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Title: JCAP images and absorption spectra for 179072 metal oxides

Abstract

Experimental data for inkjet printed metal oxides which compositions, images from a flatbed scanner, and absorption spectra from dual-sphere UV-vis. See 10.1039/C8SC03077D for details.

Creator(s)/Author(s):
ORCiD logo ; ORCiD logo ; ; ;
Publication Date:
Other Number(s):
10.22002/D1.1103
DOE Contract Number:  
SC0004993
Product Type:
Dataset
Research Org.:
California Inst. of Technology (CalTech), Pasadena, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
Subject:
36 MATERIALS SCIENCE
Keywords:
metal oxides; optical absorption; solar fuels; high throughput experimentation
OSTI Identifier:
1479489
DOI:
10.22002/D1.1103

Citation Formats

Gregoire, John M, Stein, Helge S, Soedarmadji, Edwin, Newhouse, Paul F, and Guevarra, Dan. JCAP images and absorption spectra for 179072 metal oxides. United States: N. p., 2018. Web. doi:10.22002/D1.1103.
Gregoire, John M, Stein, Helge S, Soedarmadji, Edwin, Newhouse, Paul F, & Guevarra, Dan. JCAP images and absorption spectra for 179072 metal oxides. United States. doi:10.22002/D1.1103.
Gregoire, John M, Stein, Helge S, Soedarmadji, Edwin, Newhouse, Paul F, and Guevarra, Dan. 2018. "JCAP images and absorption spectra for 179072 metal oxides". United States. doi:10.22002/D1.1103. https://www.osti.gov/servlets/purl/1479489. Pub date:Mon Oct 29 00:00:00 EDT 2018
@article{osti_1479489,
title = {JCAP images and absorption spectra for 179072 metal oxides},
author = {Gregoire, John M and Stein, Helge S and Soedarmadji, Edwin and Newhouse, Paul F and Guevarra, Dan},
abstractNote = {Experimental data for inkjet printed metal oxides which compositions, images from a flatbed scanner, and absorption spectra from dual-sphere UV-vis. See 10.1039/C8SC03077D for details.},
doi = {10.22002/D1.1103},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {10}
}

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Works referenced in this record:

Machine learning of optical properties of materials – predicting spectra from images and images from spectra
journal, January 2019

  • Stein, Helge S.; Guevarra, Dan; Newhouse, Paul F.
  • Chemical Science, Vol. 10, Issue 1
  • DOI: 10.1039/C8SC03077D

    Works referencing / citing this record:

    Machine learning of optical properties of materials – predicting spectra from images and images from spectra
    journal, January 2019

    • Stein, Helge S.; Guevarra, Dan; Newhouse, Paul F.
    • Chemical Science, Vol. 10, Issue 1
    • DOI: 10.1039/C8SC03077D