ tanks. Transient and non-uniform distribution characteristics of heat leakage across various tank structures are investigated to improve the accuracy of thermodynamic state predictions for LH₂ storage. Subsequently, a systematic comparison is conducted on the performance of vertical, horizontal, and spherical tanks to evaluate effectiveness in managing pressure, temperature, and boil-off. The results indicate that the HRW model can provide a more accurate prediction of the average pressurization rate than the NHRW model, with the pressure RMSE decreasing from 1.54 to 0.63. Exhibiting a connection between the internal fluid state and the tank structure, the redistribution of heat leakage through the wall serves as a key driver of the transient non-uniformity in the heat leakage flux. The redistribution of heat leakage in the spherical tank is the most significant. For the

φ

=20%,

q_{l}

rises by nearly 55% over the 36 h, increasing from 1.69 W/m² to 2.62 W/m². For a given fill ratio, the vertical tank demonstrates the maximum time-averaged

q_{u}

, followed by the horizontal tank, and lowest in the spherical tank. Increasing the fill ratio results in lower pressurization rates across all tank types. When

φ

=80%, the average pressurization rates for vertical and horizontal tanks exceed that of the spherical tank by 40.3% and 31.3% respectively. Vertical and horizontal tanks exhibit a complementary performance of temperature rise and boil-off rate, while spherical tanks can offer superior overall performance. The research provides critical insights into the thermodynamic behavior of LH₂ in long-term storage and valuable guidance for tank design.

引入了一个非平衡热力学模型，结合罐壁上的热泄漏再分布效应，描述了LH2储罐的长周期无排气储罐过程。为了提高LH2储罐热力学状态预测的准确性，研究了不同储罐结构间热泄漏的瞬态和非均匀分布特征。随后，对垂直罐、水平罐和球形罐的性能进行了系统的比较，以评估控制压力、温度和蒸发的有效性。结果表明：HRW模型比NHRW模型能更准确地预测平均加压速率，压力RMSE由1.54降至0.63；泄漏热通过壁面的重新分布是泄漏热通量瞬态非均匀性的主要驱动因素，表明了内部流体状态与罐体结构之间的联系。热泄漏在球形罐内的再分布最为显著。当φ=20%时，在36 h内，ql增加了近55%，从1.69 W/m2增加到2.62 W/m2。对于给定的填充比，垂直罐显示最大的时间平均qu，其次是水平罐，最低的是球形罐。增加填充比可以降低所有储罐类型的增压率。当φ=80%时，垂直罐和卧式罐的平均加压率分别比球形罐高40.3%和31.3%。立式罐和卧式罐在温升和蒸发率方面表现出互补的性能，而球形罐的综合性能更优。该研究为LH2在长期储存中的热力学行为提供了重要的见解，并为储罐设计提供了有价值的指导。

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引用次数: 0

Multi-model fusion methods with strong generalization capability for online SOH estimation of lithium-ion batteries 具有较强泛化能力的锂离子电池SOH在线估计多模型融合方法

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-02-04 DOI: 10.1016/j.est.2026.120879

Ankit Sonthalia , Femilda Josepin JS , Edwin Geo Varuvel , Ferzat Anka

Lithium-ion cells are essential in daily life, but accurately assessing their state of health (SOH) is challenging because deep learning models need large, consistent cycling datasets that are often impractical to obtain. Moreover, the real-world data can be incomplete or inconsistent. In this study, the SOH was predicted online utilizing fusion models of convolutional neural network (CNN), long short-term memory (LSTM) convolution block attention mechanism (CBAM), and multi-head attention mechanism (MHA) based architecture. Datasets prepared by the reaserchers at Massachussets Institute of Technology (MIT), and Sandia National Laboratory (SNL) were combined for training various models. Bayesian optimization algorithm was used to optimize the hyperparameters. The results reveal that the CNN-LSTM fusion model enhances the accuracy of capacity estimation. Oxford University dataset was used to test the efficacy of the models. Highest accuracy in prediction was found with the CNN-LSTM model having lowest root mean squared error (RMSE) of 0.0136. Ablation experiments were carried out and the performance of the fusion models was found better than the base models. The trained models were also retrained for another voltage range. CALCE dataset, provided by the University of Maryland, was utilized for the experiments. 2 and 7 cells dataset were separately used for the training. The CNN-CBAM framework with 5 CNN layers was found to be the best model. The models generated in this study can be used for predicting the SOH online for cells having different kind of form, chemistry, charged/discharged at different rates and varying temperatures demonstrating its practicality and generalization ability.

锂离子电池在日常生活中至关重要，但准确评估其健康状态（SOH）具有挑战性，因为深度学习模型需要大量一致的循环数据集，而这些数据集通常难以获得。此外，真实世界的数据可能是不完整或不一致的。在本研究中，利用卷积神经网络（CNN）、长短期记忆（LSTM）、卷积块注意机制（CBAM）和多头注意机制（MHA）的融合模型在线预测SOH。由麻省理工学院（MIT）和桑迪亚国家实验室（SNL）的研究人员准备的数据集被结合起来训练各种模型。采用贝叶斯优化算法对超参数进行优化。结果表明，CNN-LSTM融合模型提高了容量估计的精度。使用牛津大学的数据集来测试模型的有效性。CNN-LSTM模型预测精度最高，均方根误差（RMSE）最低，为0.0136。进行了烧蚀实验，发现融合模型的性能优于基本模型。训练好的模型也被重新训练到另一个电压范围。实验使用马里兰大学提供的CALCE数据集。分别使用2单元格和7单元格数据集进行训练。发现5个CNN层的CNN- cbam框架是最好的模型。本研究建立的模型可用于在线预测不同形态、化学性质、不同充放电速率和不同温度下电池的SOH，具有实用性和推广能力。

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引用次数: 0

Design and analysis of polyoxometalate-based metal-organic framework/MXene composite: Achieving ultra-high proton conduction for intelligent supercapacitor 多金属氧酸盐基金属有机骨架/MXene复合材料的设计与分析：实现智能超级电容器的超高质子传导

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-02-04 DOI: 10.1016/j.est.2026.120758

Xiaoshu Qu, Guangyu Yang, Zeyu Wang, Jilong Wang, Shuang Zhou, Yueting Wang, Xiaoyang Yu, Yanyan Yang

Herein, a new polyoxometalate-based metal–organic framework (POMOF) single crystal, Co(bbi)₂(bbi)_0.5[Mo₈O₂₆]_0.5·H₂O (denoted as Co(bbi)Mo₈), was synthesized via a hydrothermal process. Following this, a composite material Co(bbi)Mo₈/Ti₃C₂T_x consisting of Co(bbi)Mo₈ and Ti₃C₂T_x MXene was created using a physical grinding technique. Co(bbi)Mo₈ possesses numerous redox-active sites and hydrogen bonding distributions, enabling the formation of a widespread hydrogen-bonding network with the surface functional groups of Ti₃C₂T_x. Proton transport occurs via the Grotthuss mechanism, involving proton hopping along hydrogen bonds within the composite matrix, where intrinsic ultra-high proton conductivity is observed (2.50 × 10⁻² S cm⁻¹ at 98% RH, 60 °C). Based on the principles of proton-coupled electron transfer (PCET), the composite exhibits enhanced proton and electron transfer kinetics, achieving an areal specific capacitance of 1165.0 mF cm⁻² at 1.0 mA cm⁻², which represents a 436% enhancement over Co(bbi)Mo₈ and ten times higher than Ti₃C₂T_x. The practical potential of the composite material is demonstrated through the fabrication of asymmetric intelligent supercapacitors, which utilize ion storage film electrodes composed of Co(bbi)Mo₈ and Ti₃C₂T_x. The device enables visual power monitoring and quantitative energy display. This research presents crucial perspectives on the implementation of ultra-high proton-conducting materials in smart energy storage systems.

本文采用水热法合成了一种新的多金属氧酸盐基金属有机骨架（POMOF）单晶Co(bbi)2(bbi)0.5[Mo8O26]0.5·H2O（记为Co(bbi)Mo8）。在此基础上，采用物理研磨技术制备了由Co(bbi)Mo8和Ti3C2Tx MXene组成的Co(bbi)Mo8/Ti3C2Tx复合材料。Co(bbi)Mo8具有大量的氧化还原活性位点和氢键分布，能够与Ti3C2Tx表面官能团形成广泛的氢键网络。质子传输通过Grotthuss机制发生，涉及质子在复合基质内沿氢键跳跃，其中观察到固有的超高质子电导率（在98% RH， 60°C下为2.50 × 10−2 S cm−1）。基于质子耦合电子转移（PCET）原理，复合材料表现出增强的质子和电子转移动力学，在1.0 mA cm - 2下实现了1165.0 mF cm - 2的面积比电容，比Co(bbi)Mo8提高了436%，比Ti3C2Tx提高了10倍。利用Co(bbi)Mo8和Ti3C2Tx组成的离子存储膜电极制备非对称智能超级电容器，证明了该复合材料的实用潜力。该装置可实现可视化功率监测和定量能量显示。本研究为超高质子导电材料在智能储能系统中的应用提供了重要的视角。

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引用次数: 0

Cell-to-pack transfer learning for battery health estimation using domain-adversarial parallel networks 基于域对抗并行网络的电池健康估计的cell -pack迁移学习

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2026-02-04 DOI: 10.1016/j.est.2026.120930

Xing Shu , Haohua Yan , Fei Chen , Renhua Feng , Hongqian Zhao

Accurate estimation of the state of health (SOH) for lithium-ion battery packs is essential for ensuring the safety, performance of electric vehicles. However, cell inconsistency and limited labeled pack-level data significantly hinder reliable estimation. This study presents a cell-to-pack transfer learning framework for SOH estimation using a domain-adversarial parallel spatiotemporal network. First, robust health features, including voltage tangent angles and their corresponding time, are extracted from partial charging curves and validated via Spearman correlation. A parallel long short-term memory–Informer network is then constructed to jointly capture local temporal dependencies and global aging trends, with its hyperparameters optimized using Bayesian optimization. To realize effective knowledge transfer across domains, a domain adversarial training strategy with a gradient reversal layer is introduced, aligning the feature distributions between individual cells (source domain) and the battery pack (target domain) without explicit modeling of cell inconsistencies. Finally, a fine-tuning strategy with frozen shallow layers and hierarchical learning rates adapts the model to target data with minimal supervision. Experimental results on a four-cell series-connected battery pack demonstrate superior accuracy, achieving a maximum error of 2.29%. The proposed method offers a data-efficient and generalizable solution for battery SOH estimation under real-world constraints.

准确估计锂离子电池组的健康状态（SOH）对于确保电动汽车的安全性和性能至关重要。然而，单元不一致和有限的标记包级数据显着阻碍了可靠的估计。本研究提出了一个使用域对抗并行时空网络进行SOH估计的cell-to-pack迁移学习框架。首先，从部分充电曲线中提取稳健性健康特征，包括电压正切角及其对应的时间，并通过Spearman相关进行验证。然后构建了一个并行的长短期记忆-信息网络，以共同捕获局部时间依赖性和全局老化趋势，并使用贝叶斯优化对其超参数进行了优化。为了实现有效的跨领域知识转移，引入了一种具有梯度反转层的领域对抗训练策略，在不显式建模单元不一致性的情况下，对单个单元（源域）和电池组（目标域）之间的特征分布进行对齐。最后，一个具有冻结浅层和分层学习率的微调策略使模型在最小监督下适应目标数据。在四节串联电池组上的实验结果表明，该方法具有较高的精度，最大误差为2.29%。该方法为实际约束下的电池SOH估计提供了一种数据高效且可推广的解决方案。

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引用次数: 0