Energy Conversion and Management-X最新文献

{"title":"Enhancing fault detection in bifacial photovoltaic systems: a two-stage CNN-RF approach with I-V curve analysis","authors":"Abdul-Kadir Hamid ,&nbsp;Mena Maurice Farag ,&nbsp;Tareq Salameh ,&nbsp;Mousa Hussein","doi":"10.1016/j.ecmx.2025.101275","DOIUrl":"10.1016/j.ecmx.2025.101275","url":null,"abstract":"<div><div>Rising global energy demand, driven by population growth and industrialization, threatens environmental sustainability, necessitating renewable solutions to combat climate change and resource depletion. Bifacial photovoltaic (PV) modules, capturing sunlight on both sides, yield 20–30% higher energy in high-albedo environments than monofacial modules but suffer 10–40% efficiency losses from faults like shading, dust, aging, degradation, and cracks, with dual-sided designs complicating detection. This study pioneers a multi-fault classification framework for bifacial PV systems, integrating mathematical modeling of dual-sided fault impacts on I-V curves and a 180-day synthetic dataset with randomized severities. Combining I-V curve and maximum power point-based power profile analyses, it demonstrates bifacial resilience, achieving up to 100% power advantage under severe shading and 11.7–30% superior outputs across faults. The proposed two-stage CNN-RF model delivers 100% accuracy in Stage 1, classifying baseline, degradation, and obstruction, and 97.6% accuracy in Stage 2, identifying specific faults such as dust, shading, aging, and cracks, with an area under the curve (AUC) of 0.999 and false positive rate (FPR) of 0.006. It surpasses standalone CNN at 89.7% accuracy in Stage 2 with an 8.8% accuracy gain, AUC of 0.994, and FPR of 0.026, as well as RBF-SVM at 96.1% and GBRT at 91.8%, due to its synergistic feature extraction and robust ensemble classification. The model’s low computational footprint enables real-time scalability for large PV farms through edge computing or cloud integration, enhancing reliability and maintenance strategies for bifacial systems.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"28 ","pages":"Article 101275"},"PeriodicalIF":7.6,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two-stage robust planning of data center microgrid considering batch load flexibility and multi-energy complementarity","authors":"Yu He ,&nbsp;Junqiu Fan ,&nbsp;Jiayu Lin ,&nbsp;Zetao Li ,&nbsp;Jing Zhang ,&nbsp;Wuqin Tang ,&nbsp;Qiang Yang","doi":"10.1016/j.ecmx.2025.101266","DOIUrl":"10.1016/j.ecmx.2025.101266","url":null,"abstract":"<div><div>The intrinsic coupling between dynamic batch load characteristics of data centers and robust microgrid planning presents significant challenges in coordinating economic efficiency with power supply reliability, particularly under high renewable energy penetration. This paper proposes a novel temporal flexibility modeling framework for batch workloads and establishes a two-stage robust optimization method for data center microgrid planning. Three fundamental innovations are introduced: (1) A matrix-based adjustable domain model quantifying batch load transfer capability with 2-hour delay constraints, mathematically characterizing temporal flexibility through shiftable power matrices; (2) A min–max-min robust planning architecture coordinating photovoltaic-storage-gas turbine systems, employing C&amp;CG algorithm for hierarchical solution of capacity configuration (upper-level) and operational scheduling (lower-level) under renewable-load uncertainties; (3) Practical validation through Guizhou’s data center cluster demonstrates 14.7% reduction in capital expenditure and 23.2% improvement in load scheduling flexibility while maintaining service quality constraints. The proposed method provides a quantitative tool for optimizing infrastructure planning-operational dynamics in renewable-dominated microgrids, supporting low-carbon transition of data center clusters in Guian New Area. Comparative analysis reveals the model’s superiority over conventional robust approaches in achieving Pareto-efficient solutions between cost reduction (¥12,819/$1,789 daily operational savings) and reliability enhancement (63% gas turbine capacity optimization under 30% uncertainty scenarios).</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"28 ","pages":"Article 101266"},"PeriodicalIF":7.6,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of the feasibility and techno-economic viability of a SPV-driven autonomous power generation system for electrification in remote areas of India","authors":"Rajeev Kumar Chauhan ,&nbsp;Anand Prakash Singh ,&nbsp;Dipankar Pramanick ,&nbsp;Himanshu Sharma ,&nbsp;Pankaj Kumar","doi":"10.1016/j.ecmx.2025.101265","DOIUrl":"10.1016/j.ecmx.2025.101265","url":null,"abstract":"<div><div>The integration of conventional and renewable energy sources offers a viable solution for electrifying remote and underserved regions of India, where reliable grid connectivity remains a challenge. This paper presents a comprehensive techno-economic analysis of a Solar Photovoltaic (SPV)-based System for Integrated Electricity Generation (SIEG) tailored for a remote area in West Bengal, Eastern India. The system’s performance is rigorously evaluated using a suite of performance indices, alongside a detailed feasibility study that incorporates both economic and environmental metrics. The SPV system exhibits a performance ratio of 77.50 % and an average annual capacity factor of 16.78 %, attributable to the local climatic conditions. The system design and optimization are carried out using the Hybrid Optimization Model for Electric Renewables (HOMER) software, which facilitates the integration of solar energy with conventional generation resources and storage solutions. The optimal configuration, designed to meet a 30.39 kWh/d load, consists of a 12.4 kW SPV array, a 6 kW diesel generator set (DGS), a 19 kWh battery storage unit, and a 4.83 kW converter. This hybrid setup delivers the lowest cost of electricity (COE) at $0.248/kWh, with a total present cost (TPC) of $35,627.85. The system achieves a high renewable fraction (RF) of 96.66 %, substantially reducing carbon emissions by 97.5 % compared to a standalone DGS configuration. Furthermore, the hybrid system’s TPC and COE are 76.4 % lower than those of a conventional DGS-only setup. To evaluate the robustness and adaptability of the proposed system, a multi-dimensional sensitivity analysis is performed. This analysis examines the impact of variations in critical parameters, including energy resource availability, fuel costs, and load profiles, on the COE and system performance. The findings underscore the feasibility and economic viability of the hybrid SIEG system as a sustainable and resilient energy solution for rural electrification in Eastern India.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"28 ","pages":"Article 101265"},"PeriodicalIF":7.6,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating cost and emission reduction potentials with stochastic PPA portfolio optimization for green hydrogen production in a decarbonized glassworks","authors":"Jonas Brucksch ,&nbsp;Jonas van Ouwerkerk ,&nbsp;Dirk Uwe Sauer","doi":"10.1016/j.ecmx.2025.101251","DOIUrl":"10.1016/j.ecmx.2025.101251","url":null,"abstract":"<div><div>The decarbonization of heavy industries demands large volumes of green hydrogen. To produce green hydrogen via electrolysis, the EU’s Renewable Energy Directive II imposes rules to ensure the use of renewable electricity. Hydrogen producers can use portfolios of power purchase agreements (PPAs) to buy renewable electricity. These portfolios must meet hydrogen demand cost-effectively, and battery storage can help by shifting excess renewable generation. However, high uncertainty around future electricity prices and demand complicates optimal portfolio design. Current literature lacks comprehensive models that evaluate such portfolio optimization under uncertainty for real-world case studies including battery storage. This work addresses the gap by introducing a stochastic mixed-integer linear programming model tailored to industrial applications. We demonstrate the model using a real-world glass manufacturing site in Germany. Our findings show that portfolio optimization alone can reduce the levelized cost of hydrogen (LCOH) by 6.24% under EU rules. Adding a battery further cuts costs, achieving an LCOH of 11.8 €₂₀₂₄ kg⁻¹. Exploring different temporal matching schemes reveals that weekly matching reduces LCOH by 2 €₂₀₂₄kg⁻¹ while maintaining a high share of renewable energy. The model offers a flexible tool for optimizing PPA portfolios in various industrial settings.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"28 ","pages":"Article 101251"},"PeriodicalIF":7.6,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pricing and trading strategies in networked microgrid systems: A comprehensive review","authors":"Syed Muhammad Ahsan ,&nbsp;Akhtar Hussain ,&nbsp;Petr Musilek","doi":"10.1016/j.ecmx.2025.101249","DOIUrl":"10.1016/j.ecmx.2025.101249","url":null,"abstract":"<div><div>As microgrids evolve from isolated systems into interconnected networks, pricing and trading strategies have emerged as the economic backbone of networked microgrid systems. These strategies are essential to enable energy self-sufficiency, facilitate energy exchanges within the network, and support scalable coordination. However, the development of effective trading approaches remains a complex and challenging task for researchers. To address these challenges, several studies have been proposed in the literature to overcome the complexities of trading in networked microgrids. This article presents a comprehensive comparative review of existing studies on pricing and trading strategies in networked microgrids. The reviewed methods are classified into five major categories: mathematical optimization techniques, market mechanisms, game-theoretic approaches, reinforcement learning methods, and blockchain-based models. Each category is examined in terms of its technical foundations and the application of the respective strategy within networked microgrids. Furthermore, four key evaluation criteria — fairness, privacy, scalability, and computational efficiency — are identified to facilitate a detailed comparative analysis of the studies within each category. This review highlights the strengths and trade-offs of each approach based on these criteria. Finally, the article highlights real-world pilot projects that demonstrate the practical viability of each categorized approach, while also outlining key research gaps that hinder broader implementation of pricing and trading strategies in networked microgrid systems.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"28 ","pages":"Article 101249"},"PeriodicalIF":7.6,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing energy density in thin-film nanocomposite dielectric capacitors through surface functionalization of nanoparticles","authors":"Bartosz Mikolaj Gackowski ,&nbsp;Mohit Sharma ,&nbsp;Alexandru Valuta ,&nbsp;Thomas Ebel ,&nbsp;William Greenbank","doi":"10.1016/j.ecmx.2025.101260","DOIUrl":"10.1016/j.ecmx.2025.101260","url":null,"abstract":"<div><div>In this work, barium titanate nanoparticles were chemically functionalized to increase the energy density of polypropylene-based nanocomposite film capacitors. The nanoparticles were treated with: i) nitric acid or hydrogen peroxide to hydroxylate the surface of nanoparticles, ii) organic surface agents, i.e., silane, amine, phosphorous acid, dopamine hydrochloride, and maleic anhydride, iii) polypropylene coating, iv) grafting of polypropylene co-polymer with maleic anhydride. Nanocomposite dielectrics were manufactured by spin-coating a polypropylene gel with dispersed nanoparticles on a conductive substrate, which resulted in a thickness of the dielectric layers below 1 µm. Functional capacitor devices were fabricated by deposition of aluminium on top of the dielectric layers. The electrical testing data indicated that devices with functionalized nanoparticles showed an up to 47 % increase in capacitance, a<!--> <!-->36 % improvement in the dielectric constant, and a<!--> <!-->doubling of the breakdown voltage with respect to capacitors with unfunctionalized nanoparticles. Overall, the energy densities reached up to 5.2 J cm⁻³, which was four times higher than untreated counterparts. These data highlight the importance of chemical functionalization of nanoparticles for achieving high energy density of nanocomposite film capacitors and show the way forward to high-efficiency power electronics devices with reduced weight and volume.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"28 ","pages":"Article 101260"},"PeriodicalIF":7.6,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Life cycle cost assessment of PEM water electrolysis systems: a system dynamics–intuitionistic fuzzy bayesian network approach","authors":"Wenda Zhang,&nbsp;Tiejiang Yuan,&nbsp;Yue Teng","doi":"10.1016/j.ecmx.2025.101237","DOIUrl":"10.1016/j.ecmx.2025.101237","url":null,"abstract":"<div><div>Proton exchange membrane water electrolysis is a core technology for green hydrogen production, but its widespread adoption is hindered by a prohibitively high and uncertain life cycle cost. To address the dynamic complexity and multi-source uncertainties inherent in cost assessment, this paper proposes an integrated modeling framework that combines system dynamics with an intuitionistic fuzzy bayesian network. The system dynamics model captures the macro-level feedback loops driving long-term cost evolution, such as technological innovation, economy-of-scale effects, and other critical factors. To model and infer causal dependencies among uncertain variables that are challenging to specify precisely within the system dynamics model, the intuitionistic fuzzy bayesian network is incorporated, enabling quantification of relationships under conditions of incomplete data and cognitive fuzziness. Through comprehensive simulations, the framework forecasts the cost evolution trajectories. Results indicate a potential 77 % reduction in the unit power cost of a 1 MW system by 2060. Uncertainty analysis revealed that the initial prediction variance for the catalyst layer was approximately 20 %, significantly higher than the 6.5 % for the bipolar plate, highlighting a key investment risk. A comparative analysis demonstrates that the proposed framework achieves a superior forecast accuracy, with a mean absolute percentage error of 4.8 %. The proposed method provides a more accurate and robust decision support tool for long-term investment planning and policy formulation for hydrogen production through proton exchange membrane water electrolysis technology.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"28 ","pages":"Article 101237"},"PeriodicalIF":7.6,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An updated kinetic mechanism for aluminum gas-phase combustion in oxygen and steam environments","authors":"Yue Qiu ,&nbsp;Xue-Song Bai ,&nbsp;Elna J.K. Nilsson","doi":"10.1016/j.ecmx.2025.101238","DOIUrl":"10.1016/j.ecmx.2025.101238","url":null,"abstract":"<div><div>Aluminum (Al), as a carbon-free energy source, features favorable characteristics regarding its production, transportation, utilization, and recyclability. The combustion of single Al particles mainly occurs as a vapor-phase diffusion flame, wherein the gas-phase combustion kinetics plays an important role. However, the understanding of the kinetics is still limited and rate constants for the same reactions implemented in the mechanisms are quite different. Building on a previous review and analysis work of available Al gas-phase combustion mechanisms in the literature, this paper presents an updated selection of rate constants for the Al/O₂/H₂O system based on both experimental and theoretical studies from published literature. The performance of the proposed mechanism is evaluated against experimental data and other mechanisms using an in-house boundary layer resolved model to simulate the steady-state combustion stage of a liquid Al droplet. Distinct reaction pathways in different mechanisms are explored and discussed. Global sensitivity analysis is conducted to identify the important elementary reactions that affect the prediction of the flame structure. The proposed mechanism provides more consistent predictions of flame parameters under various conditions compared to existing mechanisms. With the attempt to unify existing mechanisms and combine latest experimental and theoretical studies on the rate constants, the proposed mechanism provides a reliable framework for Computational Fluid Dynamics (CFD) modelers to use in large-scale simulations. Further refinement of Al combustion kinetics necessitates additional experimental validation and quantum chemistry analysis.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"28 ","pages":"Article 101238"},"PeriodicalIF":7.6,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A blockchain-based P2P regional energy trading and credit mechanism","authors":"Yijie Ke ,&nbsp;Zhide Chen ,&nbsp;Chen Feng ,&nbsp;Meiling Xie ,&nbsp;Kexin Zhu ,&nbsp;Jincheng Su","doi":"10.1016/j.ecmx.2025.101193","DOIUrl":"10.1016/j.ecmx.2025.101193","url":null,"abstract":"<div><div>As the popularity of distributed photovoltaic (PV) power generation increases, the consumption pressure on the conventional grid also increases. At the same time, it also increases the scheduling complexity and the lack of fairness in peer-to-peer (P2P) energy trading. This study proposes a novel Regional Electricity Trading Framework (RETF) based on consortium blockchain technology to cope with the above problems. The framework uses the organizational structure of consortium blockchain to enable secure and transparent intra- and extra-regional trading within a microgrid architecture, thereby increasing order turnover. Its core innovation is the direct integration of credit scores (calculated from users’ historical market behavior) into the dynamic pricing mechanism. The combination of a user’s credit score and acceptable price determines the prioritization of trades, aiming to inject fairness into the system and enhance trading credibility. The mechanism combines with self-regulating price equilibrium coefficients to effectively promote fair price gaming and stability. Experimental results show that RETF increases trading volume and reduces trading uncertainty by increasing user default costs while enhancing profitability. RETF provides a viable solution for decentralized energy markets.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"28 ","pages":"Article 101193"},"PeriodicalIF":7.6,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cost-benefit and net zero impact analysis of PV-grid-battery systems for EV charging stations in Bangladesh","authors":"Munyem Ahammad Muyeed,&nbsp;Moslema Hoque Oeishee,&nbsp;Abu S.M. Mohsin","doi":"10.1016/j.ecmx.2025.101256","DOIUrl":"10.1016/j.ecmx.2025.101256","url":null,"abstract":"<div><div>The transition to sustainable energy solutions is critical for achieving net zero emissions, particularly in the transportation sector. This study presents a comprehensive cost-benefit and net-zero emission impact analysis of hybrid photovoltaic (PV)-grid-battery systems designed for electric vehicle (EV) charging stations in Bangladesh, which evaluates various configurations of PV systems, battery storage, and grid connectivity during the preliminary design phase, optimizing energy provision and system reliability based on demand load profiles reflecting anticipated EV usage patterns. The proposed system supports up to 54 EVs within 24 h, with a total demand load of 2800 kW. The study focuses on five locations—Dhaka, Sirajganj, Faridpur, Cumilla, and Habiganj—selected based on solar irradiance levels and urban density. Using the HOMER Pro database, the analysis identifies significant seasonal variations in solar radiation, with Sirajganj achieving a peak of 6.05 kWh/m²/day in April. Energy performance analysis across the five locations shows that generic flat-plate PV systems contribute nearly 100 % of the total annual energy production, with specific yields ranging from 67,882,490 kWh/yr in Cumilla to 75,474,534 kWh/yr in Sirajganj. The three different variant configurations for the EVCS were evaluated in order to determine the best scenario for efficiency, each being composed of PV generation, grid connectivity, and energy storage combinations. In Case 3, grid sales exceed purchases, with Dhaka reporting the highest grid sales at 39,025,459 kWh/yr. The renewable fraction stabilizes at around 90.5 % in Case 3 across all locations, demonstrating balanced integration of renewables. Simpler system configurations yield higher ROIs, with Case 1 in Cumilla achieving 171.8 %. The study recommends a grid-connected net metering system to optimize excess PV energy contributions. The proposed system can reduce energy costs by up to 30 % compared to grid-only solutions. This research underscores the role of PV-grid-battery systems in advancing Bangladesh towards a net-zero emissions future with a decrease of approximately 910,395.488 kg CO₂ per year, offering a scalable and economically feasible model for EV charging infrastructure. Deploying EV charging stations in Bangladesh presents challenges, including site selection based on population densities and travel patterns and integrating PV systems into EVCS networks without proper sizing guidelines. The intermittent nature of solar energy necessitates hybrid energy management solutions, highlighting the need for strategic planning to ensure reliable and sustainable EVCS operations.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"28 ","pages":"Article 101256"},"PeriodicalIF":7.6,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145045752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}