Theses supervised by Prof. Dr. Ramazan Yıldırım
24 theses · Selçuk University, Boğaziçi University, İstanbul University
İdare hukuku açısından ekolojik kamu düzeni
Kamu düzeninin klasik unsurları, genel olarak insan merkezlidir bu nedenle klasik kamu düzeni çevreyi insanlar için bir tehlike söz konusu olduğunda dikkate alır. Ayrıca klasik kamu düzeni, yaşayan insanlarla ilgilenir, ancak çevrenin korunması gelecek kuşakları da ilgilendirir ki sürdürülebilir kalkınma, sürdürülebilir çevre gibi kavramlar bu kabulden hareketle ortaya çıkmıştır. Bu sınırlı perspektif nedeniyle kamu düzeninin klasik unsurları pek çok durumda çevreyi koruma açısından yetersiz kalmaktadır. Ekolojik kamu düzeni, çevreyi, doğal kaynakları, flora ve faunayı korumayı, çevresel yararı sağlamayı ve mekânsal rahatsızlıkları önlemeyi amaçlayan bilimle harmanlanmış kamu düzenidir. Ekolojik verinin ve bir faaliyetin çevrenin çeşitli unsurları üzerindeki sonuçlarına ilişkin bilimsel bulgular ekolojik kamu düzenine kaynaklık etmektedir. Ekolojik kamu düzeninin insan merkezci olmayışı onu kamu düzeninin klasik unsurları olan güvenlik, kamu sağlığı ve esenlik unsurundan ayırır. Ekolojik kamu düzeni, çevresel rahatsızlık insanı doğrudan etkilememiş olsa dahi, salt çevreyi korumak üzere önlem alınması ve uygulanması gerektiğini kabul eder. Ekolojik kamu düzeni eşik aracılığı ile somutlaşır. Çevrenin tolere edemeyeceği rahatsızlığın, teknik ölçü birimleri veya bilimsel değerlerle ifade edilmesi ile eşik değerler ortaya çıkar. Türk hukukunda da eşik değer, sınır değer, limit değer gibi farklı adlarla mevzuatta yer almaktadır. Eşik değerler, bilimsel gerçeği ve mevzuatı birbirine uygun hale getirmeye olanak sağlar. Ayrıca ekolojik kamu düzenini bozacak nitelikte bir çevresel rahatsızlığın gerçekleşip gerçekleşmediğini saptamaya ilişkin somut bir değerlendirme ölçütü oluşturur. Bu tezin amacı, kavramın ortaya çıktığı Fransız doktrini başta olmak üzere konuya ilişkin teorik temelleri ve uygulamaya ilişkin esasları ortaya koyarak idare hukuku açısından ekolojik kamu düzeni kavramına ışık tutmaktır.
Neural networks analysis of water gas shift reactions over noble metal catalysts using published data in literature
The aim of this thesis is to apply the machine learning methodologies for knowledge extraction from experimental data for water gas shift reaction over noble metal catalysts from the papers published in the literature to understand the general trends and improve the catalyst design. First, the experimental data were extracted from 85 articles in the literature between 2002 and 2012 and a database containing 4372 data points with 87 variables was constructed. Then the methodology for knowledge extraction was selected; the neural networks and support vector machines, which are the two most effective machine learning tools, were compared using a dataset that was analyzed in our group before, and the neural network method showed better performance on prediction the unseen data. Hence the water gas shift reaction database was analyzed by using neural networks. An optimal network structure was determined by constructing various neural network topologies and comparing the testing RMSE, which is a measure of generalization ability of the model (prediction ability for the unseen data); two hidden layer network containing 21 nodes in each layer was found to be optimum to represent the database. Then, the experimental CO conversions in each article were predicted by the neural networks trained using the data from the remaining articles. The results in 29 articles out of 85 were predicted with a R2 value of higher than 0.5, which can be considered as successful. The effects and relative significances of the catalyst design and operation variables were also analyzed and found to be generally in agreement with the literature.
Design and characterization of polymer-fullerene bulk heterojunction solar cells
Design and characterization of polymer-fullerene bulk heterojunction solar cells were experimentally studied in this study. In the experiments, ITO or highly conductive PEDOT:PSS coated glasses were used as anode, P3HT and [60]PCBM or [70]PCBM were used as active layer materials and conductive PEDOT:PSS used as hole conducting layer. Aluminum, Woods metal and Ga-In eutectic were tested as cathode in the devices. All the experiments were done under atmospheric conditions. Conductive and highly conductive PEDOT:PSS, and blend of P3HT:PCBM materials were applied by spin coater. Al deposition was done by thermal evaporator. On the other hand, Ga-In eutectic was directly applied over the active layer while Woods metal was deposited after melting. Electrical characterizations of devices are done by Keithley 2400 and 2612A source meter and 100 W halogen lamp. Light intensity of halogen lamp was measured by MP-100 Apogee Instruments Pyranomoter and set to 1000 W/m2. In Al cathode structure, two working devices with appropriate diode characteristics were recorded. This was the same for Ga-In eutectic devices while no devices with Woods metal cathode structure were successfully performed. The best working device, which is one of with Ga-In eutectic cathode, showed the electrical characteristics of 0.14 % power conversion efficiency, 470 mV open circuit voltage, 1.09 mA/cm2 short circuit current density and 27 % fill factor over 0.03 cm2 active area; these values are not as good as the values reported in the literature, probably because of the high degradation with oxygen under atmospheric conditions. In addition to this, the difficulties encountered during Al coating further decreased the efficiency of devices containing this metal.
Oxidative coupling of methane over lanthanum and strontium promoted magnesium catalyst
The oxidative coupling of methane (OCM) over 10wt.%SrO/10wt.%La2O3/MgO, in the form of particulate and monolithic structures, was investigated in this thesis. The OCM performance of the catalyst, which was prepared using incipient to wetness impregnation and then wall-coating over the monolithic support, was investigated in a microflow quartz reactor.. The diameter of reactor was 10 mm around the catalyst bed and reduced to 2 mm at the exit to decrease the void volume, which was also filled with quarts chips to prevent undesired gas phase reactions. At the beginning of work, 10wt.%La2O3/MgO particulate catalyst was prepared by incipient to wetness impregnation and tested. At the following stages, the additional metal oxides (CaO and SrO) were also added. The highest yield was 8wt.% in particulate catalysts and it was observed over 10wt.%SrO/10wt.% La2O3/MgO. For the test over mullite monolith, the monolith blocks were shaped to 17 mm height and 8 mm ID first, and then they were wash-coated with MgO followed by La2O3 and/or SrO. The highest C2 yield (14.5%) was obtained at 650 oC with CH4/O2 ratio of 15 using 10wt.%SrO/10wt.% La2O3/MgO over monolith.
Application of data mining tools to extract knowledge for dry reforming of methane from published papers in literature
The aim of this thesis is to extract knowledge for dry reforming of methane reaction using data mining techniques that are decision trees and artificial neural networks. Firstly, the experimental data were collected from 101 papers published between 2005 and 2014. The data set consisted of 5521 data points with 63 variables. The conversion of methane as a function of catalyst preparation and operational variables was modeled in MATLAB. CH4 conversion values were classified as 0-50, 50-75 and 75-100 for the decision tree analyses of total data, and Ni, Co, Pt and wet impregnation bases subsets. Training and testing errors of these trees were 21.1%-21.5%, 16.7%-19.0%, 10.2%-10.9%, 9.3%-12.6%, and 13.6%-15.1%, respectively. The neural networks were also used for modeling data; tansig was used as activation function and trainlm and trainbr were used as training algorithms for training and testing, respectively. The optimal neural network topology was found as 63-20-1 (20 neuron in hidden layer) using the prediction ability of testing result. R2 and corresponding RMSE values for training and testing were found to be 0.97-4.23 and 0.89-8.66, respectively. The relative significances of input variables were also determined using the optimal neural network topology. It was found that reaction temperature was the most significant variable, and operational variables had higher group significance than the catalyst design variables within the range of data set. Finally, the optimal neural network topology was used to predict the results of experiments and papers. 590 out of 753 experiments (78.4%) were predicted with RMSE values lower than 15. The results of 46 out of 101 papers (45.5%) were predicted with R2 values higher than 0.5 and the RMSE values of 65 out of 101 papers (64.4%) had lower than 15.
Machine learning analysis of biofuels using published data
One of the key objective of this dissertation is to develop a comprehensive understanding of previous machine learning (ML) studies on various biofuel production routes, specifically microalgae biodiesel, lignocellulosic ethanol, and biochar production, through bibliometric analysis and literature review. Microalgae show high potential for biofuel production but are costly, requiring better strains, value-added chemicals and reduced energy consumption for commercial viability. Converting lignocellulosic biomass to ethanol is promising but remains expensive, particularly due to pretreatment step. Biochar, especially in its functionalized and engineered forms, is likely to become more important for environmental remediation. This work also aims to construct comprehensive datasets for lipid production from the oleaginous yeast strain Yarrowia lipolytica and tri-reforming process from biogas, analyzing them with ML tools to estimate unperformed experiments, determine critical variables, and develop optimal heuristics. It was found that the potential of Yarrowia lipolytica for lipid production can be effectively categorized using decision tree (DT) algorithms, and descriptor effects can be determined using association rule mining. Found that, C/N ratio with fermentation time being influential for biomass production, while pH and glucose concentration for lipid content. The tri-reforming models developed using random forest (RF) and artificial neural network (ANN) algorithms also showed high predictive capabilities. Transfer learning methods, using source models from dry-reforming and steam reforming datasets were implemented to enhance the prediction accuracy with smaller datasets. DT algorithms were employed for interpretable knowledge extraction, resulting in the development of hierarchical rules for methane conversion, carbon dioxide conversion, and H2/CO ratios in the produced syngas. While high reaction temperature with high W/F results with high CH4 conversion, moderate reaction temperature with low O2 ratio promote high CO2 conversion. In all cases, not depending on other conditions, increasing H2O, and decreasing CO2 in the feed composition increases H2/CO ratio. The findings align with the literature, indicating that data mining and machine learning methods effectively provide predictive models and detect trends and patterns that are not readily observable.
Catalytic and photocatalytic CO2 conversion into valuable chemicals
This thesis explores catalytic and photocatalytic CO2 conversion processes with a focus on catalyst design, performance analysis, and machine learning assisted interpretation. A series of datasets compiled from the literature were analyzed to identify patterns governing CO2 methanation, CO2 hydrogenation to methanol, and photocatalytic CO2 reduction using halide perovskites. In methanation, Ni emerged as the most commonly used active metal, with CeO2 and ZrO2 supports yielding the highest conversions. Machine learning model, particularly random forest, demonstrated high predictive accuracy (R2=0.95 for training and R2=0.87 for testing), with temperature and catalyst formulation as key descriptors. For CO2 hydrogenation to methanol, a larger dataset was evaluated. SHAP and association rule mining (ARM) highlighted the significance of Ga, Ru, Y, and support materials such as ZnO-ZrO2 and In2O3-ZrO2 in enhancing selectivity. Cu and Ru catalysts prepared via precipitation and deposition-precipitation methods, respectively, were identified as favorable combinations. ARM results also emphasized promising but underexplored metal–support pairs warranting further experimental validation. Photocatalytic CO2 reduction over halide perovskites was also examined through an extensive dataset. CsPbBr3 dominated the literature, though FA and Bi-based perovskites showed higher gas production rates. MOFs, Ti3C2, and WO3 were among the most effective cocatalysts. The random forest model successfully predicted bandgap values and gas-phase production rates, with preparation methods and cocatalyst strategies identified as key features. Complementing the data-driven analysis, experimental studies were conducted on Pt and Cu-loaded TiO2 photocatalysts, with and without ionic liquids, under gas and liquid-phase conditions. While gas-phase tests yielded limited CO2 reduction, liquid-phase experiments demonstrated measurable CH4 evolution, particularly over IL-modified Cu/TiO2, highlighting the synergistic effect of Cu and IL in enhancing selectivity and activity under water-based, sacrificial agent-free conditions.
Machine learning analysis of biogas production using waste as a resource
This study aims to use machine learning techniques to examine the production of biogas from waste materials. Our goal is to forecast important output characteristics including biogas yield, biogas generated, CH4 yield, and biodegradability using experimental data on biogas production. Waste type, pre-treatment, co-digestion status, reactor type, and operational parameters (such as TS/VS ratio, C/N ratio, temperature, pH, and hydraulic retention length) are among the input features that are taken into account in this study. The dataset includes experimental data gathered from several studies that cover a range of waste types, including wastewater, food waste, agricultural waste, municipal solid waste (MSW), and organic fraction of municipal solid waste (OFMSW). These inputs are utilized for training machine learning models, such as Random Forest (RF), to predict output variables. Prior to model training, the dataset was cleaned and organized using preprocessing techniques such feature selection, and missing value treatment. Boruta analysis was also performed to decide on input parameters. High predictive performance was demonstrated by the data, especially for biogas generated (R2 = 0.92) and yield (R2 = 0.94). Operational parameters, particularly working volume and temperature, have a considerable impact on production projections, according to feature importance analysis. This study provides important insights for upcoming waste-to-energy systems and shows how machine learning may be used to improve biogas production processes. In order to increase model precision, future research can concentrate on adding more input and output parameters. It can also investigate the use of additional machine learning approaches to improve performance.
Photoelectrochemical water splitting using perovskite semiconductors
In this work, the photoelectrochemical cells with SrTiO3 and TiO2 photoanodes were constructed and the effects of preparation method, Al and Fe metal doping, the use heterostructure as well as the type, pH and molarity of electrolyte on photoelectrochemical water splitting performance were investigated. Solid state reaction, sol-gel and hydrothermal methods were used in synthetization of catalysts while in-situ coating, spin coating, dip coating and doctor blade methods were utilized in coating of the conductive substrates in fabrication electrodes. In addition, the precursor ratios of Sr and Ti were also changed. Linear sweep voltammetry from -1 to 2 V with scan rate of 10 mV/s was employed to measure the photoelectrochemical performances of the photoelectrodes by construction of the current voltage curves. XRD was used to determine the crystal structure while UV-VIS analysis was used to obtain diffuse reflectance spectra of catalysts; Kubelka-Munk method was applied to calculate the band gap energies. The solid state reaction followed by doctor blade coating method was found to be the best route to prepare an efficient photoelectrode. When the molar ratio of the Sr and Ti precursors were 2:3, the photoelectrochemical performance increased up to 2.5 folds compared to the ratio of 1:1. XRD analysis showed that cubic perovskite SrTiO3 was obtained. The band gap energy of SrTiO3 slightly changed from 3.2 eV to 3.17 eV by Fe-doping, but Al-doping did not change the band gap; no significant improvement observed in the performance. The best electrolyte was found to be NaOH. In addition to photoelectrochemical water splitting, the same materials were also tested in photocatalytic system, in which the particulate catalysts were used; the highest hydrogen production rate, which was with 600 µmol/h.gcat, was observed on the catalyst with the Sr:Ti ratio of 2:3.
Comparative study of hydrogen evolution over perovskites and other oxides
This study aims to compare the hydrogen evolution efficiency of photocatalysts based on titanate, tantalate, and niobium perovskite as well as some other oxides in 20% aqueous solution of various sacrificial agent. The solid-state reaction (SSR) method was used to prepare perovskites while nanopowder TiO2, Ta2O5 and Nb2O5 were used directly as purchased. 1 wt.% Pt cocatalyst was loaded on the samples by the incipient-to-wetness impregnation method; 0.2 wt.% Au, 1 wt.% Cu and 0.2 wt.% Au-0.8 wt.% Cu cocatalysts were also tested by loading them over TiO2 via deposition precipitation with urea (DPU) and sequential-DPU (S-DPU) methods. The hydrogen production rate on Pt/SrTiO3 under UV-VIS irradiation was much higher in D(+)-glucose monohydrate (GLU) (136.2 μmol/h.gcat), methanol (MeOH) (107.2 μmol/h.gcat), and ethylene glycol (EG) (112.5 μmol/h.gcat) solutions but it decreased after a maximum. However, the hydrogen generation rate in formic acid (FA) (54.8 μmol/h.gcat) and glycerol (GLY) (14.6 μmol/h.gcat) solutions were more stable. Pt/TiO2 was also tested in GLY solution, and the hydrogen production rate was found as 1146 μmol/h.gcat indicating a better potential than SrTiO3. 0.2 wt.% Au/TiO2 catalyst also produced 1085.1 μmol/h.gcat hydrogen even though Au loading is five times lower than Pt; furthermore, this catalyst also resulted in 201.4 μmol/h.gcat hydrogen, which is still significant and much higher than Pt under visible light irradiation. The distribution and size of shiny spherical gold particles around 40-50 nm size on TiO2 was observed by the scanning electron microscope (SEM) while the band gap energies were determined around 2.97 eV, which is quite close to TiO2, using UV-VIS spectroscopy by Kubelka-Munk method. X-ray diffraction (XRD) showed that mainly anatase phase exists in nanopowder TiO2 while SrTiO3 was mainly in the cubic crystal phase.
Machine learning analysis of photocatalytic CO2 reduction on perovskite materials
The purpose of this study is to construct a database from the experimental studies about CO2 reduction on perovskite materials from published articles, then to extract information from this dataset to predict CO2 production yields and the bandgap of the perovskites by using machine learning methods such as decision tree (DT), random forest (RF), gradient boosting (XGBoost), association rule mining (ARM), and linear regression (LR). By using Web of Science, relevant articles were examined, and 61 articles were selected for data extraction; 309 samples with 29 features (14 numerical and 15 categorical) were collected; these features included properties of perovskites such as bandgap, elemental information, and conditions of the experiments such as reaction temperature, phase of reaction collected as the features. Before the machine learning applications, pre-processing steps were applied to the dataset for cleaning and organizing. For the missing bandgap values, linear regression was applied for prediction from the available data. The biased and the highly absent features were eliminated while the missing values of others were filled with the mod or mean of the dataset. The ML methods were applied using two separate databases which were for gas and liquid phase reactions. 133 out of 309 samples with 30 features were used for gas phase dataset while the remaining 176 samples with 29 features were for liquid phase. 17 missing band gap values were predicted using linear regression with the R-square and RMSE were found as 0.75 and 0.36 respectively for validation set. With DT, the accuracy for test set was obtained 0.76 for gas phase and 0.84 for liquid phase. In the RF predictions, R-square and RMSE were found to be 0.64 and 24.5, respectively for test set in gas phase while they were 0.49 and 221.0 in liquid phase. Bandgap was the most important feature for gas phase while the most important feature for the liquid phase was found to be the cocatalyst. Finally, in the XGBoost, R-square and RMSE for test set in gas phase were 0.65 and 14.75, respectively and for liquid phases, they were 0.79 and 145.6.
Photocatalytic hydrogen production over ionic liquid coated semiconductors
The objective of this thesis is to develop active and stable dye sensitized and ionic liquid (IL) encapsulated photocatalysts for hydrogen production, and to investigate the roles of photocatalysts constituents on hydrogen production rate. First, comprehensive experimental datasets for photocatalytic (PWS) and photoelectrochemical (PECWS) water splitting were constructed from literature while a large dataset for water solubility in ILs were created computationally using DFT and COSMO-RS. Then, these datasets were analyzed by machine learning (ML); association rule mining (ARM), decision tree (DT), random forest (RF) and deep learning (DL) were implemented in R and Python environment. In PWS analysis, the clear trends and the high fitness of the models constructed, especially those involved the band gap, indicates that PWS over perovskites is predictable but the sound solutions like ion doping, use of co-catalyst, or use of sacrificial donors did not help as much as desired. The prediction accuracies of DL and classification accuracy of DT models for the water solubility in ILs were also high, and the properties of anionic parts of ILs are more influential for water solubility. The band gap of semiconductors used in PECWS were also predicted successfully even though the prediction accuracy of photocurrent density was not satisfactory. In the experimental part of the thesis, the enhancement of photocatalytic hydrogen production over 1 wt% Pt/TiO2 sensitized by N719 dye and coated by a thin layer of ionic liquid ([BMIM][BF4]) has been investigated; SEM-EDAX, CTEM, FTIR, XRD, and UV-Vis characterization of the photocatalysts, and electrochemical analysis of the respective photoelectrodes were performed. The IL coating increased the performance of 1%Pt/TiO2 by providing better charge transfer between the photocatalyst and the aqueous reaction medium while simultaneously preventing the recombination of photogenerated electron-hole pairs; the improvement was much higher with the use of IL and N719 together. The performance of 1% Pt/SrTiO3 was also tested but the reproducible results could not be obtained. Finally, the factors related to the structure of the reactor and operational conditions (like dead volume, gas-liquid interfacial area, sweep gas flowrate and stirring speed) were also found to be influential over the hydrogen production rate.
Design, construction and testing of various reactor geometries for gas-phase photocatalytic carbon dioxide reduction
This thesis proposes a comprehensive preliminary design of a gas-phase photocatalytic carbon dioxide reduction system with water. The aim was to design, construct and operate a reaction system using titania-based photocatalytic materials and various sources of light. To accomplish this, the lab-scale process system was constructed from scratch, which was followed by calibration of the equipment, synthesis of the photocatalyst material, and initial operation of the process as a whole under varying operating conditions. The main operational variables were the type of light source, the weight of photocatalyst, the inlet gas flowrates and the water heating of the water bubbler, which was used to generate moisture and transport it with CO2 into the system. The reactions were carried out over photocatalysts containing single (Pt or Cu) and bimetallic (Pt + Cu) co-catalyst loading onto TiO2 with or without coating with ionic liquid after metal loading. Two tubular and one balloon photoreactor geometries were tested, and the balloon photoreactor geometry proved to be the most effective. Syngas was obtained as the main product using the single metal photocatalysts, while syngas and methane were obtained using the bimetallic photocatalyst. Using single metal loaded TiO2, the maximum product yield obtained was 11.79 (with Pt) and 83.72 μmol/(h.gcat) (with Cu) for H2 and CO, respectively. With the bimetallic photocatalyst, those values increased to 164.76, 1757.29, and 60.26 μmol/(h.gcat) for H2, CO, and CH4, respectively. Establishing better gas-photocatalyst contact in the photoreactor design and enhancing the properties of the photocatalyst by applying various modifications were proposed for future studies to further improve the system performance.
Machine learning analysis of data collected from published literature on photocatalytic reforming of glycerol
In this thesis, the aim is to extract knowledge from the data that was collected from published literature about photocatalytic reforming of glycerol. 791 data points were collected from 93 articles. This data was cleaned, organized, and prepared for the machine learning methods. Random forest and ANN (Artificial Neural Network) were used as machine learning techniques. By using them, the models for band gap and hydrogen production rates were constructed. Cross validation was applied to all models to prevent overfitting. For hydrogen production rate model, the missing values for band gap were filled with the predicted values of ANN of band gap. In random forest, feature importance was determined and the variables with the highest effect on the result were found. For band gap, the most important variables were weight percent of cocatalyst, percent of semiconductor and calcination temperature and duration. For hydrogen production rate, the most significant variables were photocatalyst load, band gap, glycerol concentration, weight percent of cocatalyst and pH. In random forest, the best model was determined by changing test/train split and k values in k-fold cross validation for various tree number and number of samples in a leaf node. For band gap model, 0.25 test/train split and 4-fold with 41 trees and 1 sample was the best model with RMSE (Root Mean Square Error) of 0.234 and R-squared of 0.73. For hydrogen production rate model, 0.25 test/train split and 5-fold with 81 trees and 2 samples was the best model with RMSE of 1.09 x 104 and R-squared value of 0.71. For ANN, test/train split ratio, k value for k-fold cross validation, the number of neurons and activation function were changed to find the best model. For band gap, 52 neurons and ReLU function gave the best model with RMSE of 0.282 and R-squared value of 0.70 with 0.3 test/train split and 4-fold cross validation. For hydrogen production rate model, 0.25 test/train split ratio, 7-fold cross validation, 63 neurons and ReLU function gave the best model with RMSE of 1.47 x 104 and R-squared value of 0.60.
Kuzey Afrika ibadîliği ve imâmet düşüncesi
Kelâm kitaplarında imâmet veya hilâfet başlıkları altında yer verilen devlet başkanlığı meselesi, Müslümanların hem dinî hem de siyasî lideri olan Hz. Peygamber'in vefatından sonra ortaya çıkan en önemli problemdir. Bu problem ilk olarak Benî Sâide gölgeliğinde (Sakîfetü Benî Sâʿide) ortaya çıkmıştır. Neticede sahabenin tecrübeleri sayesinde problemin üstesinden gelinmiştir. Fakat Hz. Osman'ın son dönemlerinde tekrar canlanan bu çekişme bir tür iç savaş olan Cemel, Sıffîn, Nehrevan ve Kerbela hadiseleri ile şiddetlenmiştir. Sonuçta imâmet meselesi ile bağlantılı olarak itikadi birer mezhep iddiasında olan Şiîlik ve Haricîlik akımları ortaya çıktı. Aslında imâmet, inançla alakalı bir mesele olmamasına rağmen Şiîliğin bunu itikadî bir mesele olarak kabul etmesinden dolayı kelâm ve akaid kitaplarında yer almıştır. İlk dönemlerde Haricîliğin bir alt kolu olarak ortaya çıkan, ardından müstakil bir akım olarak varlığını sürdüren İbadîlik, diğer bazı kollardaki aşırı görüşler nedeniyle kendilerine özel bir imâmet düşüncesi oluşturmak istemişlerdir. Bu nedenle İbadî kaynaklarda siyaset ve imâmet ile ilgili tartışmalar oldukça fazladır. İbadîler'in Kuzey Afrika'daki varlığı siyasî bir karardır. Çünkü onlar, diğer Müslüman guruplarından farklı olarak kendilerine özgü bir anlayışı temellendirmek istemişlerdir. Öte yandan İbadîler, imâmet meselesinde Kureyşîlik şartını kabul etmeyip tartışma ortamından uzaklaşarak Kuzey Afrika'ya yönelmişlerdir. Kuzey Afrika'ya gönderilen dâîler (propogandacılar) aracılığıyla bu bölgede II./VIII. asrın sonlarında kendilerine ait bir devlet kurmayı başarmışlardır. Ancak bu devlet uzun müddet varlığını sürdürememiştir. İbadîler, imâmet ile ilgili görüşlerini geliştirerek Azzâbe sistemini kurmuşlar ve varlıklarını günümüze kadar sürdürmüşlerdir.
Ebü'l-Hüseyin el-Basrî'nin kelam sistemi
Son dönem Muʿtezile'sinin en önemli kelâmcılardan biri Ebü'l-Hüseyin el-Basrî'dir. Kendisinden sonra Muʿtezilî düşüncesinin farklı bir boyuta evrilmesini sağladığı gibi kelâm-felsefe ilişkisinin de öncülerinden olan önemli bir halkanın da temsilcisidir. Ebü'l-Hüseyin el-Basrî'nin eserlerinin büyük bir çoğunluğu maalesef günümüze ulaşamamıştır. Lakin gerek takipçileri gerek farklı mezhep ve ekollerden âlimler tarafından alıntılanmış ve sürekli atıf yapılmıştır. Özellikle kendisinden sonra gelen Muʿtezilî âlimlerin başvuru kaynağı haline gelmiştir. Buna ilave olarak kelâm-felsefe bütünlüğünün zirveye taşınmasının en önemli aktörlerinden addedilen Fahreddin er-Râzî tarafından Ebü'l-Hüseyin el-Basrî'nin alıntılanması da müteahhir dönem kelâm geleneği içerisinde önemli bir farkındalık oluşturmuştur. Bu çalışma Ebü'l-Hüseyin el-Basrî'nin düşünce sistemini ortaya çıkarmayı hedeflemektedir. Ebü'l-Hüseyin el-Basrî'nin elimizde bulunan kaynaklarının, takipçilerinin eserlerinin ve ayrıca kendisinden sonra gelen âlimlerin Ebü'l-Hüseyin el-Basrî'ye yaptıkları atıfların izi sürülecektir. Kaynak çeşitliliğinin çok olması ve ayrıntı olarak tek tek atıfların toplanıp inşa edilmesi araştırmayı zorlaştıran hususlardandır. Her ne kadar bu şekilde geniş bir literatür taraması ihtiyacı olsa da kaynakların çoğunluğunun Basrî'nin genel görüşleri hakkında hemfikir olması da avantaj sağlamaktadır. Araştırmada ilk olarak Ebü'l-Hüseyin el-Basrî hakkındaki literatüre değinilmiş peşi sıra hayatı, eserleri, hocaları, öğrencileri ve etkileşim ağı incelenmiştir. Ardından dört bölüm halinde Ebü'l-Hüseyin el-Basrî'nin bilgi, varlık, tevhid, adalet, nübüvvet ve sem'iyyâta dair konular hakkındaki görüşleri ele alınmıştır.
İbadiliğin itikadi konularda nakli delille istidlal metodu
The study theoretically and practically tackles the Ibadis methodology in inference method the evidence transfer on matters of belief. The study reviews the Ibadi position on the authenticity of the evidence transfer on doctrinal matters, Then the Ibadi methodology in the extent of reliance on transference to prove the doctrinal origins, and the amount of space occupied by the transfer evidence in the matters of belief. Then ,It gives a clear and rooted view of the Ibadis methodology of inference by evidence transfer on matters of belief, and explaining the attitude of the in the methods of generating evidences and the extent of reliance, on describing analyzing and studying them. The Ibadis prove the authenticity of evidence transfer as the first reliable source in Islamic beliefs, As long as people did not obtain anything from the knowledge of the law except through revelation, Then the evidence transfer is the origin of the evidence and by it the people are rewarded, Except that the Ibadis have a method through which they determine valid evidence to infer the doctrinal issues, The authenticity of evidence and significance is an inevitable origin, And this approach is represented in the theory of knowledge for Ibadis. The epistemology of the Ibadis represents the cornerstone on which the legal principles are built, Where the evidences is divided between an arguing origin and arguable one, And what must be interpreted or rejected if the interpretation is not possible. Keywords: Ibadis, Methodology, Authenticity, evidence transfer, Epistemology.
İzmirli Muhammed b. Veli ve Mesâilü'l-Hilâfiyyât Beyne'l-Eş'ariyyeti ve'l-Mâtürîdiyyeti isimli eserinin tahkik ve tahlili
Kelâm ilmi müslümanlar nezdinde en ince ve en çok dikkat edilmesi gereken ilimdir, zira bu ilme dair her bir söz, altın terazisinden daha hassas bir terazide ölçülür. Bu terazide hataya yer yoktur, çünkü bu hatalar bazen küfre sebep olur. Bu yüzden küçük ya da büyük herhangi bir ihtilaf, araştırma, inceleme ve tedkiki hak eden bir meseledir. Bundan hareketle, fırka ve mezhepleri karşılaştırıp, akidelerini ve görüşlerini araştırmak, bu ilmin en önemli rükunlarından biri olarak kabul edilmiştir. Bu sebeple Mâtürîdî ve Eş'arî mezheplerinden her birini karşılaştırmalı olarak çalışmak kendisinden istiğna edilemeyecek temel bir konu olarak karşımıza çıkmaktadır. Çünkü Ehl-i sünnet kelâmının temsilcileri bu iki mezheptir. Şaşırtıcı olan şey ise söz konusu iki mezhebin birbirlerini tekfir etmemiş, Ehl-i sünnetdışı görmemiş ve bid'at ehli olarak kabul etmemiş olmasıdır. Bu konu kuvvetli ilim ve derin zekaya sahip bir şahsın araştırma ve çalışmasına ihtiyaç duyan bir olgudur. el-Mesâilü'l-hilâfiyye beyne'l-Eşâira ve'l-Mâturîdiyye adlı eserin yazarı Muhammed b. Veli b. Resul el-Kırşehîrî el-İzmîrî de işte böyle bir şahıstır. Müellif söz konusu eserinde Mâtürîdîler ve Eş'arîler arasında ihtilaflı olan altmış yedi meseleyi bir araya getirmiş olup, önemine binaen bu kitabın tahkiki araştırmamızın konusunu teşkil etmiştir.
İmamiye Şia'sında masumiyet anlayışı
In this research, I did my best to clarify the concept of infallibility and its evidence for the Imami Shiites, and to state what they believe about it and the attributes of those immaculate . I have shown with the concept of infallibility and the evidence for it, the matters in wherein the infallible are consideref as such, along with their debstes . Afterwords I gave my comment and make comparisons between their creed and the the creeds of other islamic denominations as well as what I see in duch controvertial matters with details. Ascribed infallibility The Imami Shiites are difrent from the rest of the Islamic schools in that they do not devote infallibility to the prophets only. The Imamates attribute infallibility to their imams especially to Wali al-Faqih and I stated in every topic and chapter of the chapters their words and their evidence, and I have added in each chapter what is required for clarification of the statement, such as introducing the Imami Shiites, their doctrine and their emergence, introducing some of their beliefs on the subject of prophecies, and a comprehensive statement on the issue of the Imamate and its philosophy for them. In the last chapter, I clarified the issue of guardianship of the Fakih, which has sparked deep debate among the Shiites in contemporary history, and the statement about the infallibility of the Wali al-Faqih among the Shiites and others in the Islamic arena of controversy and debate. Keywords: Infallibility, Imami Shiites, the Prophets, the Imamate, the Wali al-Faqih
Dâvûd-i Karsî ve Şerhu Kasîdet'i Bed'i'l-Emâlî isimli eserinin tahkik ve tahlili
Kelam alanında nazım türünde çeşitli eserler kaleme alınmış olup Siracüddîn Ali b. Osman el-Ûşî'de (ö. 575/1179) bu tür eser yazan müelliflerden birisidir. Yazmış olduğu eser büyük bir üne kavuşmuş ve Osmanlı devleti gibi Matüridi mezhebini takip eden topluluklar tarafından okunarak medreselerde ders kitabı olarak okutulmuştur. Kazandığı bu büyük ünden dolayı Siracüddîn Ali b. Osman el-Ûşî'ye ait olan Kasîdetü'l-Emâlî isimli eser üzerine çeşitli zaman ve mekanlarda yazılmış birçok şerh bulunmaktadır. Bu şerhlerden gün yüzüne çıkarılanlar olduğu gibi halen araştırmacılar tarafından bulunarak ilim dünyasına kazandırılmayı bekleyenler vardır. XVIII. yüzyıl Osmanlı coğrafyasında yaşamış olan Dâvûd-i Karsî'ye (ö. 1169/1756) ait olan Şerh'u Kasîdeti Bedü'l-Emâlî isimli eseri de gün yüzüne çıkarılmayı bekleyen eserlerden birisidir. Biz bu çalışmamızda söz konusu eserin çeşitli kütüphanelerdeki farklı nüshalarını karşılaştırarak bu eseri ilim camiasına kazandırmayı amaçladık.
İmam Mâtürîdî ve Zemahşerî'nin irâde ve meşîet konusuyla ilgili âyet-i kerimelere dair yorumlarının karşılaştırılması
Kur'ân, indirildiği günden bugüne doğru anlaşılma gayesine matuf farklı tefsir metodlarıyla açıklanmaya çalışılmıştır. Bu metodlar içerisinde dirâyet metodu, aklı merkeze almanın yanında dilin imkânlarını çokça kullanmasıyla temayüz etmiştir. Mâtürîdî'nin Te'vîlâtü Ehli's-sünne (Te'vîlâtü'l-Kur'ân) isimli tefsiri, Kur'ân'ı başından sonuna kadar bir bütün halinde dirâyet ağırlıklı bir şekilde tefsir etmeyi amaçlayan ilk eser olma özelliğini taşımaktadır. Bunun yanında dil sanatlarını kullanmada son derece mahir olan Zemahşerî'nin el-Keşşâf isimli tefsiri de bu alanın başat eseri sayılmıştır. Diğer yandan bu iki tefsirin müelliflerinden biri Ehl-i sünnet kelamının önemli bir kolu olan Mâtürîdiyye mezhebi kurucusu İmam Matürîdî, diğeri ise Mu'tezile kelâmının geç dönem savunucularından Zemahşerî'dir. İki ayrı kelâmî ekolü temsil eden bu imamlar, söz konusu kelâmî mezheplerini tefsirlerine yansıtmış, dahası âyetleri yorumlarken mezheplerini savunucu bir rol üstlenmişlerdir. Bu açıdan iki tefsirin kelâmî içerikli âyetlere dair yorumlarının karşılaştırmalı incelenmesi önem arz etmektedir. Bu çalışmada iki müfessirin irâde ve meşîet ile ilgili âyetlere yaptıkları yorumlar öncelikle kelâmî açıdan ikincil olarak dilbilimsel açıdan ele alınmıştır. Dilbilim ise çeşitli alt dallara sahip geniş bir bilimdir. Âyet yorumlarının dilbilimin bu geniş alanını kuşatacak şekilde ele alınması, birden çok çalışmanın konusu olacağı müsellemdir. Bu sebeple dilbilimsel analizler, müelliflerin yalnızca kelâmî mezheplerini savundukları yerlerde konunun esasını ilgilendirdiği kadarıyla yapılmıştır. Çalışmada özetle Mâtürîdî ve Zemahşerî'nin dilbilimsel yönlerinin kelâmî yönlerini öncelemedikleri; bilakis kalâmî bir alt yapıya sahip olduktan sonra dilin imkânlarından faydalanarak âyetleri yorumladıkları görülmüş ve ortaya konulmuştur.
Fâtımîler Dönemi İsmâilî inanç sistemi
Fikir ve eylemleri, toplumun önemli sosyolojik konularından biri olduğu gibi aynı zamanda toplumun biçimlenmesinde etkin role sahip bir olgudur. İslam dünyasında siyasî iktidarın kimde veya hangi gurupta olacağı ve bunun neye göre belirleneceği hususu tartışmalıdır. Kimileri bu hususun ayetlerde ve hadislerde belirtilmeyerek toplumun iradesine ve seçim esasına bırakıldığını savunurken kimileri de idarenin kimde olacağı hususunun Allah ve resulü tarafından net ve kesin bir şekilde belirtildiğini iddia etmektedir. Bu farklı yaklaşımlar, İslam toplumunda günümüze kadar gelen bölünmelere sebep olmuştur. Bu nedenle İslam toplumundaki farklılaşmanın ve gruplaşmanın mihenk taşını, iktidarın kimde ve nasıl olması gerektiği hususunun oluşturduğunu söylemek mümkündür. İslam tarihinde bu noktadan hareketle ortaya çıkan en önemli fırkalardan biri de İsmâiliyye fırkasıdır. Bu fırkanın temel felsefesi, siyasî iktidarın, dinin kurucusu konumunda olan Hz. Peygamber'in damadı ve amcazadesi olan Hz. Ali ve ailesinin hakkı olduğu ve bunun da Allah ve resulü tarafından nasla belirlendiği fikrine dayanmaktadır. Bu inancın bir yansıması olarak itikadi alandaki diğer konularda da bu fikri destekleyecek yaklaşımlar sergilenmiş ve metotlar geliştirilmiştir. İsmâilîler bu fikirlerini ispatlamak için her türlü argümanı kullanmış ve kendi fikirlerine engel teşkil eden Kur'ân'ın ayetlerini batınî yoruma başvurarak fikirleriyle uyumlu hale getirmeye çalışmışlardır. Ortaya attıkları İmâmet doktrinini ispatlamak için kainattaki nizamdan örnekler vermiş ve vesâyet olgusunu icat etmişlerdir. Ayrıca nübüvvet ve ahiret konularına Sünnî düşünceden farklı bakış açıları geliştirmişlerdir.
Seyyid Kutub'un siyasi düşüncesinin teolojik temelleri
20. yüzyılın düşünürlerinden biri olan Seyyid Kutub, İslam dünyasının birçok coğrafyada hem sosyal hem siyasi karışıklık içinde bulunduğu bir dönemde (d.1906 – ö.1966) yaşamıştır. Benzer sıkıntıların olduğu Mısır'da, İslam toplumu adına orjinal tespitlerde bulunmuştur. Müslümanları yeniden Kur'ân ile bilinçlenmeye, cahili tüm kuşatmalardan kimliklerini arındırarak Müslüman ümmetini diriltecek olan örnek Kur'ân neslini inşa etmeye çağırmıştır. Bu hedefe yönelik varolan düzene ciddi eleştiriler getirmiş, İslami bir uyanış süreci için ise mantıklı, tutarlı, merkezini Kur'ân'dan alan yeni bir eğitim müfredatı oluşturmaya çalışmıştır. Kutub'a göre inanan insanların hayatlarındaki tüm hukuki gerek ve yükümlülüklerin tevhid ilkesine göre düzenlenmesi için Kur'ân, tevhide vurgu yapar. Tevhid ilkesi ibadette mabud birliğine, hukuk ve kanunda kaynak birliğine, sosyal hayatı şekillendiren sosyal düzen birliğine ulaştırır. Herhangi bir sosyal, siyasal, ekonomik, ahlaki ya da devletlerarası sistemin sağlam ve istikrarla varolabilmesi için Allah'ın birliği ilkesine dayanması gerekir. Yüce Allah'ın Rabb'lık, egemenlik, kayıtsız-şartsız-ortaksız otorite gibi tamamı ile kendine özgü yetkileri vardır. İnsanlık tarihi boyunca birtakım insanlar, Allah'ın hakkını gasbederek, çalınmış ve sahte otoritelerine itaatı isteyerek, insanlığı kendilerine köle yapmışlardır. Nebi'nin görevi bu "çalınmış" otoriteyi zorba insanların elinden alıp, insanı gerçek onuruna ve Allah'a boyun eğme özgürlüğüne ulaştırmaktır. Kur'ân'ı esas alan İslami hareketler de aynı mücadeleyi yapmalıdır. Kutub'a göre inanç pratik hayata dökülüp Kur'an yaşanmadığı müddetçe kişi beşeri anarşi karşısında kalır. Egemenlik yetkisi sadece Allah'a özgüdür. Kullar için tek yasa koyucu merci Allah'tır. İnsanlar yasa koyabilir fakat Allah'ın şeriatine dayanmak zorundadır. Kitap değişen insanlık hayatı için kalıcı bir sistemin temellerini koymuştur. İhtiyaç duyulduğu takdirde, ikinci derece hükümlerin çıkarılması kalıcı sistemin ilkeleriile çelişmediği takdirde mümkündür. Kutub, günümüz metaryalist dünyasında insana hak ettiği değerin verilmediğini ve onu eşyaya bağımlı görmekle insanın tutsaklaştırıldığını ifade eder. İslam'ın insanlar için uygun gördüğü milliyetçiliği, bütün insanların Allah'ın sancağı altında bir ve eşit kabul edildiği inanç milliyetçiliği olarak tarif ve kabul eder. Kutub'un ortaya koyduğu tespit ve eleştirilerine bütünüyle baktığımızda, onun siyaset düşüncesinin Kur'an merkezli bir ihya projesi, ideal ve örnek bir Kur'an nesli inşa etmeyi amaçladığını söyleyebiliriz. Kutub, yüzyıllardır devam edegelen İslamî ıslah anlayışının, kendi yaşadığı dönemdeki temsilcisi rolünü taşmıştır. Bunu yaparken de Kuran'ı Kerim'deki ana esasları (şirk, tevhid, hâkimiyet) kendine özgü net ve kesin çizgilerle açıklamış, kendi ihya görüşünün merkezine koymuştur. Kutub, fikirlerini nihai itibariyle, Kur'an temelli bir akideden ve yalnızca bu akidenin hayat verdiği İslamî bir hareketin İslam toplumunun yeniden inşası adına önemli bir adım olduğuna ve İslam'dan örnek bir İslamî topluma varılması gerektiği tezine dayandırır. Bu sonucu aynı zamanda amaç olarak görür. Bu amaca dair yapılması gerekenleri ve attığı adımları İslam düşüncesinde yeni bir dönemin işaretçisi olan, kendi düşünsel süreçlerinin nihayetinde fikirlerini kuvvetli ve net bir şekilde sunduğu, bu tezimizin de ana kaynaklarını oluşturan ''Fi Zılali'l Kur'an'' (Kur'an'ın gölgesinde) ve ''Me'alimFi't-tarik'' (Yoldaki işaretler) eserinde dile getirmiştir.
Machine learning in solar energy utilization
In this dissertation, the solar energy utilization processes were studied via machine learning algorithms. First, a bibliometric analysis of the topic was performed; it was observed that photovoltaics and hydrogen-related applications have been studied more extensively while machine learning, mostly neural network and deep learning algorithms, has been mainly used for forecasting and optimization. Desalination, dye-sensitized solar cells and photo(electro)catalysis, which are the most commonly studied solar technologies, were selected for further analysis in this dissertation. The data were collected using Web of Science database search with related keywords while R language was used for the analysis. Tree-based ensemble methods gave higher predictive power, apparently due to the presence of a large number of categorical variables; the decision trees were used to deduce heuristic rules for high performance, especially for the cases in which the predictive models were not successful. Although the band gaps of semiconductors were generally predicted successfully, the accuracy in the prediction of gas production rate and photocurrent density was lower; hence, the classification with a decision tree was employed to identify the range of input variables for high performance. Results in desalination analysis suggested that the inlet water and air temperatures and flow rates have a higher influence on the performance. The dye type was found to be the most important variable for the performance of both synthetic and natural dye solar cells; the type of counter electrode also becomes important for synthetic dyes whereas electrolyte is more influential in natural dye counterparts. In photocatalysis, it was also found that the band gap mostly depended on the preparation method of the semiconductor while the photocurrent density was affected by bias and electrolyte. For $CO_2$ reduction, the method used for co-catalyst deposition and reaction temperature were important for the gas and liquid phase systems, respectively.