LEE- Fizik Mühendisliği-Doktora
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ÖgeCSA'nın P3HT VE MEH-PPV polimerlerinin fiziksel özelliklerine etkisi(Lisansüstü Eğitim Enstitüsü, 2023-04-07)Bu tez çalışmasında iki temel organik yarıiletken polimerin P3HT ve MEH-PPV kullanılması hedeflenmiştir. İlk olarak P3HT analiz edilmiştir. Daha önceki çalışmalarda, kamfor sülfonik asitin (CSA) konjuge polimerler üzerindeki doping (katkılama) etkisi belirtilmiş ve nanofilmler aracılığıyla polimer üzerinde elektriksel (dc) iletkenliklerinin artışına sebep olduğu gözlemlenmiştir. Öte yandan, bir çözücü olarak m-cresolün asitliği nedeniyle polimerlerdeki taşıyıcı yük hareketliliğini arttırdığı da öne sürülmüştür. P3HT polimerinde CSA'nın katkılama etkisi ile ilgili birçok çalışma olmasına rağmen, P3HT, CSA ve m-cresolün birlikte kombinasyonu ile ilgili bir çalışmaya rastlanmamıştır. Bu çalışmanın ilk aşamasında çözücü m-cresolün ve CSA'nın P3HT üzerindeki etkisi açıklanmıştır. P3HT ince filmlerin optik absorpsiyonunu ve dc elektriksel özelliklerini geliştirmek için katkı maddesi olarak CSA ve ayrıca çözücü olarak m-cresol kullanılmıştır. İnce film örneklerinin yapısal, optik ve elektriksel özellikleri için çözücü m-cresolde CSA'nın P3HT üzerindeki katkılama etkisi incelenmiştir. Ayrıca ilk aşamada, P3HT filmlerin iletkenlik-sıcaklık özellikleri incelenmiş ve daha sonra ince filmlerdeki CSA miktarlarının etkilerine katkı sağlanarak her bir numunenin aktivasyon enerjileri hesaplanmıştır. P3HT'nin (Poly (3-hexylthiophene)) yapısal, optik ve elektriksel özellikleri, CSA m-cresol içindeki katkılama etkisi ile incelenmiştir. P3HT ince film örneklerinin SEM görüntüleri ve optik mikroskopisi, CSA'nın P3HT yüzeyinde dağılması yoluyla morfolojik etki göstermiştir. Optik absorpsiyon analizinde, 650 nm ile 900 nm arasında CSA filmleriyle katkılı P3HT'de kırmızıya kayma ve genişleme araştırılmıştır. Ayrıca, P3HT ince filmlerin elektriksel iletkenliklerinin, 313-337 K sıcaklıkları arasında doğrusal bir artış gösterdiği ve CSA'nın P3HT'nin dc iletkenliğini Kelvin başına 7.04x10-9 S/cm'den 1.31x10-6 S/cm'ye yükselttiği ortaya konmuştur. İlk aşamanın sonunda, Arrhenius denklemi kullanılarak örneklerin aktivasyon enerjileri hesaplanmıştır. Çözücü m-cresolde CSA'nın P3HT üzerindeki artan etkisi sonucu, P3HT'nin aktivasyon enerjisi 0.605 eV'den 0.302 eV'ye düşmüş ve dolayısıyla elektriksel iletkenliğe katkısının olduğu ispatlanmıştır. P3HT polimerinin analizinin ikinci aşamasında dielektrik özellikler incelenerek polimerin kapasitif etkisine bakılmıştır. P3HT/CSA kompozitlerinin kompleks elektriksel geçirgenlik, kayıp tanjantı, kompleks elektrik modülü dahil olmak üzere frekansa bağlı elektriksel özellikleri incelenmiştir. Numunelerin yapısal özellikleri FT-IR spektroskopisi ve Taramalı Elektron Mikroskobu (SEM) görüntüleme ile gerçekleştirilirken; enerji depolama potansiyelini ortaya çıkarmak için empedans ve iletkenlik ilişkisi, 20 Hz ile 10 MHz arasında empedans analizörü kullanılarak yapılmıştır. Numunelerin kompleks elektriksel geçirgenlik analizi, CSA takviyesinin P3HT'nin hem enerji depolama kabiliyetini hem de iletkenliğini artırmada olumlu bir etkiye sahip olduğunu ortaya çıkarmıştır. Özellikle 0.011M CSA içeren kompozitin ' değerinin diğerlerine göre daha yüksek olması, daha düşük kayıp tanjantına sahip olması ve iletkenliğinin tüm numunelere göre yüksek olması bu kompoziti birçok uygulama için cazip kılmaktadır. Ayrıca P3HT'nin süperkapasitif yapısının bir göstergesi olan yüksek frekanslarda (3-10 MHz) P3HT'nin -90o'ye çok yakın bir faz farkına sahip olduğu ilk kez tespit edilmiştir. Tez çalışmasının son aşamasında MEH-PPV polimeri analiz edilmiştir. MEH-PPV/CSA kompozitleri çeşitli spektroskopik metotlarla analiz edilmiş; frekansa bağlı elektriksel özellikleri ayrıca değerlendirilmiştir, CSA'nın polimer matrisine dâhil edilmesi, FTIR, UV, PL, SEM ve AFM sonuçları ile doğrulanmış, ayrıca DC iletkenlik analizi, polimerin elektrik doğasını lineer değişimden farklı şekilde etkilediğini göstermiştir.
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ÖgeTheoretical characterization of colloid-polymer nano-composites(Graduate School, 2023-02-28)The goal of the thesis is to observe microscopic mechanisms in colloid dispersions that cause shear thinning and shear thickening. We develop the necessary tools to model these phenomena. We present a non-equilibrium molecular dynamics study of the Couette flow of rigid spherical nanoparticles in a simple Lennard-Jones fluid. We evaluate the viscosity of the dispersion as a function of shear rate and nanoparticle volume fraction. We observe shear thinning behavior at low shear rates; as the shear rate increases, the shear forces overcome the Brownian forces, resulting in more frequent and more violent collisions between the nanoparticles. This in turn results in more energy dissipation and increased shear stress. We show that in order to stay in the shear-thinning regime the nanoparticles have to order themselves into layers longitudinal to the flow to minimize the collisions after Brownian forces become negligible. As the nanoparticle volume fraction increases, there is less room to form the ordered layers; consequently, as the shear rate increases, the nanoparticles collide more, which results in turn in shear thickening. Most interestingly, we show that at intermediate volume fractions the system exhibits metastability, with successions of ordered and disordered states along the same trajectory, and these states correspond to shear thinning and shear thickening respectively. Two-dimensional pair correlation functions are evaluated for further analyses of microscopic states of the non-Newtonian regimes. At low shear rates shear thinning is related to the deformation of the microscopic structure dominated by Brownian forces. Our results suggest that layering may lead to shear thinning in the right conditions but it's not necessary. Results also support the order-disorder transition but it's also not necessary. The leading reason for shear thickening is the increase in the frequency and intensity of the frictional interactions of dispersed particles. Layer formation is a mechanism that prevents the emergence of shear thickening.
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ÖgeEnsemble and deep learning on astronomical data with different modalities(Graduate School, 2023-03-20)Light curves inform us how the brightness of an astronomical object changes over time. They are obtained by subtracting successive images of astronomical objects of a photometric band. In this thesis, the first task was to focus on the classification of 14 astronomical objects in the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC) data set which was prepared to model future observations of the Vera Rubin Observatory. The light curve of each object was divided into two separate parts using a Haar wavelet transform. By using these two wavelet components, statistical properties such as the mean, standard deviation, and minimum were obtained for each band. The classification was performed with boosted artificial neural networks and boosted decision trees by using extracted features and also including additional features such as the photometric redshift and its uncertainty. The training set was highly biased toward low-redshifted objects. Importance weights were estimated for each training object, and more representative data were given larger weights. The combination of boosted decision trees, random forests and extremely randomized trees was found to give the best performance for type Ia supernovae which are important indicators for cosmological measurements. The role of photometric redshift was examined by excluding the redshift parameter. The performance of superluminous supernovae (SLSN-I) was significantly affected by the omission of the redshift parameter with a 10% decrease in the area under the receiver operating characteristic curve (AUC) score. The relevant features of each object class were ranked using a neural network classifier. The time-frequency images were also obtained using a continuous wavelet transform as an alternative to discrete Haar wavelets. Since all data points of the light curves were used instead of utilizing feature extraction, a powerful model was needed to estimate the missing data. Gaussian process regression was employed for that task as one of the most successful models in filling the gaps of the light curves. As discussed previously in the literature, it is very difficult to accurately estimate 14 astronomical objects with only one kernel. Therefore we limited our attention to only include type Ia and II supernovae for the classification task. One of the difficulties that will be faced in future observations is that researchers will not be able to obtain any data on some photometric bands, depending on the status of the observation. Villar et al. proposed a 2D Gaussian process regression for this situation. The missing data in this part of the thesis was estimated using this two-dimensional kernel. The convolutional neural network (CNN) structures were decomposed using a tensor decomposition method (CP decomposition). It was observed that rank selection, which changes the number of parameters, also affects the classifier performance. While the classifier performed poorly on very small ranks, an optimal rank was determined for better performance. This indicates that tensor decomposition methods may be significant enough to include in the analysis of noisy light curves. This method provides an alternative to feature engineering that applies principal component analysis (PCA) to wavelet components. Another main task that was performed in this thesis was the morphological classification of Galaxy Zoo images. The images used in the Galaxy Zoo challenge were taken from the seventh data release (DR7) of the Sloan Digital Sky Survey (SDSS). SDSS made observations in 5 photometric bands which are labeled as u, g, r, i and z. The Galaxy Zoo photos are composite photos of galaxies observed in the r, g, and i bands. As galaxy images do not have a fixed or preferred orientation, any classifier that aims to correctly classify galaxies should be expected to properly detect when two galaxies are rotated versions of each other. Although convolutional layers are successful in processing images and preserve feature maps when encountering a translated version of an object, they fail in identifying rotated objects as the same. The convolution operation does not commute with rotation and this causes the feature map to change when it is generated for different orientations of the same galaxies. To overcome the problem of not identifying rotated versions of the same object, an equivariant structure is needed for an image classifier. Convolutional layers can be excellent ingredients in defining generalized equivariant architectures. Instead of using traditional convolution layers, it is possible to define a generalized convolution operation with group operations that preserve different symmetries. A dynamic structure using the p4m group convolutional layers (p4m is the plane symmetry group of translations, reflections, and rotations by 90 degrees) is proposed in this thesis, which introduces additional angles to the architecture after the initial training of the p4m group convolutional layers.
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ÖgeEnhancement of dispenser cathode fabrication with pre – design activation simulations and polymer doping(Graduate School, 2023-04-05)This study includes dispenser cathode activation design including therefore cathode's peripheral parts and fabricating two different types of cathodes with some improvements. Activation which is a must for all of the dispenser cathodes is modeled for both M-type and scandate cathodes. The simulation results are verified with experimental data. This modeling study helps improve the thermal tests of cathodes. Besides the modeling studies, both cathodes are fabricated and tested. Polymer material and polymer-tungsten composition research is carried out also. The effects of polymer doping on the cathode matrix material on the surface roughness are investigated. Metal–polymer composition and its debinding process before sintering are also studied and new recipes are created. At the end of the study, it was examined that scandate cathodes operates at lower temperatures and their production has more controllable fabrication parameters. They can be used instead of M–type cathodes for the same current level at lower temperatures. Before the fabrication of the cathode, the components of the cathode are determined and designed with modeling, then polymer doping can be used to reduce surface roughness if pure tungsten is used. If there is an oxide compound in it, the polymer may not be needed. Scandate cathodes can be safely used for even its "as-sintered" form to operate at lower temperatures. Besides, the modeling study is also verified by commonly used cathodes and newly developed cathode types as well. It can be also used for any of the impregnated dispenser cathode types confidently.
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ÖgeYukawa-type screening inherent in higher dimensional gravity and cosmology(Graduate School, 2022-10-19)At the intersection of gravitation and cosmology, a study of the large-scale structure of the Universe, and particularly, the search for a general relativistic approach appropriate for formulating structure formation at all-scales makes up the principle objective of this thesis. It introduces a scheme that combines the characteristics of such an approach, namely, the cosmic screening approach towards all-scale cosmological perturbations, with the screening of gravity emerging through a distinct mechanism as part of the relativistic perturbation theory. Subsequently, it presents an effective screening length (the effective interaction range of Yukawa gravity) for gravitational interactions at cosmological scales, which matches the size of the largest-yet-observed cosmic structure, and thereby, argues for homogeneity and isotropy in the Universe not from few hundred megaparsecs, but from a few gigaparsecs on. The analysis is first carried out for the flat LCDM model, but later it is extended to involve curved spaces with the same energy components. A comparison of Newtonian approximation and Yukawa behavior is performed in terms of single particle gravitational force calculations relevant to structure formation simulations, and impacts of periodicity on the Yukawa force are investigated to reveal the extent of deviations from the free-boundary problem. Finally, metric coefficients of certain multidimensional f(R) models are studied in the weak-field limit, which also acquire corrections in the form of Yukawa potentials subject to constraints form the inverse-square law experiments.