IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-02-09 DOI: 10.1016/j.energy.2026.140280

Jixiang Chen , Zhitao Zuo , Jiaxi Chen , Ran Xu , Xin Zhou , Hailiang Tao , Jianting Sun , Haisheng Chen

This study combines numerical simulation and experimental testing to systematically evaluate the influence of radial and axial inlet configurations on the performance of a mixed-flow compressor for compressed air energy storage (CAES) systems. Comparative analyses were carried out using an inlet volute for radial intake and a straight inlet pipe for axial intake. The investigation encompasses overall compressor performance, including outlet flow field distortion and total pressure loss in the inlet volute, static pressure distribution along the blade tip, and circumferential static pressure distribution in the outlet volute. Results demonstrate that under design conditions, the axial intake compressor attains a total pressure ratio of 1.7 and an isentropic efficiency of 83.72%, representing relative increases of 1.19% in total pressure ratio and 4.8% in isentropic efficiency compared with the radial intake configuration. Furthermore, the stable operating range of the axial intake compressor is 9.7 % wider than that of the radial intake variant. Through variable speed regulation, this range can be further extended to 45.14%. In contrast, the radial intake configuration exhibits pronounced outlet flow distortion and elevated total pressure loss attributable to the inlet volute geometry. These effects are especially marked under high speed and high mass flow conditions, where both the distortion coefficient and total pressure loss increase substantially. The resulting non-uniformity in the impeller inlet flow field leads to a deterioration in overall compressor performance. The study confirms good consistency between numerical predictions and experimental measurements, thereby providing a theoretical basis and technical support for the optimization of inlet structures and the enhancement of variable condition operation in high-efficiency, wide-operating range compressors for CAES applications.

本研究将数值模拟和实验测试相结合，系统地评估了径向和轴向进口配置对压缩空气储能（CAES）系统中混流压缩机性能的影响。对径向进气采用进口蜗壳，轴向进气采用直进气管道进行了对比分析。该研究涵盖了压气机的整体性能，包括出口流场畸变和进口蜗壳内的总压损失，沿叶片尖端的静压分布以及出口蜗壳内的周向静压分布。结果表明，在设计条件下，轴向进气压气机的总压比为1.7，等熵效率为83.72%，与径向进气相比，总压比提高了1.19%，等熵效率提高了4.8%。此外，轴向进气压缩机的稳定工作范围比径向进气压缩机宽9.7%。通过变速调节，此范围可进一步扩大到45.14%。相比之下，径向进气结构表现出明显的出口流动扭曲和归因于进口蜗壳几何形状的总压损失升高。这些影响在高速大质量流条件下尤为明显，畸变系数和总压损失都大幅增加。叶轮进口流场的不均匀性导致压气机整体性能的恶化。该研究证实了数值预测与实验测量结果的良好一致性，从而为CAES应用中高效、宽工况范围压缩机进气道结构的优化和变工况运行的增强提供了理论依据和技术支持。

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引用次数: 0

Characterization and experimental verification of wake model for offshore fixed wind turbines under wind-wave coupling 海上固定风力机风浪耦合尾流模型表征及实验验证

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-02-09 DOI: 10.1016/j.energy.2026.140392

Yanzhong Ren , Jinlian Wang , Yi Hong , Xiaoxia Gao , Zhe Wu , Lei Zhang , Zhonghe Han

Offshore fixed wind turbines operate under coupled wind-wave boundary conditions, resulting in more complex velocity decay characteristics in the wake region of the turbine. The manuscript proposed an anisotropic three-dimensional wake model to analyze the velocity distribution patterns of the wake region of offshore fixed wind turbines. The new model accounts for the effects of wind shear and wave-induced stress on the incoming flow velocity and further refines the original Gaussian-shaped wake velocity profile based on the principle of wake velocity reflection. Furthermore, laser radar field wind measurement experiments were conducted. By combining the data collected by the radar with the existing wake models, the accuracy of the model proposed in the manuscript was verified. Furthermore, the proposed model was validated using publicly available data from the literature. The results show that the field wind measurement experiments successfully measured the wake field data, and the wake model proposed in the manuscript has higher accuracy, with the relative error of the model generally controllable within 10%. This research can provide reference for the flow field structure analysis and operational control of offshore fixed wind turbines.

海上固定风力机在耦合风波边界条件下运行，导致风机尾迹区速度衰减特性更为复杂。本文提出了一种各向异性的三维尾流模型来分析海上固定风力机尾流区域的速度分布规律。新模型考虑了风切变和波浪应力对来流速度的影响，并基于尾流速度反射原理对原有的高斯型尾流速度曲线进行了细化。此外，还进行了激光雷达现场测风实验。将雷达采集的数据与已有的尾流模型相结合，验证了本文模型的准确性。此外，使用文献中公开可用的数据验证了所提出的模型。结果表明，野外风测实验成功地测量了尾流场数据，文中提出的尾流模型具有较高的精度，模型的相对误差一般控制在10%以内。该研究可为海上固定风力机的流场结构分析和运行控制提供参考。

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引用次数: 0

Energy saving potential of the Indian chemical Industry: Role of innovation and export 印度化学工业的节能潜力：创新和出口的作用

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-02-09 DOI: 10.1016/j.energy.2026.140357

Showkat Ahmad Shah , Salman Haider , Rafiq Hussain Ganaie

This analysis aims to estimate the savings potential through energy efficiency and explore the effects of innovation and exporting. We consider data from 85 firms in the Indian chemical industry for the period from 2003 to 04 to 2019-20. Widely used stochastic frontier analysis has been used to estimate production function-based Energy Efficiency (EE). Overall, the EE estimate has a median of 78 per cent, showcasing significant potential for energy savings in the industry. Firm-level total factor energy efficiency (TFEE) ranges from 55 to 82 per cent, with considerable variation. Our analysis reveals that firms with greater accumulated innovative capabilities tend to achieve higher energy efficiency. Additionally, factors such as firm age, financial performance and exporting are positively associated with better TFEE. Whereas firms with geographically dispersed production facilities and higher energy prices lead to lower energy efficiency. The results underscore the vital role of exporting, regional disparities, and technological gaps when designing EE strategies at the firm level. Our study offers valuable insights for policymakers.

本分析旨在通过提高能源效率来估计节能潜力，并探讨创新和出口的影响。我们考虑了印度化工行业85家公司2003 - 2004年至2019- 2020年期间的数据。随机前沿分析已被广泛应用于基于生产函数的能源效率估算。总体而言，EE估计的中位数为78%，显示了该行业节能的巨大潜力。公司一级的全要素能源效率从55%到82%不等，差别很大。我们的分析表明，积累创新能力更强的企业往往实现更高的能源效率。此外，公司年龄、财务业绩和出口等因素与更好的TFEE呈正相关。然而，生产设施分散的企业和较高的能源价格导致能源效率较低。研究结果强调了出口、地区差异和技术差距在企业层面设计电子商务战略时的重要作用。我们的研究为政策制定者提供了有价值的见解。

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引用次数: 0

Efficiency mapping and loss analysis of ORC radial inflow turbines using an optimized mean-line design methodology 采用优化平均线设计方法的ORC径向流入涡轮效率映射和损失分析

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-02-09 DOI: 10.1016/j.energy.2026.140342

Yubo Yao , Zhuoren Xu , Song Fang , Shaolong Zhu , Qasir Iqbal , Keping Chen , Limin Qiu , Kai Wang

Radial inflow turbines (RITs) are widely regarded as suitable expanders for small-to medium-scale organic Rankine cycle (ORC) systems due to their compact structure, high efficiency, and ability to accommodate large enthalpy drops in a single stage. While one-dimensional (1D) mean-line design methodologies and optimization techniques for ORC RITs have been extensively reported, a systematic understanding of how turbine efficiency, loss mechanisms, and geometric characteristics evolve across the broader design parameter space remains limited. In particular, performance maps consistent with mainstream enthalpy-drop-based design practice and accounting for real-gas effects are still scarce.

In this study, a systematic performance mapping framework for ORC radial inflow turbines is established using R245fa as the working fluid. An optimized preliminary design methodology is developed by combining Aungier's 1D mean-line model with a Particle Swarm Optimization (PSO) algorithm, incorporating refined aerodynamic and geometric constraints and real-gas thermophysical properties. The model is validated against published reference designs, demonstrating a maximum improvement of 1.60% in total-to-static efficiency, with a peak efficiency of 88.04%. Based on the validated model, efficiency maps in terms of total-to-static efficiency, specific speed, and velocity ratio (η_ts–n_s–v_s) are generated over a range of size parameters and volumetric expansion ratios.

The resulting maps quantitatively reveal the coupled influence of size parameter, volumetric expansion ratio, specific speed, and velocity ratio on turbine efficiency, internal loss distribution, and optimal rotor geometry. The results indicate that increasing the size parameter slightly enhances peak efficiency while broadening the high-efficiency region, thereby improving design robustness. In contrast, higher volumetric expansion ratios lead to a pronounced reduction in efficiency, primarily due to increased tip leakage losses, and cause significant shifts in the optimal design parameters. The proposed efficiency maps provide a practical and transferable reference for rapid preliminary design and robust parameter selection of ORC radial inflow turbines under diverse operating conditions.

径向流入涡轮（RITs）由于结构紧凑、效率高、能够在单级内适应较大的焓降，被广泛认为是适合中小型有机朗肯循环（ORC）系统的膨胀器。虽然ORC rit的一维（1D）平均线设计方法和优化技术已经被广泛报道，但对涡轮机效率、损失机制和几何特性如何在更广泛的设计参数空间中演变的系统理解仍然有限。特别是，与主流基于焓降的设计实践相一致的性能图，以及考虑实际气体效应的性能图仍然很少。本文以R245fa为工作流体，建立了ORC径向入流涡轮的系统性能映射框架。通过将Aungier的一维平均线模型与粒子群优化（PSO）算法相结合，结合精细的空气动力学和几何约束以及真实气体的热物理性质，开发了优化的初步设计方法。该模型与已发表的参考设计进行了验证，结果表明，总静态效率的最大改进为1.60%，峰值效率为88.04%。基于经过验证的模型，可以在一系列尺寸参数和体积膨胀比下生成总静态效率、比速度和速度比（ηts-ns-vs）的效率图。所得到的图定量地揭示了尺寸参数、体积膨胀比、比转速和速比对涡轮效率、内部损失分布和最佳转子几何形状的耦合影响。结果表明，增大尺寸参数可略微提高峰值效率，同时扩大高效率区域，从而提高设计的鲁棒性。相反，较高的体积膨胀比会导致效率显著降低，这主要是由于叶尖泄漏损失增加，并导致最佳设计参数发生重大变化。所提出的效率图为ORC径向流入水轮机在不同工况下的快速初步设计和稳健参数选择提供了实用和可转移的参考。

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引用次数: 0

Dynamic characteristics of compressed air energy storage system embedded with abandoned oil well storage: A numerical approach 基于废弃油井库的压缩空气储能系统动态特性的数值分析

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-02-09 DOI: 10.1016/j.energy.2026.140378

Hua Yang , Jiachao Wu, Jingyu Cui, Cong Du, Liang Tian, Fuxing Zhao

Compressed air energy storage (CAES) is a promising solution for large-scale energy storage. This study develops a three-stage compression and two-stage expansion thermal-storage CAES (TS-CAES) system with abandoned oil well (AOW) storage. Simulation results show: (1) During the energy storage stage, the underground well (UG) achieves the fastest pressure buildup rate, reaching 15 MPa in 6.3 h, 1.0 h faster than the first on-ground tank (OG1) and 1.6 h faster than the second on-ground tank (OG2); (2) During the energy release stage, UG maintains the most stable internal temperature, with an energy release duration of 4.2 h, shorter than OG1 (4.5 h) and OG2 (5.3 h), thus ensuring stable turbine inlet conditions; (3) UG benefits from geothermal coupling with surrounding strata (343 K), which accelerates pressurization, stabilizes discharge, and enables the highest recoverable waste heat (6.95 × 10⁴ MJ), surpassing OG1 and OG2 by over 10%. This geothermal contribution transforms the UG chamber from a passive air reservoir into an active energy conversion component. This study confirms the feasibility of using abandoned oil well as alternative air storage tanks (ASTs) in TS-CAES systems, providing theoretical support for their integration with geothermal resources to optimize large-scale energy storage performance.

压缩空气储能（CAES）是一种很有前途的大规模储能解决方案。本研究开发了一种具有废弃油井（AOW）储存的三级压缩两级膨胀储热CAES （TS-CAES）系统。仿真结果表明：(1)在蓄能阶段，地下井（UG）的蓄压速率最快，在6.3 h内达到15 MPa，比地面第一储罐（OG1）快1.0 h，比地面第二储罐（OG2）快1.6 h；(2)在能量释放阶段，UG保持最稳定的内部温度，能量释放持续时间为4.2 h，短于OG1 （4.5 h）和OG2 (5.3 h)，从而保证了涡轮进口条件的稳定；(3) UG利用与周围地层（343 K）的地热耦合，加速加压，稳定排放，最大可回收余热（6.95 × 104 MJ），超过OG1和OG2 10%以上。这种地热贡献将UG室从被动空气储层转变为主动能量转换组件。本研究证实了废弃油井作为替代储气罐在TS-CAES系统中的可行性，为其与地热资源的整合优化大规模储能性能提供了理论支持。

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引用次数: 0

A hard-constrained physics-informed neural network for localized digital twin modeling 面向局部数字孪生模型的硬约束物理信息神经网络

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-02-09 DOI: 10.1016/j.energy.2026.140379

Yanjie Kang , Jun Yang , Yuan Zhou , Yuan Yuan , Sulin Qin , Yong Li , Yupeng Yang

Constructing high-fidelity, real-time 3D digital twins for critical local regions is essential for the safe operation of advanced nuclear energy systems. However, conventional CFD-based full-order models are computationally expensive and struggle to meet real-time simulation demands, while mainstream data-driven reduced-order models suffer from weak interpretability and poor extrapolation capabilities. Physics-Informed Neural Networks (PINNs) offer a promising approach for integrating physical principles with data, yet the prevalent soft-constraint paradigm faces limitations such as inadequate strict enforcement of physical laws, difficulties in balancing loss weights, and challenges in handling missing boundary information in local modeling. To address these issues, this study proposes a novel hard-constrained PINN method. The core of this approach lies in reconstructing the pressure Poisson equation into an explicit algebraic relationship between velocity and pressure mode coefficients via proper orthogonal decomposition and Galerkin projection, which is embedded into the neural network's forward propagation process, ensuring strict adherence to physical laws. Validation on an unsteady 3D finite square cylinder flow case demonstrates the superior performance of the proposed method over soft-constrained approaches: it reduces the extrapolation mean absolute error by 48.1%, with enhanced robustness; achieves faster, more stable convergence with 20.6% fewer training epochs and reduced sensitivity to physical weights; and saves 30.2% in prediction time while achieving comparable accuracy with a more lightweight network. This study provides a reliable and efficient technical pathway for constructing high-dimensional localized digital twins with limited boundary information.

为关键局部区域构建高保真、实时三维数字孪生体对于先进核能系统的安全运行至关重要。然而，传统的基于cfd的全阶模型计算成本高，难以满足实时仿真需求，而主流数据驱动的降阶模型可解释性弱，外推能力差。物理信息神经网络（pinn）为将物理原理与数据集成提供了一种很有前途的方法，但普遍存在的软约束范式面临着诸如物理定律执行不严格、平衡损失权值困难以及在局部建模中处理缺失边界信息的挑战等局限性。为了解决这些问题，本研究提出了一种新的硬约束PINN方法。该方法的核心是通过适当的正交分解和Galerkin投影将压力泊松方程重构为速度和压力模态系数之间的显式代数关系，并嵌入到神经网络的前向传播过程中，确保严格遵守物理定律。对非定谔三维有限方柱体流场的验证表明，该方法优于软约束方法：外推平均绝对误差降低48.1%，鲁棒性增强；实现更快、更稳定的收敛，减少20.6%的训练次数，降低对物理权重的敏感性；并且节省了30.2%的预测时间，同时实现了与更轻量级的网络相当的准确性。该研究为构建边界信息有限的高维局部数字孪生提供了可靠、高效的技术途径。

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引用次数: 0

Geographic information system-based closed-loop co-optimization of site-capacity-operation for multi-energy complementary bases 基于地理信息系统的多能互补基地场地-能力-运行闭环协同优化

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-02-09 DOI: 10.1016/j.energy.2026.140398

Su Guo , Chen Wang , Zherui Ma , Yanjun Zhang , Zhenkun Qin , Jingshu Yan , Yanhan Qiao

The efficient planning of multi-energy complementary bases necessitates coordinated decision-making across geographical siting, capacity allocation, and dispatch. Prevailing approaches often treat geospatial suitability as a static, upfront constraint, lacking a closed-loop mechanism to dynamically refine siting and capacity decisions based on operational feedback. To bridge this gap, this study proposes a geographic information system-based closed-loop co-optimization framework. The framework seamlessly integrates high-resolution spatial analysis with system-level techno-economic optimization. Specifically, geographic information system-derived multi-criteria site evaluations are quantified and directly embedded as weighting factors in the capacity allocation model, ensuring optimal spatial resource distribution. Subsequently, a hybrid energy storage model co-optimizes net present value and loss of power supply probability. Crucially, the actual loss of power supply probability obtained from the hourly operational simulation is fed back to iteratively adjust the upper-layer capacity configuration, establishing a robust planning-operation feedback loop. A case study of a wind-solar-hydro-coal-storage system in Bortala, China, shows that the framework achieves a 4.58% higher net present value and a 42.27% lower initial investment than conventional open-loop planning, while ensuring 100% renewable accommodation and a 1.64% loss of power supply probability. This work highlights the indispensable role of deeply coupling dynamic operational feedback with granular spatial intelligence for designing high-performance multi-energy systems.

多能源互补基地的高效规划需要跨地域选址、容量分配和调度的协调决策。流行的方法通常将地理空间适宜性视为静态的、预先的约束，缺乏一个闭环机制来动态地改进基于操作反馈的选址和容量决策。为了弥补这一差距，本研究提出了一个基于地理信息系统的闭环协同优化框架。该框架将高分辨率空间分析与系统级技术经济优化无缝集成。具体而言，将地理信息系统衍生的多准则站点评价量化并直接作为权重因子嵌入到容量分配模型中，确保空间资源的最优配置。随后，混合储能模型对净现值和供电损失概率进行了共同优化。关键是将每小时运行仿真得到的实际供电损失概率进行反馈，迭代调整上层容量配置，建立鲁棒的规划-运行反馈回路。通过对中国博尔塔拉市的风电-太阳能-水电-煤储电系统的案例研究表明，与传统开环规划相比，该框架的净现值提高4.58%，初始投资降低42.27%，同时保证了100%的可再生能源发电和1.64%的电力供应损失概率。这项工作强调了动态操作反馈与颗粒空间智能的深度耦合在设计高性能多能系统中不可或缺的作用。

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引用次数: 0

Multi-physics field study of CO low-temperature catalytic reactor based on CFD-GNN approach 基于CFD-GNN方法的CO低温催化反应器多物理场研究

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-02-09 DOI: 10.1016/j.energy.2026.140401

Fuqing Wang , Kun Wang , Lixin Tang , Chun Wang , Kunlun Li

This study addresses excessive CO emissions and associated energy waste in flue gas by employing low-temperature catalytic oxidation of CO, combined with computational fluid dynamics (CFD) and orthogonal experiments to investigate key process parameters affecting catalytic performance and temperature rise. The investigation reveals that catalyst layer quantity substantially influences CO conversion efficiency, with CO concentration being the primary factor in flue gas temperature elevation. At 15000 ppm CO concentration, the sintering flue gas temperature increases by approximately 130 K, translating to potential savings of 43780 m³/h of blast furnace gas. A novel CFD-graph neural network (GNN) methodology was developed to expedite temperature and concentration field simulations within the catalytic reactor. The proposed GNN-autoencoder framework utilizes gradient-based dimensionality reduction and a weighted loss function to enhance predictive accuracy. The model demonstrates exceptional performance, achieving a minimum validation loss of 0.0106, with R² values of 0.9812 and 0.9831 for training and testing sets. Notably, the model predicts CO concentrations and temperatures with average relative errors of 0.8564% and 0.0336%, respectively. This approach significantly reduces computational complexity while accurately capturing intricate physical field characteristics, offering efficient technical support for CO emission mitigation and energy recovery in sintering processes.

本研究采用CO低温催化氧化技术，结合计算流体动力学（CFD）和正交试验，研究影响催化性能和升温的关键工艺参数，解决烟气中CO排放超标及相关能源浪费问题。研究表明，催化剂层数对CO转化效率有较大影响，CO浓度是影响烟气温度升高的主要因素。在15000ppm的CO浓度下，烧结烟气温度提高了约130k，相当于每小时节省43780立方米的高炉煤气。提出了一种新的cfd图神经网络（GNN）方法来加速催化反应器内温度和浓度场的模拟。提出的gnn自编码器框架利用基于梯度的降维和加权损失函数来提高预测精度。该模型表现出优异的性能，最小验证损失为0.0106，训练集和测试集的R2分别为0.9812和0.9831。值得注意的是，该模型预测CO浓度和温度的平均相对误差分别为0.8564%和0.0336%。该方法显著降低了计算复杂度，同时准确捕获了复杂的物理场特征，为烧结过程中的CO减排和能量回收提供了有效的技术支持。

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引用次数: 0

Compression scheme comparison for a carbon dioxide energy storage system 某二氧化碳储能系统压缩方案比较

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-02-09 DOI: 10.1016/j.energy.2026.140298

Xintao Fu , Yuwei Jiao , Zhan Liu

The gas-liquid type compressed carbon dioxide energy storage is an emerging potential energy storage technology to stable the renewable power output. The trying improvements that this paper is focused on are effective realization of the gas-liquid conversion of the high pressure CO₂ without utilizing extra cold sources and efficient allocating the pressure ratio in the compression/expansion lines. Two self-condensing systems with qual pressure ratio and equal outlet temperature arrangements are proposed and evaluated. Numerical simulations to the considered systems are conducted on an in-house code that is compiled with the established energy, exergy and economic mathematical models. Results indicate that the equal outlet temperature system is more suggested due to its lower levelized cost of storage at the optimized operating conditions, being 0.11329 $/kWh when the high-pressure cooler cold-side temperature difference is 11 °C, liquid CO₂ temperature is 16 °C and throttling pressure is 7.8 MPa. In the component level, the gas holder and liquid CO₂ tank constitute the highest portion to the overall system purchase cost. The compressors, turbines, evaporator and condenser account for the largest share of thermodynamic inefficiencies in sequence. The pinch temperature difference of the condenser and evaporator should not be higher than 8 °C.

气液型压缩二氧化碳储能是一种新兴的有潜力的稳定可再生能源输出的储能技术。本文的改进重点是在不使用额外冷源的情况下有效地实现高压CO2的气液转化和有效地分配压缩/膨胀管线的压力比。提出并评价了两种等压比、等出口温度布置的自凝系统。对所考虑的系统进行数值模拟是在一个内部代码上进行的，该代码是用已建立的能源、能源和经济数学模型编译的。结果表明，在优化工况下，当高压冷却器冷侧温差为11℃、液态CO2温度为16℃、节流压力为7.8 MPa时，等温系统的平准化储能成本为0.11329美元/kWh，因此更适合采用等温系统。在部件层面，气柜和液态CO2罐构成了整个系统采购成本的最高部分。压缩机、涡轮机、蒸发器和冷凝器依次占热力学效率低下的最大份额。冷凝器与蒸发器夹点温差不应高于8℃。

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引用次数: 0

Hierarchical carbon aerogels via catalyst-free spinodal engineering: A pathway to sustainable high-performance supercapacitors 分层碳气凝胶通过无催化剂的spinodal工程：可持续高性能超级电容器的途径

IF 9.4 1区工程技术 Q1 ENERGY & FUELS

Energy

Pub Date : 2026-02-09 DOI: 10.1016/j.energy.2026.140404

Haryeong Choi , Vinayak G. Parale , Taehee Kim , Jiseung Kim , Shraddha Bhosale , Sang-Hyun Kim , Varsha D. Phadtare , Younghun Kim , Wonjun Lee , Mukund G. Mali , Santosh S. Sutar , Tukaram Dongale , Sang Eun Shim , Hyung-Ho Park

Despite considerable progress in porous carbons, there is still a need for methods that couple phase separation and carbonization to produce thick, binder free monoliths that combine continuous electron pathways with rapid ion access for high performance supercapacitor electrodes. Here, spinodal decomposition is employed to synthesize aerogels with tunable hierarchical pore structures by varying the ratios of resorcinol, formaldehyde, and water. After carbonization, the aerogels show enhanced mechanical strength, surface area, and electrical conductivity. The optimized sample exhibits a compressive modulus of approximately 1.67 GPa and an electrical conductivity of approximately 55 S m⁻¹ and delivers a specific capacitance of 339.2 F g⁻¹ at 0.5 A g⁻¹ in 6 M KOH with approximately 98.4 percent retention over 40,000 cycles. A symmetric coin cell supercapacitor using 1 M tetraethylammonium tetrafluoroborate in acetonitrile achieves 22.9 Wh kg⁻¹ at 1000 W kg⁻¹ and approximately 98.38 percent stability after 100,000 cycles. These properties arise from a continuous coral like architecture that shortens ion diffusion paths and promotes rapid transport. In addition, a long short term memory model is used to model and forecast cycling stability, in agreement with the experimental trends. Overall, this catalyst free spinodal approach offers a practical pathway to high performance, hierarchically porous carbon aerogels for next generation supercapacitors and related energy storage systems.

尽管多孔碳已经取得了相当大的进展，但仍然需要将相分离和碳化相结合的方法来生产厚的、无粘结剂的单体，将连续的电子路径与快速的离子通道结合起来，用于高性能超级电容器电极。在这里，通过改变间苯二酚、甲醛和水的比例，采用spinodal分解来合成具有可调分层孔结构的气凝胶。碳化后，气凝胶表现出增强的机械强度、表面积和导电性。优化后的样品的压缩模量约为1.67 GPa，电导率约为55 S m−1，在6 m KOH中，0.5 a g−1时的比电容为339.2 F g−1，在40,000次循环中保持率约为98.4%。在乙腈中使用1 M四氟硼酸四乙基铵的对称硬币电池超级电容器在1000 W kg - 1时达到22.9 Wh kg - 1，在10万次循环后稳定性约为98.38%。这些特性源于连续的珊瑚状结构，缩短了离子扩散路径，促进了快速运输。此外，利用长短期记忆模型对循环稳定性进行了建模和预测，与实验结果一致。总的来说，这种无催化剂的spinodal方法为下一代超级电容器和相关储能系统提供了高性能、分层多孔碳气凝胶的实用途径。

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引用次数: 0

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