Cleaner Engineering and Technology最新文献

{"title":"Modeling and optimizing the atmospheric water harvesting System: Application of PAN-PDMS polymeric membrane","authors":"Sepehr Sanaye ,&nbsp;Pouya Rezvani Gil Kalaee ,&nbsp;Javad Mahmoudimehr","doi":"10.1016/j.clet.2025.101003","DOIUrl":"10.1016/j.clet.2025.101003","url":null,"abstract":"<div><div>Potable water scarcity is an increasingly demanding global issue and the extraction of potable water from the humidity of ambient air can be a solution to this problem. In this research combination of membranes, vacuum pump and vapor compression refrigeration (VCR) system is proposed as a water harvesting system. Polymeric membranes Polydimethylsiloxane (PDMS) and polyacrylonitrile (PAN), helped to separate water vapor from air by increasing the partial pressure of water vapor on the permeate side due to the separation process. The water vapor permeability has been assumed constant even with change in the pressure difference on two sides of the membrane in many research studies. However, this research uses its own developed relations obtained based on experimental results for variable pressure difference on both sides of membranes. As this proposed membrane system provides the air with near saturated water vapor conditions, thus, VCR system requires lower cooling capacity and lower electricity consumption for the condensation process. This proposed water harvesting system is modeled in energy and economic aspects for the first time and is optimized in this research by applying multi-objective Genetic Algorithm (GA) technique. The water production rate and the total annual cost rate were considered as two objective functions. Also, five design variables are selected after considering their effects on the objective functions. The optimization procedure performed for four different climate zones of Iran. Optimization results for the second zone showed 3.56 L per hour water production rate with about 29 % lower energy consumption in comparison with that for typical condensation process of water vapor in the same atmospheric air. The improved values for water vapor removal efficiency, water production cost, and the energy consumption were 63.6 %, 0.31 $ per liter, and 1714 <span><math><mrow><mtext>kJ</mtext></mrow></math></span> per liter respectively.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"27 ","pages":"Article 101003"},"PeriodicalIF":5.3,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144170719","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":"Multi-perspective analysis of a parabolic trough collector with a gradient porous structure and hybrid nanofluid: Thermal, thermodynamic, and exergoeconomic evaluation","authors":"Iman Shahdad,&nbsp;Mahdi Moghimi,&nbsp;Mahdi Navidbakhsh","doi":"10.1016/j.clet.2025.101001","DOIUrl":"10.1016/j.clet.2025.101001","url":null,"abstract":"<div><div>Research highlights that porous media significantly enhance parabolic trough collector performance by increasing surface area and minimizing thermal losses, thereby improving energy capture. Adding nanoparticles to the heat transfer fluid can further boost this improvement by increasing the heat transfer coefficient. The present study examined a porous ring with non-uniform porosity inside the receiver, which decreases radially toward the absorber tube's inner wall. A hybrid nanofluid was created by adding Al₂O₃ and MWCNT nanoparticles to Therminol-VP1 oil. The main objective was to investigate the influence of the novel receiver with and without the hybrid nanofluid. Additionally, an exergoeconomic analysis was conducted to assess the cost-effectiveness of incorporating the porous ring and hybrid nanofluid. Computational fluid dynamics simulations using OpenFOAM software analyzed the effects of various Reynolds numbers (<span><math><mrow><msup><mn>10</mn><mn>4</mn></msup><mo>,</mo><mn>5</mn><mo>×</mo><msup><mn>10</mn><mn>4</mn></msup><mo>,</mo><mn>20</mn><mo>×</mo><msup><mn>10</mn><mn>4</mn></msup></mrow></math></span>, and <span><math><mrow><mn>50</mn><mo>×</mo><msup><mn>10</mn><mn>4</mn></msup></mrow></math></span>), inlet temperatures (400 K and 500 K), porous ring thicknesses (0.008 m, 0.016 m, and 0.024 m), and nanoparticle volume fractions (0 %, 2 %, and 4 %) on parabolic trough collector performance. Results indicated that the gradient porous ring increased the Nusselt number by more than threefold and enhanced thermal and exergy efficiencies up to 17.3 % and 18.5 %, respectively. Adding nanoparticles optimized the Nusselt number at high Reynolds numbers but only modestly improved thermal and exergy efficiencies by 1.7 % and 2.3 %. Exergoeconomic analysis revealed that the porous ring increased net profit up to 30.3 % and reduced the total cost per unit of heat load by 7.39 %, whereas the addition of nanoparticles decreased net profit by 25.5 % and increased costs by 9.2 %.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"27 ","pages":"Article 101001"},"PeriodicalIF":5.3,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144134526","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":"Ultra-small defect-engineered UiO-66 on cellulose nanocrystal template for advanced carbon dioxide capture membrane","authors":"Xinyu Wang ,&nbsp;Seyed Fatemeh Seyedpour ,&nbsp;Sabahudin Hrapovic ,&nbsp;Usha D. Hemraz ,&nbsp;Mohammad Mozafari ,&nbsp;Masoud Soroush ,&nbsp;Muhammad Amirul Islam ,&nbsp;Arash Mollahosseini ,&nbsp;Mohtada Sadrzadeh ,&nbsp;Jae-Young Cho","doi":"10.1016/j.clet.2025.100999","DOIUrl":"10.1016/j.clet.2025.100999","url":null,"abstract":"<div><div>Global warming and associated climate change, primarily driven by greenhouse gas emissions, are no longer a forecast but are now undeniable realities. Although membrane technology presents a highly cost-effective approach for carbon dioxide (CO₂) capture, further research is required to overcome the inherent trade-off between selectivity and permeability to achieve enhanced performance. A novel defect-engineered ultrasmall cellulose nanocrystal (CNC)-templated UiO-66 MOF (CNC-UiO-66 hybrid) was synthesized to improve the performance of Pebax membranes. The elongated geometry of the CNC-UiO-66 hybrid creates extended facilitated transport channels for CO₂, while the highly defective structure, induced by the presence of CNC during synthesis, enhances coordination interactions with both CO₂ and the polymer matrix. As a result, Pebax incorporated with CNC-UiO-66 demonstrated increased crystallinity and thermal stability. The incorporation of as little as 1 wt% of the CNC-UiO-66 hybrid into Pebax membranes achieved a remarkable CO₂ permeability of 1442 Barrer and a selectivity of 40, surpassing the Robeson upper bound (2008) for CO₂/N₂ separation. Cost analysis suggested that this membrane could reduce carbon capture costs to 62 USD per tonne, 10 USD less than conventional membranes. These results highlight the potential of CNC-UiO-66 hybrid membranes for efficient and cost-effective CCUS applications, particularly in flue gas treatment.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"27 ","pages":"Article 100999"},"PeriodicalIF":5.3,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144090607","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":"High-efficiency filtration: Smart designs for particle trapping","authors":"Bahador Abolpour ,&nbsp;Ramtin Hekmatkhah ,&nbsp;Rahim Shamsoddini","doi":"10.1016/j.clet.2025.100997","DOIUrl":"10.1016/j.clet.2025.100997","url":null,"abstract":"<div><div>Trapping solid particles within fluid flows is a critical concern for maintaining the health of living organisms, enhancing the efficiency of industrial equipment, and more. In this study, we present an optimal design for achieving the highest possible particle-trapping rate in a two-dimensional filter with turbulent fluid flow. To achieve this, we use a genetic algorithm to determine the optimal arrangement of square obstacles within a turbulent flow field. The process starts with an image processing method (IPM) that identifies geometric objects in the filtered image. Following this, the edges of these objects are delineated, and a mesh is generated throughout the fluid flow field and around the identified filter objects. To solve the hydrodynamics and turbulent equations, we apply the finite volume method. Furthermore, a staggered grid is utilized to store scalar and vector variables. The genetic algorithm (GA) iteratively generates new arrangements, which are then evaluated and selected for mutation to refine the optimized design. This refined configuration of the filters is designed to enhance the particle trapping rate. A comparison between the optimized filter locations and those of a simpler design reveals a significant reduction in the escape of particles, with a 23 % decrease observed in the optimized condition.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"27 ","pages":"Article 100997"},"PeriodicalIF":5.3,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144099717","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":"Optimization of engine parameters and emission profiles through bio-additives: Insights from ANFIS Modeling of Diesel Combustion","authors":"Abbas Rohani ,&nbsp;Javad Zareei ,&nbsp;Kourosh Ghadamkheir ,&nbsp;Seyed Alireza Farkhondeh","doi":"10.1016/j.clet.2025.100994","DOIUrl":"10.1016/j.clet.2025.100994","url":null,"abstract":"<div><div>The effects of bio-additives on combustion characteristics and engine performance in an OM355 EU II diesel engine were investigated. Numerical simulations were conducted across a wide range of operating conditions, including engine speed, fuel blends, equivalence ratio, and exhaust gas recirculation (EGR) rates. Key performance metrics, such as torque, power, engine efficiency, indicated specific fuel consumption (ISFC), combustion noise, NOx emissions, and soot behavior, were evaluated. It was found that a reduction in bioethanol content, combined with an increase in the equivalence ratio to 1.2, resulted in a significant improvement in Brake Mean Effective Pressure (BMEP). Furthermore, an increase in soybean methyl ester (SME) content in the fuel blend was observed to reduce combustion noise by alleviating sharp pressure gradients. Higher bioethanol content and EGR rates were associated with lower soot production and NOx emissions, with a blend of 50 % bioethanol and 10 % EGR achieving a 16.7 % reduction in NOx emissions compared to diesel fuel with 0 % EGR. Additionally, an Adaptive Neuro-Fuzzy Inference System (ANFIS) model was developed to predict combustion characteristics, engine parameters, and exhaust gas emissions. Various machine learning configurations and training algorithms were employed to optimize the model's performance. The findings of this study provide valuable insights into the optimization of engine performance and the reduction of emissions through the use of bio-additives.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"27 ","pages":"Article 100994"},"PeriodicalIF":5.3,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144107604","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":"Optimization of a resilient circular closed-loop supply chain network under uncertainty","authors":"Samira Mehrabi ,&nbsp;Hassan Mina ,&nbsp;Shahryar Sorooshian","doi":"10.1016/j.clet.2025.100995","DOIUrl":"10.1016/j.clet.2025.100995","url":null,"abstract":"<div><div>Lubricating oils are among the most widely used petroleum fractions since they are used by different machines and vehicles. In addition to cooling the engine and reducing the friction between moving mechanical parts, motor oil also absorbs pollutants such as sludge, peroxides, and debris that are accumulated in the engine. Therefore, used motor oils are the dangerous materials that can have adverse impacts on the environment and living organisms if not properly managed. Hence, for the first time, this article develops a new bi-objective mixed-integer linear programming (BOMILP) model to form a resilient circular closed-loop supply chain network for managing the used motor oils. Moreover, with the aim of achieving advanced sustainability and circularity goals, the proposed model manages collecting, recycling, producing, and purchasing gallons. Moreover, this study applies a scenario-based stochastic programming method to control the demand uncertainty, and provides a novel fuzzy goal programming method to solve the developed BOMILP model. Finally, the data of an Iranian motor oil production company is applied to validate the proposed optimization model and evaluate the performance of the presented multi-objective solution approach. The results derived from implementing the developed optimization model in the real world and conducting the sensitivity analysis process denote the effectiveness and accuracy of the developed optimization model and solution method.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"27 ","pages":"Article 100995"},"PeriodicalIF":5.3,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144090239","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 carbon fiber composites with fish scale biochar for superior strength and environmental sustainability","authors":"Sundarakannan Rajendran ,&nbsp;Geetha Palani ,&nbsp;Arumugaprabu Veerasimman ,&nbsp;Vigneshwaran Shanmugam ,&nbsp;Uthayakumar Marimuthu ,&nbsp;Kinga Korniejenko ,&nbsp;Herri Trilaksana ,&nbsp;Arnas Majumder ,&nbsp;Flavio Stochino","doi":"10.1016/j.clet.2025.100996","DOIUrl":"10.1016/j.clet.2025.100996","url":null,"abstract":"<div><div>There is a pressing need to develop carbon fiber composites with sustainable fillers that enhance their strength without increasing costs or environmental impact. Such advancements would not only improve performance in high-stress applications but also align with global sustainability goals by utilizing eco-friendly materials and reducing waste. This study explores the use of biochar derived from fish scales as a sustainable filler material in carbon fiber epoxy composites. The biochar was produced through pyrolysis and incorporated into the composites at various weight percentages (0 %, 1 %, 3 %, 6 %, 9 %, 12 %, and 15 %). Mechanical properties, including tensile strength, flexural strength, impact strength, and interlaminar shear strength, were evaluated according to ASTM standards. The results demonstrated that the incorporation of biochar significantly improved the mechanical properties of the composites, with optimal performance observed at 9 % biochar content. At this concentration, the tensile strength increased by 60.02 %–674.21 MPa, the tensile modulus by 74.96 % to 46.05 GPa, the flexural modulus by 58.32 GPa, and the impact strength reached 102.32 kJ/m². It was found that achieving the optimal performance requires an optimal weight percentage of biochar. This study highlights the potential of fish scale-derived biochar as an effective and sustainable filler material for enhancing the performance of carbon fiber composites.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"27 ","pages":"Article 100996"},"PeriodicalIF":5.3,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143937888","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":"Sustainability analysis and impact assessment of food waste reduction campaign in Chinese higher institution: Towards cleaner environment and energy efficiency","authors":"Bahareh Asefi ,&nbsp;François Nkinahamira ,&nbsp;Olusegun K. Abass ,&nbsp;Moughni Said Maenrouf ,&nbsp;Yunting Liang ,&nbsp;Yuan Meng ,&nbsp;Peizheng Wang","doi":"10.1016/j.clet.2025.100998","DOIUrl":"10.1016/j.clet.2025.100998","url":null,"abstract":"<div><div>Food waste (FW) in China has drawn increasing global attention due to its significant environmental, economic, and societal impacts, necessitating effective management strategies. This study evaluates the “Empty Plate, Full Pocket” initiative, an educational campaign at Hainan Tropical Ocean University (HNTOU), to reduce FW in university canteens and its implications for cleaner production. Using direct weight calculations and questionnaire surveys, FW patterns, environmental emissions, and economic costs were analyzed in two service styles: self-service (SS) and table-service (TS). The campaign achieved an 83 % reduction in per capita FW for SS and 68 % for TS, resulting in an overall 50 % decrease in total FW. Rice and vegetables were the primary contributors to waste, with dissatisfaction with taste accounting for 80 % of FW. In TS settings, larger portion sizes led to higher waste levels. Environmental benefits derived from the initiative resulted in CO₂ emissions reduction by 86 % for TS and 64 % for SS, while FW-associated economic costs fell by 82 % in TS and 99 % in SS. The study also identified caloric content as a factor influencing purchasing behavior and highlighted key drivers of FW generation. The findings demonstrate how behavioral interventions can complement engineering approaches to address FW challenges, reduce environmental emissions, and enhance resource efficiency in institutional settings. This initiative showcases the potential of targeted campaigns to integrate sustainability principles and cleaner production practices, providing valuable insights for scalable FW management strategies in educational institutions and beyond.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"27 ","pages":"Article 100998"},"PeriodicalIF":5.3,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143937764","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":"Comparative analysis of machine learning and conventional methods for waste generation forecasting","authors":"Abdulrahman Abdeljaber ,&nbsp;Sara Al Smadi ,&nbsp;Manar Abu Talib ,&nbsp;Mohamed Abdallah","doi":"10.1016/j.clet.2025.100992","DOIUrl":"10.1016/j.clet.2025.100992","url":null,"abstract":"<div><div>The escalating complexity of waste management systems, driven by rapid environmental and socio-economic shifts, necessitates the development of robust multi-parameter waste generation prediction models. Conventional forecasting methods such as system dynamics, time series, and linear regression have been widely utilized; however, they often fail to fully capture the nuanced dynamics of waste generation, which is influenced by various seasonal and demographic factors. Artificial intelligence (AI) models have emerged as alternative predictors that perform advanced computational techniques to generate accurate forecasts. Despite the extensive research conducted, few review articles have assessed the feasibility of utilizing multiple prediction methods for different waste streams. None has comprehensively assessed and compared the various prediction methods for different waste streams. This review summarizes and analyzes the prediction methodologies implemented for different waste types. This systematic literature review compiles 119 articles from 2000 to 2024. A thorough analysis of AI-based models and a summary of the most influential explanatory variables were provided. The review indicates a predominant focus on municipal waste, with considerable gaps in the forecasting of construction and medical waste streams. System dynamics models were found to excel in strategic waste management planning but can be complex to calibrate and validate. Time series and regression analyses, while useful for identifying trends and relationships, often failed to adapt to rapid or unpredictable changes. Alternatively, machine learning algorithms offer robust capabilities for modeling complex and nonlinear data, although they require substantial data quality and are prone to overfitting. It is concluded that a combined hybrid approach is recommended, leveraging the strengths of different methods to provide more accurate waste generation forecasts. The critical analyses presented can offer insights to decision-makers in the waste management sector by providing key aspects concerning the efficiency and limitations of these predictors.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"27 ","pages":"Article 100992"},"PeriodicalIF":5.3,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144069708","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":"Multi-criteria decision-making for wind power project feasibility: Trends, techniques, and future directions","authors":"Ade Gafar Abdullah ,&nbsp;Hasna Putri Utami ,&nbsp;Budi Gunawan ,&nbsp;Barito Mulyo Ratmono ,&nbsp;Naek Tua Pasaribu","doi":"10.1016/j.clet.2025.100987","DOIUrl":"10.1016/j.clet.2025.100987","url":null,"abstract":"<div><div>The selection of wind power plant (WPP) locations is critical for renewable energy development, directly impacting plant capacity and long-term socio-economic outcomes. This study analyzes scientific research on WPP location determination across countries, trends in multi-criteria decision-making (MCDM) methods over the past decade, MCDM's effectiveness in developing countries, and key criteria in site selection. A systematic review of 30 journal articles from 16 countries was conducted. Results show that China leads in scientific production, followed by Iran, with publication peaks in 2020, 2021, and 2024. The adoption of MCDM methods, such as AHP, PROMETHEE, and FAHP, has significantly increased, reflecting the need for more complex and accurate evaluations. MCDM enhances efficiency and effectiveness in WPP site selection in developing countries, including Turkey, Iran, Saudi Arabia, and Vietnam, by providing a systematic framework to evaluate criteria holistically. Four main categories of criteria were identified: technical (e.g., wind speed, proximity to grids), environmental (e.g., impacts on protected areas and birds), social (e.g., community acceptance), and economic (e.g., initial investment, maintenance costs). These approaches enable more efficient, sustainable, and context-specific decisions. Future research should integrate artificial intelligence to address dynamic criteria. These findings offer strategic guidance for policymakers and stakeholders to advance sustainable renewable energy development.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"27 ","pages":"Article 100987"},"PeriodicalIF":5.3,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143943192","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}