International Journal of Energy Research最新文献

{"title":"Boosting Iodine Capture via Ammonization of a Multicomponent-Based Covalent Organic Framework","authors":"Muzammil Hussain,&nbsp;Inam Ullah,&nbsp;Sakthivel Kumaravel,&nbsp;Bolam Kim,&nbsp;Dae Sung Lee","doi":"10.1155/er/9008510","DOIUrl":"https://doi.org/10.1155/er/9008510","url":null,"abstract":"<p>Adsorption-based iodine capture offers an effective strategy for managing radioactive nuclear waste. In this study, a carboxylic acid–functionalized covalent organic framework (COF─COOH) was synthesized via a multicomponent Doebner reaction and postsynthetically modified with aqueous ammonia to produce an ionic framework, [COF─COO⁻][NH₄]⁺. A nonfunctionalized analog, COF─TpTta, was also synthesized for comparison. Iodine vapor uptake at 75°C followed the order [COF─COO⁻][NH₄]⁺ (2.4 ± 0.092 g/g) &gt; COF─COOH (1.8 ± 0.07 g/g) &gt; COF─TpTta (1.5 ± 0.082 g/g). Spectroscopic analyses revealed that COF─TpTta and COF─COOH primarily captured iodine via charge–transfer interactions, whereas [COF─COO⁻][NH₄]⁺ utilized an additional electrostatic and hydrogen bonding mechanism between iodine species and ammonium carboxylate groups. This dual-binding mechanism enhanced iodine uptake by 60% over COF─TpTta despite reduced surface area, pore size, and pore volume. [COF─COO⁻][NH₄]⁺ retained over 80% of its gaseous phase iodine adsorption capacity after four cycles, maintained iodine loading over 30 h, and exhibited high iodine uptake (225 ± 16.76 mg/g) from n-hexane following Langmuir-type adsorption. These results demonstrate that tailored binding-site chemistry, rather than solely textural optimization, can drives superior iodine capture. This ionic COF design strategy offers a versatile and robust platform for synthesizing next-generation radioiodine adsorbents.</p>","PeriodicalId":14051,"journal":{"name":"International Journal of Energy Research","volume":"2026 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/er/9008510","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on the Evolution of Concentrated Stress Distribution in Close-Proximity Coal Seam Residual Pillars","authors":"Dengyan Gao,&nbsp;Chenyang Ma,&nbsp;Wen Luo,&nbsp;Kuiying Gao,&nbsp;Jing Chai,&nbsp;Zhicheng Han,&nbsp;Jianhua Chen,&nbsp;Yinsu Tian","doi":"10.1155/er/8894650","DOIUrl":"https://doi.org/10.1155/er/8894650","url":null,"abstract":"<p>Closely spaced coal seams are extensively distributed across China. As shallow coal resources face increasing depletion, coal mining is gradually extending to deeper zones. Deciphering the stress distribution pattern of the residual coal pillar floor in closely spaced coal seams is of profound importance to the safe and efficient mining operations of lower coal seams while also offering certain theoretical guidance for the development of deep closely spaced coal seams. Taking the 22,206 coal working face of Daliuta Huojitu Well as the research background, this study adopted a combination of theoretical analysis and similar simulation experimental methods. Systematic analysis was conducted using multiple monitoring technologies, including distributed optical fiber sensing (DOFS), digital image correlation (DIC), and pressure sensors, to explore the evolutionary characteristics of stress distribution in the floor of residual coal pillars in closely spaced coal seams. The research results show that the depth of influence of upper residual coal pillars and goafs on the mining of lower coal seams differs. When the upper section is a goaf, the minimum safe distance is 20.4 m; when the upper structure is a residual coal pillar, the minimum safe distance is 39.9 m. The stress concentration coefficient under residual coal pillars is higher than that in goaf regions. With the advancement of the working face, the stress influence angle gradually decreases from ~80°46^′ to 46°22^′, while the peak stress concentration coefficient rises from 1.15 to 2.24 with the reduction of coal pillar width. The mining of closely spaced coal seams exhibits a pressure relief effect, and the abutment pressure concentration coefficient under coal pillars is higher than that under the goaf working face. When the underlying working face passes through residual coal pillars, disasters are prone to occur. This is attributed to the superposition of concentrated stress and advanced abutment pressure, combined with vertical splitting and subsidence of the upper rock stratum, which results in sudden stress release. The multitechnology integrated monitoring system and quantitative safety criteria established in this study provide new theoretical foundations and engineering practice references for safe mining under similar geological conditions.</p>","PeriodicalId":14051,"journal":{"name":"International Journal of Energy Research","volume":"2026 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/er/8894650","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Solid Composite Polymer Electrolyte Lithium-Ion Battery With an Improved Electrochemical Stability Window and Cycle Characteristics","authors":"Yesul Jeong,&nbsp;Yunju Choi,&nbsp;Mirang Byeon,&nbsp;Sang Geul Lee,&nbsp;Dokyung Kim,&nbsp;Sunghee Min,&nbsp;Young Joo Lee,&nbsp;Jong-Seong Bae,&nbsp;Euh Duck Jeong,&nbsp;Jong-Pil Kim","doi":"10.1155/er/6684073","DOIUrl":"https://doi.org/10.1155/er/6684073","url":null,"abstract":"<p>Polymer electrolytes for lithium-ion batteries (LIBs) face challenges such as low ionic conductivity, insufficient mechanical flexibility, and limited thermal stability, which restrict their use in high-energy density applications. To address these issues, a solid composite polymer electrolyte (SCPE) is developed by blending poly(ethylene oxide) (PEO) with poly(ethylene glycol) dimethyl ether (PEGDME) as a synthetic electrolyte and adding an F-doped lithium aluminum titanium phosphate inorganic filler. As a result, the prepared CPE exhibits a high ionic conductivity of 1.24 × 10⁻⁴ S/cm and excellent thermal stability, along with an extended electrochemical stability window (ESW) up to 6.8 V. When applied to LiFePO₄ half-cells, the CPE enables charge and discharge capacities of 152.3 and 152.0 mA h/g, respectively, while maintaining a low voltage hysteresis of approximately 0.16 V throughout the cycles. Although the initial cycle shows a relatively high irreversible capacity of 3.7 mA h/g, the cell demonstrates outstanding cycling stability, retaining 98.9% of its initial capacity after 100 cycles. The developed composite electrolyte shows potential for use in safe and high-performance all-solid-state LIBs, providing a viable pathway toward safer and high-performance solid-state LIBs suitable for advanced energy storage applications.</p>","PeriodicalId":14051,"journal":{"name":"International Journal of Energy Research","volume":"2026 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/er/6684073","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cross-System Comparative Techno-Economic and Environmental Evaluation of MCFC Integration in Power and Biogas Upgrading Systems","authors":"Kazeem Ayodeji Mohammed,&nbsp;Amirpiran Amiri,&nbsp;Ehsan Baniasadi,&nbsp;Robert Steinberger-Wilckens","doi":"10.1155/er/6871470","DOIUrl":"https://doi.org/10.1155/er/6871470","url":null,"abstract":"<p>Achieving net-zero or carbon-negative energy systems requires technologies capable of generating power while capturing or utilising CO₂ without significant efficiency losses. Molten carbonate fuel cells (MCFCs) offer such potential, yet their techno-economic competitiveness across different energy systems remains insufficiently quantified. Beyond conventional power-plant integration, this study explores a new application of MCFCs in biogas upgrading, where their electrochemical CO₂-transfer capability is harnessed to purify raw biogas to near-pipeline-quality biomethane (BM) while simultaneously generating electricity. A process-simulation-informed, bottom-up techno-economic and environmental assessment was conducted to evaluate MCFC integration within natural gas combined cycle (NGCC), integrated gasification combined cycle (IGCC) and biogas-upgrading systems, each operated with air- or O₂-fed cathodes. Results show that integrating MCFCs into different plant types significantly affects both plant efficiency and CO₂ avoidance cost, with the air-fed NGCC–MCFC configuration demonstrating the most favourable techno-economic balance, while the O₂-fed IGCC–MCFC system provides superior environmental performance in centralised applications. In decentralised settings, MCFC-assisted biogas upgrading can achieve cost-neutral or revenue-positive operation when stack costs fall below 1000 $·kW⁻¹, highlighting its potential as a self-sustaining CO₂-removal route. These findings establish a unified cross-system performance map identifying where MCFCs are most competitive across centralised and decentralised energy systems, highlighting their potential as dual-function units for power decarbonisation and renewable-gas production.</p>","PeriodicalId":14051,"journal":{"name":"International Journal of Energy Research","volume":"2026 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/er/6871470","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From Quarry to Carbon-Conscious City: The Ebbsfleet Garden City Regeneration Experience","authors":"Haoxuan Yu","doi":"10.1155/er/9942560","DOIUrl":"https://doi.org/10.1155/er/9942560","url":null,"abstract":"<p>This case study examines Dartford’s transformation through the Ebbsfleet Garden City project, demonstrating how postindustrial regeneration can balance economic revitalization, environmental restoration, and social development. Using a chronological case study methodology with satellite imagery analysis (2006–2024) and comparative international assessment, we trace development through four phases: predevelopment (2006), planning (2012), active construction (2017), and maturation (2022–2024). Key achievements include residential construction of planned 15,000 units, conversion of 40+ hectare quarries into recreational lakes, and improved London connectivity via Ebbsfleet International Station. However, challenges persist in economic diversification, infrastructure capacity under rapid growth, and environmental management continuity. Comparative analysis with Ruhr Valley, Detroit, Bilbao, and Melbourne Docklands reveals that successful regeneration requires integrated governance, sustained corporate social responsibility (CSR), and innovative low-carbon technologies. The Ebbsfleet case demonstrates both the potential and complexity of brownfield redevelopment in achieving sustainable urban growth.</p>","PeriodicalId":14051,"journal":{"name":"International Journal of Energy Research","volume":"2026 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/er/9942560","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient Porous-Medium Framework for Compact Heat Pipe Heat Exchanger","authors":"Seungjae Lee,&nbsp;Jin Hyeuk Seo,&nbsp;Yunseo Kim,&nbsp;Hoon Choi,&nbsp;Seong Hyuk Lee,&nbsp;Jungho Lee,&nbsp;Hyoungsoon Lee","doi":"10.1155/er/6962940","DOIUrl":"https://doi.org/10.1155/er/6962940","url":null,"abstract":"<p>Waste heat recovery is one of the most effective strategies for improving global energy efficiency. However, accurately modeling of compact heat pipe heat exchangers (HPHXs) remains computationally challenging due to their intricate fin geometries and complex phase-change processes. This work introduces a porous-medium modeling framework that combines anisotropic flow resistance coefficients with a local thermal nonequilibrium (LTNE) formulation. The approach enables precise resolution of thermal gradients and interfacial heat transfer while significantly reducing computational costs. Experimental validation was conducted on a representative compact HPHX and benchmarked against both a conventional local thermal equilibrium (LTE) porous-medium model and a fully resolved fin-geometry simulation. The LTNE model predicted heat transfer and pressure drop with errors within 5%, while reducing hot- and cold-side pressure drop errors by ~45% and 60%, respectively, compared to LTE. It also eliminated the systematic overprediction of heat transfer observed in LTE. Matching the accuracy of the fully resolved fin model, the LTNE framework achieved a ~97% reduction in computational time, offering an accurate and efficient alternative for large-scale simulations. These results establish the anisotropic-LTNE porous-medium framework as a robust and scalable tool for the design and optimization of next-generation compact heat recovery systems.</p>","PeriodicalId":14051,"journal":{"name":"International Journal of Energy Research","volume":"2026 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/er/6962940","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on Predictive Methods Considering the Inherent Coupling Mechanisms of Multienergy Sources and Loads in Campus Systems","authors":"Yifan Sun,&nbsp;Feng Sun,&nbsp;Xin Liu,&nbsp;Weidong Zhong,&nbsp;Lei Chen,&nbsp;Jie Xu,&nbsp;Sheng Qin,&nbsp;Licheng Wang","doi":"10.1155/er/4540116","DOIUrl":"https://doi.org/10.1155/er/4540116","url":null,"abstract":"<p>As integrated energy systems (IESs) evolve to meet growing demands for sustainable energy, accurate forecasting of multisource energy loads becomes critical. This study proposes a forecasting framework integrating Bi-directional long short-term memory (BiLSTM) networks with multitask learning (MTL) to jointly predict electricity, cooling, heating, and photovoltaic (PV) loads. Unlike single-task approaches, the MTL framework enhances performance by leveraging shared information. To improve robustness, empirical mode decomposition (EMD) denoises nonstationary time-series data, and the snow ablation optimizer (SAO) fine-tunes hyperparameters. Experimental results on real-world campus data show that the EMD–MTL–BiLSTM–SAO model outperforms existing methods, offering superior accuracy and reliability. These results demonstrate the model’s potential for optimizing future low-carbon energy systems.</p>","PeriodicalId":14051,"journal":{"name":"International Journal of Energy Research","volume":"2026 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/er/4540116","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy Harvesting Using Large Deformable Permanent Magnet","authors":"Gakuho Oe,&nbsp;Tomoya Tsuchida,&nbsp;Yuhiro Iwamoto,&nbsp;Yasushi Ido,&nbsp;Nobuyuki Makihara,&nbsp;Hisashi Tsuruta","doi":"10.1155/er/1354581","DOIUrl":"https://doi.org/10.1155/er/1354581","url":null,"abstract":"<p>In this study, we develop a permanent magnet capable of withstanding high loads (~2 kN) and large displacements (~50% compressive deformation). This magnet can be used to develop a battery-free Internet of Things device. To investigate the power generation mechanism, we build a custom compressible vibrating sample magnetometer (VSM) and examine magnetization changes during compression. X-ray computed tomography (CT) scans and image analysis are also employed. The developed permanent magnet foamed urethane elastomer (PMFUE) is fabricated by dispersing neodymium particles in a tough foamed urethane elastomer, which is then molded and magnetized. Deformation-induced magnetization changes (inverse magnetostriction) enable power generation under high-load, large-displacement, and low-frequency vibration, allowing wireless transmission. VSM measurements show that magnetization doubles at 50% compression compared to that at 0% compression. X-ray CT scans reveal that despite significant volume reduction, the internal particles barely rotate, explaining the observed effect. These findings show that volume reduction and minimal particle rotation cause dramatic changes in magnetic moment density, triggering the inverse magnetostriction effect. This mechanism could advance the development of durable magnetostrictive materials and their application in vibration energy harvesting.</p>","PeriodicalId":14051,"journal":{"name":"International Journal of Energy Research","volume":"2026 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/er/1354581","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147714935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of Base Depth on the Frequency-Dependent Impedance Characteristics of Vertical Silicon Solar Cells Using Dynamic Impedance Spectroscopy","authors":"Gökhan Şahin,&nbsp;Sabir Rüstemli","doi":"10.1155/er/7618204","DOIUrl":"https://doi.org/10.1155/er/7618204","url":null,"abstract":"<p>This theoretical study investigates the frequency-dependent impedance behavior of vertical parallel-junction silicon (Si) solar cells, focusing on the impact of base depth under modulated illumination. Using dynamic impedance spectroscopy (DIS) and analyzing Bode and Nyquist diagrams, key electrical parameters, including series and parallel resistances, capacitance, and inductance, are extracted. The results reveal that increasing the base depth leads to a decrease in both the real and imaginary components of capacitance, a reduction in parallel resistance, and a transition from predominantly capacitive to more inductive behavior. The impedance spectra show a quarter-circle arc at low frequencies and a near-linear response at high frequencies, reflecting changes in dominant charge transport and recombination mechanisms. The cutoff frequency decreases significantly with depth, highlighting spatial limitations in minority carrier generation. These findings emphasize the critical role of base depth in shaping the solar cell’s internal electrical characteristics and validate IS as a powerful tool for optimizing device design, absorber thickness, and equivalent circuit modeling in high-efficiency photovoltaic (PV) systems.</p>","PeriodicalId":14051,"journal":{"name":"International Journal of Energy Research","volume":"2026 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/er/7618204","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147714932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global Renewable Energy Forecasting Using Hybrid Deep Learning and Two-Tier Optimization Models","authors":"Salman Arafath Mohammed,&nbsp;Ibrahim M. Mehedi,&nbsp;Naim Ahmad,&nbsp;Abdulilah Mohammad Mayet,&nbsp;Mahendiran T. Vellingiri,&nbsp;Rahtul Jannat Meem","doi":"10.1155/er/8654684","DOIUrl":"https://doi.org/10.1155/er/8654684","url":null,"abstract":"<p>Energy is the most appropriate method to fill the hole of social, financial, and ecological factors for improving human growth across the world. Renewable energy prediction is of paramount importance for reliable operation and efficient management of power systems in a continuously changing climate. Nevertheless, there are still deficits in the accuracy of existing forecaster model, poor generalization, and ineffective optimization results of parameters. To cope with those difficulties, we present in this study a new global renewable energy forecasting model using hybrid deep learning and two-tier optimization technics. Our proposed model integrates wisdom of features, attention-guided spatiotemporal learning, and automatic determination of hyperparameters to ensure robust and accurate prediction. Through extensive experiments done on a benchmark global renewable energy dataset, the experimental results show that our proposed approach outperforms other state-of-the-art methods in terms of prediction accuracy, stability, and generalization ability. For the past few years, developments in technology, computing power, and artificial intelligence (AI) have delivered an effective method for tackling numerous urban computing issues such as short-term renewable energy prediction. This study presents a novel global renewable energy forecasting using a hybrid deep learning and two-Tier optimization models (GREF-HDLTOM). The proposed GREF-HDLTOM model’s main intention is to enhance the prediction model of renewable energy using advanced DL and optimization algorithms. At first, the data preprocessing stage contains input scaling using a standard scaler and output scaling using MaxAbsScaler for converting the categorical data into a numerical format. For the feature selection process, the proposed GREF-HDLTOM model designs an African vulture optimization algorithm (AVOA). This study introduces a new global renewable energy forecasting model using hybrid deep learning and two-tier optimization method. Its components consist of AVOA for feature selection and attention-convolutional gated recurrent neural networks (A-CGRNNs) for spatiotemporal predictions, while improved northern goshawk optimization (INGO) is employed to search optimal hyperparameters. Experiments show that the new method significantly outperforms existing methods. Furthermore, the hybrid of A-CGRNN has been deployed for the prediction process. At last, the INGO algorithm adjusts the hyperparameter values of the A-CGRNN model optimally and outcomes in greater prediction performance. The experimental evaluation of the GREF-HDLTOM system occurs utilizing a benchmark database. The simulation outcomes indicated the enhanced performance of the GREF-HDLTOM system compared to existing approaches.</p>","PeriodicalId":14051,"journal":{"name":"International Journal of Energy Research","volume":"2026 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/er/8654684","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}