% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Nguyen:917322,
      author       = {Nguyen, Binh Duong and Roder, Melissa and Danilewsky,
                      Andreas and Steiner, Johannes and Wellmann, Peter and
                      Sandfeld, Stefan},
      title        = {{A}utomated analysis of {X}-ray topography of 4{H}-{S}i{C}
                      wafers: {I}mage analysis, numerical computations, and
                      artificial intelligence approaches for locating and
                      characterizing screw dislocations},
      journal      = {Journal of materials research},
      volume       = {38},
      issn         = {1092-8928},
      address      = {Berlin},
      publisher    = {Springer},
      reportid     = {FZJ-2023-00550},
      pages        = {1254-1265},
      year         = {2023},
      abstract     = {The physical vapor transport (PVT) crystal growth process
                      of 4H-SiC wafers is typically accompanied by the occurrence
                      of a large variety of defect types such as screw or edge
                      dislocations, and basal plane dislocations. In particular,
                      screw dislocations may have a strong negative influence on
                      the performance of electronic devices due to the large,
                      distorted or even hollow core of such dislocations.
                      Therefore, analyzing and understanding these types of
                      defects is crucial also for the production of high-quality
                      semiconductor materials. This work uses automated image
                      analysis to provide dislocation information for computing
                      the stresses and strain energy of the wafer. Together with
                      using a genetic algorithm this allows us to predict the
                      dislocation positions, the Burgers vector magnitudes, and
                      the most likely configuration of Burgers vector signs for
                      the dislocations in the wafer.},
      cin          = {IAS-9},
      ddc          = {670},
      cid          = {I:(DE-Juel1)IAS-9-20201008},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511)},
      pid          = {G:(DE-HGF)POF4-5111},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000911279200005},
      doi          = {10.1557/s43578-022-00880-z},
      url          = {https://juser.fz-juelich.de/record/917322},
}