Exploiting OSC Models by Using Neural Networks with an Innovative Pruning Algorithm

  • Grazia Lo Sciuto
  • Giacomo Capizzi
  • Christian Napoli
  • Rafi Shikler
  • Dawid Połap
  • Marcin WoźniakEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10842)


In this paper we have investigated the relationship between the current and the active layer thickness of an organic solar cell (OSC) in order to improve its efficiency by means of a back propagation neural network. In order to preserve the generalization properties of the adopted neural network (NN) in this paper is presented also an innovative pruning technique. The extensive simulations performed show a good agreement between simulated and experimental data with an overall error of about 3%. The obtained results demostrate that the use of an MLP with associated an appropriate pruning algorithm to preserve its generalization capacities permits to accurately reproduce the relationship between the active layer thicknesses and the measured maximum power in an OSC. This neural model can be of great use in manufacturing processes.



This work has been supported by the BGU-ENEA joint lab and the ILSE-Joint Italian-Israeli Laboratory on Solar and Alternative Energies. We thank Dr. Jurgen Jopp of Ilse Katz Institute for Nanoscale Science and Technology. The Authors would like to acknowledge contribution to this research from the “Di-amond Grant 2016” No. 0080/DIA/2016/45 funded by the Polish Ministry of Science and Higher Education.


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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Grazia Lo Sciuto
    • 1
  • Giacomo Capizzi
    • 1
    • 4
  • Christian Napoli
    • 2
  • Rafi Shikler
    • 3
  • Dawid Połap
    • 1
    • 4
  • Marcin Woźniak
    • 1
    • 4
    Email author
  1. 1.Department of Electrical Electronics and Informatics EngineeringUniversity of CataniaCataniaItaly
  2. 2.Department of Mathematics and Computer ScienceUniversity of CataniaCataniaItaly
  3. 3.Department of Electrical and Computer EngineeringBen-Gurion University of the NegevBeer-ShevaIsrael
  4. 4.Institute of MathematicsSilesian University of TechnologyGliwicePoland

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