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@ARTICLE{Bornschlegl:1042669,
      author       = {Bornschlegl, Andreas J. and Duchstein, Patrick and Wu,
                      Jianchang and Rocha-Ortiz, Juan S. and Caicedo-Reina,
                      Mauricio and Ortiz, Alejandro and Insuasty, Braulio and
                      Zahn, Dirk and Lüer, Larry and Brabec, Christoph},
      title        = {{A}n {A}utomated {W}orkflow to {D}iscover the
                      {S}tructure–{S}tability {R}elations for {R}adiation {H}ard
                      {M}olecular {S}emiconductors},
      journal      = {Journal of the American Chemical Society},
      volume       = {147},
      number       = {2},
      issn         = {0002-7863},
      address      = {Washington, DC},
      publisher    = {ACS Publications},
      reportid     = {FZJ-2025-02638},
      pages        = {1957 - 1967},
      year         = {2025},
      abstract     = {Emerging photovoltaics for outer space applications are one
                      of the many examples where radiation hard molecular
                      semiconductors are essential. However, due to a lack of
                      general design principles, their resilience against
                      extra-terrestrial high-energy radiation can currently not be
                      predicted. In this work, the discovery of radiation hard
                      materials is accelerated by combining the strengths of
                      high-throughput, lab automation and machine learning. This
                      way, a large material library of more than 130 organic hole
                      transport materials is automatically processed, degraded,
                      and measured. The materials are degraded under ultraviolet-C
                      (UVC) light in a nitrogen atmosphere, serving as the
                      conditions for electromagnetic radiation hardness tests. A
                      value closely related to the differential quantum yield for
                      photodegradation is extracted from the evolution of the
                      UV–visible (UV–vis) spectra over time and used as a
                      stability target. Following this procedure, a stability
                      ranking spanning over 3 orders of magnitude was obtained.
                      Combining Gaussian Process Regression based on predictors
                      from structural fingerprints and manual filtering of the
                      materials by features, structure–stability relations for
                      UVC stable materials could be found: Fused aromatic ring
                      clusters are beneficial, whereas thiophene, methoxy and
                      vinylene groups are detrimental. Comparing the UV–vis
                      spectra of the degraded material in film and solution, bond
                      cleavage could be made out as the leading degradation
                      mechanism. Even though UVC light can in principle break most
                      organic bonds, the stable materials are able to distribute
                      and dissipate the energy well enough so that the chemical
                      structures remain stable. The established predictive model
                      quantifies the effect of specific molecular features on UVC
                      stability, allowing chemists to consider UVC stability in
                      their molecular design strategy. In the future, a larger
                      data set will allow to inversely design molecular
                      semiconductors which show high performance and radiation
                      hardness at the same time.},
      cin          = {IET-2},
      ddc          = {540},
      cid          = {I:(DE-Juel1)IET-2-20140314},
      pnm          = {1214 - Modules, stability, performance and specific
                      applications (POF4-121)},
      pid          = {G:(DE-HGF)POF4-1214},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {39752396},
      UT           = {WOS:001389970400001},
      doi          = {10.1021/jacs.4c14824},
      url          = {https://juser.fz-juelich.de/record/1042669},
}