Published March 7, 2014 | Version v1
Journal article Metadata-only

Informatics guided discovery of surface structure-chemistry relationships in catalytic nanoparticles

Creators

  • 1. Institute of Electronic Structure and Laser, FORTH, P.O. Box 1527, 71110 Heraklio, Crete (Greece)
  • 2. Department of Chemical Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15621 (United States)
  • 3. Materials Science and Engineering, Iowa State University, Ames, Iowa 50011 (United States)
  • 4. Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, Kentucky 40202 (United States)
  • 5. Department of Chemical Engineering, University of Louisville, Louisville, Kentucky 40202 (United States)
  • 6. Department of Physics and Astronomy and Center for Computational Sciences, University of Kentucky, Lexington, Kentucky 40506 (United States)

Description

A data driven discovery strategy based on statistical learning principles is used to discover new correlations between electronic structure and catalytic activity of metal surfaces. From the quantitative formulations derived from this informatics based model, a high throughput computational framework for predicting binding energy as a function of surface chemistry and adsorption configuration that bypasses the need for repeated electronic structure calculations has been developed

Additional details

Identifiers

DOI
10.1063/1.4867010;

Publishing Information

Journal Title
Journal of Chemical Physics
Journal Volume
140
Journal Issue
9
Journal Page Range
p. 094705-094705.8
ISSN
0021-9606
CODEN
JCPSA6

INIS

Country of Publication
United States
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
45076196
Subject category
S37: INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL CHEMISTRY; S77: NANOSCIENCE AND NANOTECHNOLOGY;
Descriptors DEI
ADSORPTION; BINDING ENERGY; ELECTRONIC STRUCTURE; NANOSTRUCTURES; PARTICLES; SURFACES
Descriptors DEC
ENERGY; SORPTION

Optional Information

Notes
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