Compound Hertzian Chain Model for Copper-Carbon Nanocomposites' Absorption Spectrum

The infrared range optical absorption mechanism of Carbon-Copper composite thin layer coated on the Diamond-Like Carbon (DLC) buffer layer has been investigated. By consideration of weak interactions between copper nanoparticles in their network, optical absorption is modeled using their coherent dipole behavior induced by the electromagnetic radiation. The copper nanoparticles in the bulk of carbon are assumed as a chain of plasmonic dipoles, which have coupling resonance. Considering nearest neighbor interactions for this metallic nanoparticles, surface plasmon resonance frequency ({\omega}\neg0) and coupled plasmon resonance frequency ({\omega}\neg1) have been computed. The damping rate versus wavelength is derived which leads to the derivation of the optical absorption spectrum in the term of {\omega}\neg0 and {\omega}\neg1. The dependency of the absorption peaks to the particle-size and the particle mean spacing is also investigated. The absorption spectrum is measured for different Cu-C thin films with various Cu particle size and spacing. The experimental results of absorption are compared with the obtained analytical ones.Comment: 7 pages, 4 figure

Precision photonic band structure calculation of Abrikosov periodic lattice in type-II superconductors

We have performed a numerical solution for band structure of an Abrikosov vortex lattice in type-II superconductors forming a periodic array in two dimensions for applications of incorporating the photonic crystals concept into superconducting materials with possibilities for optical electronics. The implemented numerical method is based on the extensive numerical solution of the Ginzburg-Landau equation for calculating the parameters of the two-fluid model and obtaining the band structure from the permittivity, which depends on the above parameters and the frequency. This is while the characteristics of such crystals highly vary with an externally applied static normal magnetic field, leading to nonlinear behavior of the band structure, which also has nonlinear dependence on the temperature. The similar analysis for every arbitrary lattice structure is also possible to be developed by this approach as presented in this work. We also present some examples and discuss the results.Comment: 2 pages, 2 figure

Modeling of short polypeptide chains to identify Essential Amino Acids by calculating Nuclear Magnetic Resonance spectrum

Since reducing or increasing proteins could be the signs of diseases in the body, they could be used as biomarkers for diagnosing some diseases. This study investigated small protein strings by computing the magnetic resonance spectrum of the nucleus. Amino acids are the building blocks of protein in the body, and the body does not produce the essential amino acids. They must reach the body through the food chain. Because essential amino acids are required for vital processes such as protein production and hormone synthesis, they are of great importance and are studied in this study. First, strings of two to six amino chains with the same monomers were modeled using Gauss View software, and their magnetic resonance spectrum was calculated using Gaussian09w software. These structures are modeled to investigate factors such as the type and length of the amino acid chain on the amplitude and location of the maximum peak in the magnetic resonance spectrum of the nucleus. The results show each amino acid has a unique own magnetic resonance spectrum and these amino acids in a polypeptide chain affect magnetic resonance spectrum. The ability of the nuclear magnetic resonance method to diagnose and identify a variety of diseases, its non-invasive nature, as well as the possibility of repeatability of experiments, in addition to reducing the cost of experiments, make this method as one of the novel and advanced diagnosis