Next Energy

Pub Date : 2026-01-17 DOI: 10.1016/j.nxener.2025.100510

P.R. Jubu , B.J. Akeredolu , S.J. Ikwe , K.O. Ighodalo , O.S. Obaseki , Z.S. Mbalaha , S.K. Omotayo , Y. Yusof , M.Z. Pakhuruddin

Perovskite solar cells (PSCs) commonly utilize organic materials as a hole-transport layer (HTL) to enhance hole extraction to the back electrode, thereby boosting device performance. These organic HTL are chemically and thermally unstable, degrading when exposed to air and moisture. This work, for the first time, attempts to explore the possibility of replacing the conventional organic HTL with the thermally and chemically stable, high hole mobility, inorganic III-nitride p-InGaN material as an HTL in PSC. The p-InGaN HTL-based PSC achieved a power conversion efficiency (PCE) of 21.6%, which is reasonable when compared to the PCE of 32.9% and 34.5% delivered by the conventional organic Spiro-OMeTAD HTL and the HTL-free configurations. These can be attributed to the assisted hole extraction by the HTL and the direct contact of the MAPbI₃ perovskite absorber with the optimal higher work-function Pt back contact for the Spiro-OMeTAD HTL-based and HTL-free-based devices, respectively. We observed that variations in the back metal contact have a significant impact on the PCE of Spiro-OMeTAD HTL-based and HTL-free PSC, respectively. Although the p-InGaN and Spiro-OMeTAD HTL-based PSCs demonstrate equivalent values of PCE at all high temperatures, 400–700 K. The HTL-free cell shows higher thermal resilience compared to its HTL-based counterpart devices. Our work reveals that utilizing the p-InGaN HTL increases longevity due to material stability, whereas eliminating the HTL can deliver higher PCE and reduced costs.

钙钛矿太阳能电池（PSCs）通常利用有机材料作为空穴传输层（HTL）来增强后电极的空穴提取，从而提高器件性能。这些有机HTL在化学上和热上都不稳定，暴露在空气和湿气中会降解。这项工作首次尝试探索用热化学稳定、高空穴迁移率、无机iii -氮化p-InGaN材料取代传统有机HTL作为PSC中HTL的可能性。基于p-InGaN html的PSC实现了21.6%的功率转换效率（PCE），与传统有机Spiro-OMeTAD html和无html配置的PCE分别为32.9%和34.5%相比，这是合理的。这可归因于HTL的辅助孔提取，以及MAPbI3钙钛矿吸收剂与Spiro-OMeTAD基于HTL和无HTL的器件的最佳高功函数Pt背接触的直接接触。我们观察到，后金属接触的变化分别对Spiro-OMeTAD基于html和无html的PSC的PCE有显著影响。尽管p-InGaN和Spiro-OMeTAD基于html的psc在400-700 K的所有高温下都显示出相同的PCE值。与基于html的同类设备相比，无html电池显示出更高的热弹性。我们的研究表明，由于材料的稳定性，使用p-InGaN HTL可以延长使用寿命，而消除HTL可以提供更高的PCE并降低成本。

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引用次数: 0

Evidential multi-model CNN integration for visual fault detection in solar panels 基于证据的多模型CNN集成太阳能电池板视觉故障检测

Next Energy

Pub Date : 2026-01-14 DOI: 10.1016/j.nxener.2025.100509

Nadjia Khatir , Safia Nait-Bahloul

This study proposes an evidential fusion framework for classifying visual defects in solar panels using convolutional neural networks (CNNs) and Dempster-Shafer theory (DST). Three pretrained CNN models: ResNet50, MobileNetV2, and EfficientNetB0 are fine-tuned to detect multiple defect types, and their outputs are fused at the logit level using DST. Unlike conventional ensemble strategies such as majority voting, the proposed method explicitly accounts for uncertainty and conflict among predictions by assigning belief masses to sets of hypotheses. Experimental evaluations conducted on a multiclass solar panel dataset demonstrate that DST fusion consistently outperforms individual models and majority voting across all macro-averaged metrics, particularly in underrepresented or visually ambiguous classes such as Physical-Damage and Dusty. These findings underscore the potential of uncertainty-sensitive model fusion to enhance the robustness and interpretability of automated photovoltaic inspection systems.

本研究提出了一种基于卷积神经网络（cnn）和Dempster-Shafer理论（DST）的太阳能电池板视觉缺陷分类证据融合框架。三个预训练的CNN模型：ResNet50、MobileNetV2和EfficientNetB0被微调以检测多种缺陷类型，并且它们的输出使用DST在logit级别融合。与传统的集合策略（如多数投票）不同，该方法通过将信念质量分配给假设集，明确地解释了预测之间的不确定性和冲突。在多类别太阳能电池板数据集上进行的实验评估表明，DST融合在所有宏观平均指标上始终优于单个模型和多数投票，特别是在代表性不足或视觉模糊的类别（如物理损伤和Dusty）中。这些发现强调了不确定性敏感模型融合的潜力，以提高自动化光伏检测系统的鲁棒性和可解释性。

引用次数: 0

Recent advances in bimetallic-cobalt oxides and their composites as a potential candidate for supercapacitor electrode material 双金属钴氧化物及其复合材料作为超级电容器电极材料的研究进展

Next Energy

Pub Date : 2026-01-13 DOI: 10.1016/j.nxener.2025.100505

Tekalign Aregu Tikish , Yared Worku , Nithyadharseni Palaniyandy , Eno E. Ebenso

The growing demand for green energy has made energy storage crucial in energy generation systems. Supercapacitors (SCs) are gaining popularity in energy storage due to their high-power density and long cycle life. Bimetallic cobalt oxides (MCo₂O₄) are promising electrode materials due to their enhanced electrochemical performance and synergistic effects. This review provides a unique and exclusive focus on the recent 5-year progress (2020–2025) in MCo₂O₄ materials for SC applications. It provides a detailed analysis of various synthesis processes, the relationship between crystal structure (particularly the stable spinel structure) and electrochemical activity, the inherent battery-like charge storage mechanism of cobalt oxides, and a comparative performance evaluation. It also analyzes the electrolyte in Bimetallic Metal Oxides and their composites. The review highlights the strategic inclusion of a secondary metal (M = Ni, Cu, Fe, Mn, Zn) into cobalt oxide, which enhances key metrics, including specific capacitance, rate capability, and cyclic stability. Furthermore, this review demonstrated the strategies for improving overall SC performance through composite formation with conductive additives (carbon materials, metal oxides, conducting polymers, and MOFs). Lastly, the review concludes by summarizing the advanced and outlining crucial future research pathways to guide the development of superior bimetallic cobalt oxide-based SCs.

对绿色能源日益增长的需求使得储能在能源生产系统中变得至关重要。超级电容器因其高功率密度和长循环寿命在储能领域越来越受欢迎。双金属钴氧化物（MCo2O4）具有较强的电化学性能和协同效应，是一种很有前途的电极材料。本文综述了最近5年（2020-2025年）用于SC应用的MCo2O4材料的独特和独家的进展。详细分析了各种合成工艺，晶体结构（特别是稳定的尖晶石结构）与电化学活性的关系，钴氧化物固有的类似电池的电荷储存机制，并进行了性能比较评价。对双金属氧化物及其复合材料中的电解液进行了分析。该综述强调了将二次金属（M = Ni, Cu, Fe, Mn, Zn）战略性地包含在氧化钴中，从而提高了关键指标，包括比电容、倍率能力和循环稳定性。此外，本综述还展示了通过与导电添加剂（碳材料、金属氧化物、导电聚合物和mof）形成复合材料来提高整体SC性能的策略。最后，综述总结了先进的研究进展，并概述了未来重要的研究途径，以指导高性能双金属钴基纳米材料的发展。

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引用次数: 0

Predicting methane and nitrous oxide emissions from Indian cattle farming using advanced time series techniques 利用先进的时间序列技术预测印度畜牧业的甲烷和一氧化二氮排放

Next Energy

Pub Date : 2026-01-01 DOI: 10.1016/j.nxener.2025.100496

Binita Kumari , Dipanjali Ray , Ganeshkumar D. Rede , Soumik Ray , Shiwani Tiwari , Pradeep Mishra

This study aims to forecast methane (CH₄) and nitrous oxide (N₂O) emissions from cattle rearing in India, which contribute significantly to agricultural greenhouse gas (GHG) emissions. Data on these emissions was collected from the Food and Agricultural Organization for the years 1961–2022. Three time series models, namely, exponential smoothing (Holt-Winters), autoregressive integrated moving average (ARIMA), and trigonometric seasonality, Box-Cox transformation, ARMA errors, trend, and seasonal components (TBATS) were employed to predict future emissions. The dataset was partitioned into training (1961–2012) and testing (2013–2022) sets to evaluate model performance. Diagnostic metrics, including Akaike Information Criterion, root mean square error, mean absolute percentage error, and mean absolute scaled error, were used to assess accuracy. Results indicated that the ARIMA model outperformed the other 2 forecasting models by making over 90% accurate predictions. For N₂O, ARIMA (0,1,0) was identified as the optimal model, while ARIMA (2,1,2) was selected for CH₄. Thus, the study validates the use of ARIMA model in GHG forecasting. The study projects emissions up to 2030, providing critical insights for policymakers to design targeted mitigation strategies. The study also presses the need for implementing sustainable cattle management practices for cutting emissions in India.

本研究旨在预测印度养牛过程中甲烷（CH₄）和氧化亚氮（N₂O）的排放，这两种气体对农业温室气体（GHG）排放有很大贡献。这些排放的数据是从联合国粮农组织1961年至2022年收集的。采用指数平滑（Holt-Winters）、自回归综合移动平均（ARIMA）和三角季节性、Box-Cox变换、ARMA误差、趋势和季节分量（TBATS） 3种时间序列模型对未来排放进行预测。数据集被划分为训练集（1961-2012）和测试集（2013-2022），以评估模型的性能。诊断指标包括赤池信息标准、均方根误差、平均绝对百分比误差和平均绝对比例误差，用于评估准确性。结果表明，ARIMA模型的预测准确率在90%以上，优于其他2种预测模型。对于N₂O，最优模型为ARIMA(0,1,0)，而对于CH₄，最优模型为ARIMA（2,1,2）。因此，本研究验证了ARIMA模型在温室气体预测中的应用。该研究预测了到2030年的排放量，为政策制定者设计有针对性的减排战略提供了关键见解。该研究还强调了在印度实施可持续的养牛管理措施以减少排放的必要性。

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引用次数: 0

Waste-to-hydrogen production: Recycling aluminium dross in alkali solutions 废物制氢：在碱溶液中回收铝渣

Next Energy

Pub Date : 2026-01-01 DOI: 10.1016/j.nxener.2025.100498

Ankur Srivastava, Arunabh Meshram

The valorisation of aluminium dross for hydrogen production offers a sustainable waste-to-energy pathway. This study examines hydrogen evolution from aluminium dross in aqueous NaOH and KOH (0.25–1.0 M) at 40–70 °C, measuring it as a function of time and using 3D contour mapping to determine initial rates and cumulative yields. Hydrogen evolution rises with alkali concentration and temperature; NaOH produces higher rates and volumes at lower conditions, while KOH exhibits steadier temperature-driven increases. The kinetic study reveals that the Avrami-Erofeyev model provides the best fit to the experimental data, showing excellent linearity (R² = 0.95–0.99). The calculated reaction orders (n = 0.88–1.23) indicate a near first-order behaviour consistent with nucleation-growth mechanisms. Arrhenius analysis gives activation energies of 63.07 kJ/mol (0.5 M NaOH) and 73.62 kJ/mol (0.5 M KOH), highlighting differing mechanistic regimes. This work frames dross recycling as a strategy to convert hazardous residue into low-carbon fuel, advocating integration of such benign hydrogen-generation routes into industrial design and policy to close material loops and enhance resilience.

铝渣用于制氢的增值提供了一个可持续的废物转化能源的途径。本研究考察了在40-70 °C条件下，铝渣在NaOH和KOH水溶液（0.25-1.0 M）中的析氢，测量了其作为时间的函数，并使用3D等高线映射来确定初始速率和累积产率。析氢量随碱浓度和温度的升高而升高；NaOH在较低的条件下产生更高的速率和体积，而KOH则表现出稳定的温度驱动增长。动力学研究表明，Avrami-Erofeyev模型与实验数据拟合最佳，线性良好（R2 = 0.95-0.99）。计算的反应阶数（n = 0.88-1.23）表明接近一级的行为符合成核-生长机制。Arrhenius分析得出活化能分别为63.07 kJ/mol（0.5 M NaOH）和73.62 kJ/mol（0.5 M KOH）。本研究将垃圾回收作为一种将有害残留物转化为低碳燃料的策略，倡导将这种良性的产氢路线纳入工业设计和政策中，以关闭材料循环并增强弹性。

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引用次数: 0

A hybrid CFD-neural network framework for the early prediction of longitudinal thermo-acoustic instabilities in hydrogen-fueled gas turbine combustors 用于氢燃料燃气轮机燃烧室纵向热声不稳定性早期预测的混合cfd -神经网络框架

Next Energy

Pub Date : 2026-01-01 DOI: 10.1016/j.nxener.2025.100497

Oyinbonogha Fred Agonga , Norazila Othman , Mohd Fairus Mohd Yasin

This study introduces a hybrid Computational Fluid Dynamics–Neural Network (CFD–NN) framework for real-time prediction of longitudinal thermo-acoustic instabilities in hydrogen-fueled gas turbine combustors—critical for future clean energy systems. A high-fidelity two-dimensional CFD model simulated hydrogen combustion and provided time-resolved pressure and heat release data. The Local Rayleigh Index (LRI) identified probe X₂ as a strong instability zone (LRI ≈ 10⁷ Pa·W), while X₁, X₄, and X₆ showed stable behavior. A feedforward neural network trained on early-stage data from probe X3 achieved high prediction accuracy (R² = 0.9998, Root Mean Square Error (RMSE = 924)) and delivered predictions ∼676× faster than CFD (∼334 predictions/s). By combining physics-based modeling with machine learning, this hybrid method enables real-time, physics-informed diagnostics, supporting smart combustor design and closed-loop control in next-gen hydrogen turbines.

本研究引入了一种混合计算流体动力学-神经网络（CFD-NN）框架，用于实时预测氢燃料燃气轮机燃烧器的纵向热声不稳定性，这对未来的清洁能源系统至关重要。高保真二维CFD模型模拟了氢气燃烧，并提供了时间分辨的压力和热量释放数据。局部瑞利指数（LRI）鉴定探针X2为强不稳定区（LRI≈10⁷Pa·W），而X1、X4和X6表现出稳定行为。利用探针X3的早期数据训练的前馈神经网络获得了很高的预测精度（R² = 0.9998，均方根误差（RMSE = 924）），预测速度比CFD（~ 334次预测/秒）快~ 676倍。通过将基于物理的建模与机器学习相结合，这种混合方法可以实现实时的物理诊断，支持下一代氢轮机的智能燃烧室设计和闭环控制。

引用次数: 0

Solar PV in the 21st century: Aligning technological growth with sustainability 21世纪的太阳能光伏：使技术增长与可持续性保持一致

Next Energy

Pub Date : 2026-01-01 DOI: 10.1016/j.nxener.2025.100499

Yanqiu Zhang

The escalating energy crisis and climate change necessitate a rapid transition to renewable energy, with solar photovoltaic (PV) technology emerging as a pivotal solution. This paper highlights the dual role of solar PV in reducing carbon emissions and enhancing energy security. It outlines the rapid, policy-driven expansion of solar PV in China, where installed capacity increased significantly from 43 GW in 2015 to 887 GW in 2024. A comparative analysis of PV deployment patterns and trends in the United States, India, and Brazil is also provided. The study further points out several challenges pertaining to geopolitical risks within critical mineral supply chains, the sustainable recycling of end-of-life PV modules, land-use conflicts, grid management, and durability that may impede the sustainability of solar PV. Furthermore, corresponding policy incentives, technological innovation, diversifying solar PV supply chains, multilateral cooperation, and circular principles are discussed to overcome these challenges; strategic integration of desert deployment, floating PV systems, and agrivoltaics exemplifies a spatially diversified approach to resolving land-energy conflicts. The paper further proposes a comprehensive sustainability framework for solar PV, emphasizing that factors such as maintaining policy stability and adaptive regulatory frameworks, assessments of lifecycle environmental impacts, and ensuring justice and equity in the energy transition are pivotal to achieving long-term sustainability. By aligning technological advancements with adaptive policies, solar PV can transition from exponential growth to sustainability, offering a viable pathway toward global carbon neutrality and resilient energy systems.

不断升级的能源危机和气候变化要求向可再生能源的快速过渡，太阳能光伏（PV）技术成为关键的解决方案。本文强调了太阳能光伏在减少碳排放和加强能源安全方面的双重作用。报告概述了中国太阳能光伏产业在政策驱动下的快速扩张，其装机容量从2015年的43 GW大幅增加到2024年的887 GW。本文还对美国、印度和巴西的光伏部署模式和趋势进行了比较分析。该研究进一步指出了与关键矿产供应链中的地缘政治风险、报废光伏组件的可持续回收、土地使用冲突、电网管理和耐久性相关的几个挑战，这些挑战可能会阻碍太阳能光伏的可持续性。此外，本文还讨论了相应的政策激励、技术创新、多元化太阳能光伏供应链、多边合作和循环原则，以克服这些挑战；沙漠部署、浮动光伏系统和农业发电的战略整合是解决土地能源冲突的空间多样化方法的典范。本文进一步提出了一个全面的太阳能光伏可持续性框架，强调维持政策稳定性和适应性监管框架、评估生命周期环境影响以及确保能源转型中的正义和公平等因素对于实现长期可持续性至关重要。通过将技术进步与适应性政策相结合，太阳能光伏可以从指数增长过渡到可持续性，为实现全球碳中和和弹性能源系统提供了一条可行的途径。

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引用次数: 0

Harnessing green power: A comprehensive analysis of India's renewable energy growth and future outlook 利用绿色能源：对印度可再生能源增长和未来前景的综合分析

Next Energy

Pub Date : 2026-01-01 DOI: 10.1016/j.nxener.2025.100493

Sanjay R. Kumbhar , Sanjay T. Satpute , Yogesh S. Patil

India has emerged as one of the global frontrunners in renewable energy (RE) deployment, driven by ambitious national targets, progressive policies, and rapid technological adoption. This study presents a comprehensive, data-driven assessment of India’s RE transition between 2010 and 2025, integrating secondary datasets from the Ministry of New and Renewable Energy, Central Electricity Authority, International Energy Agency, and National Institution for Transforming India Aayog. Using compound annual growth rate (CAGR), correlation, and trend analysis, the study evaluates the performance and inter-sectoral dynamics of solar, wind, hydro, and bioenergy segments. The findings reveal that India’s total installed renewable capacity increased from 17 GW in 2010–190 GW in 2025, with solar energy exhibiting the highest growth (CAGR ≈ 24.8%), followed by wind (≈ 10.3%). Regression analysis indicates a strong positive correlation (r = 0.91) between gross domestic product growth and renewable capacity expansion, emphasizing the sector’s economic significance. A novel contribution of this research lies in its multi-dimensional analytical framework, combining policy mapping, financial trends, and comparative benchmarking against Brazil, Russia, India, China, and South Africa nations to identify structural bottlenecks and feasible interventions. Key challenges such as grid integration, financing constraints, and intermittency are prioritized through a risk–impact matrix, while opportunities in green hydrogen, artificial intelligence/internet of things integration, offshore wind, and export potential are evaluated using a strengths, weaknesses, opportunities, and threats-based market feasibility model. The study concludes that achieving India’s 500 GW non-fossil target by 2030 requires annual investments exceeding USD 25–30 billion, regulatory harmonization, and digital optimization of energy systems. By synthesizing quantitative insights with policy analysis, this paper bridges the gap between descriptive reviews and empirical assessments, offering actionable guidance for policymakers, investors, and researchers engaged in India’s RE transition.

在雄心勃勃的国家目标、进步的政策和快速的技术采用的推动下，印度已成为可再生能源部署的全球领跑者之一。本研究综合了来自新能源和可再生能源部、中央电力局、国际能源署和印度国家转型机构的二手数据，对印度2010年至2025年的可再生能源转型进行了全面的数据驱动评估。利用复合年增长率（CAGR）、相关性和趋势分析，该研究评估了太阳能、风能、水电和生物能源领域的表现和部门间动态。研究结果显示，印度的可再生能源总装机容量从2010年的17 GW增加到2025年的190 GW，其中太阳能增长最快（复合年增长率≈24.8%），其次是风能（≈10.3%）。回归分析表明，国内生产总值增长与可再生能源产能扩张之间存在很强的正相关关系（r = 0.91），强调了该部门的经济意义。本研究的一个新颖贡献在于其多维分析框架，将政策映射、金融趋势以及与巴西、俄罗斯、印度、中国和南非等国的比较基准相结合，以确定结构性瓶颈和可行的干预措施。通过风险影响矩阵对电网整合、融资限制和间歇性等关键挑战进行优先排序，而绿色氢、人工智能/物联网整合、海上风电和出口潜力的机会则使用基于优势、劣势、机会和威胁的市场可行性模型进行评估。该研究得出的结论是，到2030年实现印度500吉瓦 非化石能源目标需要超过250亿至300亿美元的年度投资、监管协调和能源系统的数字化优化。通过将定量见解与政策分析相结合，本文弥合了描述性评估与实证评估之间的差距，为参与印度可再生能源转型的政策制定者、投资者和研究人员提供了可操作的指导。

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引用次数: 0

Survey of cleaner combustion in compression ignition engine fueled with nanoadditive-laded biodiesel 纳米添加剂生物柴油在压缩点火发动机中的清洁燃烧研究

Next Energy

Pub Date : 2026-01-01 DOI: 10.1016/j.nxener.2025.100500

Priyanka Singh , Nathi Ram Chauhan , Ajay Singh Verma

This review explores the role of nanoadditives in improving the performance of biodiesel used in compression ignition (CI) engines. The central idea is that introducing nanoparticles (NPs) into biodiesel can enhance combustion, engine efficiency, and emission control without requiring significant engine modifications. The study focuses on widely used NPs such as Al₂O₃, TiO₂, CeO₂, Fe₃O₄, carbon nanotubes, and graphene oxide, examining their catalytic, thermal, and stabilization effects. Biodiesel blends are typically prepared from non-edible oils, purified, and infused with NPs through ultrasonication, sometimes with surfactants to maintain dispersion stability. Key fuel properties, including viscosity, density, calorific value, and oxidation stability, are assessed before engine testing. The review highlights how NPs improve fuel atomization, oxidation reactions, and heat transfer, leading to better ignition and more efficient combustion. Results from the literature show that nanoadditives enhance brake thermal efficiency, reduce fuel consumption, and significantly lower emissions of carbon monoxide, UHCs, and particulate matter. Oxygen-donating NPs like CeO₂ and TiO₂ promote complete combustion and soot reduction, while carbon-based NPs strengthen blend stability and atomization quality. The novelty of this review lies in its systematic analysis of the mechanisms, physicochemical improvements, and performance outcomes of nanoadditives in biodiesel. It also identifies key research gaps, including optimal NP dosage, long-term durability, and large-scale engine validation, offering valuable direction for sustainable CI engine development.

本文综述了纳米添加剂在改善压缩点火发动机生物柴油性能方面的作用。其核心思想是，将纳米颗粒（NPs）引入生物柴油可以增强燃烧、发动机效率和排放控制，而无需对发动机进行重大修改。该研究的重点是广泛使用的NPs，如Al₂O₃、TiO₂、CeO₂、Fe₃O₄、碳纳米管和氧化石墨烯，研究了它们的催化、热和稳定效果。生物柴油混合物通常由非食用油制备，经过纯化，并通过超声波注入NPs，有时加入表面活性剂以保持分散稳定性。关键的燃料特性，包括粘度、密度、热值和氧化稳定性，都是在发动机测试前评估的。该综述强调了NPs如何改善燃料雾化、氧化反应和传热，从而更好地点火和更有效地燃烧。研究结果表明，纳米添加剂提高了制动热效率，降低了燃料消耗，并显著降低了一氧化碳、uhc和颗粒物的排放。供氧NPs如CeO₂和TiO₂促进完全燃烧和减灰，而碳基NPs增强混合稳定性和雾化质量。本文的新颖之处在于系统地分析了纳米添加剂在生物柴油中的作用机理、理化改进和性能结果。它还确定了关键的研究差距，包括最佳NP用量、长期耐久性和大规模发动机验证，为可持续CI发动机的开发提供了有价值的方向。

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引用次数: 0

High-performance spinel ferrites for supercapacitors: Solvothermal synthesis and electrochemical evaluation 超级电容器用高性能尖晶石铁氧体：溶剂热合成和电化学评价

Next Energy

Pub Date : 2026-01-01 DOI: 10.1016/j.nxener.2025.100506

Naeem Ullah, Tufail Ahmad, Asad Ullah, Sufaid Khan, Muhammad Nafees, Mehboob Ali, Yousra Noor, Fawad Ahmad Khan, Baseena Sardar, Majid Khan

Supercapacitors (SCs) are critical for sustainable energy storage due to their high power density and rapid charge-discharge capabilities, making them essential for renewable energy integration and electric vehicle applications. This study explores the solvothermal synthesis of spinel ferrites XFe₂O₄ (X = Mn, Co, Ni) as electrode materials for SCs. Structural characterization through X-ray diffraction confirmed phase-pure cubic structures with lattice parameters of 0.851 nm (MnFe₂O₄), 0.839 nm (CoFe₂O₄), and 0.834 nm (NiFe₂O₄), and crystallite sizes of 13.72 nm, 20.72 nm, and 11.86 nm, respectively. Scanning electron microscopy revealed agglomerated nanoparticles for MnFe₂O₄ and CoFe₂O₄, and densely packed aggregates for NiFe₂O₄. Fourier-transform infrared spectroscopy identified a conductive carbonaceous layer from residual ethylene glycol, while UV-Vis spectroscopy determined bandgaps of 2.7 eV (CoFe₂O₄), 3.12 eV (MnFe₂O₄), and 3.7 eV (NiFe₂O₄). Electrochemical assessments using cyclic voltammetry, galvanostatic charge-discharge, and electrochemical impedance spectroscopy showed CoFe₂O₄ achieving a specific capacitance of 1518 F/g at 0.5 A/g with 99.9% retention after 5000 cycles, outperforming MnFe₂O₄ and NiFe₂O₄. Symmetric devices based on CoFe₂O₄ delivered a specific capacitance of 668 F/g at 1 A/g, an energy density of 33.38 Wh/kg, and a power density of 150 W/kg. These results position CoFe₂O₄ as a promising material for next-generation SCs, advancing energy storage for sustainable systems.

超级电容器（SCs）由于其高功率密度和快速充放电能力，对可持续能源存储至关重要，使其成为可再生能源集成和电动汽车应用的必要条件。本研究探讨了溶剂热合成尖晶石铁氧体XFe2O4 （X = Mn, Co, Ni）作为SCs电极材料的方法。通过x射线衍射表征，确定了相纯立方结构，晶格参数分别为0.851 nm （MnFe2O4）、0.839 nm （CoFe2O4）和0.834 nm （NiFe2O₄），晶粒尺寸分别为13.72 nm、20.72 nm和11.86 nm。扫描电镜显示，MnFe2O4和CoFe2O4为球状纳米颗粒，而NiFe2O4为密集堆积的团聚体。傅里叶变换红外光谱在残余乙二醇中发现了导电碳质层，紫外可见光谱测定了2.7 eV （CoFe2O4）、3.12 eV （MnFe2O4）和3.7 eV （NiFe2O4）的带隙。利用循环伏安法、恒流充放电法和电化学阻抗谱进行的电化学评价表明，在0.5 a /g下，CoFe2O4的比电容达到1518 F/g，循环5000次后保持率达到99.9%，优于MnFe2O4和NiFe2O4。基于CoFe2O4的对称器件在1 a /g时的比电容为668 F/g，能量密度为33.38 Wh/kg，功率密度为150 W/kg。这些结果将CoFe2O4定位为下一代超导材料的有前途的材料，推进可持续系统的能量存储。

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引用次数: 0

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