% 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”.

@MISC{Hilgers:1017559,
      author       = {Hilgers, Robin and Wortmann, Daniel and Blügel, Stefan},
      title        = {{W}orkflow, data processing, data analysis and predictive
                      {ML} scripts used for {DFT}-integrated machine learning
                      methodology in combination with the {FLAPW} code {FLEUR};
                      v1},
      reportid     = {FZJ-2023-04199},
      year         = {2023},
      note         = {MIT License},
      abstract     = {This code collection contains the Jupyter Notebooks, which
                      were used to implement an integrated machine learning
                      approach into AiiDA workflows, including submission scripts,
                      the integrated machine-learning training, selection and
                      prediction scripts, the processed data in a tabular form,
                      the corresponding analysis, and visualization scripts and
                      the integrated machine learning predictions and metrics
                      themselves for each batch. The methodology has been used on
                      magnetic 2D films with at most three 3d transition metal
                      layers on five FCC noble metal substrate layers. The purpose
                      of this publication is to encourage and enable other
                      scientists to implement the method and workflow of
                      integrated machine learning, as described in our upcoming
                      paper, themselves for their respective applications and ab
                      initio codes.This work was performed as part of the
                      Helmholtz School for Data Science in Life, Earth and Energy
                      (HDS-LEE) and received funding from the Helmholtz
                      Association of German Research Centres.},
      cin          = {IAS-1 / PGI-1},
      cid          = {I:(DE-Juel1)IAS-1-20090406 / I:(DE-Juel1)PGI-1-20110106},
      pnm          = {1212 - Materials and Interfaces (POF4-121) / HDS LEE -
                      Helmholtz School for Data Science in Life, Earth and Energy
                      (HDS LEE) (HDS-LEE-20190612)},
      pid          = {G:(DE-HGF)POF4-1212 / G:(DE-Juel1)HDS-LEE-20190612},
      typ          = {PUB:(DE-HGF)33},
      url          = {https://juser.fz-juelich.de/record/1017559},
}