Carbon dioxide geo-sequestration (CGS) into sediments in the form of (gas) hydrates is one proposed method for reducing anthropogenic carbon dioxide emissions to the atmosphere and, thus reducing global warming and climate change. However, there is a serious lack of understanding of how such CO2 hydrate forms and exists in sediments. We thus imaged CO2 hydrate distribution in sandstone, and investigated the hydrate morphology and cluster characteristics via x-ray micro-computed tomography in 3D in-situ. A substantial amount of gas hydrate (∼17% saturation) was observed, and the stochastically distributed hydrate clusters followed power-law relations with respect to their size distributions and surface area-volume relationships. The layer-

     CdSe/CdS Core/shell nanostructures were prepared through the chemical synthesis method. XRD ,FESEM and TEM investigations confirmed the formation of core/shell structure for the sample. The AFM measurement was employed to reveal the morphology of the prepared thin films. Optical characterizations of the quantum dots were done by UV-visible and photoluminescence spectra. It was found that the quantum dots prepared has  good optical properties. Due to the presence of shell coating on core CdSe, the energy gap of the core/shell nanomaterial were increased from 2.2 to 2.3eV. The resulted QDs  are a promising candidate for photovoltaic and biosensor applications.

    This paper deals with finding an approximate solution to the index-2 time-varying linear differential algebraic control system based on the theory of variational formulation. The solution of index-2 time-varying differential algebraic equations (DAEs) is the critical point of the equivalent variational formulation. In addition, the variational problem is transformed from the indirect into direct method by using a generalized Ritz bases approach. The approximate solution is found by solving an explicit linear algebraic equation, which makes the proposed technique reliable and efficient for many physical problems. From the numerical results, it can be implied that very good efficiency, accuracy, and simplicity of the pre

    The adsorption study of thymol, was carried out at (25±0.1) ^°C, using granulated surfactant modified Iraqi Na – montmorillonite clay (initiated modified bentonite); in a down-flow packed column, the modified mineral was characterized by FT-IR spectroscopy.  A linear calibration graph for thymol was obtained, which obey Beer's law in the concentration range of 5-50 mg/L at 274 nm against reagent blank. Single-factor-at-a-time approach; showed that the equilibrium time required for complete adsorption was 45 minute with flow rate (4.0drop/ mint). The adsorption of thymol increased with rising pH of the adsorbate solution, increase of solute uptake when  the initial adsor

In this study, an efficient photocatalyst for dissociation of water was prepared and studied. The chromium oxide (Cr₂O₃) with Titanium dioxide (TiO₂) nanofibers (Cr₂O₃-TNFs) nanocomposite with (chitosan extract) were synthesized using ecologically friendly methods such as ultrasonic and hydrothermal techniques; such TiO₂ exhibits nanofibers (TNFs) shape struct

The present study was designed to investigate the possibility of exploiting the interspecies interaction of microbial cells in order to enhance the production of prodigiosin by local isolate S. marcescens S23. Prodigiosin is a promising drug owing to its characteristics of antibacterial, antifungal, immunosuppressive and anticancer activities. S. marcescens S23 was isolated from soil sample and already recognized via morphological, biochemical and molecular identification process. The first step was to detect the optimal conditions for maximum prodigiosin production using chemically defined liquid medium. The results revealed that the optimal conditions for prodigiosin production were sucrose as carbon source; peptone as nitrogen source;

The Development of Semi – Empirical Relationship for the Determination of the Half –Lives of Even – Even Heavy Nuclei that Emit Alpha – Particles

     Structure of network, which is known as community detection in networks, has received a great attention in diverse topics, including social sciences, biological studies, politics, etc. There are a large number of studies and practical approaches that were designed to solve the problem of finding the structure of the network. The definition of complex network model based on clustering is a non-deterministic polynomial-time hardness (NP-hard) problem. There are no ideal techniques to define the clustering. Here, we present a statistical approach based on using the likelihood function of a Stochastic Block Model (SBM). The objective is to define the general model and select the best model with high quality. Therefor