% 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{Mashkov:1046021,
      author       = {Mashkov, Oleksandr and Leihkamm, Lewin and Stroyuk,
                      Oleksandr and Buerhop, Claudia and Winkler, Thilo and
                      Ghaffari, Ones and Vorstoffel, Stefanie and Wittmann, Ernst
                      and Hauch, Jens and Peters, Ian Marius},
      title        = {{H}igh‐{T}hroughput {PV} {M}odule {D}iagnostics using a
                      {C}ompact {NIR} {S}pectrometer},
      journal      = {Solar RRL},
      volume       = {},
      issn         = {2367-198X},
      address      = {Weinheim},
      publisher    = {Wiley-VCH},
      reportid     = {FZJ-2025-03661},
      pages        = {202500323},
      year         = {2025},
      abstract     = {The degradation of backsheets and encapsulants in
                      photovoltaic (PV) modules compromises their long-term
                      performance and reliability. This study investigates the use
                      of a compact near-infrared (NIR) spectrometer for
                      high-throughput field diagnostics of PV materials. Operating
                      in the 1550–1950 nm spectral range, the spectrometer
                      detects key molecular absorption bands to characterize
                      polymer compositions. Principal component analysis (PCA)
                      applied to the spectral data significantly improved material
                      differentiation compared to raw data, achieving
                      classification reliability exceeding $95\%.$ Field
                      deployment at a 10 mw PV installation demonstrated the
                      method's scalability, with 981 modules analyzed at a rate of
                      one module every 3 s. Spatial mapping revealed that all
                      analyzed backsheets featured polyethylene terephthalate
                      (PET) cores, with approximately $65\%$ incorporating
                      fluoropolymer- and $35\%$ PET-based outer layers. These
                      findings demonstrate the scalability and efficiency of a
                      portable NIR spectrometer for rapid, nondestructive
                      diagnostics of PV modules. The ability to directly identify
                      polymer compositions during high-throughput field
                      measurements enables applications in predictive maintenance,
                      reliability assessment, bill-of-materials verification, and
                      efficient sorting and recycling of end-of-life modules.},
      cin          = {IET-2},
      ddc          = {600},
      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},
      doi          = {10.1002/solr.202500323},
      url          = {https://juser.fz-juelich.de/record/1046021},
}