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In Turkey, facilities for the use of biomass resources in energy production are increasing, and new conversion facilities are commissioned every year to provide environmentally friendly energy production. Therefore, reliable energy potential estimates are needed. In this study, the animal manure-based-biogas potentials of Antalya, Isparta, and Burdur provinces in the Western Mediterranean Region of Turkey were calculated. Here, special information on cattle, small ruminants, and poultry, and animal age, number, and manure amount information were used in detail. In addition, carbon dioxide emissions, coal, electricity, and thermal energy, methane emission values with the Tier 1 and Tier 2 approaches were calculated and predicted by machine learning algorithms. To determine the model with the best results, machine learning algorithms support vector machine (SVM), multi-layer perceptron (MLP), and linear regression (LR) were used, and hyper-parameter optimization was performed. According to the results of biogas potential, CO

In this study, the animal manure-based biogas potentials of Antalya, Isparta, and Burdur provinces in the Western Mediterranean region of Turkey were calculated. CO2 emission, coal, electricity, and thermal energy, CH4 emission values were calculated and machine learning modeling was performed. A total of 550305 tons/year of manure can be obtained from this animal's existence. As a result of the calculation, 130929541 m3/year of biogas can be produced from manure. Depending on biogas production; 93484 tons/year of coal, 235673174 kWh/year of electrical energy, and 2828078093 MJ/year of thermal energy can be provided and 153653 tons/year of CO2 emissions will be prevented. In this study, special information on cattle, sheep, and poultry, and animal age, number, and manure amount information were used in detail. To determine the model with the best results, machine learning algorithms Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), and Linear Regression (LR) were used and hyper-parameter optimization was performed. According to the results of biogas potential, CO2 emission, electricity production, and thermal energy estimations SVM models are seen as the best models with R2 = 0.999. When the coal amount estimation is examined, the LR models produce better results than SVM and MLP with R2 = 0.997. In the estimation of CH4 using the Tier 1 approach, the MLP model can perform the best estimation with R2 = 0.977. In the CH4 modeling obtained using the Tier 2 approach, the LR models were superior to the other models with the performance value of R2 = 0.962.

Polietilen oksitin sulu çözeltilerde ultrasonik zincir kırılması çalışılmıştır. Çözelti konsantrasyonu ve sıcaklığın polietilen oksit zincir kırılmasına etkileri incelenmiştir. Sonikasyon 20 kHz ultrases frekansında sabit güç ile 1x10-3 , 2x10-3 , 3x10-3 , 4x10-3 g/mL polietilen oksit konsantrasyonlarında ve 10, 20, 30, 40 0 C sıcaklıklarda gerçekleştirilmiştir. Polimer zincir kırılması çözeltinin spesifik viskozitesinin sonikasyon zamanına göre değişimi cinsinden karakterize edilmiştir. Teorik Madras ve Giz zincir kırılması modelleri viskozite ortalama molekül ağırlığı değişimini analiz etmek ve limit molekül ağırlığı – kırılma sabiti belirlemek için kullanılmıştır. Sonuçlar viskozite-molekül ağırlığının azaldığını ve zincir kırılmasının daha düşük sıcaklıklar ve çözelti konsantrasyonlarında daha hızlı ilerlediğini göstermektedir. The ultrasonic chain scission of polyethylene oxide was studied in aqueous solutions. The effects of solution concentration and temperature on polyethylene oxide chains scission were investigated. Sonication is performed at 20 kHz ultrasound frequency with fixed power at 1x10-3 , 2x10-3 , 3x10-3 , 4x10- 3 g/mL polyethylene oxide concentration and temperatures of 10, 20, 30, 40 0 C. Poymer chain scission was charactrized in terms of the change in the specific viscosity of the solution as a function of sonication time. Theoretical Madras and Giz chain scission models were used to analyse the viscosity average molecular weight evaluation and determine the limit molecular weight – scission constant. Results show that viscosity - molecular weight decreased and the chain scission proceeded faster for lower temperatures and solution concentrations.

Monoamine oxidases are two isozymic flavoenzymes which are the important targets for drugs used in the treatment of depression, Parkinson and Alzheimer's diseases. The catalytic reaction taking place between the cofactor FAD and amine substrate is still not completely understood. Herein we employed quantum chemical methods on the recently proposed direct hydride transfer mechanism including full active site residues of MAO isoforms in the calculations. Activation free energy barriers of direct hydride transfer mechanism for MAO-A and MAO-B were calculated by ONIOM (our own n-layered integrated molecular orbital + molecular mechanics) method with QM/QM (quantum mechanics:quantum mechanics) approach employing several density functional theory functionals, B3LYP, WB97XD, CAM-B3LYP and M06-2X, for the high layer. The formation of very recently proposed αC-flavin N5 adduct inside the enzyme has been investigated. ONIOM (M06-2X/6-31+G(d,p):PM6) results revealed that such an adduct may form only in MAO-B suggesting slightly different hydride transfer mechanisms for MAO-A and MAO-B.