Alexandra Nistor

A silica-silver nanocomposite obtained by sol-gel method in the presence of silver nanoparticles

AbstractSilver nanoparticles (AgNPs) were obtained by a redox reaction, using a glucose-containing cyclosiloxane as a reduction agent and stabilizer. Then the AgNPs aqueous solution was used as the reaction medium for the sol-gel process, starting from tetraethylorthosilicate (TEOS) as silica precursor. The nanocomposite material resulted (SilAg) after solvent removal, aging and calcination and was investigated by infrared spectroscopy (FT-IR), atomic force microscopy (AFM), scanning electron microscopy coupled with energy dispersive X-ray system (SEM/EDX), transmission electron microscopy (TEM), energy-dispersive X-ray fluorescence spectroscopy (EDXRF), X-ray diffraction (XRD) and dynamic vapor sorption (DVS). The results were compared to model silicas obtained without silver. A higher condensation degree in SilAg was obtained due to the basic medium used in the first step and was confirmed by a sorption capacity lower than for the model silicas. The solid surface area calculated with GAB analysis using DVS data for the water vapors is 210 m2 g−1. The nanocomposite showed good catalytic activity for hydrogen peroxide decomposition.

Hexa-kis-(1H-imidazole-κN)iron(II) sulfate-1H-imidazole (1/2).

The asymmetric unit of the title compound, [Fe(C3H4N2)6]SO4·2C3H4N2, contains two complex cations, two sulfate anions and four imidazole molecules. In both cations, the FeII atom is coordinated by six monodentate imidazole ligands and exhibits a slightly distorted octahedral coordination geometry. The Fe—N distances [2.184 (4)–2.218 (4) Å] point to a high-spin state of the Fe2+ ions. N—H⋯O hydrogen bonds between the ionic components generate a three-dimensional framework containing corrugated channels along [001], which are filled by N—H⋯N hydrogen-bonded imidazole chains.

Student eXchange Process Modelling and Implementation by Using an Integrated BMP-SOA Approach

One of the key processes of an open University Information System concerns managing the student exchange activities. In this paper we will try to address the challenges regarding modelling and implementation when integrating such a process by crossing different information systems. Our approach will leverage SOA architecture by using BPM in order to structure and build the service orchestration level.

Polysiloxanes modified with aromatic diamines interconnecting with silica network

Polydimethylsiloxane-α,ω-diols with different contents of pendant chloromethyl groups were reacted with an aromatic diamine (3,3′-dimethoxybenzidine) when cross-linking occurred. The reactions were performed in silica — generating sol— gel system; so two interconnected networks (silica and cross-linked polydimethylsiloxane) were formed. The resulting structures were investigated by FT-IR and 1H-NMR spectroscopies. Differential scanning calorimetry was used to emphasize the thermal transitions of the resulted materials and the water sorption capacity was investigated by dynamic vapor sorption, the obtained values being influenced by the amount of polar groups. Atomic force microscopy was used to evaluate the morphology and surface topography in dry as well as in swollen state in water and heptane.

MODELING THE THERMAL STABILITY OF THE POLYDIMETHYLSILOXANES/SILICA GREEN COMPOSITES USING NEURAL NETWORKS

This paper presents the development of artificial neural models for predicting the thermal stability of some polysiloxanes/silica composites obtained using an ecological solvent-free reaction. Four polydimethylsiloxane-α,ω-diols with different molar masses have been prepared and reinforced with different contents of silica generated in situ by sol-gel technique. The resulted materials were investigated by thermogravimetric analysis (TGA). In neural modeling, the thermal stability of the polysiloxanes/silica composites was quantified by two temperatures (the initial temperatures of thermal degradation and the temperature corresponding to the maximum degradation rate), as function of reaction conditions: molecular mass of polydimethylsiloxane, concentration of the catalyst and ratio between the reagents. Two feed-forward neural networks were developed and tested, demonstrating the possibility of obtaining accurate results with relatively simple architecture of the networks.