Leslie Kurumundayil, K. Ramspeck, S. Rein, M. Demant
{"title":"每个细胞都需要一个美丽的图像:高通量生产的实时接触测量","authors":"Leslie Kurumundayil, K. Ramspeck, S. Rein, M. Demant","doi":"10.1051/epjpv/2022033","DOIUrl":null,"url":null,"abstract":"The future of the energy transition will lead to a terrawatt-scale photovoltaic market, which can be served cost-effectively primarily by means of high-throughput production of solar cells. In addition to high-throughput production, characterization must be adapted to highest cycle times. Therefore, we present an innovative approach to detect image defects in solar cells using on-the-fly electroluminescence measurements. When a solar cell passes a standard current–voltage (I–V) unit, the cell is stopped, contacted, measured, released, and afterwards again accelerated. In contrast to this, contacting and measuring the sample on-the-fly saves a lot of time. Yet, the resulting images are blurred due to high-speed motion. For the development of such an on-the-fly contact measurement tool, a deblurring method is developed in this work. Our deep-learning-based deblurring model enables to present a clean EL image of the solar cell to the human operator and allows for a proper defect detection, reaching a correlation coefficient of 0.84.","PeriodicalId":42768,"journal":{"name":"EPJ Photovoltaics","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Every cell needs a beautiful image: on-the-fly contacting measurements for high-throughput production\",\"authors\":\"Leslie Kurumundayil, K. Ramspeck, S. Rein, M. Demant\",\"doi\":\"10.1051/epjpv/2022033\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The future of the energy transition will lead to a terrawatt-scale photovoltaic market, which can be served cost-effectively primarily by means of high-throughput production of solar cells. In addition to high-throughput production, characterization must be adapted to highest cycle times. Therefore, we present an innovative approach to detect image defects in solar cells using on-the-fly electroluminescence measurements. When a solar cell passes a standard current–voltage (I–V) unit, the cell is stopped, contacted, measured, released, and afterwards again accelerated. In contrast to this, contacting and measuring the sample on-the-fly saves a lot of time. Yet, the resulting images are blurred due to high-speed motion. For the development of such an on-the-fly contact measurement tool, a deblurring method is developed in this work. Our deep-learning-based deblurring model enables to present a clean EL image of the solar cell to the human operator and allows for a proper defect detection, reaching a correlation coefficient of 0.84.\",\"PeriodicalId\":42768,\"journal\":{\"name\":\"EPJ Photovoltaics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EPJ Photovoltaics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1051/epjpv/2022033\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"PHYSICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EPJ Photovoltaics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1051/epjpv/2022033","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PHYSICS, APPLIED","Score":null,"Total":0}
Every cell needs a beautiful image: on-the-fly contacting measurements for high-throughput production
The future of the energy transition will lead to a terrawatt-scale photovoltaic market, which can be served cost-effectively primarily by means of high-throughput production of solar cells. In addition to high-throughput production, characterization must be adapted to highest cycle times. Therefore, we present an innovative approach to detect image defects in solar cells using on-the-fly electroluminescence measurements. When a solar cell passes a standard current–voltage (I–V) unit, the cell is stopped, contacted, measured, released, and afterwards again accelerated. In contrast to this, contacting and measuring the sample on-the-fly saves a lot of time. Yet, the resulting images are blurred due to high-speed motion. For the development of such an on-the-fly contact measurement tool, a deblurring method is developed in this work. Our deep-learning-based deblurring model enables to present a clean EL image of the solar cell to the human operator and allows for a proper defect detection, reaching a correlation coefficient of 0.84.