Journal of energy storage最新文献

Energy and economic analysis of utilizing phase change materials and thermochromic coating in a building 相变材料和热致变色涂料在建筑中的能源和经济分析

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2025-12-13 DOI: 10.1016/j.est.2025.119700

Xing Yuan , Lixiao Zheng , Da Lin

With the increasing energy consumption and its environmental impacts in buildings, the utilization and development of innovative methods based on smart materials have become a necessity. Phase Change Materials (PCM) and thermochromic coatings (TC) are among the technologies that have been demonstrated to significantly lower energy consumption in buildings. This study examines the impact of applying these materials to the roof of a public building to reduce energy consumption, and it systematically optimizes the PCM melting temperature and the thermochromic transition thresholds for coupled PCM–TC roof systems. Numerical simulations were performed using DesignBuilder software to calculate the heating and cooling loads of buildings in two distinct climates: Harbin (cold) and Guangzhou (warm). The results showed that optimizing the melting temperature of PCM and the color-change temperature of thermochromic coatings can significantly reduce energy consumption. For Harbin's cold and dry climate, the optimal setup involved a PCM layer with a phase transition point of 16 °C and a thermochromic coating with a color-change threshold of 12 °C, achieving energy savings of 4.85 % and 2.05 %, respectively. Notably, combining PCM and thermochromic coatings often achieved greater energy savings compared to using each material separately. Specifically, in Harbin, the maximum total energy savings of 11.06 % were achieved.

随着建筑能耗的不断增加及其对环境的影响，基于智能材料的创新方法的利用和开发已成为一种必要。相变材料（PCM）和热致变色涂料（TC）是已经被证明可以显著降低建筑能耗的技术之一。本研究考察了将这些材料应用于公共建筑屋顶以减少能源消耗的影响，并系统地优化了PCM - tc耦合屋顶系统的PCM熔化温度和热致变色过渡阈值。利用DesignBuilder软件进行数值模拟，计算了哈尔滨（寒冷）和广州（温暖）两种不同气候条件下建筑物的冷热负荷。结果表明，优化PCM的熔融温度和热致变色涂层的变色温度可以显著降低能耗。对于哈尔滨寒冷和干燥的气候，最佳设置包括相变点为16°C的PCM层和变色阈值为12°C的热致变色涂层，分别实现了4.85%和2.05%的节能。值得注意的是，与单独使用每种材料相比，结合PCM和热致变色涂层通常可以节省更多的能源。具体来说，在哈尔滨，实现了11.06%的最大总节能。

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引用次数: 0

Lithiophilic–lithiophobic gradient electrode for dendrite-suppressed lithium metal anodes 枝晶抑制锂金属阳极用亲锂-疏石梯度电极

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2025-12-13 DOI: 10.1016/j.est.2025.119826

Byeong-Il Oh , Young Gyu Jeon , Hyun-Kyung Kim

The increasing demand for high-energy-density batteries has positioned lithium (Li) metal as a promising next-generation anode material owing to its potential to deliver significantly higher energy density than conventional anodes. However, its practical application is limited by uncontrolled dendrite formation and pronounced volume fluctuations during cycling. Here, we design a lithiophilic–lithiophobic gradient host (SnO₂/NPG-G) that effectively regulates Li nucleation and deposition. The host comprises a lithiophilic bottom layer of spherical SnO₂/nanoperforated graphene (NPG), which promotes uniform nucleation through abundant carbonyl groups and nanopores, and a lithiophobic top layer of single-walled carbon nanotubes (SWCNTs), which suppresses dendritic propagation at the electrode surface. This gradient architecture enables stable Li plating/stripping in symmetric cells for over 1350 h at 1 mA cm⁻² with low overpotential and maintains a similarly low overpotential even at a high current density of 10 mA cm⁻². Furthermore, a uniform and dendrite-suppressed Li morphology is preserved even at a high areal capacity of 6 mAh cm⁻², as confirmed by morphological analysis after Li deposition behavior evaluation. The SnO₂/NPG-G-Li||LiFePO₄ full cell demonstrates outstanding cycling stability with 92 % capacity retention after 400 cycles. These findings highlight the efficacy of the proposed gradient host design in effectively enabling high-performance Li metal batteries.

由于对高能量密度电池的需求不断增长，锂（Li）金属被定位为有前途的下一代负极材料，因为它有可能提供比传统阳极更高的能量密度。然而，它的实际应用受到不受控制的枝晶形成和循环过程中明显的体积波动的限制。在这里，我们设计了一个亲石-疏石梯度宿主（SnO2/NPG-G），可以有效地调节锂的成核和沉积。宿主材料包括亲石性的球形SnO2/纳米孔石墨烯（NPG）底层，通过丰富的羰基和纳米孔促进均匀成核；以及疏石性的单壁碳纳米管（SWCNTs）顶层，抑制电极表面枝晶的扩展。这种梯度结构能够在1 mA cm - 2的低过电位下在对称电池中稳定地镀/剥离锂超过1350小时，即使在10 mA cm - 2的高电流密度下也能保持类似的低过电位。此外，即使在6 mAh cm−2的高面积容量下，也能保持均匀的枝晶抑制的锂形态，这一点在锂沉积行为评估后的形态学分析中得到了证实。SnO2/NPG-G-Li||LiFePO4全电池在400次循环后具有出色的循环稳定性，容量保持率为92%。这些发现突出了所提出的梯度主机设计在有效实现高性能锂金属电池方面的功效。

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引用次数: 0

Methodology and results of phase change material integration in photovoltaic-thermal systems for enhanced energy production in domestic settings: A review 相变材料集成在光电热系统中用于提高国内能源生产的方法和结果：综述

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2025-12-13 DOI: 10.1016/j.est.2025.119800

Kar R. Awai , Peter King , Kumar Patchigolla

This review explores the use of phase change materials (PCMs) in photovoltaic/thermal (PV/T) systems to improve temperature control and energy storage. It provides a comprehensive overview of current PV/T systems integrated with PCMs, highlighting their potential to increase domestic energy production. The paper covers fundamental principles, benefits, and limitations of PVT technology, the role of PCM applications, and methods of integration. It also examines efficiency gains in power and thermal output, discusses challenges, and suggests future research directions for sustainable energy. Incorporating PCMs into PV/T systems marks notable progress in balancing electrical and thermal efficiencies. Finned serpentine heat exchangers improve heat transfer to PCMs, with more fins increasing surface area and cooling efficiency, while optimised flow rates balance electrical gains against thermal losses. Encapsulation prevents leakage and enhances thermal conductivity. Design factors such as a 25° inclination, insulation, and using dual PCMs in cold regions further improve performance. Economically, PV-T/PCM systems can have shorter payback periods than conventional PV panels if they are used for dual energy and in regions with high solar radiation. However, their viability depends on solar radiation, energy prices, and system costs, which vary by location.

本文综述了相变材料（PCMs）在光伏/热（PV/T）系统中的应用，以改善温度控制和能量存储。它提供了与pcm集成的当前PV/T系统的全面概述，强调了它们增加国内能源生产的潜力。本文涵盖了PVT技术的基本原理、优点和局限性、PCM应用的作用以及集成的方法。它还检查了电力和热输出的效率提高，讨论了挑战，并提出了可持续能源的未来研究方向。将pcm集成到PV/T系统中，在平衡电效率和热效率方面取得了显著进展。翅片蛇形热交换器改善了pcm的传热，更多的翅片增加了表面积和冷却效率，同时优化的流速平衡了电增益和热损失。封装防止泄漏，提高导热性。设计因素，如25°倾角，绝缘，并在寒冷地区使用双pcm进一步提高性能。从经济上讲，如果将PV- t /PCM系统用于双重能源和高太阳辐射地区，则其投资回收期比传统PV板要短。然而，它们的生存能力取决于太阳辐射、能源价格和系统成本，这些都因地点而异。

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引用次数: 0

Evaluating storage profitability: A market-based comparison of hydro and battery options in India 评估储能的盈利能力：印度基于市场的水电和电池选择比较

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2025-12-12 DOI: 10.1016/j.est.2025.119803

Adam Suski , Ilka Deleque Curiel , Debabrata Chattopadhyay , Sushanta Chatterjee , Dzenan Malovic

Energy storage provides firm peaking capacity and ancillary services to support the integration of variable renewable energy (VRE) sources, which form a critical part of the energy transition in most countries, including India. Several storage options are being pursued in India, including battery energy storage systems (BESS), pumped storage hydro plants (PSP), and conventional hydro (mostly run-of-river, ROR, with or without pondage). However, the financial viability of these options, including a market-price-based assessment, has not been explored to understand the relative merits of these competing options. This paper proposes an optimization model to undertake a market-based assessment of BESS, PSP, and ROR. The model assesses energy arbitrage opportunities, revenue from ancillary services, and risk hedging strategies, considering critical drivers such as price variability and hydrological risks. The analysis compares a notional 1 MW unit for each option using historical Indian Energy Exchange (IEX) spot prices and other publicly available data across all states in India that have potential for pumped storage and/or hydro options. The findings suggest that energy arbitrage in the incumbent IEX would have generally fallen short of a typical hurdle rate of return of 10% for all storage options in the majority of historical years. If the revenue from ancillary services is included and part of the output could be hedged through contracts, the business case improves, especially for BESS and PSP. The model provides a rigorous and transparent framework for policymakers to evaluate storage alternatives that support the energy transition.

储能提供稳定的峰值容量和辅助服务，以支持可变可再生能源（VRE）的整合，这是包括印度在内的大多数国家能源转型的关键部分。印度正在寻求几种储能方案，包括电池储能系统（BESS）、抽水蓄能水电站（PSP）和传统水力发电（主要是河流径流，ROR，有或没有池塘）。然而，这些选择的财务可行性，包括以市场价格为基础的评估，尚未进行探讨，以了解这些相互竞争的选择的相对优点。本文提出了一个优化模型，对BESS、PSP和ROR进行市场化评估。该模型考虑了价格变化和水文风险等关键驱动因素，评估了能源套利机会、辅助服务收入和风险对冲策略。该分析使用印度能源交易所（IEX）的历史现货价格和印度所有具有抽水蓄能和/或水力发电潜力的邦的其他公开数据，对每个选项的名义1mw机组进行了比较。研究结果表明，在大多数历史年份，现有IEX的能源套利通常低于所有存储选项10%的典型门槛回报率。如果包括辅助服务的收入，并且部分产出可以通过合同对冲，那么商业案例就会得到改善，尤其是对BESS和PSP而言。该模型为政策制定者评估支持能源转型的储能替代方案提供了一个严格而透明的框架。

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引用次数: 0

Green synthesis and unveiling the stable Lithium-ion storage of a lignin derived carbon supported zinc ferrite nanocomposite 绿色合成和揭示木质素衍生碳负载铁氧体锌纳米复合材料的稳定锂离子存储

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2025-12-12 DOI: 10.1016/j.est.2025.119838

Hui Zeng, Jiahui Li, Shuo Wan, Xiaojian Liu, Hongliang Li, Binghui Xu

This work demonstrates an innovative strategy to effectively dispersing zinc ferrite (ZnFe₂O₄) nanoparticles in lignosulfonate derived carbon (LigC) domains to construct a corresponding ZnFe₂O₄@LigC composite. Lignosulfonate (Lig) is firstly employed to significantly accelerate the coprecipitation between Zn²⁺ and Fe³⁺ in a mild hydrothermal condition. The as-obtained Zn-Fe-Lig intermediate sediment is further converted to ZnFe₂O₄@LigC by a thermal treatment, in which the size and aggregation of the ZnFe₂O₄ nanocrystals are remarkably controlled by the in-situ constructed porous LigC skeleton. The ZnFe₂O₄@LigC nanocomposite exhibits high and stable lithium-ion storage properties, which maintains a reversible capacity of 695.19 mAh g⁻¹ after 600 cycles at a current rate of 1000 mA g⁻¹ in half cells as well as good full cell performances. Particularly, it is preliminarily investigated the evolution of the copper (Cu) foil current collector in the ZnFe₂O₄@LigC electrode induced by the zinc (Zn) atoms, which significantly enhances the binding stability between the Cu foil and the pasted ZnFe₂O₄@LigC nanocomposite. This work not only provides a green and scalable protocol for using organic biomass materials to synthesize inorganic nanocomposites with improved microstructure, but also uncovers a novel understanding for the high and stable lithium-ion storage performances of the ZnFe₂O₄@LigC electrode.

这项工作展示了一种创新的策略，可以有效地将铁酸锌（ZnFe2O4）纳米颗粒分散到木质素磺酸衍生碳（LigC）结构域，以构建相应的ZnFe2O4@LigC复合材料。首次采用木素磺酸盐（Lig）在温和的水热条件下显著加速Zn2+与Fe3+的共沉淀。得到的Zn-Fe-Lig中间沉积物通过热处理进一步转化为ZnFe2O4@LigC，其中ZnFe2O4纳米晶的大小和聚集明显受到原位构建的多孔LigC骨架的控制。ZnFe2O4@LigC纳米复合材料具有高且稳定的锂离子存储性能，在半电池中以1000 mA g - 1的电流循环600次后保持695.19 mAh g - 1的可逆容量，并且具有良好的全电池性能。特别是，初步研究了锌原子诱导下ZnFe2O4@LigC电极中铜（Cu）箔集流体的演化，显著增强了铜（Cu）箔与粘贴的ZnFe2O4@LigC纳米复合材料之间的结合稳定性。这项工作不仅为使用有机生物质材料合成具有改进微观结构的无机纳米复合材料提供了一种绿色和可扩展的方案，而且还为ZnFe2O4@LigC电极的高稳定锂离子存储性能提供了新的认识。

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引用次数: 0

Parameter identification of lithium-ion electrochemical model using fully connected neural network and adaptive switching swarm intelligence algorithm 基于全连接神经网络和自适应切换群智能算法的锂离子电化学模型参数辨识

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2025-12-12 DOI: 10.1016/j.est.2025.119824

Mingqiang Lin , Zixiang Huang , Jinhao Meng , Wei Wang , Ji Wu , FengXiang Wang

Accurate sensing of the internal state of lithium-ion batteries and the identification of key electrochemical parameters are essential for reliable evaluations of the battery health. However, parameter identification using swarm intelligence algorithms (SIAs) alone is time-consuming, and purely neural network-based methods often require extensive experimental data. To overcome these challenges, this paper proposes a parameter identification approach, referred to as fully connected neural network and adaptive switching swarm intelligence algorithm (FCASIA), for an electrochemical model of lithium-ion batteries. The proposed approach integrates deep learning with dual neural networks: a convolutional neural network (CNN) adaptively selects the suitable SIA, and a fully connected neural network (FCNN) refines the parameter estimation. This dual-network framework substantially improves both accuracy and speed, thereby addressing the limitations of single solution. In addition, an adaptive online training mechanism coupled with the FCNN's ability to generate and inject high-potential new candidates, enable a high-precision parameter identification without relying on large volume of experimental data. By constructing an efficient parameter identification framework for pseudo two-dimensional (P2D) model, the proposed method further accelerates convergence and enhances accuracy. Comparative experiments indicate that FCASIA outperforms direct SIA-based methods, achieving an average parameter error of only a 5 % deviation from ground truth and demonstrating its potential for accurately and efficiently handling complex battery models.

锂离子电池内部状态的准确感知和关键电化学参数的识别对于电池健康状况的可靠评估至关重要。然而，单独使用群体智能算法（SIAs）进行参数识别非常耗时，而纯粹基于神经网络的方法往往需要大量的实验数据。为了克服这些挑战，本文提出了一种用于锂离子电池电化学模型的参数识别方法，即全连接神经网络和自适应切换群智能算法（FCASIA）。该方法将深度学习与双神经网络相结合：卷积神经网络（CNN）自适应选择合适的SIA，全连接神经网络（FCNN）改进参数估计。这种双网络框架大大提高了准确性和速度，从而解决了单一解决方案的局限性。此外，自适应在线训练机制与FCNN生成和注入高潜力新候选对象的能力相结合，使高精度参数识别不依赖于大量实验数据。通过构建有效的伪二维（P2D）模型参数识别框架，该方法进一步加快了收敛速度，提高了精度。对比实验表明，FCASIA优于直接基于sia的方法，平均参数误差仅与地面真实值偏差5%，并证明了其准确有效地处理复杂电池模型的潜力。

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引用次数: 0

Spatial and temporal enhancement method for predicting heat generation characteristics of pouch lithium-ion battery 袋状锂离子电池产热特性时空增强预测方法

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2025-12-12 DOI: 10.1016/j.est.2025.119818

Shiqi Xu , Siyu Zheng , Chenxing Hu , Xuhui Li , Yu Tian , Yuxuan Zhao , Hong Zhang

Detecting the time-evolving non-uniform distribution of temperature fields in pouch lithium-ion batteries remains a significant challenge in battery research. This study introduces two methods for real-time temperature reconstruction of pouch lithium-ion batteries. A numerical simulation model of the pouch-type lithium-ion cell was developed and validated using experimental data. The heat generation characteristics were analyzed at different discharge rates, and spatial and temporal data enhancement strategies were used to reconstruct the real-time temperature field under varying discharge rates and depths of discharge (DOD). Results showed the non-uniform temperature distribution of the battery was influenced by discharge rate and DOD. The proposed method allowed for reconstruction of the non-uniform temperature distribution using temperature measurements from a limited number of sensors on the battery's external surface. K-means clustering was employed to identify three primary regions of heat generation and optimal sensor placement within these clusters, enabling global field reconstruction with just three sensors. However, the reconstruction accuracy was dependent on the proportion of DOD selected for the training dataset; when the training dataset exceeds 30 % DOD, the reconstruction mean squared error (MSE) remains below 0.3 %. On the other hand, Temporal resolution enhancement was achieved using extended proper orthogonal decomposition (EPOD), which accurately captures high-resolution temperature features, reducing the need for frequent temperature monitoring. Under a discharge rate of 1.0C, the MSE remaining below 1.2 % for most of the discharge process from 13 % to 80 % DOD. This study may provide a guideline for the spatial and temporal reconstruction of the time-evolving non-uniform temperature distribution in pouch lithium-ion batteries.

探测袋状锂离子电池温度场随时间变化的非均匀分布一直是电池研究中的一个重大挑战。本研究介绍了两种用于袋状锂离子电池实时温度重建的方法。建立了袋式锂离子电池的数值模拟模型，并用实验数据进行了验证。分析了不同放电速率下的产热特性，采用时空数据增强策略重构了不同放电速率和放电深度下的实时温度场。结果表明，电池温度分布的不均匀性受到放电速率和DOD的影响。所提出的方法允许使用有限数量的电池外表面传感器的温度测量来重建非均匀温度分布。采用K-means聚类来确定三个主要的热产生区域，并在这些聚类中确定最佳传感器位置，从而仅使用三个传感器即可实现全球现场重建。然而，重建精度取决于为训练数据集选择的DOD的比例；当训练数据集超过30% DOD时，重构均方误差（MSE）保持在0.3%以下。另一方面，利用扩展适当正交分解（extended proper orthogonal decomposition， EPOD）实现了时间分辨率的增强，可以准确捕获高分辨率温度特征，减少了频繁温度监测的需要。在1.0C的放电速率下，从13%到80% DOD的大部分放电过程中，MSE保持在1.2%以下。该研究可为袋状锂离子电池中随时间变化的非均匀温度分布的时空重构提供指导。

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引用次数: 0

AI-enhanced design of liquid-PCM hybrid cooling for li-ion batteries: GA-MLPNN modeling integrated with multi-objective artificial vultures optimization 基于ai的锂离子电池液- pcm混合冷却设计：GA-MLPNN建模与多目标人工秃鹫优化相结合

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2025-12-12 DOI: 10.1016/j.est.2025.119701

Rashid Khan , Ihab Omar , As'ad Alizadeh , Narinderjit Singh Sawaran Singh , Muntadher Abed Hussein , Abdellatif M. Sadeq , Husam Rajab , Khalil Hajlaoui

This study presents a novel four-stage hybrid framework that integrates machine learning, multi-objective optimization, and multi-criteria decision-making to enhance the thermal management of lithium-ion batteries (LIBs) using a liquid-PCM hybrid cooling system. Addressing a key limitation in existing research, the fragmented treatment of modeling, optimization, and decision-making, this work unifies these components into a cohesive, decision-oriented framework. A GA-optimized multilayer perceptron neural network is first developed to predict thermal-hydraulic responses from design parameters, achieving high accuracy (R > 0.985) and excellent generalizability via cross-validation. For optimization, a novel multi-objective artificial vultures optimization (MOAVOA) is benchmarked against MOPSO, with MOPSO outperforming in Pareto front density, diversity, and convergence. Key trade-offs reveal that PCM thicknesses of 7–8.9 mm, channel widths of 8–8.99 mm, and inlet velocities >0.410 m/s yield optimal thermal performance. The final decision-making stage uses the weighted Tchebycheff method to extract twelve actionable design scenarios aligned with varied operational priorities. This integrated framework enables context-specific, robust engineering decisions across sectors such as electric vehicles and consumer electronics, contributing to the development of safer, more efficient, and sustainable battery technologies.

本研究提出了一个新的四阶段混合框架，该框架集成了机器学习，多目标优化和多标准决策，以增强使用液体- pcm混合冷却系统的锂离子电池（LIBs）的热管理。解决了现有研究中的一个关键限制，即建模、优化和决策的碎片化处理，这项工作将这些组件统一到一个有凝聚力的、面向决策的框架中。首先建立了ga优化的多层感知器神经网络来预测设计参数的热液响应，通过交叉验证获得了较高的精度（R > 0.985）和良好的泛化性。在优化方面，以一种新型的多目标人工秃鹫优化算法（MOAVOA）为基准，对比MOPSO算法，发现MOPSO算法在帕累托前密度、多样性和收敛性方面都优于MOPSO算法。关键的权衡表明，PCM厚度为7-8.9 mm，通道宽度为8-8.99 mm，入口速度为0.410 m/s，可获得最佳的热性能。最后的决策阶段使用加权Tchebycheff方法来提取12个可操作的设计方案，这些方案与不同的操作优先级相一致。这一集成框架能够在电动汽车和消费电子等领域实现特定环境下的稳健工程决策，有助于开发更安全、更高效、更可持续的电池技术。

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引用次数: 0

Control of the gallium melting rate with a non-uniform magnetic field: Experimental and numerical study 非均匀磁场下镓熔化速率的控制：实验与数值研究

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2025-12-12 DOI: 10.1016/j.est.2025.119855

Oscar Leonardo Torres-Saucedo, José Luis Morón-Cruz, Alberto Beltrán

The presence of magnetic fields in the metal melting process enables control over the phase-change in energy storage systems. In this work, the melting process of gallium in the presence of a static non-uniform magnetic field is studied experimentally and numerically. The experimental setup consists of a prismatic cavity with dimensions of 55

\times

50

\times

50 mm, filled with gallium, initially solid at 29 °

C

. A horizontal temperature difference with values of 8, 9.5, and 11 °

C

is set on two parallel faces. A permanent magnet, placed on the top wall, generates a non-uniform magnetic field. The main magnetic field component is aligned with gravity and perpendicular to the imposed temperature difference. Studies are conducted both with and without the magnetic field. Experimentally, ultrasonic Doppler techniques characterize the solid–liquid interface and velocity profiles. Additionally, a three-dimensional numerical study was conducted using ANSYS Fluent software. The experimental and numerical results for the magnetic field distribution, solid–liquid interface, and velocity profiles are consistent and demonstrate that the externally imposed magnetic field slows down the fluid flow and the melting rate by up to 38% and 22%, respectively. It also shows that the solid–liquid interface becomes flatter under the magnetic field.

金属熔化过程中磁场的存在使储能系统中的相变控制成为可能。本文采用实验和数值方法研究了在静态非均匀磁场作用下镓的熔化过程。实验装置由一个尺寸为55 × 50 × 50 mm的棱柱腔组成，填充镓，在29°C时初始为固体。水平温差值为8、9.5和11°C，设置在两个平行的面上。放置在顶部壁上的永磁体产生不均匀的磁场。主磁场分量与重力对齐，并垂直于施加的温差。研究可以在有磁场和没有磁场的情况下进行。实验上，超声多普勒技术表征了固液界面和速度分布。此外，利用ANSYS Fluent软件进行了三维数值研究。磁场分布、固液界面和速度分布的实验和数值结果一致，表明外加磁场使流体流动和熔化速度分别减慢38%和22%。在磁场作用下，固液界面变得更平坦。

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引用次数: 0

Enhanced electronic structure and electrochemical active area of ternary NiCoFe-LDH and Cu nanowire composites for superior energy storage 镍铁- ldh和铜纳米线三元复合材料的电子结构和电化学活性区增强，具有优异的储能性能

IF 8.9 2区工程技术 Q1 ENERGY & FUELS

Journal of energy storage

Pub Date : 2025-12-12 DOI: 10.1016/j.est.2025.119690

Subin Eom , Moo Young Jung , Jihye Park , Ji-Won Son , JeongHyeon Ahn , Sung Won Kim , Yong Ju Yun , Yongseok Jun

Climate change urgently necessitates the development of sustainable energy solutions alongside efficient energy storage devices. Among these, supercapacitors have emerged as promising candidates due to their fast charge/discharge capabilities and exceptional long-term cycle stability. In this study, NiCoFe-layered double hydroxide (NiCoFe-LDH) was successfully synthesized via electrodeposition onto copper nanowires (Cu NWs), which were prepared through electrochemical anodization followed by thermal reduction. The optimal Fe ratio in NiCoFe-LDH@Cu NW was determined through various electrochemical tests, with the 3-NiCoFe-LDH@Cu NW (Ni:Co:Fe = 5:3:3) exhibiting superior electrochemical performance, achieving a capacity of 130.20 μAh cm⁻² at a current density of 3.0 mA cm⁻². To evaluate practical applicability, an asymmetric supercapacitor (ASC) was fabricated using 3-NiCoFe-LDH@Cu NW as the positive electrode and 1-MXene@CuO NW as the negative electrode. The ASC demonstrated excellent energy storage performance, delivering an energy density of 1.69 mWh cm⁻² at a power density of 19.27 mW cm⁻², outperforming recently reported devices. Furthermore, the ASC retained 80.7 % of its initial capacity after 8000 cycles at 10 mA cm⁻², with a coulombic efficiency of 102.9 %, highlighting its remarkable stability and efficiency.

气候变化迫切需要开发可持续能源解决方案以及高效的能源存储设备。其中，超级电容器因其快速充放电能力和卓越的长期循环稳定性而成为有希望的候选者。在本研究中，通过电化学阳极氧化和热还原制备的铜纳米线（Cu NWs）上电沉积，成功合成了NiCoFe-LDH层状双氢氧化物（NiCoFe-LDH）。通过各种电化学实验确定了NiCoFe-LDH@Cu NW中Fe的最佳配比，结果表明3-NiCoFe-LDH@Cu NW （Ni:Co:Fe = 5:3:3）在电流密度为3.0 mA cm - 2时的容量为130.20 μAh cm - 2，表现出优异的电化学性能。为了评估其实用性，以3-NiCoFe-LDH@Cu NW为正极，1-MXene@CuO NW为负极制备了非对称超级电容器（ASC）。ASC表现出优异的储能性能，在19.27 mW cm - 2的功率密度下提供1.69 mWh cm - 2的能量密度，优于最近报道的器件。此外，在10 mA cm−2下循环8000次后，ASC保持了80.7%的初始容量，库仑效率为102.9%，突出了其卓越的稳定性和效率。

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引用次数: 0