The nonlinear refractive index and the nonlinear absorption coefficient of unmodified and functional poly(methyl methacrylate) PMMA films were studied before and after the addition of the filler by the z-scan technique, using a Q-switched Nd:YAG laser at two wavelengths: 532 nm and 1064 nm, and at three input energies (13, 33 and 53) mJ. Both linear and nonlinear refractive indices and absorption coefficients of polymer films were studied by using UV-VIS spectrophotometer. The results show that the creation of functional PMMA from unmodified PMMA will increase the nonlinear optical properties in the functional PMMA/copper matrix more than in the unmodified PMMA/copper matrix. Hence, the functional PMMA appears promising as a useful third

The effects of reinforcing polymers with glass and graphite particles on enhancing their flexural properties are investigated.   Five composites were fabricated using the same polymer matrix material with different volume fractions of reinforcement particles. They comprise glass particles and graphite particles each  having volume fractions of 20% and 30% as well as a hybrid composite having 10% glass and 10% graphite. Three-point bending tests using a Universal Testing Machine were carried out on specimens of the above mentioned composites, as well as specimens of the polymer matrix material to determine their flexural properties. The experimental test results indicate that the flexural stiffness of all the composites wer

In this work, zinc oxide nanoparticles (ZnONPs) and sawdust/epoxy composite (20:80) were mixed using a simple molding method with different ZnONPs concentrations of (0.1, 0.3, 0.5, 0.7, and 1.0 %). The samples of the nanocomposites were characterized by the Scanning Electron Microscopy (SEM) technique to demonstrate the homogeneity of the prepared ZnONPs/nanocomposites. The photocatalytic activity of the samples was examined using the methylene blue (MB) dye as a pollutant solution, through evaluation of the efficiency of the prepared compound in the treatment of organic pollutants under illumination by sunlight. The photocatalytic results showed that after 240 minutes of exposure to sunlight, the sample prepared using (0.5 vol.% of ZnON

This research estimates the effect of independent factors like filler  (3%, 6%, 9%, 11% weight fraction), normal load (5N, 10N, 15N), and time sliding (5,7 , 9 minutes) on wear behavior of unsaturated polyester resin reinforced with jute fiber and waste eggshell and, rice husk powder composites by utilizing a statistical approach. The specimens polymeric composite prepared from resin unsaturated polyester filled with (4% weight fraction) jute fiber, and (3%, 6%, 9%, 11% weight fraction) eggshell, and rice husk by utilizing (hand lay-up) molding. Dry sliding wear experiments were carried utilizing a standard (pin on disc test setup) following a well designed empirical schedule that depends on Taguchi’s experimental design L9 (MINIT

Epoxy resin has many chemical features and mechanical properties, but it has a small elongation at break, low impact strength and crack propagation resistance, i.e. it exhibits a brittle behavior. In the current study, the influence of adding kaolin with variable particle size on the mechanical properties (flexural modulus E, toughness Gc, fracture toughness Kc, hardness HB, and Wear rate WR) of epoxy resin was evaluated. Composites of epoxy with varying concentrations (0, 10, 20, 30, 40 weights %) of kaolin were prepared by hand-out method. The composites showed improved (E, Gc, Kc, HB, and WR) properties with the addition of filler. Also, similar results were observed with the decrease in particle size. In addition, in this study, mult

   This research  studyies  wear  rate  of  composite  materials  by using Epoxy Resin and Polyurethane Rubber as a matrix  of weigt percentage (90:10) (Ep/Pu) and reinforced by PVC fibers and Aluminum fibers two dimension knitted mat with fractional volume(15 %), in different conditions like: lab conditions and after submerge the samples in water for different periods of time. . four kinds of materials were prepared: (Ep+pu), (Ep+Pu+PVC), (Ep+Pu+Al.F), (Ep+Pu+PVC+Al. F) .And the results have shown that the best wear resistance are for the hybrid composite material    (Ep + Pu+ PVC + Al. F) and wear rate of  all samples increased when it was submerged in water

In this study, polyester composites reinforced with pistachio shells powder (P.) with an average
diameter (150 – 200 μm) with different weight ratios (0.5%, 1%, 1.5%, 2%, and 2.5%) were
prepared to the resin. The Shore D hardness, thermal conductivity (K), and the glass transition
temperature (Tg) of the samples were examined. The results showed that the Shore D hardness
increases with the increase of the reinforcement ratio and its maximum value is (87.55) at (2.5%
P.) While the value of hardness at (0%) is (86.5). The thermal conductivity increases slightly with
the increase in the percentage of reinforcement and its maximum value is (0.213253 W/ m. K) at
(2.5% P.), while the value of K at (0% P.)

Polycaprolactone polymer is widely used in medical applications due to its biocompatibility. Electro spinning was used to create poly (ε- caprolactone) (PCL) nanocomposite fiber mats containing hydroxyapatite (HA) at concentrations ranging from 0.05 to 0.4% wt. The chemical properties of the fabricated bio composite fibers were evaluated using FTIR and morphologically using field-emission scanning-electron microscopy (FESEM), Porosity, contact angle, as well as mechanical testing(Young Modulus and Tensile strength) of the nanofibers were also studied. The FTIR results showed that all the bonds appeared for the pure PCL fiber and the PCL/HA nano fibers. The FESEM nano fiber showed that the fiber diameter increased from 54.13 to 155.79 (n

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att