Energy Conversion and Management-X最新文献_第2页

A new methodology to easy integrate complementarity criteria in the resource assessment process for hybrid power plants: Offshore wind and floating PV

IF 7.1 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2025-02-21 DOI: 10.1016/j.ecmx.2025.100938

Laura Frías-Paredes , Martín Gastón-Romeo

The maturity of technologies of energy generation from renewable sources produces tense an increasing interest on hybrid power plant implementation. The combination of different resources, as wind and solar, introduces concepts as complementarity that must be taken into account when suitability of emplacements is made. This work presents a methodology to evaluate a geographic area under the perspective of installing hybrid wind and PV power plants. Therefore, it proposes a way to evaluate the complementarity among both resources that would avoid overestimation due to time delays and it also would offer a holistic procedure to identify the most suitable locations to host one of these hybrid power plants. The methodology is illustrated by evaluating the Off-shore Spanish area to install wind and floating PV plants and is flexible to adapt the evaluation according to dimension of each technology in the future plants. It is shown how the complementarity criteria as input in the site selection process improves the ordered of emplacements obtained when only resource amount is taken into account. The methodology can be used to identify more suitable areas in the initial stages of promoting hybrid power plants. Data from ERA5 and CAMS are used to analyze long term behavior of wind and solar resources.

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引用次数: 0

The electrical performance of a single-axis sun tracking agrivoltaic system inside a polytunnel greenhouse

IF 7.1 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2025-02-21 DOI: 10.1016/j.ecmx.2025.100940

E. Magadley , M. Matar , R. Kabha , R. Korabi , A. Hajyahya , A. Abasi , H. Barhum , M. Attrash , R. Saabne , S. Asaly , I. Yehia

This study proposes a novel agrivoltaic tracking system integrated inside rather than above the greenhouse. The innovative single axis 6 kWp photovoltaic (PV) system integrated within a greenhouse is evaluated by analysing the influence of seasonal variations and environmental factors on energy output and performance from May to October. The system achieved a maximum output of 32 kWh per day in June, corresponding with a yield of 5.5 kWh/kWp, comparable to standard outdoor PV systems under similar Mediterranean conditions. However, performance inside the greenhouse was limited by global horizontal irradiance reductions due to greenhouse covers and seasonal dust accumulation. The tracking system demonstrated a 15–20% increase in output compared to a fixed system inside the greenhouse, a reduced effectiveness by structural and environmental limitations inside the greenhouse. Capacity factors were observed to be lower inside the greenhouse (0.18–0.19) compared to outdoor systems (0.20–0.24), reflecting challenges such as partial shading and diffuse irradiance. The performance ratio for the tracking system in July was relatively low (0.65) due to the fact it was inside the greenhouse. This study underscores the potential of agrivoltaic systems inside greenhouses to generate energy effectively while addressing the unique challenges posed by the greenhouse environment.

{"title":"The electrical performance of a single-axis sun tracking agrivoltaic system inside a polytunnel greenhouse","authors":"E. Magadley , M. Matar , R. Kabha , R. Korabi , A. Hajyahya , A. Abasi , H. Barhum , M. Attrash , R. Saabne , S. Asaly , I. Yehia","doi":"10.1016/j.ecmx.2025.100940","DOIUrl":"10.1016/j.ecmx.2025.100940","url":null,"abstract":"<div><div>This study proposes a novel agrivoltaic tracking system integrated inside rather than above the greenhouse. The innovative single axis 6 kWp photovoltaic (PV) system integrated within a greenhouse is evaluated by analysing the influence of seasonal variations and environmental factors on energy output and performance from May to October. The system achieved a maximum output of 32 kWh per day in June, corresponding with a yield of 5.5 kWh/kWp, comparable to standard outdoor PV systems under similar Mediterranean conditions. However, performance inside the greenhouse was limited by global horizontal irradiance reductions due to greenhouse covers and seasonal dust accumulation. The tracking system demonstrated a 15–20% increase in output compared to a fixed system inside the greenhouse, a reduced effectiveness by structural and environmental limitations inside the greenhouse. Capacity factors were observed to be lower inside the greenhouse (0.18–0.19) compared to outdoor systems (0.20–0.24), reflecting challenges such as partial shading and diffuse irradiance. The performance ratio for the tracking system in July was relatively low (0.65) due to the fact it was inside the greenhouse. This study underscores the potential of agrivoltaic systems inside greenhouses to generate energy effectively while addressing the unique challenges posed by the greenhouse environment.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"26 ","pages":"Article 100940"},"PeriodicalIF":7.1,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143480238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficient energy management and temperature control of a high-tech greenhouse using an improved data-driven model predictive control

IF 7.1 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2025-02-20 DOI: 10.1016/j.ecmx.2025.100939

Farhat Mahmood, Rajesh Govindan, Tareq Al-Ansari

Greenhouses in arid climates require advanced control systems to maintain the microclimate and reduce energy utilization, ensuring economic viability. To address these challenges, model predictive control is an effective method that forecasts the system’s future state and adjusts control variables accordingly. However, deterministic model predictive control does not account for system uncertainties, leading to performance degradation. Therefore, this study proposes an improved model predictive control framework that utilizes an artificial neural network developed from historical greenhouse data. This method uses a double layer approach, where the primary controller provides the nominal trajectory, and an ancillary controller adjusts for uncertainties. The double layer predictive control framework was assessed under varying conditions to evaluate the performance in terms of temperature control and energy utilization. Results illustrated that, despite system uncertainties, the double layer model predictive control framework outperformed the existing greenhouse climate system, deterministic and robust model predictive control approaches. It demonstrated mean absolute errors of 0.09 °C in winter and 0.10 °C in summer, with corresponding root mean squared errors of 0.19 °C and 0.36 °C, respectively. Moreover, the double layer model predictive control method reduced energy utilization by 20.01 % in winter and 13.34 % in summer compared to the existing control system over a 4 d simulation period.

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引用次数: 0

Multi-objective combinatorial methodology for nuclear reactor site assessment: A case study for the United States

IF 7.1 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2025-02-20 DOI: 10.1016/j.ecmx.2025.100923

Omer Erdem, Kevin Daley, Gabrielle Hoelzle, Majdi I. Radaideh

As clean energy demand grows to meet sustainability and net-zero goals, nuclear energy emerges as a reliable option. However, high capital costs remain a challenge for nuclear power plants (NPP), where repurposing coal power plant sites (CPP) with existing infrastructure is one way to reduce these costs. Additionally, Brownfield sites — previously developed or underutilized lands often impacted by industrial activity — present another compelling alternative. This study introduces a novel multi-objective optimization methodology, leveraging combinatorial search to evaluate over 30,000 potential NPP sites in the United States. Our approach addresses gaps in the current practice of assigning pre-determined weights to each site attribute that could lead to bias in the ranking. Each site is assigned a performance-based score, derived from a detailed combinatorial analysis of its site attributes. The methodology generates a comprehensive database comprising site locations (inputs), attributes (outputs), site score (outputs), and the contribution of each attribute to the site score. We then use this database to train a neural network model, enabling rapid predictions of nuclear siting suitability across any location in the United States. Our findings highlight that CPP sites are highly competitive for nuclear development, but some Brownfield sites are able to compete with them. Notably, four CPP sites in Ohio, North Carolina, and New Hampshire, and two Brownfield sites in Florida and California rank among the most promising locations. These results underscore the potential of integrating machine learning and optimization techniques to transform nuclear siting, paving the way for a cost-effective and sustainable energy future.

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引用次数: 0

Spatiotemporal Forecasting of Solar and Wind Energy Production: A Robust Deep Learning Model with Attention Framework

IF 7.1 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2025-02-20 DOI: 10.1016/j.ecmx.2025.100919

Md. Shadman Abid , Razzaqul Ahshan , Mohammed Al-Abri , Rashid Al Abri

The variability in the spatiotemporal distribution of power generation is a significant challenge for accurately predicting renewable energy production patterns. Furthermore, numerous forms of unforeseen data contamination degrade the precision of forecasts since superfluous data points adversely affect the regression model. In this context, a novel robust deep learning model, termed the Convolutional Neural Network-Bidirectional Long Short-Term Memory model with spatiotemporal attention mechanism (CNN-BiLSTM-STA), is developed in this study. The suggested model integrates the feature extraction expertise of CNNs with the sequence modeling proficiency of BiLSTM networks to capture spatial linkages and temporal interdependence adeptly. Moreover, the integrated spatiotemporal attention mechanism selectively focuses on significant spatial regions and time steps to enhance the prediction of spatiotemporal sequences of time-resolved grid data. The proposed architecture allows plant proprietors and system operators to obtain accurate predictions across extensive spatiotemporal patterns by eliminating the necessity for individual model fitting for each site/horizon or an additional data preprocessing phase before training. In addition, the Correntropy-based training criterion is employed to ensure the robustness of the recommended method against various types of data contamination, including data incompletion, Gaussian noises, outliers, and a mixed combination of disturbances. Furthermore, the Partial Reinforcement Optimization technique is applied to optimize the hyperparameters of the proposed model. The suggested framework incorporates numerous photovoltaic installations in Arizona and wind power installations in Texas to provide concurrent forecasts for multiple periods. The efficacy of the suggested forecasting model is evaluated by comparing it with three state-of-the-art methods. Numerical findings demonstrate that the proposed model surpasses other methods by successfully integrating spatial and temporal characteristics.

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引用次数: 0

Techno-economic profitability of grid-scale battery storage allocation in European wholesale markets under a novel operation optimization strategy

IF 7.1 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2025-02-19 DOI: 10.1016/j.ecmx.2025.100936

Masoume Shabani , Mohadeseh Shabani , Jinyue Yan

This study evaluates the techno-economic benefits of grid-scale battery storage allocation across 25 European countries, each with distinct wholesale price variation patterns. The evaluation is based on a novel optimization-based operation strategy, which adapts to the volatile nature of electricity markets. By making smart decisions on key operational factors, the strategy optimizes battery scheduling in the day-ahead market, maximizing profits while minimizing degradation and extending battery lifespan. Additionally, a behavior-aware battery management strategy is developed to accurately simulate real-world performance and degradation. The study identifies the most attractive European markets for grid-scale battery storage by evaluating multiple key economic metrics, including annual profit per unit of energy installed, battery lifetime, total revenue, net present value, return on investment, and payback period.

The findings show that, under the proposed strategy, battery storage integration generates significant positive profits in 23 European countries. Romania, Latvia, Lithuania, and Estonia emerge as top performers, offering high profitability, short payback periods, and long-term financial sustainability. In contrast, Spain, Portugal, and Norway are currently unprofitable, though sensitivity analysis suggests that a 75 % reduction in battery costs could make these markets viable for investment.

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引用次数: 0

Production of bioethanol from citrus peel waste: A techno – economic feasibility study

IF 7.1 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2025-02-19 DOI: 10.1016/j.ecmx.2025.100916

Moses Kayanda Kiteto , Beryl Minayo Vidija , Cleophas Achisa Mecha

The quest for sustainable and clean energy solutions has sparked considerable interest in alternative energy sources to mitigate the destructive impacts of climate change and reduce over dependency on fossils fuels. Among these, biofuels, particularly bioethanol, have shown great potential based on their renewable nature, non – toxic, biodegradability and low carbon footprint. Whereas there are various reported studies on bioethanol production for organic waste, comprehensive studies targeting the technical and economic aspects are lacking. Hence, this study explores the techno – economic feasibility of the production of bioethanol from citrus peel waste using a multifaceted approach that addresses the dual challenge of energy generation and waste management. The study provides an elaborative analysis of the composition of citrus peels; technical aspects of bioethanol production and evaluated relevant unit operations. The specific reactions that occur and the optimum conditions for the processes are determined. The economic viability of the process, considering a daily processing capacity of 450 metric tons of citrus peel waste is assessed. The profitability analysis indicates a Return of Return on investment (ROR) of 23.21 %, Discounted Cash Flow Rate of Return (DCFROR) of 25.15 %, net present worth of $ 84.94 million and payout period of 2.96 years. The findings demonstrate the technological and economic feasibility of producing bioethanol from citrus peel waste, highlighting its potential as a sustainable bioenergy solution with attractive environmental, energy and economic benefits.

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引用次数: 0

Pyrolysis and kinetic analysis of marine (Isochrysis sp.) and freshwater (Monoraphidium c.) microalgae

IF 7.1 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2025-02-18 DOI: 10.1016/j.ecmx.2025.100904

Noridah B. Osman , Umi Syahirah Binti Mohd Amin , David Onoja Patrick , Nurul Asyikin Binti Badir Noon Zaman , Syazmi Zul Arif Hakimi Saadon , Suzana Yusup , Liyana Yahya

Marine and freshwater microalgae grow in two different ecosystems, which influence their properties thus requires attention prior to determining its application. This paper has successfully disclosed the thermal, chemical, and physical properties of two types of microalgae on carbon dioxide (CO₂) fixation and underwent pyrolysis process. Slow pyrolysis process for marine and freshwater microalgae (Isochrysis sp. and Monoraphidium c.) was performed in the fixed bed pyrolysis reactor and TGA (thermogravimetric analyzer) to determine the product yield and study their thermal decomposition profile. The pyrolysis was completed at various temperatures (400, 450, 500, and 550 °C) at a heating rate of 15°Cmin⁻¹ and nitrogen flow rate of 200 ml min⁻¹. Pyrolysis in TGA analyzer ran from 27 to 800 °C at three heating rates (10, 20, and 40 °Cmin⁻¹). For chemical composition, Fourier-transform Infrared (FTIR) analysis was performed on both microalgae samples. The highest yield (up to 33.9 %) of bio-oil was obtained from Isochrysis sp. for all temperatures while the highest average yield (65.78 %) of biochar was collected from Monoraphidium c. species. From TGA pyrolysis, the major decomposition occurred between 200–400 °C for Monoraphidium c. species. On the other hand, the decomposition profile of Isochrysis sp. was slightly slower, which may be due to the differences in lipid composition (FTIR peak 2929 cm⁻¹). The activation energy of all tests is lower (33.6–40.3 kJ mol⁻¹) compared to several other biomasses. Marine species fixed with CO₂ showed promising results even without addition of catalyst and no additional cost needed.

{"title":"Pyrolysis and kinetic analysis of marine (Isochrysis sp.) and freshwater (Monoraphidium c.) microalgae","authors":"Noridah B. Osman , Umi Syahirah Binti Mohd Amin , David Onoja Patrick , Nurul Asyikin Binti Badir Noon Zaman , Syazmi Zul Arif Hakimi Saadon , Suzana Yusup , Liyana Yahya","doi":"10.1016/j.ecmx.2025.100904","DOIUrl":"10.1016/j.ecmx.2025.100904","url":null,"abstract":"<div><div>Marine and freshwater microalgae grow in two different ecosystems, which influence their properties thus requires attention prior to determining its application. This paper has successfully disclosed the thermal, chemical, and physical properties of two types of microalgae on carbon dioxide (CO<sub>2</sub>) fixation and underwent pyrolysis process. Slow pyrolysis process for marine and freshwater microalgae (Isochrysis sp. and Monoraphidium c.) was performed in the fixed bed pyrolysis reactor and TGA (thermogravimetric analyzer) to determine the product yield and study their thermal decomposition profile. The pyrolysis was completed at various temperatures (400, 450, 500, and 550 °C) at a heating rate of 15°Cmin<sup>−1</sup> and nitrogen flow rate of 200 ml min<sup>−1</sup>. Pyrolysis in TGA analyzer ran from 27 to 800 °C at three heating rates (10, 20, and 40 °Cmin<sup>−1</sup>). For chemical composition, Fourier-transform Infrared (FTIR) analysis was performed on both microalgae samples. The highest yield (up to 33.9 %) of bio-oil was obtained from Isochrysis sp. for all temperatures while the highest average yield (65.78 %) of biochar was collected from Monoraphidium c. species. From TGA pyrolysis, the major decomposition occurred between 200–400 °C for Monoraphidium c. species. On the other hand, the decomposition profile of Isochrysis sp. was slightly slower, which may be due to the differences in lipid composition (FTIR peak 2929 cm<sup>−1</sup>). The activation energy of all tests is lower (33.6–40.3 kJ mol<sup>−1</sup>) compared to several other biomasses. Marine species fixed with CO<sub>2</sub> showed promising results even without addition of catalyst and no additional cost needed.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"26 ","pages":"Article 100904"},"PeriodicalIF":7.1,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Transesterification and esterification for biodiesel production: A comprehensive review of catalysts and palm oil feedstocks

IF 7.1 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2025-02-18 DOI: 10.1016/j.ecmx.2025.100931

Heba Huthaifa Naseef , Reem Hani Tulaimat

This review presents a comprehensive and critical evaluation of biodiesel production, emphasizing the synergistic integration of feedstock optimization and catalytic advancements to achieve enhanced efficiency, sustainability, and economic viability. The study systematically analyzes core production methods, including transesterification, direct esterification, and two-step processes, while evaluating the impact of crucial parameters such as alcohol-to-oil molar ratio, catalyst type and concentration, reaction temperature, and reaction time. A thorough assessment of catalytic systems is provided, encompassing homogeneous (alkaline and acidic) and heterogeneous catalysts, with special attention to advanced categories such as bifunctional, biological, and nanocatalysts. The review also examines the transformative potential of palm oil-derived feedstocks, including crude palm oil, kernel palm oil, refined palm oil, palm oil sludge, and used cooking palm oil, critically assessing their viability for biodiesel production. Additionally, the review includes an in-depth Life Cycle Assessment (LCA) of palm oil biodiesel, evaluating its environmental impact and long-term sustainability. By addressing significant research gaps, particularly the linkage between feedstock properties and catalytic performance, this work offers a cohesive framework for advancing biodiesel technology. The findings underscore the potential of customized catalytic systems and diverse feedstock utilization in driving sustainable, economically viable biofuel production. As such, this review serves as an essential resource for researchers, policymakers, and industry leaders committed to solving global energy and environmental challenges.

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引用次数: 0

Optimizing concentrated photovoltaic module efficiency using Nanofluid-Based cooling

IF 7.1 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2025-02-18 DOI: 10.1016/j.ecmx.2025.100928

Mohamed Helmy Abdel-Aziz , Mohamed Shafick Zoromba , Alaa Attar , M. Bassyouni , N. Almutlaq , O.A. Al-Qabandi , Yasser Elhenawy

Photovoltaic technology offers a promising and environmentally sustainable solution to global energy demands. However, its efficiency is often compromised by elevated temperatures caused by intense solar radiation. Effective cooling strategies are essential to enhance electricity generation and prolong the lifespan of photovoltaic cells. This study explored the enhancement of electricity production in concentrated photovoltaic systems through the use of Al₂O₃/water nanofluid as a cooling medium. An experimental analysis evaluated the thermal and electrical efficiencies of cooled versus uncooled concentrated photovoltaic panels. Aluminum oxide nanoparticles were utilized in various loadings ranging from 0.2 wt% to 0.5 wt% at a flow rate of 1.25 L/min to assess their impact on concentrated photovoltaic performance. The results demonstrated that 0.5 wt% Al₂O₃/water nanofluid achieved the most significant reduction in PV surface temperature lowering it by 55 % compared to an uncooled panel. Under peak solar intensity, the electrical output of the concentrated photovoltaic panels was recorded as 43.22 Wh for the uncooled panel. In contrast, the cooled panels produced 48.87 Wh with water, 51.01 Wh with 0.2 wt% Al₂O₃/water nanofluid, and 54.30 Wh with 0.5 wt% Al₂O₃/water nanofluid. For the 0.5 wt% Al₂O₃ nanofluid, the electrical and thermal efficiencies were measured at 34.80 % and 64.42 %, respectively.

{"title":"Optimizing concentrated photovoltaic module efficiency using Nanofluid-Based cooling","authors":"Mohamed Helmy Abdel-Aziz , Mohamed Shafick Zoromba , Alaa Attar , M. Bassyouni , N. Almutlaq , O.A. Al-Qabandi , Yasser Elhenawy","doi":"10.1016/j.ecmx.2025.100928","DOIUrl":"10.1016/j.ecmx.2025.100928","url":null,"abstract":"<div><div>Photovoltaic technology offers a promising and environmentally sustainable solution to global energy demands. However, its efficiency is often compromised by elevated temperatures caused by intense solar radiation. Effective cooling strategies are essential to enhance electricity generation and prolong the lifespan of photovoltaic cells. This study explored the enhancement of electricity production in concentrated photovoltaic systems through the use of Al<sub>2</sub>O<sub>3</sub>/water nanofluid as a cooling medium. An experimental analysis evaluated the thermal and electrical efficiencies of cooled versus uncooled concentrated photovoltaic panels. Aluminum oxide nanoparticles were utilized in various loadings ranging from 0.2 wt% to 0.5 wt% at a flow rate of 1.25 L/min to assess their impact on concentrated photovoltaic performance. The results demonstrated that 0.5 wt% Al<sub>2</sub>O<sub>3</sub>/water nanofluid achieved the most significant reduction in PV surface temperature lowering it by 55 % compared to an uncooled panel. Under peak solar intensity, the electrical output of the concentrated photovoltaic panels was recorded as 43.22 Wh for the uncooled panel. In contrast, the cooled panels produced 48.87 Wh with water, 51.01 Wh with 0.2 wt% Al<sub>2</sub>O<sub>3</sub>/water nanofluid, and 54.30 Wh with 0.5 wt% Al<sub>2</sub>O<sub>3</sub>/water nanofluid. For the 0.5 wt% Al<sub>2</sub>O<sub>3</sub> nanofluid, the electrical and thermal efficiencies were measured at 34.80 % and 64.42 %, respectively.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"26 ","pages":"Article 100928"},"PeriodicalIF":7.1,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143454480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0