Structural Characterization of Different Asphaltenes of Kuwaiti Origin

Asphaltenes obtained by precipitation from crude Kuwaiti oils have been analyzed by proton magnetic resonance (¹H-NMR), carbon-13 nuclear magnetic resonance (¹³C-NMR) and Infrared (IR) spectral techniques. The molecular weight and elemental analysis were also determined. These combined analytical data were used for the characterization of these Kuwaiti oils. The asphaltenes molecular weights range from approximately 4200-6500 with an H/C ratio of 0.91-1.1 with an average 45-71% aromatic carbons. The average side chain length was of 4-6 carbons. It can also be concluded that the asphaltenes under investigation contain 5-9 sets of condensed aromatic rings joined together by bridges of alkyl chains or other hetero atoms and the average number of each of these sets of condensed aromatic rings is nearly 7. There are a number of alicyclic rings and condensed alicyclic rings in asphaltene. The IR spectra showed main molecular groups including OH, NH, SH, C=O and aliphatic and aromatic C-H's.     

Study of the solid-liquid equilibria in the LiPO3-Y(PO3)3 binary system

The LiPO₃-Y(PO₃)₃ system has been studied for the first time. Microdifferential thermal analysis (μ-DTA), infrared spectroscopy (IR) and X-ray diffraction were used to investigate the liquidus and solidus relations. The only new compound observed within this system is LiY(PO₃)₄, melting incongruently at 1104 K. An eutectic appears at 4±1 mol% Y(PO₃)₃ at 933 K. LiY(PO₃)₄ crystallizes in the monoclinic system C_2/c with a unit cell: a=16.201(4) Å, b=7.013(2) Å, c=9.573(2) Å, β=125.589(9)°, Z=4 and V=884.5 Å³, which is isostructural to LiNd(PO₃)₄. The infrared absorption spectrum indicates that this salt is a chain polyphosphate.     

The Impact of Metastable Intermolrecular Nanocomposite Particles on Kinetic Decomposition of Heterocyclic Nitramines Using Advanced Solid‐Phase Decomposition Models

Journal of Inorganic and Organometallic Polymers and Materials - Surface oxygen of oxide catalyst has low coordination number; they are negatively charged. Surface oxygen can act active site for...     

The MORPHEUS Heterogeneous Dynamically Reconfigurable Platform

Reconfigurable computing offers a wide range of low cost and efficient solutions for embedded systems. The proper choice of the reconfigurable device, the granularity of its processing elements and its memory architecture highly depend on the type of application and their data flow. Existing solutions either offer fine grain FPGAs, which rely on a hardware synthesis flow and offer the maximum degree of flexibility, or coarser grain solutions, which are usually more suitable for a particular type of data flow and applications. In this paper, we present the MORPHEUS architecture, a versatile reconfigurable heterogeneous System-on-Chip targeting streaming applications. The presented architecture exploits different reconfigurable technologies at several computation granularities that efficiently address the different applications needs. In order to efficiently exploit the presented architecture, we implemented a complete software solution to map C applications to the reconfigurable architecture. In this paper, we describe the complete toolset and provide concrete use cases of the architecture.     

On partial-information optimal singular control problem for mean-field stochastic differential equations driven by Teugels martingales measures

This paper is concerned with partial-information mixed optimal stochastic continuous–singular control problem for mean-field stochastic differential equation driven by Teugels martingales and an independent Brownian motion, where the Teugels martingales are a family of pairwise strongly orthonormal martingales associated with Lévy processes. The control variable has two components; the first being absolutely continuous, and the second singular. Partial-information necessary and sufficient conditions of optimal continuous–singular control for these mean-field models are investigated. As an illustration, this paper studies a partial-information linear quadratic control problem of mean-field type involving continuous–singular control.     

Simultaneous state estimation and parameter identification in linear fractional order systems using coloured measurement noise

In the present paper, the identification and estimation problem of a single-input–single-output (SISO) fractional order state-space system will be addressed. A SISO state-space model is considered in which parameters and also state variables should be estimated. The canonical fractional order state-space system will be transformed into a regression equation by using a linear transformation and a shift operator that are appropriate for identification. The identification method provided in this paper is based on a recursive identification algorithm that has the capability of identifying the parameters of fractional order state-space system recursively. Another subject that will be addressed in this paper is a novel fractional order Kalman filter suitable for the systems with coloured measurement noise. The promising performance of the proposed methods is verified using two stable fractional order systems.     

Multivariate statistical analysis for monitoring the hydrocarbon potentiality of the source rocks in the North Western Desert,Egypt

The authors aimed to examine a multivariate statistical analysis approach for monitoring the hydrocarbon potentiality of source rocks in the North Western Desert to recognize the potentiality of source rocks and subsequently investigate the maturation level of the proven potential source formations for oil preservation. To achieve this aim, they applied multivariate statistics analysis (principle component analysis [PCA], cluster analysis, and correlation coefficient) and Rock-Eval pyrolysis analyses. The results showed that both PCA and cluster analyses have showed two types of source rocks. The first is classified as poor to fair source rock and immature to marginally mature source rock, the second is considered as fair to good source rock and mature to post mature source rock. PCA extracted two independent factors, which explained 81.87% of the total variance. The first type of source rock was responsible for 50% of the total variance and was best represented by variables TOC, S2, OI, and R_o, and the second one was responsible for 31.65% of the total variance and was represented by the HI variable. Pearson correlation coefficient showed a significant positive correlation between TOC and S2 or R_o. A positive correlation between S2 and HI or OI and also between OI and R_o was observed, while no significant correlation was noticed between HI and R_o.