The spectroscopic properties, potential energy curve, dipole moments, total charge density, Electrostatic potential as well as the thermodynamic properties of selenium diatomic halides have been studied using code Mopac.7.21 and hyperchem, semi-empirical molecular orbital of MNDO-method (modified neglected of differential overlap) of parameterization PM3 involving quantum mechanical semi-empirical Hamiltonian. The relevant molecular parameters like interatomic distance, bond angle, dihedral angle and net charge were also calculated.
The research aims to identify the level of balance in the architectural thought influenced by the rational type human consciousness, the materialistic based on the Empirical type, moral based on human experience as source of knowledge.
This was reflected in architecture in the specialized thought that the mind is the source of knowledge which explains the phenomena of life. The rational approach based on objectivity and methodology in (Form Production), the other approach is based on subjectivity in form production (Form Inspiration).
The research problem is that there is imbalance in the relationship between the rational side and the human experience in architecture, which led into imbalance between theo
... Show MorePumpkin waste powder was used as a coloring and strengthening filler in epoxy to prepare a natural gelcoat . The Pumpkin powder was mixed with different weight ratios (1, 2, 3, 4, 5, 6, 7, and 8%) to the epoxy matrix to select the best value of powder addition. The effect of the pumpkin particle size on the mechanical properties (impact, flexural, hardness, and wear loss) using two different sizes (2.5 and 1.25 microns) was studied. The impact strength increased from (10.09 KJ/ m2) for neat epoxy to (14.79 KJ/ m2) for epoxy with 1% of micron pumpkin fibers ( MPF) with particle size 2.5 micrometer and (14.21 KJ/ m2) for epoxy with 4% (1.25 MPF), flexural strength increased from (41.94 MPa) for n
... Show MoreFour new copolymers were synthesized from reaction of bis acid monomer 3-((4-carboxyphenyl) diazenyl)-5-chloro-2-hydroxybenzoic acid with five diacidhydrazide in presence of poly phosphoric acid. The resulted monomers and copolymers have been characterized by FT-IR, 1H-NMR, 13C-NMR spectroscopy as well as EIMs technique. The number averages of molecular weights of the copolymers are between 4822 and 9144, and their polydispersity indexes are between 1.02 and 2.15. All the copolymers show good thermal stability with the temperatures higher than 305.86 C when losing 10% weight under nitrogen. The cyclic voltammetry (CV) measurement and the electrochemical band gaps (Eg) of these copolymers are found below 2.00 ev.
In this work we experimentally investigated SWCNTs and MWCNTs to increase their thermal conductivity and electrically functionalization process using different reagents ((nitric acid, HNO3 followed by acid treatment with H2SO4), then washed with deionized water (DW) and then treated with H2O2 via ultrasonic technique. Then repeated the steps with MWCNTs and compare their results in an effort to improve experimental conditions that efficiently differentiate the surface of the single walled carbon nanotubes (SWCNTs) and multi walled carbon nanotubesi(MWCNTs) that less nanotubes destroy and to enhance the properties of them and also to reduce aggregation in liquid. the results were prove by XRD, and infrared spectroscopy (FTIR). The FTIR sp
... Show MoreThis study focused on spectral clustering (SC) and three-constraint affinity matrix spectral clustering (3CAM-SC) to determine the number of clusters and the membership of the clusters of the COST 2100 channel model (C2CM) multipath dataset simultaneously. Various multipath clustering approaches solve only the number of clusters without taking into consideration the membership of clusters. The problem of giving only the number of clusters is that there is no assurance that the membership of the multipath clusters is accurate even though the number of clusters is correct. SC and 3CAM-SC aimed to solve this problem by determining the membership of the clusters. The cluster and the cluster count were then computed through the cluster-wise J
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