Exploring High-Dimensional Data Space: Identifying Optimal Process Conditions in Photovoltaics

Changwon Suh; David Biagioni; Stephen Glynn; John Scharf; Miguel A. Contreras; Rommel Noufi; Wesley B. Jones

doi:10.1109/pvsc.2011.6186065

Exploring High-Dimensional Data Space: Identifying Optimal Process Conditions in Photovoltaics

Changwon Suh, David Biagioni, Stephen Glynn, John Scharf, Miguel A. Contreras, Rommel Noufi, Wesley B. Jones

Research output: Contribution to conference › Paper › peer-review

3 Scopus Citations

Abstract

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 CuIn _xGa _1-xSe ₂ (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.

Original language	American English
Pages	762-767
Number of pages	6
DOIs	https://doi.org/10.1109/pvsc.2011.6186065 https://doi.org/10.1109/PVSC.2011.6186065
State	Published - 2011
Event	37th IEEE Photovoltaic Specialists Conference, PVSC 2011 - Seattle, WA, United States Duration: 19 Jun 2011 → 24 Jun 2011

Conference

Conference	37th IEEE Photovoltaic Specialists Conference, PVSC 2011
Country/Territory	United States
City	Seattle, WA
Period	19/06/11 → 24/06/11

Bibliographical note

See NREL/CP-2C00-50693 for preprint

NREL Publication Number

NREL/CP-2C00-55762

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Cite this

Suh, C., Biagioni, D., Glynn, S., Scharf, J., Contreras, M. A., Noufi, R., & Jones, W. B. (2011). Exploring High-Dimensional Data Space: Identifying Optimal Process Conditions in Photovoltaics. 762-767. Paper presented at 37th IEEE Photovoltaic Specialists Conference, PVSC 2011, Seattle, WA, United States. https://doi.org/10.1109/pvsc.2011.6186065, https://doi.org/10.1109/PVSC.2011.6186065

@conference{ea24a00e5ac8478a8c2ab113e791e640,

title = "Exploring High-Dimensional Data Space: Identifying Optimal Process Conditions in Photovoltaics",

abstract = "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 CuIn xGa 1-xSe 2 (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.",

author = "Changwon Suh and David Biagioni and Stephen Glynn and John Scharf and Contreras, {Miguel A.} and Rommel Noufi and Jones, {Wesley B.}",

note = "See NREL/CP-2C00-50693 for preprint; 37th IEEE Photovoltaic Specialists Conference, PVSC 2011 ; Conference date: 19-06-2011 Through 24-06-2011",

year = "2011",

doi = "10.1109/pvsc.2011.6186065",

language = "American English",

pages = "762--767",

}

Suh, C, Biagioni, D, Glynn, S, Scharf, J, Contreras, MA, Noufi, R & Jones, WB 2011, 'Exploring High-Dimensional Data Space: Identifying Optimal Process Conditions in Photovoltaics', Paper presented at 37th IEEE Photovoltaic Specialists Conference, PVSC 2011, Seattle, WA, United States, 19/06/11 - 24/06/11 pp. 762-767. https://doi.org/10.1109/pvsc.2011.6186065, https://doi.org/10.1109/PVSC.2011.6186065

TY - CONF

T1 - Exploring High-Dimensional Data Space: Identifying Optimal Process Conditions in Photovoltaics

AU - Suh, Changwon

AU - Biagioni, David

AU - Glynn, Stephen

AU - Scharf, John

AU - Contreras, Miguel A.

AU - Noufi, Rommel

AU - Jones, Wesley B.

N1 - See NREL/CP-2C00-50693 for preprint

PY - 2011

Y1 - 2011

N2 - 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 CuIn xGa 1-xSe 2 (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.

AB - 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 CuIn xGa 1-xSe 2 (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.

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DO - 10.1109/pvsc.2011.6186065

M3 - Paper

AN - SCOPUS:84861056157

SP - 762

EP - 767

T2 - 37th IEEE Photovoltaic Specialists Conference, PVSC 2011

Y2 - 19 June 2011 through 24 June 2011

ER -

Exploring High-Dimensional Data Space: Identifying Optimal Process Conditions in Photovoltaics

Abstract

Conference

Bibliographical note

NREL Publication Number

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