Solar Energy Advances最新文献

{"title":"Azimuth orientation effects on a fixed pentagonal-pyramid solar still in tropical conditions Nagpur, India","authors":"Kapil T. Patil ,&nbsp;Aniruddha M. Nikalje ,&nbsp;Nikhil Aniruddha Bhave ,&nbsp;Sushant S. Satputaley ,&nbsp;P. Dinesha ,&nbsp;Sooraj Mohan","doi":"10.1016/j.seja.2026.100131","DOIUrl":"10.1016/j.seja.2026.100131","url":null,"abstract":"<div><div>Solar distillation offers a sustainable solution for potable water production, yet the influence of geometric alignment on multi-face systems remains a critical but often overlooked design parameter. This work experimentally isolates the influence of azimuth orientation on the thermal and distillation performance of a fixed pentagonal pyramid solar still under the tropical summer climate of Nagpur, India. Four identical units, constructed with galvanized iron basins, internal matte black coating, thirty millimeters of polyurethane insulation, and four-millimeter-thick clear float glass, were tested simultaneously with a constant basin water depth of two centimeters. The systems were oriented toward the East (90°), West (270°), South-East (135°), and South (180°) to examine azimuth-dependent solar interception over a campaign of at least three clear sky days per configuration. The experimental results, analyzed using a validated energy balance model, determined that the south-facing orientation achieved the highest daily freshwater production of 3.6 to 3.7 <strong>L/m²·day⁻¹</strong> and a thermal efficiency of 38 to 40%. The South-East orientation followed with a yield of 3.3 to 3.4 <strong>L/m²·day⁻¹</strong>, representing a performance decrease of approximately 8 to 9% compared to the optimal south orientation. Conversely, the east-facing unit produced 2.7 to 2.9 <strong>L/m²·day⁻¹</strong>, while the west-facing unit yielded 2.6 to 2.7 <strong>L/m²·day⁻¹</strong>, both showing time-shifted productivity peaks and lower cumulative output relative to the south-aligned configuration. These findings validate azimuth alignment as a zero-cost optimization parameter, establishing south orientation as the superior strategy and South-East as a viable alternative for fixed desalination installations.</div></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"6 ","pages":"Article 100131"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397383","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":"Techno-economic evaluation of PVT-sourced heat pump systems: can solar compete with air and ground in cold climates?","authors":"Francisco Beltrán,&nbsp;Nelson Sommerfeldt","doi":"10.1016/j.seja.2026.100133","DOIUrl":"10.1016/j.seja.2026.100133","url":null,"abstract":"<div><div>There are various ways to integrate solar photovoltaic-thermal (PVT) collectors with heat pumps, but using the PVT array as the sole source offers unique advantages: eliminating noise from air-source units and avoiding the cost and land use of boreholes. This work investigates whether PVT collectors can operate as the sole source for a brine-water heat pump in cold-climate multi-family houses (MFH), and how absorber design and system sizing influence techno-economic performance. Five unglazed PVT absorbers with different design characteristics, are simulated in a validated TRNSYS model of a 2000 m² Swedish MFH. Collector area is varied from 1.1 to 4.5 m²/kWₜₕ of nominal heat pump capacity, equivalent to a rooftop coverage of 25 to 100 %, while brine flow rate is varied from 24 to 96 l/h-m². Finned designs achieve the highest seasonal performance factor (SPF) of 2.4 to 2.6 at moderate rooftop coverage (2.3–3.4 m²/kWₜₕ), with 15–20 % auxiliary heating share, while unfinned concepts converge at an SPF of approximately 2.2 and 25–35 % auxiliary heating share at full rooftop coverage (4.5 m²/kWₜₕ). Arrays below ∼2 m²/kWₜₕ are non-viable (SPF &lt; 1.8; 40–70 % auxiliary heating). The economic optimum occurs at <em>an SPF</em> of around 2.2, not at the highest efficiency, yielding two optimal pathways: fin-enhanced absorbers at ∼2.3–3.4 m²/kWₜₕ, or low-cost polymeric absorbers at 4.5 m²/kWₜₕ. The best PVT-only configurations achieve cost parity with air source heat pumps (±5 %) and remain ∼10–15 % below district heating. They remain more expensive than GSHP systems, but avoid both outdoor noise and drilling requirements.</div></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"6 ","pages":"Article 100133"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147538891","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":"Ultrashort-term prediction of photovoltaic power based on a bidirectional LSTM model","authors":"Zhaoyan He","doi":"10.1016/j.seja.2026.100137","DOIUrl":"10.1016/j.seja.2026.100137","url":null,"abstract":"<div><div>The rapid increase in the use of solar PV, a climate-dependent energy source, presents a challenge for the management of power grids. This intermittency makes the development of reliable generation forecasting models critical for maintaining system balance and operational integrity. In this work, an improved long short-term-memory (LSTM) network model called Bi-LSTM, which consists of two concurrent LSTM layers, is proposed to predict subseries with different minute–hour–day intervals. The bidirectional nature of the Bi-LSTM allows it to integrate information from preceding and succeeding points in a sequence. This comprehensive context awareness underpins the success of the model in applications such as natural language processing, audio recognition, and time series analysis. Finally, a comparative study with the LSTM, MLP, SVR, Bi-LSTM, CNN, GRU, KNN and BPNN models is performed by using an actual dataset collected from the National Renewable Energy Laboratory (NREL) in the United States. The simulation results show that the proposed prediction model outperforms the other 7 prediction models with different statistical matrix methods regarding PV power forecasting in every time interval and season. According to the R² statistical metric results, the Bi-LSTM models exhibit high consistency for the training set overall, with scores approaching 0.99.</div></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"6 ","pages":"Article 100137"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147656562","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 Review of Machine Learning for the Optimization and Control of Nanoparticle-Enhanced Thermal Energy Storage in Solar Applications","authors":"Ravin Sehrawat,&nbsp;Sumit Tiwari,&nbsp;Ravinder Kumar Sahdev,&nbsp;Adarsh Kumar Pandey,&nbsp;Rohan Sharma,&nbsp;Ajay Kumar,&nbsp;Subraya Krishna Bhat","doi":"10.1016/j.seja.2026.100145","DOIUrl":"10.1016/j.seja.2026.100145","url":null,"abstract":"<div><div>Thermal energy storage (TES) plays a vital role in solar energy systems by mitigating intermittency, extending operating hours, and improving dispatchability. Conventional TES materials, particularly phase change materials (PCMs), suffer from low thermal conductivity, subcooling, slow charging-discharging rates, and complex design challenges. To address these limitations, recent research has increasingly combined nanoparticles with TES materials and machine learning (ML) techniques to enhance thermophysical properties, predict system behavior, and enable intelligent operation. This review critically examines the role of ML in optimization and control of nanoparticle-enhanced TES systems for solar applications. A PRISMA-compliant methodology was used to systematically screen and analyze relevant literature. The reviewed studies were classified according to TES type, solar application, nanoparticle system, ML algorithm, input-output variables, and performance metrics. Results show that artificial neural networks (ANN), support vector machines (SVM), Gaussian process regression (GPR), deep neural networks (DNN), long short-term memory (LSTM) networks, XGBoost, and multi-objective optimization methods are widely used for property prediction, material optimization, performance forecasting, and operational control. Reported accuracies include ANN prediction of nano-enhanced PCM thermal conductivity with R² up to 0.96, SVM-based TES performance modeling with R² values of 0.990 (training) and 0.950 (testing), GPR correlations up to 0.9998 for hybrid nanofluid properties, and ANN-based adaptive control reducing exergy destruction by 60%. Despite these advances, trade-offs involving latent heat capacity, viscosity, cost, and long-term stability remain significant. This review highlights the gap between offline optimization and real-time intelligent TES operation and proposes a roadmap toward robust and deployment-ready smart solar TES systems.</div></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"6 ","pages":"Article 100145"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148729345","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}

{"title":"Enhancing light scattering in low-temperature PDINO cathode interlayer of organic solar cells using plasmonic copper nanorods","authors":"Thapelo Ephraim Seimela,&nbsp;Mohammed SG Hamed,&nbsp;Mmantsae Diale","doi":"10.1016/j.seja.2025.100127","DOIUrl":"10.1016/j.seja.2025.100127","url":null,"abstract":"<div><div>Organic solar cells (OSCs) are a potential alternative to photovoltaic devices due to affordability. However, the power conversion efficiency (PCE) of OSCs still suffers due to charge recombination, leading to limitations in their commercialisation. The application of cathode interlayers in OSCs has garnered much interest in renewable energy due to their low-temperature fabrication. In this study, various concentrations of colloidal copper nanorods (CuNRs) have been employed to enhance light scattering in perylene diimides functionalized with amino oxide (PDINO) cathode interlayer. The 56.13 nm long CuNRs have increased the absorbance of PDINO, showing enhancement in localised surface plasmonic resonance (LSPR) observed at ∼525 nm. Due to the LSPR, CuNRs have significantly improved the PCE of ITO/PEDOT:PSS/P3HT:PCBM/PDINO:CuNRs/Ag device by 36.28% compared to the pristine device, indicating a simple and low temperature method of fabricating efficient OSCs.</div></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"6 ","pages":"Article 100127"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145927313","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":"Automated hybrid cooling of photovoltaic panels using water pump, ultrasonic humidifier, and passive fins: design, field evaluation, and techno-economic analysis","authors":"Md. Rafayet Bin Ali ,&nbsp;Tammem Hasan ,&nbsp;Mohammad Rofiqul Islam ,&nbsp;Hasan Muhommod Robin","doi":"10.1016/j.seja.2025.100126","DOIUrl":"10.1016/j.seja.2025.100126","url":null,"abstract":"<div><div>Photovoltaic (PV) systems often suffer from performance degradation under elevated temperatures, particularly in high-irradiance, water-scarce environments. Conventional cooling systems often overuse water, consume high auxiliary energy, or lack automation, limiting scalability. To overcome this, an automated hybrid system combining passive fins, active water flow, and ultrasonic humidification was developed and tested. The system features a microcontroller-based control unit that triggers staged cooling responses at defined temperature thresholds, minimizing operational resource input. Field trials were conducted under real outdoor conditions in Rajshahi, Bangladesh. The experimental results revealed average panel temperature reductions of 8°C, with peak reductions reaching 13 °C. Electrical conversion efficiency improved from 13.35% to 15.60%, corresponding to a 16.85 % relative gain, while power output increased by 15.9%. The system achieved a net daily energy gain of 0.0469 kWh with minimal auxiliary load (0.0075 kWh/day), and water consumption was limited to 40 L/day. The techno-economic assessment yielded a levelized cost of electricity of 0.052 USD/kWh for the cooled system. The analysis further indicated a payback period of roughly 18 years for the cooling investment, with a corresponding net additional energy yield of 357.7 kWh over the system's operational life. Theoretical scaling to a 68 MW facility suggests a lifetime output increase of 0.298 TWh, equivalent to powering approximately 24,800 households annually. These findings establish the proposed system as a resource-efficient, scalable, and climate-adaptive solution for enhancing PV performance in thermally stressed environments, supporting broader deployment of solar technologies in challenging climatic contexts.</div></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"6 ","pages":"Article 100126"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145842807","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":"Make every kilowatt count: Modeling solar power integration with thermal storage and heating electrification","authors":"Ueli Schilt ,&nbsp;Somesh Vijayananda ,&nbsp;Sarah Schneeberger ,&nbsp;Santhosh Iyyakkunnel ,&nbsp;Pascal Marc Vecsei ,&nbsp;Philipp Schuetz","doi":"10.1016/j.seja.2026.100135","DOIUrl":"10.1016/j.seja.2026.100135","url":null,"abstract":"<div><div>Solar photovoltaic (PV) power is expected to supply a large share of renewable electricity in future energy systems. However, scaling up solar PV in isolation is insufficient to achieve net-zero targets due to challenges such as supply variability, demand-supply mismatch, and grid constraints. Additional measures like heating electrification, storage, flexibility, and local energy management are needed. While most studies either focus on individual case studies or aggregate the national energy system into a single entity, this work combines municipality-level resolution with a nationwide assessment. Using an hourly multi-energy system model, we simulate the energy systems of 2131 Swiss municipalities to assess the impact of solar PV expansion with and without complementary measures. Alongside PV expansion, we study the effects of replacing 50% of fossil-based heating with heat pumps (HP) and implementing thermal energy storage (TES) sized up to 20% of annual heat demand. At the national scale, emissions decrease by 40%, and the renewable share increases from 43% to 66%. The largest improvements result from replacing fossil heaters with HPs, which lower emissions and absorb additional PV generation. TES further increases renewable utilization by shifting HP demand to periods of high PV yield. At the municipal scale, the impact of each measure depends strongly on existing PV capacity and demand profiles. In municipalities with high PV implementation, HP and TES deliver larger benefits than further PV expansion alone. The findings show that PV expansion must be combined with system integration measures to achieve substantial emission reductions and higher renewable supply.</div></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"6 ","pages":"Article 100135"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147656561","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":"GHI-based PV yield assessment in high-altitude Andean sites: workflow performance and systematic limitations of irradiance decomposition models","authors":"Miriam Manrique Medina,&nbsp;Rubén Ledesma,&nbsp;Nicolás Rivera-Lera,&nbsp;Manoel H. Oliveira Pedrosa Filho,&nbsp;Germán Salazar","doi":"10.1016/j.seja.2026.100148","DOIUrl":"10.1016/j.seja.2026.100148","url":null,"abstract":"<div><div>This study develops and evaluates a practical workflow for estimating annual PV energy yield in remote, data-scarce Andean locations, and tests it at two climatically contrasting sites in southern Peru: Cota Cota (4240 m a.s.l.) and Pampas de Majes (1498 m a.s.l.). Three years of local irradiance and temperature measurements were combined with ERA5 reanalysis, using machine learning to correct systematic biases and generate a 25-year hourly climatology, from which irradiance components and PV energy yield were estimated across the full range of tilt and azimuth configurations. Bias correction performed well at both sites, and optimal annual yields reached approximately 1042 kWh per panel at Majes and 1018 kWh at Cota Cota, with low sensitivity to small deviations from the ideal orientation. The analysis also revealed a systematic, altitude-dependent divergence between two independent estimates of the diffuse fraction: at Cota Cota, the Engerer2 decomposition and the satellite-based Solargis product differ by over 25 percentage points, a gap considerably smaller at Majes. As both are model-based estimates and no in-situ component measurements were available, the true bias cannot be resolved from this comparison, and substituting the clear-sky model did not reduce the divergence. These findings highlight both the value and the current limitations of the workflow, and underscore the need for in-situ component measurements to validate and locally calibrate irradiance decomposition models.</div></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"6 ","pages":"Article 100148"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148934973","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}

{"title":"Experimental investigation of PV Panel using cupric oxide nanofluid and aluminum fin cooling techniques in Kalaburagi’s hot and dry climate","authors":"Md Moyeed Abrar,&nbsp;Sangamesh G. Sakri","doi":"10.1016/j.seja.2026.100144","DOIUrl":"10.1016/j.seja.2026.100144","url":null,"abstract":"<div><div>Temperature and solar radiation have a noteworthy effect on the performance of the Photovoltaic (PV) panel. In this experimental study, two thermal management approaches were evaluated under identical operating conditions. One PV panel was cooled using circulating cupric oxide (CuO) nanofluid through a heat collector integrated with a helical heat exchanger, while the second panel employed passive aluminum fin cooling. The two cooling systems were examined based on their temperature behavior and electrical efficiency. The CuO nanofluid cooled PV panel operated at an average temperature of 32.5 °C, lower than the 44.7 °C recorded for the aluminium finned PV panel. Consequently, the CuO nanofluid cooled panel exhibited a higher gross average power output of 91 W compared to 85 W for the aluminum finned panel. Similarly, the PV panels integrated with aluminum fin cooling and CuO nanofluid cooling demonstrated average electrical efficiencies of 23.6% and 25.1%, respectively. Nevertheless, after accounting for the auxiliary power consumption of the 12 V circulating pump, the net electrical efficiency of the active CuO nanofluid cooling became comparable to that of the passive aluminum finned panel. Under the hot and dry climatic conditions of Kalaburagi, the passive aluminum fin cooling method showed beneficial thermal management capability without needing auxiliary power, rendering it a straightforward, economical, and energy efficient cooling solution for PV applications. Despite the active CuO nanofluid cooling system being relatively more expensive and intricate, it offered enhanced thermal management, significantly lowered PV operating temperature and improved the gross electrical performance under the same climatic conditions.</div></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"6 ","pages":"Article 100144"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148640247","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}

{"title":"Modeling and assessment of a hybrid pyramid solar still-humidification-dehumidification desalination system for sustainable freshwater production in SWGHs: A case study","authors":"Sevda Allahyari ,&nbsp;Amirhossein Barzigar ,&nbsp;Mohsen Fathi ,&nbsp;Sasan Asiaei ,&nbsp;Mahdi Moghimi ,&nbsp;Arun S Mujumdar ,&nbsp;S.M. Hosseinalipour","doi":"10.1016/j.seja.2026.100132","DOIUrl":"10.1016/j.seja.2026.100132","url":null,"abstract":"<div><div>Demand and the urgent need for energy conservation and sustainable resource management. Addressing this challenge requires desalination systems that are both energy-efficient and adaptable to climate variability. This study proposes a hybrid seawater greenhouse (SWGH) system that integrates humidification–dehumidification (HDH) desalination with a pyramid solar still (PSS) through thermal coupling to enhance overall energy utilization and freshwater productivity. To enable long-term performance assessment, convolutional neural network (CNN), gated recurrent unit (GRU), and hybrid CNN–GRU deep learning models were developed to predict freshwater production using historical and projected climatic data, including global horizontal irradiation (GHI) and air temperature (T2M), over the period 1985–2034. The CNN–GRU model demonstrated superior predictive performance and was coupled with thermodynamic simulations of the hybrid system to estimate long-term freshwater yield. Results indicate an annual cumulative freshwater production of approximately 4250-4400 L/m²·year. The HDH subsystem, with a surface area of 300 m², contributed 1450–1500 L/m²·year, while the 150 m² solar still unit produced 2800–2900 L/m²·year annually. These findings confirm that thermal integration between the desalination units significantly improves overall freshwater production while reducing thermal losses. The novelty of this work lies in the combined application of a CNN–GRU predictive framework with a thermally integrated hybrid solar desalination system, enabling reliable long-term forecasting under climate-sensitive conditions. The proposed approach provides a scalable, energy-efficient solution for sustainable freshwater generation and offers a data-driven decision-support tool for adaptive water management in arid coastal environments.</div></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"6 ","pages":"Article 100132"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147538892","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}