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Article Citation - WoS: 7Citation - Scopus: 10Ann-Assisted Forecasting of Adsorption Efficiency To Remove Heavy Metals(Tubitak Scientific & Technological Research Council Turkey, 2019) Buaısha, Magdi; Balku, Şaziye; Yaman, Şeniz ÖzalpIn wastewater treatment, scientific and practical models utilizing numerical computational techniques suchas artificial neural networks (ANNs) can significantly help to improve the process as a whole through adsorption systems.In the modeling of the adsorption efficiency for heavy metals from wastewater, some kinetic models have been used such as pseudo first-order and second-order. The present work develops an ANN model to forecast the adsorption efficiency of heavy metals such as zinc, nickel, and copper by extracting experimental data from three case studies. To do this, we apply trial-and-error to find the most ideal ANN settings, the efficiency of which is determined by mean square error (MSE) and coefficient of determination (R2). According to the results, the model can forecast adsorption efficiency percent (AE%) with a tangent sigmoid transfer function (tansig) in the hidden layer with 10 neurons and a linear transferfunction (purelin) in the output layer. Furthermore, the Levenberg–Marquardt algorithm is seen to be most ideal for training the algorithm for the case studies, with the lowest MSE and high R2 . In addition, the experimental results and the results predicted by the model with the ANN were found to be highly compatible with each other.Article Analysis of the Effect of Propellant Temperature on Interior Ballistics Problem(2018) Evci, C.; Işık, H.This study investigates the effect of conditioning temperature of double base propellants on the interiorballistic parameters such as burning gas temperature, barrel wall temperature, pressure and stresses generated inthe barrel. Interior ballistic problem was solved employing experimental, numerical and analytical methods witha thermo-mechanical approach. Double base propellants were conditioned at different temperatures (52, 35, 21, 0,-20, -35, -54oC). The maximum pressure in the barrel and projectile muzzle velocity were measured for all thepropellants by conducting shooting tests with a special test barrel using 7.62x51 mm NATO ammunition. Vallier-Heydenreich method was employed to determine the transient pressure distribution along the barrel. Thetemperature of burnt gases was calculated by using Noble-Abel equation. The heat transfer analysis was doneusing the commercial software ANSYS to get the transient temperature and stress distributions. Temperaturedistribution through the barrel wall thickness was validated using a FLIR thermal imager. Radial, circumferentialand axial stresses and corresponding equivalent Von Misses stresses were determined numerically andanalytically. The results of the analytical solution for stress analysis validated the finite element solution of interiorballistic problem. Increasing the initial temperature of the propellant resulted in higher temperature and pressureinside the barrel which in turn increased the stresses in the barrel.Article Hydrogen Implantation Effects on the Electrical and Optical Properties of Inse Thin Films(2012) Qasrawı, Atef Fayez; Ilaıwı, Khaled Faysal; Polımenı, AntonioThe effects of hydrogen ion implantation on the structural, electrical and optical properties of amorphous InSe thin films have been investigated. X-ray diffraction analysis revealed no change in the structure of the films. An implantation of 7.3 × $10^{18}$ ions/$cm^2$ decreased the electrical conductivity by three orders of magnitude at 300 K. Similarly, the conductivity activation energy, which was calculated in the temperature range of 300–420 K, decreased from 210 to 78 meV by H-ion implantation. The optical measurements showed that the direct allowed transitions energy band gap of amorphous InSe films has decreased from 1.50 to 0.97 eV by implantation. Furthermore, significant decreases in the dispersion and oscillator energy, static refractive index and static dielectric constants are also observed by hydrogen implantation.Article Gold-Assembled Silica-Coated Cobalt Nanoparticles as Efficient Magnetic Separation Units and Surface-Enhanced Raman Scattering Substrate Lütfiye Sezen Yildirim1,, Murat Kaya2,∗,, Mürvet Volkan(Tubitak Scientific & Technological Research Council Turkey, 2019) Yıldırım, Lütfiye Sezen; Kaya, Murat; Volkan, MürvetMagnetic and optical bifunctional nanoparticles that combine easy separation, preconcentration, and efficientSERS capabilities have been fabricated with high sensitivity and reproducibility through a low-cost method. Thesegold nanoparticles attached on magnetic silica-coated cobalt nanospheres (Co@SiO2 /AuNPs) display the advantageof strong resonance absorption due to gaps at nanoscale between neighboring metal nanoparticles bringing large fieldenhancements, known as “hot spots”. The prepared particles can be controlled by using an external magnetic field,which makes them very promising candidates in biological applications and Raman spectroscopic analysis of dissolvedorganic species. The magnetic property of the prepared particles lowers the detection limits through preconcentrationwith solid-phase extraction in SERS analysis. The performance of the prepared nanostructures was evaluated as a SERSsubstrate using brilliant cresyl blue (BCB) and rhodamine 6G (R6G) as model compounds. The solid-phase affinityextraction of 4-mercapto benzoic acid (4-MBA) using bifunctional Co@SiO2 /AuNPs nanoparticles followed by magneticseparation and the measurement of the SERS signal on the same magnetic particles without elution were investigated.Approximately 50-fold increase in SERS intensity was achieved through solid-phase extraction of 8.3 × 10 −6 M 4-MBAin 10 min.
