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Título
Defect recognition by means of light and electron probe techniques for the characterization of mc-Si wafers and solar cells
Autor
Año del Documento
2016
Editorial
Elsevier
Descripción
Producción Científica
Documento Fuente
Superlattices and Microstructures, 2016, Volume 99, Pages 45-53
Abstract
Multicristalline Silicon (mc-Si) is the preferred material for current terrestrial photovoltaic applications. However, the high density of defects present in mc-Si deteriorates the material properties, in particular the minority carrier diffusion length. For this reason, a large effort to characterize the mc-Si material is demanded, aiming to visualize the defective areas and to quantify the type of defects, density and its origin. In this work, several complementary light and electron probe techniques are used for the analysis of both mc-Si wafers and solar cells. These techniques comprise both fast and whole-area detection techniques such as Photoluminescence imaging, and highly spatially resolved time consuming techniques, such as light and electron beam induced current techniques and μRaman spectroscopy. These techniques were applied to the characterization of different mc-Si wafers for solar cells, e.g. ribbon wafers, cast mc-Si as well as quasi-monocrystalline material, upgraded metallurgical mc-Si wafers, and finished solar cells.
Palabras Clave
Silicio multicristalino
Multicristalline Silicon
Corriente inducida por haz de luz
Light Beam Induced Current
Correiente inducida por electronos
Electron Beam Induced Current
LBIC
EBIC
ISSN
0749-6036
Revisión por pares
SI
Patrocinador
Junta de Castilla y León (programa de apoyo a proyectos de investigación - Ref. VA166A11-2)
Ministerio de Ciencia e Innovación (Proyect IPT-420000-2010-022 INNPACTO)
Ministerio de Economía, Industria y Competitividad (Project ENE2014-56069-C4-4-R)
Ministerio de Ciencia e Innovación (Proyect IPT-420000-2010-022 INNPACTO)
Ministerio de Economía, Industria y Competitividad (Project ENE2014-56069-C4-4-R)
Version del Editor
Idioma
eng
Derechos
openAccess
Collections
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