Exploring high-dimensional data space
Subtitle: identifying optimal process conditions in photovoltaics : preprint
By: Changwon Suh ... [et al.].
Contributors: National Renewable Energy Laboratory (U.S.); University of Colorado, Boulder; IEEE Photovoltaic Specialists Conference (37th : 2011 : Seattle, Wash.)
Series: NREL/CP -- 2C00-50693; Conference paper (National Renewable Energy Laboratory (U.S.)) -- NREL/CP-2 C 00-50693.
Publisher: National Renewable Energy Laboratory
Published: 2011
Place of publication: Golden, CO]
Language: eng
Format: [electronic resource] :
Subjects: Thin films; Research; Data mining; Photovoltaic power systems; Data processing; Visualization
Other titles: Exploring high dimensional data space
Description: We demonstrate how advanced exploratory data analysis coupled to data-mining techniques can be used to scrutinize the high-dimensional data space of photovoltaics in the context of thin films of Al-doped ZnO (AZO), which are essential materials as a transparent conducting oxide (TCO) layer in CuInxGa1-xSe2 (CIGS) solar cells. AZO data space, wherein each sample is synthesized from a different process history and assessed with various characterizations, is transformed, reorganized, and visualized in order to extract optimal process conditions. The data-analysis methods used include parallel coordinates, diffusion maps, and hierarchical agglomerative clustering algorithms combined with diffusion map embedding.
Notes: Title from title screen (viewed August 1, 2011).

"July 2011."

"Presented at the 37th IEEE Photovoltaic Specialists Conference (PVSC 37), Seattle, Washington, June 19-24, 2011."

Includes bibliographical references (p. 6).

DE-AC36-08GO28308

Full text available via Internet in .pdf format. Adobe Acrobat Reader required.