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Chemical Shifts in Molecular Solids by Machine Learning Datasets

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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>Ceriotti, Michele</dc:creator>
  <dc:creator>Emsley, Lyndon</dc:creator>
  <dc:creator>Paruzzo, Federico</dc:creator>
  <dc:creator>Hofstetter, Albert</dc:creator>
  <dc:creator>Musil, Félix</dc:creator>
  <dc:creator>De, Sandip</dc:creator>
  <dc:creator>Engel, Edgar A.</dc:creator>
  <dc:creator>Anelli, Andrea</dc:creator>
  <dc:date>2019-10-22</dc:date>
  <dc:description>We present a database of energy and NMR chemical shifts DFT calculations of 4150 crystal organic solids. The structures contain only H/C/N/O/S atoms and were subject to all-atoms geometry optimisation. Calculations were carried out using Quantum Espresso and GIPAW.</dc:description>
  <dc:identifier>https://materialscloud-archive-failover.cineca.it/record/2019.0023/v2</dc:identifier>
  <dc:identifier>doi:10.24435/materialscloud:2019.0023/v2</dc:identifier>
  <dc:identifier>mcid:2019.0023/v2</dc:identifier>
  <dc:identifier>oai:materialscloud.org:138</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>NMR</dc:subject>
  <dc:subject>Quantum Espresso</dc:subject>
  <dc:subject>GIPAW</dc:subject>
  <dc:subject>Energy Calculations</dc:subject>
  <dc:subject> Organic Solids</dc:subject>
  <dc:subject>Chemical Shifts</dc:subject>
  <dc:subject>SNSF</dc:subject>
  <dc:subject>MARVEL/DD1</dc:subject>
  <dc:title>Chemical Shifts in Molecular Solids by Machine Learning Datasets</dc:title>
  <dc:type>Dataset</dc:type>
</oai_dc:dc>