Data Mining-Aided Crystal Engineering for the Design of Transparent Conducting Oxides: Preprint

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The purpose of this paper is to accelerate the pace of material discovery processes by systematically visualizing the huge search space that conventionally needs to be explored. To this end, we demonstrate not only the use of empirical- or crystal chemistry-based physical intuition for decision-making, but also to utilize knowledge-based data mining methodologies in the context of finding p-type delafossite transparent conducting oxides (TCOs). We report on examples using high-dimensional visualizations such as radial visualization combined with machine learning algorithms such as k-nearest neighbor algorithm (k-NN) to better define and visualize the search space (i.e. structure maps) of functional materials ... continued below

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10 p.

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Suh, C.; Kim, K.; Berry, J. J.; Lee, J. & Jones, W. B. December 1, 2010.

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Description

The purpose of this paper is to accelerate the pace of material discovery processes by systematically visualizing the huge search space that conventionally needs to be explored. To this end, we demonstrate not only the use of empirical- or crystal chemistry-based physical intuition for decision-making, but also to utilize knowledge-based data mining methodologies in the context of finding p-type delafossite transparent conducting oxides (TCOs). We report on examples using high-dimensional visualizations such as radial visualization combined with machine learning algorithms such as k-nearest neighbor algorithm (k-NN) to better define and visualize the search space (i.e. structure maps) of functional materials design. The vital role of search space generated from these approaches is discussed in the context of crystal chemistry of delafossite crystal structure.

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10 p.

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  • Presented at the Materials Research Society Fall Meeting, 29 November - 3 December 2010, Boston, Massachusetts

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  • Report No.: NREL/CP-2C00-50079
  • Grant Number: AC36-08GO28308
  • Office of Scientific & Technical Information Report Number: 1001448
  • Archival Resource Key: ark:/67531/metadc833714

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  • December 1, 2010

Added to The UNT Digital Library

  • May 19, 2016, 3:16 p.m.

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  • April 4, 2017, 12:55 p.m.

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Suh, C.; Kim, K.; Berry, J. J.; Lee, J. & Jones, W. B. Data Mining-Aided Crystal Engineering for the Design of Transparent Conducting Oxides: Preprint, article, December 1, 2010; Golden, Colorado. (digital.library.unt.edu/ark:/67531/metadc833714/: accessed October 20, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.