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  • Küçük Resim
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    Polyfluorene Thin Films Synthesized by a Novel Plasma Polymerization Method
    (Springer, 2012) Göktaş, Hilal; Mansuroğlu, Doğan; Atalay, Betül; Bilikmen, Sinan; Kaya, İsmet
    The synthesis of polyfluorene (PF) thin films by simultaneously superposing a continuous and pulsed discharge and the characterizations of these samples are presented. The double discharge plasma system is constructed by superposing two discharges; namely, a low pressure dc glow one and a high current pulsed one. The fluorene monomer in powder form was vaporized in the system at argon plasma without any modification, at 0.5 mbar operating pressure. The structure of the thin films was investigated via XPS, UV-visible, FTIR, XRD and SEM. The FTIR and the UV-visible results revealed that the fluorene structure was retained at the produced samples. Semi-conducting behavior was established, and upon the iodine doping, the optical energy band gap (E-g) dropped down from 3.7 to 2.4 eV. The morphology of the synthesized PF thin films was amorphous, with granular structures of different sizes depending on the location of the substrate.
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    Signal and noise detection in magnetotelluric data by the artificial neural network method
    (Hacettepe Universitesi Yerbilmleri, 2013) Uluocak, Ebru Şengül; Ulugergerli, Emin U.; Göktaş, Hilal
    In this study artificial neural network method was used to classify noisy components in the MT method data. For this purpose a multi-layered, feed-foorward and back propagation model was employed. Noisy time windows were determined to an accuracy of 89% depending on the training data set. In addition, when all types of noise in the data are defined (synthetic data), all noisy time windows can be sellected and eliminated by artificial neural network method.Test results from synthetic and field data indicate that artificial neural network classification is succesfull in identifying and eliminating the noisy data windows compared to both visual inspection and conventional assessment methods.
  • Küçük Resim
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    The optical properties of plasma polymerized polyaniline thin films
    (Elsevier Science Sa, 2013) Göktaş, Hilal; Demircioğlu, Zahide; Sel, Kıvanç; Güneş, Taylan; Kaya, İsmet
    We report herein the characterizations of polyaniline thin films synthesized using double discharge plasma system. Quartz glass substrates were coated at a pressure of 80 Pa, 19.0 kV pulsed and 1.5 kV dc potential. The substrates were located at different regions in the reactor to evaluate the influence of the position on the morphological and molecular structure of the obtained thin films. The molecular structure of the thin films was investigated by Fourier transform infrared (FTIR) and UV-visible photospectrometers (UV-vis), and the morphological studies were carried out by scanning electron microscope. The FTIR and UV-vis data revealed that the molecular structures of the synthesized thin films were in the form of leuocoemeraldine and exhibited similar structures with the films produced via chemical or electrochemical methods. The optical energy band gap values of the as-grown samples ranged from 2.5 to 3.1 eV, which indicated that these materials have potential applications in semiconductor devices. The refractive index in the transparent region (from 650 to 1000 nm) steadily decreased from 1.9 to 1.4 and the extinction coefficient was found to be on order of 10(-4). The synthesized thin films showed various degrees of granular morphologies depending on the location of the substrate in the reactor. (C) 2013 Elsevier B.V. All rights reserved.
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    Öğe
    Yapay sinir ağı yöntemi ile manyetotellürik veride sinyal ve gürültü ayırımı
    (2013) Uluocak, Ebru Şengül; Ulugergerli, Emin U.; Göktaş, Hilal
    Bu çalışma kapsamında manyetotellürik yöntem verisindeki gürültü bileşenlerini sınıflamak için yapay sinir ağı yöntemi kullanılmıştır. Bu amaçla çok katmanlı, ileri beslemeli ve geri yayılımlı bir model oluşturulmuştur. Seçilen eğitim setine bağlı olarak gürültülü zaman pencereleri % 89 doğrulukla belirlenmiştir. Ayrıca verideki gürültü türlerinin hepsi tanımlandığında (yapay veri), tüm gürültülü pencereler yapay sinir ağı yöntemi ile seçilip elenebilmektedir. Yapay veri ve arazi verisi ile yapılan uygulamalar sonucunda, hem görsel denetlemeye hem de geleneksel değerlendirme yöntemlerine göre, gürültülü veri pencerelerini sınıflayıp elemede yapay sinir ağı yönteminin daha başarılı oldugu gösterilmiştir.