Datamining and analysis of the key parameters in organic solar cells

Conference item

The production process of organic solar cells (OSCs) is investigated and the effects of parameter variations on experimental results are analysed with the Principal Component Analysis (PCA). This statistical method is applied to an exemplar data set, in which the materials' concentration in the absorber solution and the spincoating speed of the absorber solution were varied intentionally. In addition to the remaining production parameters, the time intervals between the steps were included in the analysis. A large part of the variance in the experimental results can be explained with the evaporation conditions, the spincoating speed and the concentrations in the absorber solution. The PCA also confirms that the OSC is a complex and interdependent system, where one has to analyse the influence of several parameters at the same time in order to understand their effects on the OSC properties. The PCA results will be used to focus further experiments on the identified key parameters.

Authors: Riede, M; Liehr, A; Glatthaar, M; Niggemann, M; Zimmermann, B

• Publication status: Published
• Peer review status: Reviewed (other)
• Publisher: Society of Photo-Optical Instrumentation Engineers
• Host title: Proceedings of SPIE - The International Society for Optical Engineering
• Volume: 6197
• Publication date: 2006-01-01
• DOI: 10.1117/12.662974
• ISSN: 0277-786X
• ISBN-10: 0819462535
• ISBN-13: 9780819462534
• Language: English
• Keywords: Datamining; Electronic Laboratory Notebook; Principal Component Analysis; Organic Solar Cells