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

Changwon Suh, Kwiseon Kim, Joseph J. Berry, Jinsuk Lee, Wesley B. Jones

Research output: Contribution to conferencePaperpeer-review

1 Scopus Citations


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.

Original languageAmerican English
Number of pages7
StatePublished - 2012
Event2010 MRS Fall Meeting - Boston, MA, United States
Duration: 29 Nov 20103 Dec 2010


Conference2010 MRS Fall Meeting
Country/TerritoryUnited States
CityBoston, MA

NREL Publication Number

  • NREL/CP-2C00-49937

Other Report Number

  • Paper No. 1315-MM02-07


  • material discovery process
  • transparent conducting oxides


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