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Energy-efficient smart gateway framework with QoS-aware resource allocation in IoT ecosystem 物联网生态系统中具有qos感知资源分配的节能智能网关框架

Next Energy

Pub Date : 2025-10-01 Epub Date: 2025-08-26 DOI: 10.1016/j.nxener.2025.100413

Gunjan Beniwal , Anita Singhrova

Energy-efficient smart gateways are the heart of an IoT ecosystem, as they are essential for efficiently handling incoming data and resources. Due to the exponential increase in IoT devices and applications, a vast amount of data is collected from the surrounding environment. This data needs to be processed and analyzed for further executions. Smart gateways play a crucial role in catering to user needs while handling vast amounts of data, and consuming less energy. Therefore, a smart gateway framework is proposed in this work to make dynamic decisions based on the user requirements while providing the best quality of service with efficient energy consumption. The proposed gateway framework is capable of handling urgent tasks that are latency-sensitive and also optimally allocating resources based on their computational needs in a fog-cloud environment. The incoming user-generated tasks are efficiently scheduled using the proposed Dynamic Priority-Multilevel Feed Back Queue Algorithm (DP-MFBQ). Whereas, the Machine Learning-based Resource Allocation (MLRA) algorithm was proposed to make dynamic decisions based on past learnings of the smart gateway. The proposed framework is simulated using the Yet Another Fog Simulator (YAFS) simulation toolkit, and it outperformed the existing work when evaluated on the Quality of Service parameters, including latency, wait time, energy consumption, and throughput.

节能智能网关是物联网生态系统的核心，因为它们对于有效处理传入的数据和资源至关重要。由于物联网设备和应用的指数级增长，从周围环境中收集了大量数据。需要对这些数据进行处理和分析，以便进一步执行。智能网关在满足用户需求、处理大量数据和消耗更少能源方面发挥着至关重要的作用。因此，本文提出了一种基于用户需求动态决策的智能网关框架，同时提供最优的服务质量和最高效的能耗。所提出的网关框架能够处理延迟敏感的紧急任务，并在雾云环境中根据其计算需求优化分配资源。采用提出的动态优先级-多级反馈队列算法（DP-MFBQ）对传入的用户生成任务进行高效调度。提出了基于机器学习的资源分配（MLRA）算法，该算法基于智能网关过去的学习进行动态决策。使用另一个雾模拟器（YAFS）仿真工具包对所提出的框架进行了模拟，在评估服务质量参数（包括延迟、等待时间、能耗和吞吐量）时，它优于现有的工作。

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引用次数: 0

Semi-empirical calendar capacity degradation modeling of graphite/lithium iron phosphate (LFP) pouch cells: Non-constant fitting coefficient functions 石墨/磷酸铁锂（LFP）袋状电池半经验日历容量退化模型：非常数拟合系数函数

Next Energy

Pub Date : 2025-10-01 Epub Date: 2025-10-10 DOI: 10.1016/j.nxener.2025.100456

Yu Hui Lui , Xinyou Ke , Sheng Liu , Lei Zhang , Yong Wang , Huanhuan Wang

To accurately and efficiently predict the lifetime of Li-ion batteries for their practical applications in battery electric vehicles, hybrid electric vehicles, plug-in hybrid electric vehicles, energy storage systems, etc., accurate semiempirical life models are desired for battery lifetime simulation. In this work, semiempirical calendar aging models considering nonconstant fitting coefficient functions based on storage aging tests for 20 Ah graphite/lithium iron phosphate pouch cells under various temperatures ranging from 0℃ to 60℃ and state-of-charges ranging from 20% to 100% were developed. It was found that the “best” calendar capacity life model with non-constant fitting coefficient functions compared with the common calendar capacity life model with constant fitting coefficients reduces the mean absolute error and root mean square error of the calendar capacity fitting by 7.4% and 6.6%, respectively. Moreover, the “best” calendar capacity life model proposed in this work outperforms 2 existing reference models reported in the literature, especially at high temperatures, that is, 40℃ and 60℃. It is expected that this work would benefit accurate and efficient calendar capacity prediction of Li-ion batteries.

为了准确有效地预测锂离子电池在纯电动汽车、混合动力汽车、插电式混合动力汽车、储能系统等实际应用中的寿命，需要精确的半经验寿命模型进行电池寿命仿真。本文建立了20个 Ah石墨/磷酸铁锂袋状电池在0℃~ 60℃、20% ~ 100%荷电状态下，考虑非常数拟合系数函数的半经验日历老化模型。结果表明，采用非常数拟合系数的“最佳”日历产能寿命模型与采用常数拟合系数的普通日历产能寿命模型相比，日历产能拟合的平均绝对误差和均方根误差分别降低了7.4%和6.6%。此外，本文提出的“最佳”日历容量寿命模型优于文献报道的2个现有参考模型，特别是在高温下，即40℃和60℃。期望这项工作将有利于锂离子电池准确、高效的日历容量预测。

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引用次数: 0

A comprehensive review of carbon capture: From conventional to emerging electrochemical technologies 碳捕获的综合综述：从传统的到新兴的电化学技术

Next Energy

Pub Date : 2025-10-01 Epub Date: 2025-09-10 DOI: 10.1016/j.nxener.2025.100415

Aymen Ihsan Hadi , An Yan , Yiping Hu , Bing Lin , Taigang Zhou , Denghao Ouyang , Junlei Tang

The increasing levels of atmospheric carbon dioxide (CO₂) from various emission sources have become a critical factor in global climate change, making the urgent development of effective carbon capture technologies necessary. This review offers a comprehensive analysis of both conventional and emerging electrochemical carbon capture technologies, with a specific emphasis on electrochemical CO₂ capture (ECC) technologies. Conventional approaches encompass a range of technologies, including absorption, adsorption, membrane separation, and cryogenic processes, as well as combustion-based strategies such as pre-combustion, post-combustion, and oxy-fuel combustion techniques. They are widely implemented at an industrial scale but frequently face challenges due to high energy demands, operational complexity, and limited scalability. In contrast, electrochemical technologies present promising alternatives because of their lower energy requirements, modular design, and compatibility with renewable energy sources. The review critically evaluates key ECC strategies such as pH-swing processes, redox-active carriers, bipolar membrane electrodialysis, CO₂ electroreduction, and electrochemical mineralization. Advancements in catalyst development, membrane engineering, and system integration are assessed concerning CO₂ capture efficiency, Faradaic efficiency, selectivity, and scalability. Despite significant advancements, challenges remain in the areas of material stability, energy efficiency optimization. The transformative potential of ECC and the future research pathways aimed at addressing current limitations and accelerating commercialization are also explored.

来自各种排放源的大气二氧化碳（CO 2）水平的增加已成为全球气候变化的关键因素，因此迫切需要开发有效的碳捕获技术。本文对传统的和新兴的电化学碳捕集技术进行了全面的分析，特别强调了电化学二氧化碳捕集（ECC）技术。传统的方法包括一系列技术，包括吸收、吸附、膜分离和低温过程，以及基于燃烧的策略，如燃烧前、燃烧后和全氧燃料燃烧技术。它们在工业规模上得到了广泛的应用，但由于高能量需求、操作复杂性和有限的可扩展性，它们经常面临挑战。相比之下，电化学技术由于其较低的能源需求、模块化设计以及与可再生能源的兼容性，呈现出很有前途的替代方案。该综述批判性地评估了关键的ECC策略，如ph -摆动过程、氧化还原活性载体、双极膜电渗析、CO 2电还原和电化学矿化。对催化剂开发、膜工程和系统集成方面的进展进行了有关CO₂捕获效率、法拉第效率、选择性和可扩展性的评估。尽管取得了重大进展，但在材料稳定性和能效优化方面仍存在挑战。还探讨了ECC的变革潜力以及旨在解决当前限制和加速商业化的未来研究途径。

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引用次数: 0

Evaluating the role of state and federal incentives in residential solar adoption: Evidence from Nevada 评估州和联邦政府在住宅太阳能采用方面的激励作用：来自内华达州的证据

Next Energy

Pub Date : 2025-10-01 Epub Date: 2025-09-25 DOI: 10.1016/j.nxener.2025.100434

Faraz Farhidi

This study examines how state and federal incentives affect rooftop solar adoption in Nevada using contract-level data from 99 customers between 2017 and 2023. A fixed-effects regression framework is applied to isolate the effects of rebates, tax credits, utility rates, and vendor behavior on system prices. The analysis reveals that state-level rebates significantly reduce upfront costs: a $1000 increase in rebate support corresponds to an average $0.09/W reduction in system price. In contrast, federal Investment Tax Credits show limited price-lowering effects and may indirectly raise quoted prices, consistent with subsidy pass-through behavior. Nevada’s retail electricity rates emerge as the most significant determinant of pricing, with higher rates associated with an increase of nearly $27–31/W in average system costs, reflecting vendors’ ability to price against the utility benchmark.

The results demonstrate that state rebates provide the clearest pathway to lowering customer costs and accelerating adoption, while federal incentives require regulatory safeguards to ensure consumer benefit. These findings carry important implications for renewable energy policy, particularly in regulated markets where vendor pricing strategies can dilute the effectiveness of national subsidies. Overall, the evidence highlights the critical role of targeted state policies and competitive vendor oversight in advancing affordability, market participation, and progress toward renewable energy and climate goals.

本研究使用2017年至2023年间99个客户的合同级数据，研究了州和联邦激励措施如何影响内华达州屋顶太阳能的采用。固定效应回归框架应用于分离回扣、税收抵免、公用事业费率和供应商行为对系统价格的影响。分析显示，州一级的返利显著降低了前期成本：每增加1000美元的返利支持，对应于系统价格平均每瓦降低0.09美元。相比之下，联邦投资税收抵免显示出有限的降价效果，并可能间接提高报价，与补贴传递行为一致。内华达州的零售电价是电价的最重要决定因素，较高的电价与平均系统成本增加近27-31美元/瓦有关，反映了供应商根据公用事业基准定价的能力。结果表明，各州的回扣为降低客户成本和加速采用提供了最清晰的途径，而联邦政府的激励措施则需要监管保障来确保消费者的利益。这些发现对可再生能源政策具有重要意义，特别是在供应商定价策略可能削弱国家补贴有效性的受监管市场中。总的来说，证据强调了有针对性的国家政策和竞争性供应商监督在提高可负担性、市场参与度以及实现可再生能源和气候目标方面的关键作用。

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引用次数: 0

Energizing tomorrow: A scientometric exploration into energy storage integration in hybrid power systems 激励明天：混合动力系统储能集成的科学计量学探索

Next Energy

Pub Date : 2025-10-01 Epub Date: 2025-10-10 DOI: 10.1016/j.nxener.2025.100450

Alpesh Kumar Dauda, Ambarish Panda

In promoting the decarbonization of power systems, integrating cleaner energy sources is essential. However, the intermittent nature of renewable energy (wind and solar) presents challenges for seamless grid integration. This issue can be mitigated by strategically deploying electrical energy storage (EES) systems in hybrid power systems (HPS), which combine conventional and renewable generators. While prior studies have focused on specific aspects like modeling, sizing, and economic analysis, a comprehensive review of EES integration and operational challenges in HPS is still lacking. This study offers an in-depth overview of recent advancements in EES integration into HPS, highlighting key objectives, operational concerns, and solution methodologies. It explores issues related to small-scale energy storage technologies such as batteries, supercapacitors, superconducting magnetic energy storage (SMES), flywheels, hydrogen fuel cells, and hybrid energy storage systems (ESSs) in HPS. A scientometric analysis based on 250 Scopus-indexed articles is conducted, including co-authorship, citation, and keyword co-occurrence analysis. Key findings include (1) A 510% growth in publications during the last decade (over 120 articles in 2020–2023), reflecting accelerating global attention. (2) China (11%), Iran (11%), and India (9%) contribute most of the journal articles, while Germany achieves the highest average citation impact (229.5 citations per paper) and (3) identification of “SMES” and “flywheels” as underexplored areas, suggesting potential research gaps in the domain of EES-integrated HPS.

为了促进电力系统的脱碳，整合清洁能源是必不可少的。然而，可再生能源（风能和太阳能）的间歇性给无缝电网整合带来了挑战。这个问题可以通过在混合动力系统（HPS）中战略性地部署电能存储（EES）系统来缓解，混合动力系统结合了传统和可再生发电机。虽然之前的研究主要集中在建模、规模和经济分析等具体方面，但对HPS中EES集成和运营挑战的全面审查仍然缺乏。本研究深入概述了EES与HPS集成的最新进展，突出了关键目标、操作关注点和解决方案方法。它探讨了与小型储能技术相关的问题，如电池、超级电容器、超导磁储能（sme）、飞轮、氢燃料电池和HPS中的混合储能系统（ess）。基于250篇scopus索引文章进行了科学计量分析，包括共同作者、引文和关键词共现分析。主要发现包括：(1)在过去十年中，出版物增长了510%（2020-2023年超过120篇），反映了全球关注的加速。(2)中国（11%）、伊朗（11%）和印度（9%）贡献了最多的期刊论文，而德国的平均引用影响最高（229.5次/篇）；(3)“中小企业”和“飞轮”被认为是研究不足的领域，表明ees集成HPS领域存在潜在的研究空白。

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引用次数: 0

Evaluating the hydrogen supply chain so far—An assessment and review of critical aspects for an economy supported by a “hydrogen infrastructure” 对“氢基础设施”支持的经济的关键方面进行评估和回顾

Next Energy

Pub Date : 2025-10-01 Epub Date: 2025-10-03 DOI: 10.1016/j.nxener.2025.100448

Julien Göthel , Andreas Corsten , Olena Volkova

This paper critically evaluates hydrogen's role as a decarbonization strategy, addressing key technical and economic constraints that challenge its widespread adoption. We analyze inherent energy conversion losses that make hydrogen-based systems less efficient than direct electrification for many applications, along with persistent issues in scalable storage, distribution, and production costs. The analysis highlights the specific limitations of the 2 primary production pathways: green hydrogen, constrained by the high cost of electrolyzers and the sourcing of critical materials, and blue hydrogen, which faces concerns regarding methane leakage and the long-term viability of carbon capture technologies. We argue that hydrogen's most effective application is as a strategic enabler for hard-to-abate sectors, such as heavy industry and long-distance transport. The paper also explores innovative concepts like thermochemical looping with metal oxides and the integration of hydrogen into a circular carbon economy as pathways to enhance its efficiency and economic viability. Ultimately, the transition to a global hydrogen economy is a complex, multi-decade undertaking that necessitates a pragmatic, targeted approach with substantial investment and coordinated international policy to realize its full potential.

本文批判性地评估了氢作为脱碳战略的作用，解决了挑战其广泛采用的关键技术和经济限制。我们分析了固有的能量转换损失，这使得氢基系统在许多应用中比直接电气化效率低，以及可扩展存储、分配和生产成本方面的持续问题。该分析强调了两种主要生产途径的具体局限性：绿色氢，受到电解槽和关键材料采购的高成本的限制；蓝色氢，面临甲烷泄漏和碳捕获技术长期可行性的担忧。我们认为，氢最有效的应用是作为难以减少的行业（如重工业和长途运输）的战略推动者。本文还探讨了一些创新概念，如金属氧化物热化学环，以及将氢整合到循环碳经济中，作为提高其效率和经济可行性的途径。最终，向全球氢经济过渡是一项复杂的、长达数十年的任务，需要采取务实、有针对性的方法，进行大量投资和协调一致的国际政策，以充分发挥其潜力。

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引用次数: 0

Gliding arc plasma dry reforming of n-dodecane for H2 production: A mechanism study combined with experimental methods and kinetic modeling 滑行电弧等离子体干重整制氢：实验方法与动力学建模相结合的机理研究

Next Energy

Pub Date : 2025-10-01 DOI: 10.1016/j.nxener.2025.100449

Baowei Wang, Weiyue Huo, Yi Cheng, Shize Liu, Jijun Zou

Dry reforming technology is promising because it can simultaneously produce syngas (H₂ and CO) and efficiently convert the greenhouse gas CO₂. This study investigated the dry reforming (DR) of n-dodecane in a gliding arc plasma (GAP) reactor through integrated experimental and kinetic simulation approaches. Key operating parameters—O/C molar ratio, input power, and residence time—were evaluated for their influence on syngas production and reactant conversion. Optical emission spectroscopy (OES) identified active species, with spectral line intensities analyzed across varying O/C ratios. A validated zero-dimensional kinetic model, aligned with experimental data, revealed that H₂ generation during C₁₂H₂₆ conversion is predominantly driven by recombination of n-dodecane with H atoms. H₂ production primarily arises from hydrocarbon electron impact reactions (e.g., C₂H₆, C₂H₄) and H atom recombination with species such as C₃H₆, CH₄, and C₃H₈. Detailed reaction pathways and mechanisms in the dry reforming system are elucidated through integrated experimental and kinetic modeling analyses. The n-dodecane conversion follows the following order: X(DR) > X(SR) > X(POR).

干式重整技术可以同时生产合成气（H2和CO）并有效地转化温室气体CO2，因此具有广阔的应用前景。采用实验和动力学模拟相结合的方法研究了正十二烷在滑动电弧等离子体反应器中的干重整过程。考察了关键操作参数o /C摩尔比、输入功率和停留时间对合成气产量和反应物转化率的影响。光学发射光谱（OES）鉴定了活性物种，并分析了不同O/C比率下的光谱线强度。验证的零维动力学模型与实验数据一致，表明C12H26转化过程中H2的生成主要是由正十二烷与H原子的重组驱动的。H₂的产生主要来自碳氢化合物的电子冲击反应（例如，C₂H₆，C₂H₄）和H原子与C₃H₆，CH₄和C₃H₈等品种的复合。通过实验和动力学模型的综合分析，详细阐述了干式重整体系的反应途径和机理。正十二烷的转化顺序为：X(DR) >； X(SR) >； X（POR）。

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引用次数: 0

Machine learning modeling for thermochemical biohydrogen production from biomass 生物质热化学制氢的机器学习建模

Next Energy

Pub Date : 2025-10-01 Epub Date: 2025-07-31 DOI: 10.1016/j.nxener.2025.100377

Yingju Chang , Wei Wang , Jo-Shu Chang , Duu-Jong Lee

This paper outlines the steps for applying machine learning (ML) models to predict biohydrogen yields from biomass using thermochemical treatments. Input features include elemental compositions and thermochemical process parameters, while outputs are biohydrogen yields reported in existing studies. Procedures and software for performing ML modeling on biohydrogen yield predictions are provided. Input features were analyzed using Random Forest (RF) and eXtreme Gradient Boosting (XGB) models, interpreted through SHapley Additive exPlanations (SHAP) and Partial Dependence Plot analyses. XGB demonstrated superior performance over RF in predicting hydrogen yields, as measured by mean squared error values. Fixed carbon content, moisture, and volatile matter content significantly influenced the yields. Process temperature and fixed carbon content showed an increase in yield when temperatures were below 600 °C and carbon content was below 20%. The provided programs are adaptable for ML modeling and help users efficiently organize datasets to develop their models.

本文概述了应用机器学习（ML）模型使用热化学处理来预测生物质生物氢产量的步骤。输入特征包括元素组成和热化学过程参数，而输出是现有研究报告的生物氢产量。程序和软件执行ML建模对生物氢产量预测提供。使用随机森林（RF）和极端梯度增强（XGB）模型分析输入特征，通过SHapley加性解释（SHAP）和部分依赖图分析进行解释。通过均方误差值测量，XGB在预测氢气产出量方面表现出优于RF的性能。固定碳含量、水分和挥发物含量对产量有显著影响。当温度低于600℃，碳含量低于20%时，工艺温度和固定碳含量均有提高。所提供的程序适用于ML建模，并帮助用户有效地组织数据集来开发他们的模型。

引用次数: 0

Seaside port operation optimization and energy management system with integrated seaport microgrid and cold ironing 海港微电网与冷熨一体化的滨海港口运营优化与能源管理系统

Next Energy

Pub Date : 2025-10-01 Epub Date: 2025-09-24 DOI: 10.1016/j.nxener.2025.100439

Nur Najihah Abu Bakar , Najmeh Bazmohammadi , Juan C. Vasquez , Josep M. Guerrero

Electrification of port operations requires new adaptations to system operation which introduces new complexities and operating challenges. The carbon capture of cold ironing is gaining attention to mitigate shipping emissions, but implementing it impacts conventional workflow scheduling and increases the energy burden at ports. Hence, it necessitates optimal coordination of operations scheduling and novel energy management strategies. This research proposes a two-level optimization framework to address coordination problems. The first level of optimization develops the algorithm for three different operation scheduling problems: the berth allocation problem (BAP), the cold ironing assignment problem (CIAP), and the quay crane allocation problem (QCAP) to minimize the ship stay duration. Meanwhile, a multi-objective optimization problem is formulated at the second level to minimize energy operation costs and port emissions from the seaport microgrid. The output from numerical simulations demonstrates substantial improvements in operation performance, cost savings, and emission reduction, which benefit both port operators and shipping companies. By coordinating these two problems through an integrated optimization strategy, ports can reliably adopt innovative electrification solutions while maintaining competitive performance. Besides, the set of Pareto optimal solutions is provided to the port operators, enabling them to perform a tradeoff analysis and incorporate strategic priorities. This integrated approach lays the groundwork for next-generation operation management systems at ports.

港口操作电气化需要对系统操作进行新的调整，这带来了新的复杂性和操作挑战。冷熨烫的碳捕获正在引起人们的关注，以减少航运排放，但实施它会影响传统的工作流程调度，并增加港口的能源负担。因此，需要优化操作调度和新的能源管理策略。本文提出了一个两级优化框架来解决协调问题。第一级优化针对泊位分配问题（BAP）、冷熨分配问题（CIAP）和码头起重机分配问题（QCAP）这三个不同的作业调度问题开发了算法，以最小化船舶停留时间。同时，在第二层提出了一个多目标优化问题，以最小化海港微电网的能源运行成本和港口排放。数值模拟的结果表明，在运营绩效、成本节约和减排方面有了实质性的改善，这对港口运营商和航运公司都有好处。通过综合优化策略协调这两个问题，港口可以可靠地采用创新的电气化解决方案，同时保持竞争力。此外，还向港口运营商提供了帕累托最优解集，使他们能够进行权衡分析并纳入战略优先级。这种综合方法为下一代港口运营管理系统奠定了基础。

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引用次数: 0

First-principles DFT and BoltzTraP investigation of multifunctional properties of XNiH3 (X = Li, Na, K) perovskite hydrides: Thermoelectric and hydrogen storage potential XNiH3 （X = Li, Na， K）钙钛矿氢化物多功能性质的第一性原理DFT和BoltzTraP研究：热电和储氢势

Next Energy

Pub Date : 2025-10-01 Epub Date: 2025-08-23 DOI: 10.1016/j.nxener.2025.100402

Ayoub Koufi , Younes Ziat , Hamza Belkhanchi

This work presents a comprehensive first-principles investigation of the structural, electronic, thermoelectric, and hydrogen storage properties of XNiH₃ (X = Li, Na, K) perovskite-type hydrides, using density functional theory (DFT) within the generalized gradient approximation (GGA), coupled with the WIEN2k and BoltzTraP codes. The novelty of this study lies in the dual exploration of the thermoelectric and hydrogen storage functionalities of these unexplored materials, which have not yet been synthesized experimentally. Structural optimization confirms stable cubic perovskite configurations (Pm-3m), with lattice parameters increasing from Li to K. Electronic band structure and density of states analyses reveal metallic behavior across all compounds, which is favorable for both charge transport and hydrogen desorption kinetics. Thermoelectric calculations in the 300–900 K range show n-type conduction with negative Seebeck coefficients, and a maximum ZT of 0.09 for LiNiH₃ at 800 K, outperforming several known oxide and halide perovskites. Additionally, the calculated gravimetric hydrogen storage capacities are 4.37% (LiNiH₃), 3.54% (NaNiH₃), and 2.98% (KNiH₃), confirming the lightweight character and storage potential of these hydrides. These results highlight the multifunctional potential of XNiH₃ compounds for integrated energy applications, particularly in systems combining waste heat recovery and reversible hydrogen storage. Theoretical insights provided here can serve as a foundation for future experimental validation and material design.

本文利用广义梯度近似（GGA）中的密度泛函理论（DFT），结合WIEN2k和BoltzTraP代码，对XNiH3 （X = Li, Na， K）钙钛矿型氢化物的结构、电子、热电和储氢性能进行了全面的第一性原理研究。本研究的新颖之处在于对这些尚未通过实验合成的未开发材料的热电和储氢功能进行了双重探索。结构优化证实了稳定的立方钙钛矿构型（Pm-3m），晶格参数从Li增加到k。电子能带结构和态密度分析揭示了所有化合物的金属行为，这有利于电荷传输和氢的脱附动力学。在300-900 K范围内的热电计算表明，LiNiH3在800 K时的最大ZT为0.09，优于几种已知的氧化物和卤化物钙钛矿。此外，计算出的重量储氢容量分别为4.37% （LiNiH3）、3.54% （NaNiH3）和2.98% (KNiH3)，证实了这些氢化物的轻质特性和储氢潜力。这些结果突出了XNiH3化合物在综合能源应用方面的多功能潜力，特别是在结合废热回收和可逆储氢的系统中。这里提供的理论见解可以作为未来实验验证和材料设计的基础。

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引用次数: 0