A new optoelectronic flow injection method is proposed for the determination of ferrous ions (Fe ²⁺ ) based on thiocyanate complexation to form a deep-red FeSCN ²⁺ complex.

Aluminum doped zinc selenide ZnSe/n-Si thin films of (250∓20 nm) thickness with (0.01, 0.02 and 0.03), are depositing on the two type of substrate (glass and n-Si) to manufacture (ZnSe/n-Si) solar cell through using thermal vacuum evaporation procedure. physical and optoelectronic properties were examined for the samples. X-Ray and AFM techniques are using to study the structure properties. The energy band gap of as-deposited ZnSe thin films for changed dopant ratio were ranging from (2.6-2.68 eV). The results of Hall effect show that pure and doping films were (p-type), and the concentration carriers and the carriers mobility increases with increase Al-dopant ratio. The (C-V) have shown that the heterojunction were of abrupt type. In add

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

ZnO organic hybrid junction (electroluminescence EL device) was fabricated using phase segregation method. ZnO-nanoparticle (NPs) was prepared as a colloidal by self–assembly method of Zinc acetate solution with KOH solution. Nanoparticle is employed to form organic-inorganic hybrid film and generate white light emission, while N,N’–diphenyl-N,N’ –bis(3-methylphenyl)-1,1’-biphenyl 4,4’-diamine (TPD) and polymethyl methacrylate (PMMA) are adopted as the organic matrices. ZnO NPs was used to fabricate TPD: PMMA: ZnO NPs hybrid junction device. The photoluminescence (PL) and electroluminescence (EL) spectra of the TPD: PMMA: ZnO NPs hybrid device provided a broad emission band covering entirely the visible spectrum (∼350-∼700

The synthesis and bioactivity of zinc oxide nanoparticles has been extensively studied. The antibacterial activity of different antibiotics individually (ceftriaxone (C), chloramphenicol (CRO), penicillin (P) and amoxicillin (Ax)) and Zinc oxide nanoparticles (60μg/ml) in combination with the previously mentioned antibiotics has been demonstrated in the present study by using the disk diffusion assay method. The results showed a synergistic effect between Zinc oxide nanoparticles (ZnO NPs) and both Ax and P for most of the studied Gram-positive isolates (Staphylococcus aureus1, Staphylococcus aureus2, Staphylococcus epidermidis1, Staphylococcus epidermidis2, Enterococcus faecalis1, Enterococcus faecalis2 ) and between ZnO NPs and both C