A chemical optical fiber sensor based on surface plasmon resonance (SPR) was developed and implemented using multimode plastic optical fiber. The sensor is used to detect and measure the refractive index and concentration of various chemical materials (Urea, Ammonia, Formaldehyde and Sulfuric acid) as well as to evaluate the performance parameters such as sensitivity, signal to noise ratio, resolution and figure of merit. It  was noticed that the value of the sensitivity of the optical fiber-based SPR sensor, with 60nm and 10 mm long, Aluminum(Al) and Gold (Au) metals film exposed sensing region, was 4.4 μm, while the SNR was 0.20, figure of merit was 20 and resolution 0.00045. In this work a multimode

High temperature superconductors materials with composition Bi1.6-xSbxPb0.4Sr2Ca2-yCdyCu3OZ (x = 0, 0.1, 0.2 and 0.3) and (y = 0.01 and 0.02), were prepared by using the chemical reaction in solid-state ways, and test influence of partial replacement of Bi and Ca with Sb and Cd respectively on the superconducting properties, all samples were sintered at the same temperature (850 oC) and for the same time (195 h). The structural analysis of the prepared samples was carried out using X-ray diffraction (XRD) measurements performed at room temperature, scanning electron microscope (SEM) and dc electrical resistivity was measured as a function of temperature. It was found that the sample prepared by partial substitution of Sb at ratio (x= 0.2

RKRAS L. K. Abdul Karem, F. H. Ganim, Biochemical and Cellular Archives, 2018 - Cited by 2

SYNTHESIS, CHARACTERIZATION, STRUCTURAL, THERMAL, POM STUDIES, ANTIMICROBIAL AND DNA CLEAVAGE ACTIVITY OF A NEW SCHIFF BASE-AZO LIGAND AND ITS COMPLEXATION WITH SELECTED METAL IONS

The most significant function in oil exploration is determining the reservoir facies, which are based mostly on the primary features of rocks. Porosity, water saturation, and shale volume as well as sonic log and Bulk density are the types of input data utilized in Interactive Petrophysics software to compute rock facies. These data are used to create 15 clusters and four groups of rock facies. Furthermore, the accurate matching between core and well-log data is established by the neural network technique. In the current study, to evaluate the applicability of the cluster analysis approach, the result of rock facies from 29 wells derived from cluster analysis were utilized to redistribute the petrophysical properties for six units of Mishri