Identifying the structure of supported metal catalysts using vibrational fingerprints from ab initio nanoscale models


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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Salcedo, Agustin</dc:creator>
  <dc:creator>Zengel, Deniz</dc:creator>
  <dc:creator>Maurer, Florian</dc:creator>
  <dc:creator>Casapu, Maria</dc:creator>
  <dc:creator>Grunwaldt, Jan-Dierk</dc:creator>
  <dc:creator>Michel, Carine</dc:creator>
  <dc:creator>Loffreda, David</dc:creator>
  <dc:date>2023-06-16</dc:date>
  <dc:description>The anharmonic infrared spectrum of adsorbed CO is simulated using density functional theory (DFT) to gain insight into the nature of Pd nanoparticles (NPs) supported on ceria. The authors systematically determine how the simulated infrared spectra are affected by CO coverage, NP size (0.5–1.5 nm), NP morphology (octahedral, icosahedral), and metal-support contact angle, by exploring a diversity of realistic models inspired by ab initio molecular dynamics.</dc:description>
  <dc:identifier>https://archive.materialscloud.org/record/2023.95</dc:identifier>
  <dc:identifier>doi:10.24435/materialscloud:5w-g1</dc:identifier>
  <dc:identifier>mcid:2023.95</dc:identifier>
  <dc:identifier>oai:materialscloud.org:1785</dc:identifier>
  <dc:language>en</dc:language>
  <dc:publisher>Materials Cloud</dc:publisher>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>carbon monoxide</dc:subject>
  <dc:subject>ceria</dc:subject>
  <dc:subject>palladium</dc:subject>
  <dc:subject>infrarred</dc:subject>
  <dc:subject>spectroscopy</dc:subject>
  <dc:title>Identifying the structure of supported metal catalysts using vibrational fingerprints from ab initio nanoscale models</dc:title>
  <dc:type>Dataset</dc:type>
</oai_dc:dc>