This research explores the preparation of polypyrrole (PPy) using chemical oxidation and its enhancement with graphene oxide (GO) for optical sensor applications. PPy was synthesized by polymerizing pyrrole monomers with ferric chloride (Fe2Cl3) as the oxidant. The resulting PPy was then combined with GO to form a composite material, aiming to improve its electrical and optical properties. Polypyrrole nanofibers were obtained and after adding graphene oxide, the sensitivity increased. Characterization techniques including UV-Vis spectroscopy, DC conductivity measurements, Field Emission Scanning Electron Microscopy (FESEM) and response of photocurrent analysis were employed. The incorporation of GO into PPy resulted in a significant reduction in the energy gap, increased DC conductivity, and enhanced photocurrent response, highlighting the potential of PPy-GO composites for advanced optical sensors. These findings suggest that PPyGO composites could offer improved performance in sensor applications where sensitivity and response speed are critical.
Represent a topic occupational safety and health management is one of the priorities of the loading organization in the business environment ,and one of the requirement for the success and its impact on the productivity of workers and their performance in an appropriate working environment .The international responses to the problems that accompany the technological and industrial development of the business environment are the issuance of ISO 45001:2018 aimed at providing an appropriate framework for controlling risks , reducing injuries and work accidents and improving work performance ,after realizing the environmental relationship between safe and sound work with competition .The search’s issue is represented with the exist
... Show MoreThe two-neutron halo-nuclei (17B, 11Li, 8He) was investigated using a two-body nucleon density distribution (2BNDD) with two frequency shell model (TFSM). The structure of valence two-neutron of 17B nucleus in a pure (1d5/2) state and in a pure (1p1/2) state for 11L and 8He nuclei. For our tested nucleus, an efficient (2BNDD's) operator for point nucleon system folded with two-body correlation operator's functions was used to investigate nuclear matter density distributions, root-mean square (rms) radii, and elastic electron scattering form factors. In the nucleon-nucleon forces the correlation took account of
... Show MoreThe study evaluated endophytic communities associated with five oil-bearing plants, including sesame, corn, sunflower, olives and castor, which were collected from Baghdad and Diyala (Iraq), evaluated their oil production capacity and identified metabolites from the lipid fraction. Out of 151 isolates were collected from 21 taxa. Aspergillus niger showed the highest frequency (6.62 %), while the genera Aspergillus and Fusarium were the most dominant endophytes. The highest oil yield was identified and recorded in Aspergillus terreus (24.12 %). While the lowest oil yield was observed in Sclerotinia spp. (3.96 %). Gas chromatography-mass spectrometry (GC-MS) analysis of A. terreus revealed a profile dominated by pentadecyl acrylate (2
... Show MoreThe research examines the mechanism of application of )ISO 21001: 2018( in the Energy Branch- Electromechanical Engineering at the University of Technology to achieve the quality of the educational service to prepare the branch to obtain the certificate of conformity with the requirements of) ISO 21001: 2018(, the necessary data were collected Depending on the (CHEKLIST) of (ISO 21001: 2018), field interviews and records of the concerned department, The researchers reached a number of results, the most prominent of which was the adoption of high quality leadership leaders and their willingness to implement the standard requirements, The university has a basic structure that qualifies it to implement the international standard, as
... Show MoreEmpirical 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
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