June 7, 2022 Dataset Open Access

Zhdanov, Maksim; Ganeva, Marina; Randolph, Lisa; Kluge, Thomas; Hoffmann, Nico

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  <identifier identifierType="DOI">10.14278/rodare.1690</identifier>
  <creators>
    <creator>
      <creatorName>Zhdanov, Maksim</creatorName>
      <givenName>Maksim</givenName>
      <familyName>Zhdanov</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-3832-2577</nameIdentifier>
      <affiliation>Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany</affiliation>
    </creator>
    <creator>
      <creatorName>Ganeva, Marina</creatorName>
      <givenName>Marina</givenName>
      <familyName>Ganeva</familyName>
      <affiliation>Forschungszentrum Jülich GmbH, Jülich Centre for Neutron Science (JCNS) at Heinz Maier-Leibnitz Zentrum (MLZ), Garching, Germany</affiliation>
    </creator>
    <creator>
      <creatorName>Randolph, Lisa</creatorName>
      <givenName>Lisa</givenName>
      <familyName>Randolph</familyName>
      <affiliation>Department Physik, Universität Siegen, Siegen, Germany</affiliation>
    </creator>
    <creator>
      <creatorName>Kluge, Thomas</creatorName>
      <givenName>Thomas</givenName>
      <familyName>Kluge</familyName>
      <affiliation>Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany</affiliation>
    </creator>
    <creator>
      <creatorName>Hoffmann, Nico</creatorName>
      <givenName>Nico</givenName>
      <familyName>Hoffmann</familyName>
      <affiliation>Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Dataset for Inversion of GISAXS data (3 layers)</title>
  </titles>
  <publisher>Rodare</publisher>
  <publicationYear>2022</publicationYear>
  <subjects>
    <subject>GISAXS</subject>
    <subject>Inverse problems</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2022-06-07</date>
  </dates>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://rodare.hzdr.de/record/1690</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsIdenticalTo">https://www.hzdr.de/publications/Publ-34770</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.14278/rodare.1689</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://rodare.hzdr.de/communities/rodare</relatedIdentifier>
  </relatedIdentifiers>
  <version>0.1</version>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;The dataset consists of 50000 X-ray diffraction patterns simulated by BornAgain [1] software. For each simulation, a multilayer sample model of the following structure was used: air, tantalum oxide, tantalum, copper nitride, silicon dioxide, and substrate. Parameters of air, silicon dioxide, and substrate were kept fixed. Hence, each diffraction pattern is set to depend on the parameters of tantalum oxide, tantalum, and copper nitride layers. For each layer, those are real and complex parts of refractive index, thickness, roughness, Hurst parameter, and correlation length. Each simulation output is stored in an h5py file consisting of 1) diffraction image as a NumPy array of shape [1200, 120]; 2) parameters of a sample as a NumPy array with 18 elements. For further details regarding simulation see https://github.com/maxxxzdn/gisaxs-reconstruction/simulation/simulation.&lt;/p&gt;

&lt;p&gt;[1] Pospelov, G., Van Herck, W., Burle, J., Carmona Loaiza, J.M., Durniak, C., Fisher, J., Ganeva, M., Yurov, D., &amp;amp; Wuttke, J. (2020). BornAgain: software for simulating and fitting grazing-incidence small-angle scattering. &lt;em&gt;Journal of Applied Crystallography, 53&lt;/em&gt;, 262 - 276.&lt;/p&gt;</description>
  </descriptions>
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