Pub Date : 2025-11-10DOI: 10.1109/JPHOTOV.2025.3625301
Apoorva Choumal;M. Rizwan;Shatakshi
Reliable operation of photovoltaic (PV) fleets with high grid penetration demands prediction tools that translate plant-level irradiance variability into actionable intelligence for PV power management and balance-of-system design. Reliably managing high penetrations of solar PV within modern grids requires predictions that reflect the systemic consequences of fast renewable variability across cyber-physical energy infrastructure. This article proposes RR-LTNet, a ramp-rate (RR)-centric prediction architecture that elevates the RR as the core variability feature linking plant-level intermittency to grid-level operational risk. RR-LTNet first performs dynamic clustering of RR regimes to characterize rapid weather transitions and stability conditions. These regimes taken as feature for hybrid temporal learner that fuses recurrent memory with temporal convolution to capture multiscale dynamics. For predictive assessment, numerical experiments are conducted on one year solar power database of the Yulara Solar Project, Australia. The proposed RR-LTNet consistently outperforms other feature extraction methods by achieving up to 90% reductions in root mean square error (RMSE) for 5-min resolution. The reductions are significantly larger when baseline models are augmented with RR-aware features than when those features are absent. Cross-site validation on two additional PV plants with different capacity and data distribution confirms robustness and consistency required for system engineering deployment across fleets. By surfacing variability intelligence in real time, RR-LTNet supports PV-specific tasks central to reserve scheduling, advanced simulation of PV plant-grid interactions. This framework thus bridges PV monitoring analytics with system level reliability engineering, accelerating the integration of large-scale PV into modern power systems.
{"title":"RR-LTNet: Ramp-Rate-Centric Deep Learning Framework for Short-Horizon Photovoltaic Power Prediction","authors":"Apoorva Choumal;M. Rizwan;Shatakshi","doi":"10.1109/JPHOTOV.2025.3625301","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3625301","url":null,"abstract":"Reliable operation of photovoltaic (PV) fleets with high grid penetration demands prediction tools that translate plant-level irradiance variability into actionable intelligence for PV power management and balance-of-system design. Reliably managing high penetrations of solar PV within modern grids requires predictions that reflect the systemic consequences of fast renewable variability across cyber-physical energy infrastructure. This article proposes RR-LTNet, a ramp-rate (RR)-centric prediction architecture that elevates the RR as the core variability feature linking plant-level intermittency to grid-level operational risk. RR-LTNet first performs dynamic clustering of RR regimes to characterize rapid weather transitions and stability conditions. These regimes taken as feature for hybrid temporal learner that fuses recurrent memory with temporal convolution to capture multiscale dynamics. For predictive assessment, numerical experiments are conducted on one year solar power database of the Yulara Solar Project, Australia. The proposed RR-LTNet consistently outperforms other feature extraction methods by achieving up to 90% reductions in root mean square error (RMSE) for 5-min resolution. The reductions are significantly larger when baseline models are augmented with RR-aware features than when those features are absent. Cross-site validation on two additional PV plants with different capacity and data distribution confirms robustness and consistency required for system engineering deployment across fleets. By surfacing variability intelligence in real time, RR-LTNet supports PV-specific tasks central to reserve scheduling, advanced simulation of PV plant-grid interactions. This framework thus bridges PV monitoring analytics with system level reliability engineering, accelerating the integration of large-scale PV into modern power systems.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"16 1","pages":"176-186"},"PeriodicalIF":2.6,"publicationDate":"2025-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802381","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 : 2025-11-07DOI: 10.1109/JPHOTOV.2025.3619977
Saravana Kumar;Hari Narayan;Christian Diestel;Jurriaan Schmitz;Jonas Haunschild;Stefan Rein;Stefan J. Rupitsch
This study presents an inline-compatible technique based on reflectance spectroscopy for characterizing both the thickness and crystalline volume fraction of polysilicon (poly-Si) layers in tunnel oxide passivated contact solar cell precursors, serving as an intermediate characterization step suitable for production and process control. An optical model based on the Fresnel equations and the transfer-matrix method is used to simulate the reflectance of a poly-Si layer on a planar silicon substrate quantitatively. The Bruggeman effective medium approximation is used to define poly-Si as crystalline silicon particles dispersed in an amorphous silicon matrix. By treating the poly-Si layer thickness and crystalline volume fraction as fit parameters, estimates of these values can be obtained from the measured inline reflectance spectra using the developed optical model. The estimated thicknesses and the crystalline volume fractions show a good correlation with the reference thickness values measured from scanning electron microscopy (SEM) and reference crystalline volume fraction values estimated with Raman spectroscopy, respectively. The maximum relative difference in thickness values obtained from reflectance spectra and SEM measurements is only 3%. Moreover, the maximum relative difference in crystalline volume fractions derived from reflectance and Raman spectra is just 1.8%.
{"title":"Inline Characterization of Polysilicon Layers in TOPCon Solar Cell Precursors With Reflectance Spectroscopy","authors":"Saravana Kumar;Hari Narayan;Christian Diestel;Jurriaan Schmitz;Jonas Haunschild;Stefan Rein;Stefan J. Rupitsch","doi":"10.1109/JPHOTOV.2025.3619977","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3619977","url":null,"abstract":"This study presents an inline-compatible technique based on reflectance spectroscopy for characterizing both the thickness and crystalline volume fraction of polysilicon (poly-Si) layers in tunnel oxide passivated contact solar cell precursors, serving as an intermediate characterization step suitable for production and process control. An optical model based on the Fresnel equations and the transfer-matrix method is used to simulate the reflectance of a poly-Si layer on a planar silicon substrate quantitatively. The Bruggeman effective medium approximation is used to define poly-Si as crystalline silicon particles dispersed in an amorphous silicon matrix. By treating the poly-Si layer thickness and crystalline volume fraction as fit parameters, estimates of these values can be obtained from the measured inline reflectance spectra using the developed optical model. The estimated thicknesses and the crystalline volume fractions show a good correlation with the reference thickness values measured from scanning electron microscopy (SEM) and reference crystalline volume fraction values estimated with Raman spectroscopy, respectively. The maximum relative difference in thickness values obtained from reflectance spectra and SEM measurements is only 3%. Moreover, the maximum relative difference in crystalline volume fractions derived from reflectance and Raman spectra is just 1.8%.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"16 1","pages":"113-119"},"PeriodicalIF":2.6,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802326","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 : 2025-11-03DOI: 10.1109/JPHOTOV.2025.3616590
Anupam Yedida;Revathy Padmanabhan
While bifacial tandem photovoltaic technology is promising as it is able to generate higher electrical power output by accessing illumination from both front and rear surfaces, a thorough investigation of the performance limits of bifacial tandems with different architectures/arrangements and under different conditions has not been explored. In this work, we present a comprehensive analytical framework based on the principle of detailed balance to assess the performance limits of bifacial tandems spanning multiple architectures, including unconstrained, current-matched (CM), and voltage-matched (VM) configurations. Our methodology explores the performance benefits of incorporating area-decoupled subcells across layers and examines the impact of different bandgap arrangements (monotonic and non-monotonic) on the performance. We show that having non-monotonic arrangement of bandgaps under optimal albedo conditions can significantly enhance the performance of bifacial tandems. In addition, we analyze the performance resilience of each configuration and bandgap arrangement to spectral variations induced by environmental factors such as shading, fluctuations in temperature, and albedo. This provides crucial design guidelines for the design, fabrication, and estimation of the performance limits of these solar cell architectures in different conditions.
{"title":"Performance Limits in Bifacial Tandem Solar Cell Modules for Multiple Configurations","authors":"Anupam Yedida;Revathy Padmanabhan","doi":"10.1109/JPHOTOV.2025.3616590","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3616590","url":null,"abstract":"While bifacial tandem photovoltaic technology is promising as it is able to generate higher electrical power output by accessing illumination from both front and rear surfaces, a thorough investigation of the performance limits of bifacial tandems with different architectures/arrangements and under different conditions has not been explored. In this work, we present a comprehensive analytical framework based on the principle of detailed balance to assess the performance limits of bifacial tandems spanning multiple architectures, including unconstrained, current-matched (CM), and voltage-matched (VM) configurations. Our methodology explores the performance benefits of incorporating area-decoupled subcells across layers and examines the impact of different bandgap arrangements (monotonic and non-monotonic) on the performance. We show that having non-monotonic arrangement of bandgaps under optimal albedo conditions can significantly enhance the performance of bifacial tandems. In addition, we analyze the performance resilience of each configuration and bandgap arrangement to spectral variations induced by environmental factors such as shading, fluctuations in temperature, and albedo. This provides crucial design guidelines for the design, fabrication, and estimation of the performance limits of these solar cell architectures in different conditions.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"16 1","pages":"98-112"},"PeriodicalIF":2.6,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802335","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 : 2025-11-03DOI: 10.1109/JPHOTOV.2025.3619980
Daolei Wang;Zhi Huang;Lei Peng;Peng Yan;Shaokai Zheng;Jiawen Liu;Yang Long
To address the challenges of blurred target boundaries, uneven feature distribution, and high computational cost in complex photovoltaic (PV) environments, this article proposes a lightweight uncrewed aerial vehicle (UAV)-based infrared hotspot detection model—real-time detection transformer (RTDETR)-CELite. Utilizing RTDETR-R18, the model incorporates the CSP_ELGCA_CGLU module, which integrates local-global attention and gated channel enhancement. This improves the perception of key regions while reducing computational complexity. In addition, a ConvEdgeFusion module is designed to combine shallow edge structures with multiscale semantic features. This improvement improves the model’s ability to accurately depict hot spot boundaries and their distribution areas, thereby significantly reducing false positives and false negatives. Experimental results show that RTDETR-CELite significantly reduces the model scale without affecting detection performance. Compared to the original RTDETR-R18, mAP50 improves from 82.04% to 84.06%, and mAP50:95 improves from 62.01% to 62.56%. The number of parameters decreases by 31.6% to 13.6M, computational cost drops by 17.4% to 47.1 GFLOPs, and inference speed increases to 300.5 FPS. These results indicate that RTDETR-CELite strikes an effective compromise between precision and computational efficiency, rendering it highly applicable to UAV-based or edge-device deployment for timely identification of PV hotspots, and showcasing promising potential in practical scenarios.
{"title":"RTDETR-CELite: Lightweight Remote Sensing PV Defect Detection via Edge-Aware and Cross-Channel Feature Fusion","authors":"Daolei Wang;Zhi Huang;Lei Peng;Peng Yan;Shaokai Zheng;Jiawen Liu;Yang Long","doi":"10.1109/JPHOTOV.2025.3619980","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3619980","url":null,"abstract":"To address the challenges of blurred target boundaries, uneven feature distribution, and high computational cost in complex photovoltaic (PV) environments, this article proposes a lightweight uncrewed aerial vehicle (UAV)-based infrared hotspot detection model—real-time detection transformer (RTDETR)-CELite. Utilizing RTDETR-R18, the model incorporates the CSP_ELGCA_CGLU module, which integrates local-global attention and gated channel enhancement. This improves the perception of key regions while reducing computational complexity. In addition, a ConvEdgeFusion module is designed to combine shallow edge structures with multiscale semantic features. This improvement improves the model’s ability to accurately depict hot spot boundaries and their distribution areas, thereby significantly reducing false positives and false negatives. Experimental results show that RTDETR-CELite significantly reduces the model scale without affecting detection performance. Compared to the original RTDETR-R18, mAP50 improves from 82.04% to 84.06%, and mAP50:95 improves from 62.01% to 62.56%. The number of parameters decreases by 31.6% to 13.6M, computational cost drops by 17.4% to 47.1 GFLOPs, and inference speed increases to 300.5 FPS. These results indicate that RTDETR-CELite strikes an effective compromise between precision and computational efficiency, rendering it highly applicable to UAV-based or edge-device deployment for timely identification of PV hotspots, and showcasing promising potential in practical scenarios.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"16 1","pages":"160-175"},"PeriodicalIF":2.6,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802390","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 : 2025-10-31DOI: 10.1109/JPHOTOV.2025.3620568
Wilkin Wöhler;Johannes M. Greulich;Andreas W. Bett
We derive an analytical description of leakage currents in an ohmic system of two conductive layers, with current in- and outflow at two line contacts on the first layer, and current flow in the second layer induced over a resistive interface. Examples of such interfaces in the photovoltaic context include the tunnel interface of TOPCon solar cells, the high-low junction of silicon heterojunction (SHJ) solar cells, and p-n junctions for low current densities. Experimentally the modeled leakage currents are observed in measurements of transfer length method (TLM) samples of SHJ solar cells due to the finite shunt resistivity of the p-n junction. Using the new model, we find that for a typical TLM-setup with a contacting distance of $l_{text{c}}=text{1 cm}$, apparent sheet resistance reductions of 0.3, 2.6, and 9.6 $Omega$ for a top layer of $R_{1}=text{100};{Omega }$ occur for interface resistivities $rho _{text{c}}$ of 100, 10, and 1 $text{k}Omega text{cm}^{2}$, respectively. Evaluating the measurement example by the commonly used linear regression, a twice higher contact resistivity is found in comparison to a numerical least square fit of the new model. Similar results are obtained in a synthetic data study using the solar cell simulation software Quokka3, with contact resistivity deviations of up to $text{10 m} Omega text{cm}^{2}$ for the linear regression evaluation. By evaluating the same data with the new analytical model, the original simulation parameters of contact resistivity and sheet resistance are recovered with relative deviations below 0.2%.
{"title":"Analytical Model of Leakage Currents in Contact Resistivity Measurements on Silicon Solar Cells","authors":"Wilkin Wöhler;Johannes M. Greulich;Andreas W. Bett","doi":"10.1109/JPHOTOV.2025.3620568","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3620568","url":null,"abstract":"We derive an analytical description of leakage currents in an ohmic system of two conductive layers, with current in- and outflow at two line contacts on the first layer, and current flow in the second layer induced over a resistive interface. Examples of such interfaces in the photovoltaic context include the tunnel interface of TOPCon solar cells, the high-low junction of silicon heterojunction (SHJ) solar cells, and p-n junctions for low current densities. Experimentally the modeled leakage currents are observed in measurements of transfer length method (TLM) samples of SHJ solar cells due to the finite shunt resistivity of the p-n junction. Using the new model, we find that for a typical TLM-setup with a contacting distance of <inline-formula><tex-math>$l_{text{c}}=text{1 cm}$</tex-math></inline-formula>, apparent sheet resistance reductions of 0.3, 2.6, and 9.6 <inline-formula><tex-math>$Omega$</tex-math></inline-formula> for a top layer of <inline-formula><tex-math>$R_{1}=text{100};{Omega }$</tex-math></inline-formula> occur for interface resistivities <inline-formula><tex-math>$rho _{text{c}}$</tex-math></inline-formula> of 100, 10, and 1 <inline-formula><tex-math>$text{k}Omega text{cm}^{2}$</tex-math></inline-formula>, respectively. Evaluating the measurement example by the commonly used linear regression, a twice higher contact resistivity is found in comparison to a numerical least square fit of the new model. Similar results are obtained in a synthetic data study using the solar cell simulation software Quokka3, with contact resistivity deviations of up to <inline-formula><tex-math>$text{10 m} Omega text{cm}^{2}$</tex-math></inline-formula> for the linear regression evaluation. By evaluating the same data with the new analytical model, the original simulation parameters of contact resistivity and sheet resistance are recovered with relative deviations below 0.2%.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"16 1","pages":"120-127"},"PeriodicalIF":2.6,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802344","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 : 2025-10-28DOI: 10.1109/JPHOTOV.2025.3626191
{"title":"2025 Index IEEE Journal of Photovoltaics","authors":"","doi":"10.1109/JPHOTOV.2025.3626191","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3626191","url":null,"abstract":"","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"15 6","pages":"995-1026"},"PeriodicalIF":2.6,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11219677","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145405266","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.2025.3611428
Mirra M. Rasmussen;J. Diego Zubieta Sempertegui;Nicholas Moser-Mancewicz;Jonathan L. Bryan;Natasha E. Hjerrild;Kristopher O. Davis;Mariana I. Bertoni;Laura S. Bruckman;Ina T. Martin
Advanced Si photovoltaic architectures incorporate different materials and processing pathways that influence degradation modes. Ultraviolet-induced degradation (UVID) is an understudied degradation mode for advanced cell architectures and is of increasing concern to industry due to growing adoption of UV-transparent encapsulation and bifacial technologies. In order to adopt new and evolving technologies confidently, novel component materials and processing techniques must be evaluated and designed for long-term stability, in addition to the conventional design focus on efficiency. In this work, a study protocol framework is presented for the rapid screening of unencapsulated devices against UVID. Unencapsulated passivated emitter rear contact (PERC) and tunnel oxide passivated contact (TOPCon) devices were aged under different UV irradiance intensities and measured via conventional nondestructive electrical characterization methods to assess performance degradation. Based on the results, protocol efficacy and recommendations for further study are discussed. This work is part of a broader effort to develop rapid screening processes that cut across architectures and exposure conditions to aid module manufacturers in vetting new materials choices for long-term stability.
{"title":"High-Intensity UV Exposure for the Rapid Screening of Silicon Photovoltaic Architectures","authors":"Mirra M. Rasmussen;J. Diego Zubieta Sempertegui;Nicholas Moser-Mancewicz;Jonathan L. Bryan;Natasha E. Hjerrild;Kristopher O. Davis;Mariana I. Bertoni;Laura S. Bruckman;Ina T. Martin","doi":"10.1109/JPHOTOV.2025.3611428","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3611428","url":null,"abstract":"Advanced Si photovoltaic architectures incorporate different materials and processing pathways that influence degradation modes. Ultraviolet-induced degradation (UVID) is an understudied degradation mode for advanced cell architectures and is of increasing concern to industry due to growing adoption of UV-transparent encapsulation and bifacial technologies. In order to adopt new and evolving technologies confidently, novel component materials and processing techniques must be evaluated and designed for long-term stability, in addition to the conventional design focus on efficiency. In this work, a study protocol framework is presented for the rapid screening of unencapsulated devices against UVID. Unencapsulated passivated emitter rear contact (PERC) and tunnel oxide passivated contact (TOPCon) devices were aged under different UV irradiance intensities and measured via conventional nondestructive electrical characterization methods to assess performance degradation. Based on the results, protocol efficacy and recommendations for further study are discussed. This work is part of a broader effort to develop rapid screening processes that cut across architectures and exposure conditions to aid module manufacturers in vetting new materials choices for long-term stability.","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"16 1","pages":"142-149"},"PeriodicalIF":2.6,"publicationDate":"2025-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802368","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 : 2025-10-22DOI: 10.1109/JPHOTOV.2025.3621371
{"title":"Call for Papers for a Special Issue of IEEE Transactions on Electron Devices on “Reliability of Advanced Nodes”","authors":"","doi":"10.1109/JPHOTOV.2025.3621371","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3621371","url":null,"abstract":"","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"15 6","pages":"993-994"},"PeriodicalIF":2.6,"publicationDate":"2025-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11214299","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145339711","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.2025.3621367
{"title":"IEEE Journal of Photovoltaics Information for Authors","authors":"","doi":"10.1109/JPHOTOV.2025.3621367","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3621367","url":null,"abstract":"","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"15 6","pages":"C3-C3"},"PeriodicalIF":2.6,"publicationDate":"2025-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11214302","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145339692","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.2025.3621369
{"title":"Call for Papers for a Special Issue of IEEE Transactions on Electron Devices on “Ultrawide Band Gap Semiconductor Device for RF, Power and Optoelectronic Applications”","authors":"","doi":"10.1109/JPHOTOV.2025.3621369","DOIUrl":"https://doi.org/10.1109/JPHOTOV.2025.3621369","url":null,"abstract":"","PeriodicalId":445,"journal":{"name":"IEEE Journal of Photovoltaics","volume":"15 6","pages":"991-992"},"PeriodicalIF":2.6,"publicationDate":"2025-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11214309","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145339687","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}
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