skip to main content

SciTech ConnectSciTech Connect

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

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.
Authors:
 [1] ;  [2] ; ;  [3] ;  [4] ;  [5] ;  [6]
  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)
Publication Date:
OSTI Identifier:
22255002
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Chemical Physics; Journal Volume: 140; Journal Issue: 9; Other Information: (c) 2014 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL CHEMISTRY; 77 NANOSCIENCE AND NANOTECHNOLOGY; ADSORPTION; BINDING ENERGY; ELECTRONIC STRUCTURE; NANOSTRUCTURES; PARTICLES; SURFACES