Article
Energy & Fuels
Marc-Antoine Llobel, Guillaume Riviere, Charline Arrive, Stephanie Courtel, Godefroy Vannier, Stephane Cros, Muriel Matheron
Summary: Organic photovoltaics (OPV) have matured for market deployment, excelling in low-light performance for indoor light harvesting. Lack of methods to detect defective modules hinders their application. Discrepancies in parallel resistance between cells greatly affect OPV module performance.
Article
Energy & Fuels
Jackson W. Schall, Andrew Glaws, Nutifafa Y. Doumon, Timothy J. Silverman, Michael Owen-Bellini, Kent Terwilliger, Md Aslam Uddin, Prem Rana, Joseph J. Berry, Jinsong Huang, Laura T. Schelhas, Dana B. Kern
Summary: In this study, electroluminescence (EL) and thermal imaging were used to investigate the degradation of metal halide perovskite (MHP) photovoltaic (PV) mini-modules. Different spatial patterns were observed in the EL images depending on the external stress conditions. Dark speckle features dominated after UV stress, while lateral intensity gradients were prominent after thermal cycling stress. Multimodal electro-optical imaging, including EL, photoluminescence and dark lock-in thermography, provided a deeper understanding of the degradation modes. UV exposure and thermal cycling stress testing alone could not replicate the same degradation signatures observed after outdoor deployment, indicating the occurrence of multiple degradation modes. The spatial characterization of degradation modes provides a foundation for developing targeted accelerated stress testing procedures by comparing with outdoor aging.
Article
Materials Science, Multidisciplinary
Bernd Doll, Ernst Wittmann, Larry Lueer, Johannes Hepp, Claudia Buerhop-Lutz, Jens A. Hauch, Christoph J. Brabec, Ian Marius Peters
Summary: On-site imaging of modules in photovoltaic (PV) systems requires contact-free techniques with high throughput and low cost. This study presents a photoluminescence aerial imaging (PLAI) setup that uses a hexacopter drone equipped with an illumination unit and a near-infrared camera. The setup is capable of detecting and identifying defects in PV modules and achieves a high throughput of 13.6 PV modules per minute, with a feasible throughput of 300 PV modules per minute.
PHYSICA STATUS SOLIDI-RAPID RESEARCH LETTERS
(2023)
Article
Energy & Fuels
Abdelilah Et-taleby, Yassine Chaibi, Amine Allouhi, Mohammed Boussetta, Mohamed Benslimane
Summary: This study proposes a new model for detecting and classifying faults in electroluminescence images of PV panels. The model combines Convolutional Neural Network (CNN) and Support Vector Machine (SVM) for feature extraction and classification, resulting in improved classification performance.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Article
Energy & Fuels
Yihao Wang, Robert Lee Chin, Appu Paduthol, Weixin Zhai, Xiaojing Hao, Thorsten Trupke, Ziv Hameiri
Summary: This method utilizes an electroluminescence-based imaging technique to detect broken fingers in solar cells by comparing EL images taken with different injected current paths, effectively addressing series resistance-related problems, suitable for different types of solar cells, and easily implementable in commercial luminescence imaging systems.
Article
Physics, Applied
M. Vukovic, M. Hillestad, M. Jakovljevic, A. S. Flo, E. Olsen, I. Burud
Summary: Photoluminescence imaging under different irradiance conditions has been studied in the inspection of field-installed photovoltaic modules. The potential of photoluminescence images in defect analysis has been shown at low irradiance levels. A new method without the use of the lock-in technique has been proposed for photoluminescence imaging to filter sunlight. This study demonstrates the valuable information that can be obtained from photoluminescence imaging under diffuse irradiance conditions.
JOURNAL OF APPLIED PHYSICS
(2023)
Article
Energy & Fuels
Julien Dupuis, Gilles Plessis, Gilbert El Hajje, Eric Lajoie-Mazenc, Eric Sandre, Khalid Radouane, Patrick Dupeyrat
Summary: The authors report on the impact of light- and elevated temperature-induced degradation (LeTID) on bifacial photovoltaic modules and its potential effects on photovoltaic plants performance. They found that the rear side of bifacial modules is more sensitive to LeTID, leading to a variation in the bifaciality factor. The difficulty in evaluating maximal power degradation caused by LeTID is highlighted, but simulation results show that the impact of LeTID on PV plants can be mitigated by careful module selection based on climatic conditions.
PROGRESS IN PHOTOVOLTAICS
(2021)
Article
Energy & Fuels
Urtzi Otamendi, Inigo Martinez, Marco Quartulli, Igor G. Olaizola, Elisabeth Viles, Werther Cambarau
Summary: This article introduces an end-to-end deep learning pipeline that utilizes deep learning techniques to detect, locate, and segment cell-level anomalies in photovoltaic modules via EL images. The modular pipeline combines object detection, image classification, and weakly supervised segmentation techniques, allowing for upgrades and extensions towards further improvements and new functionalities in the state-of-the-art.
Article
Energy & Fuels
Ross Michael Dix-Peek, Eugene Ernest van Dyk, Frederik Jacobus Vorster
Summary: This paper presents a method for determining the electrical response of individual photovoltaic cells, which can be applied in commercial facilities and research laboratories. This method combines dark IV response and electroluminescence imaging technology, utilizing commercial equipment and standard PV labs. By optimizing the electrical parameters of individual cells, it can be used to investigate atypical module electrical responses and degradation in individual cells within modules.
ENERGY SCIENCE & ENGINEERING
(2021)
Review
Energy & Fuels
M. Waqar Akram, Guiqiang Li, Yi Jin, Xiao Chen
Summary: Photovoltaic (PV) has grown rapidly as a promising renewable energy technology, but there have been numerous cases of early failure and degradation, as well as increasing fire risks associated with PV modules. Timely, fast and accurate detection of failures is crucial for producing efficient and durable modules. However, the current visual monitoring and assessment methods in the field are dependent on human abilities and prone to human error, making them impractical for large-scale applications. Therefore, the automation of PV monitoring and assessment methods is becoming increasingly important.
Article
Energy & Fuels
Yang Zhao, Ke Zhan, Zhen Wang, Wenzhong Shen
Summary: This research presents a deep learning-based automatic detection method for multiple types of defects in PV modules production line, achieving improved efficiency and accuracy in defect detection. The method shows high potential for practical application in real production lines, demonstrating effectiveness in normal/defective module classification.
PROGRESS IN PHOTOVOLTAICS
(2021)
Article
Chemistry, Analytical
Jiachuan Yu, Yuan Yang, Hui Zhang, Han Sun, Zhisheng Zhang, Zhijie Xia, Jianxiong Zhu, Min Dai, Haiying Wen
Summary: This paper presents an automatic defect-inspection method for multi-cell monocrystalline PV modules using Electroluminescence (EL) imaging. The proposed method effectively extracts defect features and eliminates the influence of intrinsic structural features through processing and analysis of EL images. Experiments on multiple samples have demonstrated the robust performance of the method, which can accurately and quickly detect defects in PV modules.
Article
Energy & Fuels
Vishal E. Puranik, Rajesh Gupta
Summary: This study develops standardized electroluminescence (EL) methods for efficient investigation of potential-induced degradation shunting (PID-s) in photovoltaic modules. Three general cases are considered based on the availability of reference, and the proposed methods are validated experimentally and compared with standard I-V measurements. The results show that the EL methods efficiently investigate PID-s before significant power loss (<= 5%).
Article
Energy & Fuels
Ziyao Meng, Shengzhi Xu, Lichao Wang, Youkang Gong, Xiaodan Zhang, Ying Zhao
Summary: This paper proposes a YOLO-based object detection algorithm, YOLO-PV, which achieves high precision and real-time processing of photovoltaic module EL images through targeted network architecture design and data augmentation methods.
ENERGY SCIENCE & ENGINEERING
(2022)
Article
Instruments & Instrumentation
Maurycy Maziuk, Laura Jasinska, Jaroslaw Domaradzki, Pawel Chodasewicz
Summary: This article provides an overview of modern imaging methods used to detect various types of defects found in photovoltaic cells and panels, and offers comprehensive guidance and recommendations on the range of applicability and types of defects.
METROLOGY AND MEASUREMENT SYSTEMS
(2023)
Article
Energy & Fuels
Andreas Distler, Christoph J. Brabec, Hans-Joachim Egelhaaf
Summary: The research demonstrates the successful upscaling of highly efficient OPV systems to large area modules, achieving two new certified world record efficiencies by optimizing module layout and laser structuring processes, and maximizing geometric fill factors.
PROGRESS IN PHOTOVOLTAICS
(2021)
Article
Chemistry, Multidisciplinary
Nadine J. Schrenker, Zhuocheng Xie, Peter Schweizer, Marco Moninger, Felix Werner, Nicolas Karpstein, Mirza Makovic, George D. Spyropoulos, Manuela Goebelt, Silke Christiansen, Christoph J. Brabec, Erik Bitzek, Erdmann Spiecker
Summary: This study investigates the fundamental deformation modes of five-fold twinned AgNWs in anisotropic networks and observes the impact of network anisotropy on electrical performance. By using a scale-bridging microscopy approach, three fundamental deformation modes of NWs are identified, which can explain the behavior observed in the study.
Article
Multidisciplinary Sciences
Zhenrong Jia, Shucheng Qin, Lei Meng, Qing Ma, Indunil Angunawela, Jinyuan Zhang, Xiaojun Li, Yakun He, Wenbin Lai, Ning Li, Harald Ade, Christoph J. Brabec, Yongfang Li
Summary: The study demonstrates a simple strategy of extending the conjugation length of acceptor Y6 to synthesize a new narrow bandgap acceptor BTPV-4F, which shows great potential in tandem organic solar cells. By using BTPV-4F in the rear cell, tandem devices achieved a high power conversion efficiency of over 16.4% with good photostability, addressing previous limitations in near-infrared absorbing materials for tandem organic solar cells.
NATURE COMMUNICATIONS
(2021)
Article
Chemistry, Multidisciplinary
Rui Sun, Tao Wang, Yao Wu, Meng Zhang, Yunlong Ma, Zuo Xiao, Guanghao Lu, Liming Ding, Qingdong Zheng, Christoph J. Brabec, Yongfang Li, Jie Min
Summary: This study introduces a strategy using a binary solvent-chlorinated indium tin oxide (ITO) anode to enhance the performance of non-fullerene polymer solar cells (PSCs). Experimental results show that devices based on ITO-Cl-ODCB:H2O2 exhibit significantly better performance compared to those based on ITO/PEDOT:PSS, indicating its great potential for application in PEDOT:PSS-free PSCs.
ADVANCED FUNCTIONAL MATERIALS
(2021)
Article
Chemistry, Multidisciplinary
Manuel Daum, Sarah Deumel, Mykhailo Sytnyk, Hany A. Afify, Rainer Hock, Andreas Eigen, Baolin Zhao, Marus Halik, Albert These, Gebhard J. Matt, Christoph J. Brabec, Sandro F. Tedde, Wolfgang Heiss
Summary: The Cs3Bi2Br3I6 polycrystalline wafers, as a novel X-ray detector material, outperform other Bi-based semiconductors in terms of detector parameters and exhibit self-healing effects during aging, leading to an overall improvement in detector performance. This self-healing mechanism, expected to be beneficial for various polycrystalline ionic semiconductors, acts as an optimization tool for enhancing detector performance.
ADVANCED FUNCTIONAL MATERIALS
(2021)
Article
Chemistry, Multidisciplinary
Anna Aubele, Yakun He, Teresa Kraus, Ning Li, Elena Mena-Osteritz, Paul Weitz, Thomas Heumueller, Kaicheng Zhang, Christoph J. Brabec, Peter Baeuerle
Summary: A novel donor-acceptor dyad, 4, with excellent photovoltaic performance and stability, has been synthesized and applied in solution-processed single-material organic solar cells (SMOSCs).
ADVANCED MATERIALS
(2022)
Article
Physics, Applied
Fatima Akhundova, Larry Lueer, Andres Osvet, Jens Hauch, Ian Marius Peters, Karen Forberich, Ning Li, Christoph Brabec
Summary: A study was conducted on the influence of processing parameters on nonradiative losses in perovskite bulk, revealing the potential to control the photoluminescence quantum yield and optimize material morphology by varying the processing conditions. The research also found that nonradiative losses in polycrystalline perovskite films are attributed to increased domain size dispersion.
APPLIED PHYSICS LETTERS
(2021)
Editorial Material
Chemistry, Multidisciplinary
Ning Li, Christoph J. Brabec
SCIENCE CHINA-CHEMISTRY
(2021)
Article
Chemistry, Physical
Fu Yang, Lirong Dong, Dongju Jang, Begench Saparov, Kai Cheong Tam, Kaicheng Zhang, Ning Li, Christoph J. Brabec, Hans-Joachim Egelhaaf
Summary: This study presents a low-temperature fully printed perovskite solar cell production scheme using carbon as the top electrode, achieving highly efficient and stable PSCs under ambient conditions and meeting the requirements for industrial-scale production. The optimized carbon-PSCs show efficiencies exceeding 18% with enhanced stability, retaining 100% of their initial efficiency after 5000 hours in a humid atmosphere. Large-area perovskite modules with an efficiency of 15.3% are successfully obtained by optimizing femtosecond laser parameters. These results represent important progress towards the scalable production and global application of PSCs.
ADVANCED ENERGY MATERIALS
(2021)
Article
Energy & Fuels
Mathis Hoffmann, Thomas Koehler, Bernd Doll, Frank Schebesch, Florian Talkenberg, Ian Marius Peters, J. Christoph Brabec, Andreas Maier, Vincent Christlein
Summary: Visual inspection of solar modules is crucial in photovoltaic power plants. By applying multiframe superresolution (MFSR) to low-resolution measurements and fusing it with standard algorithms, defect recognition can be improved significantly. Additionally, automated crack segmentation using this method outperforms bicubic upsampling and the current state-of-the-art in automated inspection.
IEEE JOURNAL OF PHOTOVOLTAICS
(2021)
Article
Chemistry, Multidisciplinary
Yakun He, Benedict Hanisch, Andres Osvet, Larry Luer, Anna Aubele, Peter Bauerle, Weiwei Li, Ning Li, Christoph J. Brabec
Summary: The exciton dissociation between donor and acceptor is crucial for determining the photovoltaic performance of organic solar cells. Time-resolved photoluminescence investigations offer a potential method to separately determine the exciton splitting efficiency of donor and acceptor moieties in single component materials. Post-treatment can adjust the exciton splitting efficiency of donor or acceptor moieties separately in these materials, while excessive phase separation occurs in BHJ composites under external stress.
ISRAEL JOURNAL OF CHEMISTRY
(2022)
Article
Chemistry, Multidisciplinary
Hany A. Afify, Viktor Rehm, Anastasiia Barabash, Albert These, Jiyun Zhang, Andres Osvet, Christoph Schuesslbauer, Dominik Thiel, Tobias Ullrich, Martin Dierner, Thomas Przybilla, Johannes Will, Erdmann Spiecker, Dirk M. Guldi, Christoph J. Brabec, Wolfgang Heiss
Summary: This study demonstrates an antisolvent-vapor-assisted crystallization method for epitaxial growth of metal-halide-perovskites. By controlling the shape of micro-crystallites, single-mode operation of lasers with high environmental stability can be achieved, which is competitive with vapor-phase epitaxial microstructures.
ADVANCED FUNCTIONAL MATERIALS
(2022)
Article
Crystallography
Christian Kupfer, Jack Elia, Masashi Kato, Andres Osvet, Christoph J. Brabec
Summary: This paper presents a novel and facile synthesis route to obtain phase-pure Cs2TiBr6 and its lesser-studied iodine-based relatives via high-energy mechanochemical ball milling. The materials have certain optoelectronic properties and show potential for photovoltaic applications.
CRYSTAL RESEARCH AND TECHNOLOGY
(2023)
Proceedings Paper
Energy & Fuels
Mathis Hoffmann, Johannes Hepp, Bernd Doll, Claudia Buerhop-Lutz, Ian Marius Peters, Christoph Brabec, Andreas Maier, Vincent Christlein
Summary: This study successfully narrowed the gap in predicting power loss of photovoltaic modules between photoluminescence images and electroluminescence images using deep learning methods, achieving accurate prediction of module power and localizing power loss regions.
2021 IEEE 48TH PHOTOVOLTAIC SPECIALISTS CONFERENCE (PVSC)
(2021)
Article
Chemistry, Physical
Jinlong Hu, Xin Xu, Yijun Chen, Shaohang Wu, Zhen Wang, Yousheng Wang, Xiaofang Jiang, Boyuan Cai, Tingting Shi, Christoph J. Brabec, Yaohua Mai, Fei Guo
Summary: This study compensates for electronic defects at grain boundaries and surfaces in perovskite crystals by passivating with natural amino acid molecules, leading to enhanced performance and stability of solar devices. Arginine molecules exhibit the best passivation effects, improving optoelectronic properties and device performance of the perovskite films.
JOURNAL OF MATERIALS CHEMISTRY A
(2021)
