Semiconductor-based metal oxide gas detector of five mixed from zinc chloride Z and tin chloride S salts Z:S ratio 0, 25, 50, 75 and 100% were fabricated on glass substrate by a spray pyrolysis technique. With thickness were about 0.2 ±0.05 μm using water soluble as precursors at a glass substrate temperature 500 ºC±5, 0.05 M, and their gas sensing properties toward CH4, LPG and H2S gas at different concentration (10, 100, 1000 ppm) in air were investigated at room temperature which related with the petroleum refining industry.
Furthermore structural and morphology properties were scrutinize. Results shows that the mixing ratio affect the composition of formative oxides were (ZnO, Zn2SnO4, Zn2SnO4+ZnSnO3, ZnSnO3, SnO2) ratios ment

Dielectric barrier discharges (DBD) can be described as the presence of contact with the discharge of one or more insulating layers located between two cylindrical or flat electrodes connected to an AC/pulse dc power supply. In this work, the properties of the plasma generated by dielectric barrier discharge (DBD) system without and with a glass insulator were studied. The plasma was generated at a constant voltage of 4 kV and fixed distance between the electrodes of 5 mm, and with a variable flow rate of argon gas (0.5, 1, 1.5, 2 and 2.5) L/min. The emission spectra of the DBD plasmas at different flow rates of argon gas have been recorded. Boltzmann plot method was used to calculate the plasma electron temperature (Te), and Stark broadeni

(Cu1-x,Agx)2ZnSnSe4 alloys have been fabricated with different Ag content(x=0, 0.1, and 0.2) successfully from their elements. Thin films of these alloys have been deposited on coring glass substrate at room temperature by thermal evaporation technique under vacuum of 10-5Torr with thickness of 800nm and deposition rate of 0.53 nm/sec. Later, films have been annealed in vacuum at (373, and 473)K, for one hour. The crystal structure of fabricated alloys and as deposited thin films had been examined by XRD analysis, which confirms the formation of tetragonal phase in [112] direction, and no secondary phases are founded. The shifting of main polycrystalline peak (112) to lower Bragg’s angle as compared to Cu2ZnSnSe4 angle refers to incorpora

Silicon nitride nanostructures were prepared by reactive sputtering technique using silicon targets with different types of electrical conductivity (n-type and p-type) and Ar:N2 gas mixing ratio of 70:30. The optical microscopy and spectroscopic characteristics of these films were determined in order to introduce the effect of target conductivity type on these characteristics. The results showed that using p-type silicon target would produce Si3N4 films with lower tendency to adsorb water vapor and other constituents of the atmospheric air, higher absorbance in the visible range 400-700nm, and lower variation in the energy band gap with film thickness than the Si3N4 films prepared from n-type silicon target.

Denture bases are fabricated routinely using Poly(methyl methacrylate) (PMMA) acrylic resin. Yet, it is commonly known for its major drawbacks such as insufficient strength and ductility. The purpose of this study was to improve the performance of PMMA acrylic resin as a denture base material by reinforcement with surface treated lithium disilicate glass ceramic powder. The ceramic powder was prepared by grinding and sieving IPS e.max CAD MT blocks. Then, the powder was surface treated with an organosilane coupling agent (TMSPM) and added to PMMA in amount of 1%, 3%, 5% and 7% by weight. Characterizations of the powder was done by particle size analysis, XRD and FTIR. Transverse strength, Impact strength, Shore D hardness and surface roughn

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m