In this study the as-deposited and heat treated at 423K of conductive blend graphene oxide (GO)/ poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) thin films was prepared with different PEDOT:PSS concentration (0, 0.25, 0.5, 0.75 and 1)w/w on pre-cleaned glass substrate by spin coater. The XRD analysis indicate the existence of the preffered peak (001) of GO around 2θ=8.24° which is domain in all GO/ PEDOT:PSS films characterized for GO, this result approve the good quality of the PEDOT:PSS dispersion in GO, this peak shifted to the lower 2θ with increasing PEDOT:PSS concentration and after annealing process. The scanning electron microscopy (SEM) images and atomic force microscopy (AFM) clearly sh

This study shows that it is possible to fabricate and characterize green bimetallic nanoparticles using eco-friendly reduction and a capping agent, which is then used for removing the orange G dye (OG) from an aqueous solution. Characterization techniques such as scanning electron microscopy (SEM), Energy Dispersive Spectroscopy (EDAX), X-Ray diffraction (XRD), and Brunauer-Emmett-Teller (BET) were applied on the resultant bimetallic nanoparticles to ensure the size, and surface area of particles nanoparticles. The results found that the removal efficiency of OG depends on the G‑Fe/Cu‑NPs concentration (0.5-2.0 g.L-1), initial pH (2‑9), OG concentration (10-50 mg.L-1), and temperature (30-50 °C). The batch experiments showed

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

Background: The world is in front of two emerging problems being scarceness of virgin re-sources for bioactive materials and the gathering of waste production. Employment of the surplus waste in the mainstream production can resolve these problems. The current study aimed to prepare and characterize a natural composite CaO-SiO2 based bioactive material derived from naturally sustained raw materials. Then deposit this innovative novel bioactive coating composite materials overlying Yttria-stabilized tetragonal zirconia substrate. Mate-rials and method; Hen eggshell-derived calcium carbonate and rice husk-derived silica were extracted from natural resources to prepare the composite coating material. The manufac-tured powder was characterized

            A spectrophotometric- reverse flow injection analysis (rFIA) method has been proposed for the   determination of Nitrazepam (NIT) in pure and pharmaceutical preparations. The method is based upon the coupling reaction of NIT with a new reagent O-Coumaric acid (OCA) in the presence of sodium periodate in an aqueous solution. The blue color product was measured at 632 nm. The variation (chemical and physical parameters) related with reverse flow system were estimated. The linearity was over the range 15 - 450 µg/mL of NIT with detection limits and limit of quantification of 3.425 and 11.417 µg mL^-1 NIT,respectively. The sample throughput of 28 samples

The population of Ephemeroptera was studied in three selected stations of Rawanduz River (Gali Ali Beg water fall, Rawanduz River and after the junction of these two waters) during the three seasons of spring, summer and autumn in 2016. In addition,sixteen physicochemical parameters (pH, EC, turbidity, DO, BOD₅, NO₃, TDN, TDP, HCO₃^-, Hardness, Ca²⁺, Mg²⁺, Na⁺, K⁺, Cl^-, SO₄^2-, Na% and SAR) of water in these stations were estimated and used to calculate the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI). Eleven species of aquatic insects were identified,which belong to four families of th