Pub Date : 2025-10-22DOI: 10.1109/JPHOTOV.2025.3616635
Gabriel Lopez;Dmitrii Bogdanov;Rasul Satymov;Christian Breyer
Energy transition pathways for large continental areas are largely understood to be achievable using a diverse set of onshore renewable energy technologies. Previous research for the integrated United States and Canada energy–industry system indicated that solar photovoltaics (PVs) may dominate the primary energy structure, complemented by onshore wind power. However, societal constraints may require increased supply diversity, and onshore renewable energy may not be sufficient for densely populated regions, especially on the east coast of the United States. The LUT Energy System Transition Model was applied to investigate the role of floating offshore solar PV coupled with offshore wind and wave power when onshore solar PV is limited. The results indicate that, when onshore solar PV is limited to 60% of electricity generation, 434 GW of floating offshore solar PV may be installed by 2050 as part of a hybrid power plant sharing the same grid connection as offshore wind power, which reaches 414 GW of installed capacity, contributing 607 and 1576 TWh to the electricity supply, respectively. In total, 7.4 TW of solar PV capacity is installed by 2050, complemented by 1.4 TW of onshore wind power. Increased supply diversity still leads to a 42% reduction in the levelized cost of electricity, reaching 32.7 €/MWh in 2050. Compared with cost-optimal conditions, the levelized cost of final energy and nonenergy use in 2050 increases by 28% to 52.7 €/MWh. Nevertheless, such increased costs may be justifiable to meet societal constraints, and a diverse power-to-X economy structure for the United States and Canada may still be technoeconomically viable.
{"title":"Floating Offshore Solar Photovoltaics for Land-Constrained and Diverse Renewable Supply Conditions in the United States and Canada","authors":"Gabriel Lopez;Dmitrii Bogdanov;Rasul Satymov;Christian Breyer","doi":"10.1109/JPHOTOV.2025.3616635","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3616635","url":null,"abstract":"Energy transition pathways for large continental areas are largely understood to be achievable using a diverse set of onshore renewable energy technologies. Previous research for the integrated United States and Canada energy–industry system indicated that solar photovoltaics (PVs) may dominate the primary energy structure, complemented by onshore wind power. However, societal constraints may require increased supply diversity, and onshore renewable energy may not be sufficient for densely populated regions, especially on the east coast of the United States. The LUT Energy System Transition Model was applied to investigate the role of floating offshore solar PV coupled with offshore wind and wave power when onshore solar PV is limited. The results indicate that, when onshore solar PV is limited to 60% of electricity generation, 434 GW of floating offshore solar PV may be installed by 2050 as part of a hybrid power plant sharing the same grid connection as offshore wind power, which reaches 414 GW of installed capacity, contributing 607 and 1576 TWh to the electricity supply, respectively. In total, 7.4 TW of solar PV capacity is installed by 2050, complemented by 1.4 TW of onshore wind power. Increased supply diversity still leads to a 42% reduction in the levelized cost of electricity, reaching 32.7 €/MWh in 2050. Compared with cost-optimal conditions, the levelized cost of final energy and nonenergy use in 2050 increases by 28% to 52.7 €/MWh. Nevertheless, such increased costs may be justifiable to meet societal constraints, and a diverse power-to-X economy structure for the United States and Canada may still be technoeconomically viable.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"16 1","pages":"60-68"},"PeriodicalIF":2.6,"publicationDate":"2025-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11214224","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-22DOI: 10.1109/JPHOTOV.2025.3620446
{"title":"Golden List of Reviewers","authors":"","doi":"10.1109/JPHOTOV.2025.3620446","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3620446","url":null,"abstract":"","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"15 6","pages":"988-990"},"PeriodicalIF":2.6,"publicationDate":"2025-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11214300","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145339715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-22DOI: 10.1109/JPHOTOV.2025.3608474
Tajrian Mollick;Md Jobayer;Md. Samrat Hossin;Shahidul Islam Khan;A. S. Nazmul Huda;Saifur Rahman Sabuj
Solar energy adoption is rapidly growing as a sustainable option, with solar panels used on residential buildings, commercial properties, and large-scale farms. However, the unpredictable nature of solar power can lead to suboptimal energy generation from photovoltaic (PV) panels. Despite the high effectiveness of deep learning (DL) models in forecasting PV power, they often struggle with the perception of being “closed boxes” that lack clear explanations for their prediction results, which fail to highlight the key features for PV prediction. To address the critical issue of full transparency, this study explores a well-known DL model named lightweight deep neural network (LWDNN) in PV power forecasting, along with the application of explainable artificial intelligence (XAI) tools like Shapley Additive exPlanations (SHAP) and local interpretable model-agnostic explanations (LIME). Real-time data collected from a grid-connected solar PV system located in Dhaka were utilized to perform the prediction. By enabling XAI model interpretation, we identified feature contributions and explained individual predictions, reducing training computational demands without compromising accuracy. The reliability of the LWDNN model is assessed using both complete and reduced feature sets through performance metrics such as root mean squared error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). The test results show that the proposed LWDNN model based on SHAP analysis outperforms conventional schemes by achieving RMSE = 6.180 kW, MAE = 1.939 kW, and R2 = 0.988. Finally, the model was implemented on a Raspberry Pi for low-power solar forecasting, demonstrating the feasibility of edge deployment.
{"title":"An Interpretable Deep Learning Model for Solar Power Generation Forecasting in a Grid-Connected Hybrid Solar System","authors":"Tajrian Mollick;Md Jobayer;Md. Samrat Hossin;Shahidul Islam Khan;A. S. Nazmul Huda;Saifur Rahman Sabuj","doi":"10.1109/JPHOTOV.2025.3608474","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3608474","url":null,"abstract":"Solar energy adoption is rapidly growing as a sustainable option, with solar panels used on residential buildings, commercial properties, and large-scale farms. However, the unpredictable nature of solar power can lead to suboptimal energy generation from photovoltaic (PV) panels. Despite the high effectiveness of deep learning (DL) models in forecasting PV power, they often struggle with the perception of being “closed boxes” that lack clear explanations for their prediction results, which fail to highlight the key features for PV prediction. To address the critical issue of full transparency, this study explores a well-known DL model named lightweight deep neural network (LWDNN) in PV power forecasting, along with the application of explainable artificial intelligence (XAI) tools like Shapley Additive exPlanations (SHAP) and local interpretable model-agnostic explanations (LIME). Real-time data collected from a grid-connected solar PV system located in Dhaka were utilized to perform the prediction. By enabling XAI model interpretation, we identified feature contributions and explained individual predictions, reducing training computational demands without compromising accuracy. The reliability of the LWDNN model is assessed using both complete and reduced feature sets through performance metrics such as root mean squared error (RMSE), mean absolute error (MAE), and coefficient of determination (R<sup>2</sup>). The test results show that the proposed LWDNN model based on SHAP analysis outperforms conventional schemes by achieving RMSE = 6.180 kW, MAE = 1.939 kW, and R<sup>2</sup> = 0.988. Finally, the model was implemented on a Raspberry Pi for low-power solar forecasting, demonstrating the feasibility of edge deployment.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"15 6","pages":"941-954"},"PeriodicalIF":2.6,"publicationDate":"2025-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145339706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-17DOI: 10.1109/JPHOTOV.2025.3614768
Íñigo de la Parra;Miguel García;Javier Marcos;Luis Marroyo
The adoption of bifacial photovoltaic (PV) modules has grown significantly due to their potential for higher energy yield. However, their real-world performance under outdoor conditions remains insufficiently explored. This study analyzes the energy gains of bifacial PV modules in a horizontally tracked power plant in the Atacama Desert, Chile, comparing a conventional single-axis tracker with an optimized tracker designed for bifacial performance. Results show that bifacial modules on conventional trackers achieve ∼5% higher energy production, while those on optimized trackers reach up to 6.1%, emphasizing the role of tracker design in maximizing bifacial PV efficiency.
{"title":"Performance Enhancement of Bifacial PV Modules on Horizontal Single-Axis Trackers in Desert Environments","authors":"Íñigo de la Parra;Miguel García;Javier Marcos;Luis Marroyo","doi":"10.1109/JPHOTOV.2025.3614768","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3614768","url":null,"abstract":"The adoption of bifacial photovoltaic (PV) modules has grown significantly due to their potential for higher energy yield. However, their real-world performance under outdoor conditions remains insufficiently explored. This study analyzes the energy gains of bifacial PV modules in a horizontally tracked power plant in the Atacama Desert, Chile, comparing a conventional single-axis tracker with an optimized tracker designed for bifacial performance. Results show that bifacial modules on conventional trackers achieve ∼5% higher energy production, while those on optimized trackers reach up to 6.1%, emphasizing the role of tracker design in maximizing bifacial PV efficiency.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"16 1","pages":"128-135"},"PeriodicalIF":2.6,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11206410","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-16DOI: 10.1109/JPHOTOV.2025.3616601
Nils-Peter Harder
In the search for new sites, photovoltaic (PV) system installations spread out into complex places and contexts, such as hilly terrain, floating PV, and agriPV. It is, therefore, plausible to assume that PV power plants will increasingly need to use space and, thus, sunlight more efficiently, e.g., by not wasting solar energy in the space between module rows. This means it may become increasingly important to consider the energy output of PV systems per area of land use, i.e., the “efficiency of the PV system.” To increase this efficiency, power plants with high density of PV modules are needed. For tracked systems, this necessitates adapting the tracking strategies to avoid excessive losses from either row-to-row shading or angle-of-incidence losses in backtracking. This article explores different tracking strategies that could contribute to enabling high-density PV power plants with high efficiency. The advantages of these advanced tracking strategies are quantified at two different latitudes as a function of the ground coverage ratio.
{"title":"Tracking Concepts for High-Density PV Power Plants","authors":"Nils-Peter Harder","doi":"10.1109/JPHOTOV.2025.3616601","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3616601","url":null,"abstract":"In the search for new sites, photovoltaic (PV) system installations spread out into complex places and contexts, such as hilly terrain, floating PV, and agriPV. It is, therefore, plausible to assume that PV power plants will increasingly need to use space and, thus, sunlight more efficiently, e.g., by not wasting solar energy in the space between module rows. This means it may become increasingly important to consider the energy output of PV systems per area of land use, i.e., the “efficiency of the PV system.” To increase this efficiency, power plants with high density of PV modules are needed. For tracked systems, this necessitates adapting the tracking strategies to avoid excessive losses from either row-to-row shading or angle-of-incidence losses in backtracking. This article explores different tracking strategies that could contribute to enabling high-density PV power plants with high efficiency. The advantages of these advanced tracking strategies are quantified at two different latitudes as a function of the ground coverage ratio.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"16 1","pages":"54-59"},"PeriodicalIF":2.6,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Floating photovoltaics (FPVs) are gaining traction as a land-saving alternative to ground-mounted photovoltaics (GPV). A commonly cited advantage of FPVs is their potential for lower operating temperatures due to the cooling effect of water. However, existing literature shows that the thermal performance of FPV systems may not consistently exceed that of GPV systems, as it is influenced by technology and location. Consequently, studying the thermal properties of a range of FPV systems is crucial to optimize power output and enable accurate energy yield modeling for new sites. This work investigates the thermal properties and calculated heat loss coefficients, or U-values, associated with the Faiman model for an FPV system using Ciel & Terre's Hydrelio Air floats, located in a pond in South Africa. A dependence of U-values on wind direction was observed, with improved cooling when the wind approaches from the rear side of the system. The estimated U-value components were U0 = 21.6 W/m2·K and U1 = 3.60 W·s/m3·K for wind from the front and U0 = 19.4 W/m2·K and U1 = 7.10 W·s/m3·K for wind from the rear side. The impact of the observed cooling variation due to wind direction on system performance was also evaluated, revealing a 1.7% increase in median performance ratio when the wind originates from the rear side.
{"title":"Impact of Wind Speed and Direction on Cooling of a Pontoon-Based Floating Photovoltaic System","authors":"Vilde Stueland Nysted;Torunn Kjeldstad;Dag Lindholm;Marit Sandsaunet Ulset;Josefine Selj","doi":"10.1109/JPHOTOV.2025.3611425","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3611425","url":null,"abstract":"Floating photovoltaics (FPVs) are gaining traction as a land-saving alternative to ground-mounted photovoltaics (GPV). A commonly cited advantage of FPVs is their potential for lower operating temperatures due to the cooling effect of water. However, existing literature shows that the thermal performance of FPV systems may not consistently exceed that of GPV systems, as it is influenced by technology and location. Consequently, studying the thermal properties of a range of FPV systems is crucial to optimize power output and enable accurate energy yield modeling for new sites. This work investigates the thermal properties and calculated heat loss coefficients, or <italic>U</i>-values, associated with the Faiman model for an FPV system using Ciel & Terre's Hydrelio Air floats, located in a pond in South Africa. A dependence of <italic>U</i>-values on wind direction was observed, with improved cooling when the wind approaches from the rear side of the system. The estimated <italic>U</i>-value components were <italic>U</i><sub>0</sub> = 21.6 W/m<sup>2</sup>·K and <italic>U</i><sub>1</sub> = 3.60 W·s/m<sup>3</sup>·K for wind from the front and <italic>U</i><sub>0</sub> = 19.4 W/m<sup>2</sup>·K and <italic>U</i><sub>1</sub> = 7.10 W·s/m<sup>3</sup>·K for wind from the rear side. The impact of the observed cooling variation due to wind direction on system performance was also evaluated, revealing a 1.7% increase in median performance ratio when the wind originates from the rear side.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"15 6","pages":"955-964"},"PeriodicalIF":2.6,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145341070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-03DOI: 10.1109/JPHOTOV.2025.3611430
Szymon Pelczar
The land equivalent ratio (LER) is a widely used coefficient by researchers in studies related to agrivoltaic systems. Although the indicator mentioned was developed to determine the benefits of intercropping, it has also been found useful for evaluating agrivoltaic installations. The objective of the LER is to describe the effectiveness of land use under agrivoltaic conditions versus conventional conditions, which implies separate production of crops and electricity. However, the mentioned coefficient does not give a complete description of an agrivoltaic system and its performance. To do so, additional indicators are developed. This study aims to demonstrate that additional parameters, which can be used to better describe an agrivoltaic system in terms of its comparison with conventional conditions. The coefficients presented can help assess the validity of agrivoltaic implementation and to make the decision whether, considering given conditions, it is more desirable to realize a conventional photovoltaic power plant or an agrivoltaic one.
{"title":"Is the Land Equivalent Ratio (LER) a Sufficient Indicator to Describe the Efficiency of Agrivoltaic System?","authors":"Szymon Pelczar","doi":"10.1109/JPHOTOV.2025.3611430","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3611430","url":null,"abstract":"The land equivalent ratio (LER) is a widely used coefficient by researchers in studies related to agrivoltaic systems. Although the indicator mentioned was developed to determine the benefits of intercropping, it has also been found useful for evaluating agrivoltaic installations. The objective of the LER is to describe the effectiveness of land use under agrivoltaic conditions versus conventional conditions, which implies separate production of crops and electricity. However, the mentioned coefficient does not give a complete description of an agrivoltaic system and its performance. To do so, additional indicators are developed. This study aims to demonstrate that additional parameters, which can be used to better describe an agrivoltaic system in terms of its comparison with conventional conditions. The coefficients presented can help assess the validity of agrivoltaic implementation and to make the decision whether, considering given conditions, it is more desirable to realize a conventional photovoltaic power plant or an agrivoltaic one.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"15 6","pages":"977-983"},"PeriodicalIF":2.6,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145339600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-29DOI: 10.1109/JPHOTOV.2025.3611424
Rodrigo del Prado Santamaría;Gisele A. dos Reis Benatto;Thøger Kari;Aysha Mahmood;Peter B. Poulsen;Sergiu V. Spataru
Potential-induced degradation (PID) in photovoltaic (PV) modules can be identified using electroluminescence (EL) imaging by comparing the luminescence of degraded cells to that of healthy cells. In nondegraded modules, cells exhibit consistent radiative recombination and luminescence properties, whereas PID alters these, creating measurable differences. This work presents a methodology to quantify relative changes in luminescence between degraded cells and a reference cell within the same module by acquiring EL images at two distinct current injection levels. The resulting metric enables automatic PID characterization and reduces reliance on subjective visual interpretation. The approach was further adapted for daylight field EL inspections using a multibias modulation technique, which introduces an intermediate current bias between high-current injection and open-circuit voltage (Voc). This adaptation mitigates variability from changing irradiance, allowing effective PID characterization under low irradiance conditions. Validation in both field and lab environments confirmed the robustness of the method, with module luminescence differences exceeding 2.5% even at 50% current bias. These results highlight the potential of the proposed metric for reliable PID diagnosis in PV modules.
{"title":"Diagnosing PID in Field Electroluminescence Inspections of PV Modules Using Multilevel Forward Current Biasing","authors":"Rodrigo del Prado Santamaría;Gisele A. dos Reis Benatto;Thøger Kari;Aysha Mahmood;Peter B. Poulsen;Sergiu V. Spataru","doi":"10.1109/JPHOTOV.2025.3611424","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3611424","url":null,"abstract":"Potential-induced degradation (PID) in photovoltaic (PV) modules can be identified using electroluminescence (EL) imaging by comparing the luminescence of degraded cells to that of healthy cells. In nondegraded modules, cells exhibit consistent radiative recombination and luminescence properties, whereas PID alters these, creating measurable differences. This work presents a methodology to quantify relative changes in luminescence between degraded cells and a reference cell within the same module by acquiring EL images at two distinct current injection levels. The resulting metric enables automatic PID characterization and reduces reliance on subjective visual interpretation. The approach was further adapted for daylight field EL inspections using a multibias modulation technique, which introduces an intermediate current bias between high-current injection and open-circuit voltage (<italic>V</i><sub>oc</sub>). This adaptation mitigates variability from changing irradiance, allowing effective PID characterization under low irradiance conditions. Validation in both field and lab environments confirmed the robustness of the method, with module luminescence differences exceeding 2.5% even at 50% current bias. These results highlight the potential of the proposed metric for reliable PID diagnosis in PV modules.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"16 1","pages":"39-46"},"PeriodicalIF":2.6,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-22DOI: 10.1109/JPHOTOV.2025.3605941
Long Ji;Zhi David Chen;Shibin Li
The [4-(3,6-dimethyl-9h-carbazol-9yl)butyl]phosphonic acid (Me-4PACz) self-assembled molecules (SAM) constitute a hole transport layer, which is widely applied to modify NiOx. In addition, it has been exploited to address some of the issues between the buried interface of NiOx and perovskite. Nevertheless, the Me-4PACz molecule is unable to completely cover the buried interface or effectively passivate the buried interface defects, thus limiting the efficiency of inverted perovskite solar cells. Consequently, a molecule containing carboxyl (-COOH) and amino (-NH3) groups, 5-ammonium valeric acid iodide (5-AVAI), is incorporated into Me-4PACz. Notably, 5-AVAI interacts with NiOx and the underlying perovskite to form a bridging ligand that passivates interfacial defects, thereby facilitating hole transport and reducing nonradiative interfacial recombination. As a result, a buried interface device based on 5-AVAI realizes a conversion efficiency of 24.62%. Overall, this work demonstrates a new approach to improve the performance of perovskite cells by modifying the buried interface NiOx with 5-AVAI molecules.
{"title":"5-Ammonium Valeric Acid Iodide (5-AVAI) Molecules Modified Buried Interface for Realizing High-Performance Perovskite Solar Cells","authors":"Long Ji;Zhi David Chen;Shibin Li","doi":"10.1109/JPHOTOV.2025.3605941","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3605941","url":null,"abstract":"The [4-(3,6-dimethyl-9h-carbazol-9yl)butyl]phosphonic acid (Me-4PACz) self-assembled molecules (SAM) constitute a hole transport layer, which is widely applied to modify NiO<sub>x</sub>. In addition, it has been exploited to address some of the issues between the buried interface of NiO<sub>x</sub> and perovskite. Nevertheless, the Me-4PACz molecule is unable to completely cover the buried interface or effectively passivate the buried interface defects, thus limiting the efficiency of inverted perovskite solar cells. Consequently, a molecule containing carboxyl (-COOH) and amino (-NH<sub>3</sub>) groups, 5-ammonium valeric acid iodide (5-AVAI), is incorporated into Me-4PACz. Notably, 5-AVAI interacts with NiO<sub>x</sub> and the underlying perovskite to form a bridging ligand that passivates interfacial defects, thereby facilitating hole transport and reducing nonradiative interfacial recombination. As a result, a buried interface device based on 5-AVAI realizes a conversion efficiency of 24.62%. Overall, this work demonstrates a new approach to improve the performance of perovskite cells by modifying the buried interface NiO<sub>x</sub> with 5-AVAI molecules.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"16 1","pages":"75-80"},"PeriodicalIF":2.6,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-17DOI: 10.1109/JPHOTOV.2025.3602602
Niklas Pyrlik;Christina Ossig;Svenja Patjens;Giovanni Fevola;Jan Hense;Catharina Ziska;Martin Seyrich;Frank Seiboth;Andreas Schropp;Jan Garrevoet;Gerald Falkenberg;Christian G. Schroer;Romain Carron;Michael E. Stuckelberger
Multimodal imaging of thin-film solar cells has been demonstrated at hard X-ray nanoprobes: simultaneously assessing X-ray beam induced current and X-ray fluorescence, lateral variations in the electrical performance and the distribution of absorber and trace elements can be correlated. Here, we complement the suite of modalities with scanning X-ray diffraction and map the crystallographic structure of Cu(In,Ga)Se2(CIGS) at the nanoscale: in the quaternary compound semiconductor, lattice strain and structural defects induced by tetragonal lattice distortions, steep vertical In/Ga gradients, and lateral inhomogeneities pose a great challenge. Investigating a series of solar cells with varying In/Ga ratio, we probed for the first time a statistically significant number of nearly 500 CIGS grains in the bulk layer of operational cells. Overall, we assessed the entirety of the Cu(In,Ga)Se2 Materials Science Tetrahedron—thanks to, first, extraordinary sensitivity with K-edge excitation allowing to correlate the lateral Cd and In/Ga distribution, local performance, and lattice spacing, second, detection of voids, some filled with CdS, in the CIGS layer, and third, performance-relevant findings from a crystallographic analysis of grain orientation and boundaries. Beyond further optimization of Cu(In,Ga)Se2 photovoltaic cells toward the detailed balance limit of solar-cell conversion efficiency, the developed methodology paves the way to extract a maximum of information from correlative hard X-ray nanoscopy at diffraction-limited storage rings.
{"title":"Correlation of Nanoscale Structure, Composition, and Performance: A Study of the CIGS Materials Paradigm","authors":"Niklas Pyrlik;Christina Ossig;Svenja Patjens;Giovanni Fevola;Jan Hense;Catharina Ziska;Martin Seyrich;Frank Seiboth;Andreas Schropp;Jan Garrevoet;Gerald Falkenberg;Christian G. Schroer;Romain Carron;Michael E. Stuckelberger","doi":"10.1109/JPHOTOV.2025.3602602","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3602602","url":null,"abstract":"Multimodal imaging of thin-film solar cells has been demonstrated at hard X-ray nanoprobes: simultaneously assessing X-ray beam induced current and X-ray fluorescence, lateral variations in the electrical performance and the distribution of absorber and trace elements can be correlated. Here, we complement the suite of modalities with scanning X-ray diffraction and map the crystallographic structure of Cu(In,Ga)Se<sub>2</sub>(CIGS) at the nanoscale: in the quaternary compound semiconductor, lattice strain and structural defects induced by tetragonal lattice distortions, steep vertical In/Ga gradients, and lateral inhomogeneities pose a great challenge. Investigating a series of solar cells with varying In/Ga ratio, we probed for the first time a statistically significant number of nearly 500 CIGS grains in the bulk layer of operational cells. Overall, we assessed the entirety of the Cu(In,Ga)Se<sub>2</sub> Materials Science Tetrahedron—thanks to, first, extraordinary sensitivity with K-edge excitation allowing to correlate the lateral Cd and In/Ga distribution, local performance, and lattice spacing, second, detection of voids, some filled with CdS, in the CIGS layer, and third, performance-relevant findings from a crystallographic analysis of grain orientation and boundaries. Beyond further optimization of Cu(In,Ga)Se<sub>2</sub> photovoltaic cells toward the detailed balance limit of solar-cell conversion efficiency, the developed methodology paves the way to extract a maximum of information from correlative hard X-ray nanoscopy at diffraction-limited storage rings.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"16 1","pages":"18-32"},"PeriodicalIF":2.6,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11168884","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：