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Effects of PCPDTBT:PCBM Ratio on the Electrical Analysis and the Prediction Of I-V Data Using Machine Learning Algorithms for Au/PCPDTBT:PCBM/n-Si MPS SBDs

Year 2023, Volume: 3 Issue: 1, 36 - 44, 01.05.2023

Abstract

In this study, Au/Poly[2,6-(4,4-bis-(2-ethylhexyl)-4H-cyclopenta[2,1-b;3,4-b′]dithiophene)-alt-4,7(2,1,3-benzothiadiazole)] (PCPDTBT) : [6,6]-phenyl C61 butyric acid methyl ester (PCBM) /n-Si heterojunction Schottky barrier diodes (SBDs) with 1:1 and 2:1 PCPDTBT:PCBM doping ratios were produced, and the electrical analysis of metal-polimer-semiconductor (MPS) SBDs with different concentrations was investigated. Ideality factor (n), saturation current values (I0) and barrier heights (F0) of the materials were obtained based on the current-voltage (I-V) measurements performed. According to the results obtained, the PCBM concentration has significant effects on the electrical properties of the Au/PCPDTBT:PCBM/n-Si MPS SBD. To predict the electrical characterization of a system in detail, based on its doping concentration, the I-V data set consisting of 2 samples is typically split into a 70% training set and a 30% test set, which is used to train machine learning algorithms. Various methods, including Fine Tree, Cubic SVM, Fine KNN, Boosted Trees, Bagged Trees, Subspace KNN, RUSBoosted Trees, Wide Neural Network, Trilayered Neural Network, and Logistic Regression Kernel, have been analyzed. The obtained results indicate that certain algorithms can predict the I-V data of Au/PCPDTBT:PCBM/n-Si MPS SBD with full accuracy, i.e., 100%.

Supporting Institution

İzmir Bakırçay University Unit of Scientific Research Projects Coordination

Project Number

BBAP.2022.012

Thanks

This study was supported by İzmir Bakırçay University Unit of Scientific Research Projects Coordination with project number BBAP.2022.012.

References

  • [1] Sze, S.M. and Ng, K.K., (2007). Physics of Semiconductor Devices, (3rd ed.), John Wiley & Sons, Hoboken, New Jersey.
  • [2] Chiguvare, Z., Parisi, J., & Dyakonov, V. (2003). Current limiting mechanisms in indium-tin-oxide/poly3-hexylthiophene/aluminum thin film devices. Journal of Applied Physics, 94(4), 2440-2448.
  • [3] Hoppe, H. and Sariciftci, N.S., (2004). Organic solar cells: an overview. Journal of Materials Research, 19(7), 1924-1945.
  • [4] Turmuş, M., (2014). N tipi silisyum tabanlı altlık üzerine pyrene (C16H10) maddesinin kaplanarak elde edilen yapıların akım iletim mekanizmaları, [Yüksek Lisans Tezi, Bingöl Üniversitesi]. Bingöl-Türkiye.
  • [5] Nalçalıgil, S.Z., (2011). Perylene türevi oranik yarıiletken ince filmlerin optik özelliklerinin incelenmesi, [Yüksek Lisans Tezi, Selçuk Üniversitesi]. Konya-Türkiye.
  • [6] Boy, F., (2013). Organik arayüzeyli GaAs schottky diyodların elektriksel karakterizasyonu, [Yüksek Lisans Tezi, Selçuk Üniversitesi]. Konya-Türkiye.
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  • [8] Şimşir, N., (2012). Metal/organik/inorganik schottky diyodların sıcaklığa bağlı elektriksel karakterizasyonu, [Yüksek Lisans Tezi, Selçuk Üniversitesi]. Konya-Türkiye.
  • [9] Özdemir, A.F., Aldemir, D.A., Kökce, A. & Altindal, S., (2009). Electrical properties of Al/conducting polymer (P2ClAn)/p-Si/Al contacts. Synthetic Metals, 159(14), 1427-1432.
  • [10] Demirezen, S. and Altındal Ş., (2010). Possible current-transport mechanisms in the (Ni/Au)/Al0. 22Ga0. 78N/AlN/GaN schottky barrier diodes at the wide temperature range. Current Applied Physics 10(4), 1188-1195.
  • [11] Tüzün Özmen, Ö., (2014). Effects of PCBM concentration on the electrical properties of the Au/P3HT:PCBM/n-Si (MPS) schottky barrier diodes. Microelectronics Reliability, 54(12), 2766–2774.
  • [12] Yang, M., (2018). A machine learning approach to evaluate Beijing air quality. [Senior Thesis, University of California].
  • [13] Mohri, M., Rostamizadeh, A. & Talwalkar, A., (2012). Foundations of machine learning. The MIT Press, Cambridge
  • [14] Hal Daume´ III, (2017). A course in machine learning. <http://ciml.info/dl/v0_99/ciml-v0_99-all.pdf> [Accessed: 19 Mar 2023].
  • [15] Alpaydın, E., (2014). Introduction to machine learning. MIT Press, Cambridge.
  • [16] Özbay Karakuş, M. and Er, O., A 2022. comparative study on prediction of survival event of heart failure patients using machine learning algorithms. Neural Comput & Applic, 34, 13895–13908.
  • [17] Tüzün Özmen, Ö., (2014). “Effects of PCBM concentration on the electrical properties of the Au/P3HT:PCBM/n-Si (MPS) Schottky barrier diodes”, Microelectronics Reliability, 54, 2766-2774.
  • [18] D. Braun ve A.J Heeger, (1991). Visible-light emission from semiconducting polymer diodes. Applied Physics Letters, 58, 1982-1984.
  • [19] Yağlıoğlu E., and Tüzün Özmen, Ö., (2014). F4-TCNQ concentration dependence of the current voltage characteristics in the Au/P3HT:PCBM:F4-TCNQ/n-Si (MPS) Schottky barrier diode, Chinese Physics B, 23(11), 117306.
Year 2023, Volume: 3 Issue: 1, 36 - 44, 01.05.2023

Abstract

Project Number

BBAP.2022.012

References

  • [1] Sze, S.M. and Ng, K.K., (2007). Physics of Semiconductor Devices, (3rd ed.), John Wiley & Sons, Hoboken, New Jersey.
  • [2] Chiguvare, Z., Parisi, J., & Dyakonov, V. (2003). Current limiting mechanisms in indium-tin-oxide/poly3-hexylthiophene/aluminum thin film devices. Journal of Applied Physics, 94(4), 2440-2448.
  • [3] Hoppe, H. and Sariciftci, N.S., (2004). Organic solar cells: an overview. Journal of Materials Research, 19(7), 1924-1945.
  • [4] Turmuş, M., (2014). N tipi silisyum tabanlı altlık üzerine pyrene (C16H10) maddesinin kaplanarak elde edilen yapıların akım iletim mekanizmaları, [Yüksek Lisans Tezi, Bingöl Üniversitesi]. Bingöl-Türkiye.
  • [5] Nalçalıgil, S.Z., (2011). Perylene türevi oranik yarıiletken ince filmlerin optik özelliklerinin incelenmesi, [Yüksek Lisans Tezi, Selçuk Üniversitesi]. Konya-Türkiye.
  • [6] Boy, F., (2013). Organik arayüzeyli GaAs schottky diyodların elektriksel karakterizasyonu, [Yüksek Lisans Tezi, Selçuk Üniversitesi]. Konya-Türkiye.
  • [7] Sharma, B.L., (1984). (Ed.), Metal-semiconductor schottky barrier junctions and their applications, Plenum Press, New York.
  • [8] Şimşir, N., (2012). Metal/organik/inorganik schottky diyodların sıcaklığa bağlı elektriksel karakterizasyonu, [Yüksek Lisans Tezi, Selçuk Üniversitesi]. Konya-Türkiye.
  • [9] Özdemir, A.F., Aldemir, D.A., Kökce, A. & Altindal, S., (2009). Electrical properties of Al/conducting polymer (P2ClAn)/p-Si/Al contacts. Synthetic Metals, 159(14), 1427-1432.
  • [10] Demirezen, S. and Altındal Ş., (2010). Possible current-transport mechanisms in the (Ni/Au)/Al0. 22Ga0. 78N/AlN/GaN schottky barrier diodes at the wide temperature range. Current Applied Physics 10(4), 1188-1195.
  • [11] Tüzün Özmen, Ö., (2014). Effects of PCBM concentration on the electrical properties of the Au/P3HT:PCBM/n-Si (MPS) schottky barrier diodes. Microelectronics Reliability, 54(12), 2766–2774.
  • [12] Yang, M., (2018). A machine learning approach to evaluate Beijing air quality. [Senior Thesis, University of California].
  • [13] Mohri, M., Rostamizadeh, A. & Talwalkar, A., (2012). Foundations of machine learning. The MIT Press, Cambridge
  • [14] Hal Daume´ III, (2017). A course in machine learning. <http://ciml.info/dl/v0_99/ciml-v0_99-all.pdf> [Accessed: 19 Mar 2023].
  • [15] Alpaydın, E., (2014). Introduction to machine learning. MIT Press, Cambridge.
  • [16] Özbay Karakuş, M. and Er, O., A 2022. comparative study on prediction of survival event of heart failure patients using machine learning algorithms. Neural Comput & Applic, 34, 13895–13908.
  • [17] Tüzün Özmen, Ö., (2014). “Effects of PCBM concentration on the electrical properties of the Au/P3HT:PCBM/n-Si (MPS) Schottky barrier diodes”, Microelectronics Reliability, 54, 2766-2774.
  • [18] D. Braun ve A.J Heeger, (1991). Visible-light emission from semiconducting polymer diodes. Applied Physics Letters, 58, 1982-1984.
  • [19] Yağlıoğlu E., and Tüzün Özmen, Ö., (2014). F4-TCNQ concentration dependence of the current voltage characteristics in the Au/P3HT:PCBM:F4-TCNQ/n-Si (MPS) Schottky barrier diode, Chinese Physics B, 23(11), 117306.
There are 19 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Articles
Authors

Ömer Berkan Çelik This is me 0009-0004-0116-766X

Burak Taş 0000-0002-9928-5004

Özgün Uz 0000-0002-6752-2861

Hüseyin Muzaffer Şağban 0000-0001-8820-5622

Özge Tüzün Özmen 0000-0002-5204-3737

Project Number BBAP.2022.012
Publication Date May 1, 2023
Published in Issue Year 2023 Volume: 3 Issue: 1

Cite

APA Çelik, Ö. B., Taş, B., Uz, Ö., Şağban, H. M., et al. (2023). Effects of PCPDTBT:PCBM Ratio on the Electrical Analysis and the Prediction Of I-V Data Using Machine Learning Algorithms for Au/PCPDTBT:PCBM/n-Si MPS SBDs. Artificial Intelligence Theory and Applications, 3(1), 36-44.