This research include synthesized and characterization the compound [I] by reaction terephthaldehyde , mercaptoacetic acid and thiosemicarbazide with concentrated sulfuric acid then this compound reaction with ethyl chloroacetate and sodium acetate to product ester compound [II],the latter compound reaction with hydrazine hydrate to synthesized acid hydrazide [III] after that reaction with 4-alkoxy benzaldehyde[IV]n to synthesized Schiff bases compounds [V]n, the compound [VI] synthesized via reaction compound [I] with chloroacetic acid and sodium acetate then the compound[VI] reaction with 2-phenylenediamine in 4 N hydrochloric acid to product benzimidazole compound[VII]. The compounds characterized by melting points, FTIR and 1HNMR spectroscopy. The mesomorphic behavior studied by using polarized optical microscopy
The doping process with materials related to carbon has become a newly emerged approach for achieving an improvement in different physical properties for the obtained doped films. Thin films of CuPc: C60 with doping ratio of (100:1) were spin-coated onto pre-cleaned glass substrates at room temperature. The prepared films were annealed at different temperatures of (373, 423 and 473) K. The structural studies, using a specific diffractometry of annealed and as deposited samples showed a polymorphism structure and dominated by CuPc with preferential orientation of the plane (100) of (2θ = 7) except at temperature of 423K which indicated a small peak around (2θ = 3
Silver selenide telluride Semiconducting (Ag2Se0.8Te0.2) thin films were by thermal evaporation at RT with thickness350 nm at annealing temperatures (300, 348, 398, and 448) °K for 1 hour on glass substrates .using X-ray diffraction, the structural characteristics were calculated as a function of annealing temperatures with no preferential orientation along any plane. Atomic force microscopy (AFM) and X-ray techniques are used to analyze the Ag2SeTe thin films' physical makeup and properties. AFM techniques were used to analyze the surface morphology of the Ag2SeTe films, and the results showed that the values for average diameter, surface roughness, and grain size mutation increased with annealing temperature (116.36-171.02) nm The transm
... Show MoreIn this work ,pure and doped(CdO)thin films with different concentration of V2O5x (0.0, 0.05, 0.1 ) wt.% have been prepared on glass substrate at room temperature using Pulse Laser Deposition technique(PLD).The focused Nd:YAG laser beam at 800 mJ with a frequency second radiation at 1064 nm (pulse width 9 ns) repetition frequency (6 Hz), for 500 laser pulses incident on the target surface At first ,The pellets of (CdO)1-x(V2O5)x at different V2O5 contents were sintered to a temperature of 773K for one hours.Then films of (CdO)1-x(V2O5)x have been prepared.The structure of the thin films was examined by using (XRD) analysis..Hall effect has been measured in orded to know the type of conductivity, Finally the solar cell and the effici
... Show MoreThis paper reviews the distribution range of wild goat Capra aegagrus (Erxleben, 1777) in Iraq with new sighting of very small herd of wild goat occur in Alqosh mountain, north of Nineveh province, where wild goat have a little informations on the distribution areas in Iraq according to the Red List of the International Union for Conservation of Nature (IUCN).
In current study, the dye from flowers petals of Strelitzia reginae used for the first time to prepare natural photosensitizer for DSSC fabrication. Among five different solvents used to extract the natural dye from S. reginae flowers, the ethanol extract of anthocyanin dye revealed higher absorption spectrum of 0.757a.u. at wavelength of 454nm. A major effect of temperature was studied to increase the extraction yield. The results show that the optimal temperature was 70 °C and there was a sharp decrease of dye concentration from 0.827 at temperature of 70 °C to 0.521 at temperature of 90°C. The extract solution of flowers of S. reginae showed higher concentration in acidic media, especially at pH 4 (0.902). The
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreVarious theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp
... Show MoreAmong a collection of leafhoppers from Erbil Province in Kurdistan/Iraq, a new species of the genus Arboridia Zakhvatkin, 1946 was designated and described here as a new species to the science. The erection of this species was mainly built on the external characters included the male genitalia. Sites and dates of collections so as the host-plants were verified.
During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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