• Journal of Environmental Science International
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• v.7 no.5
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• pp.669-677
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• 1998

A porous $\alpha$-alumina tube of 2.5 mm O.D. and 1.9 mm I.D. was used as the support of an inorganic membrane. Macropores of the tube, about 150 nm in size, were plugged with silica formed by thermal decomposition of tetraethylorthosilicate at $600^{\circ}C$. The forced cross-flow CVD method that reactant was evacuated through the porous wall of the support was very effective in plugging macropores. The H$_2$ permeance of the prepared membrane was of the order of $10^{-8}/ molㆍs^{-1}/ㆍm^{-2}/. Pa{-1}$/, while the $N_2$ permeance was below $10^{-11}/ molㆍs^{-1}/ㆍm^{-2}/ㆍPa^{-1}$/ at $600^{\circ}C$. This was comparable to that of silica-modified Vycor glass whose size was 4 nm.

• Journal of Powder Materials
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• v.21 no.1
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• pp.21-27
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• 2014

In this study, diatomite based materials were investigated as a support filter for silica particle coating. The silica sol for coating was synthesized by a st$\ddot{o}$ber process. The diatomite support was dry-pressed at 10 MPa and sintered at $1200^{\circ}C$ for 1 hour. The coating sol was prepared as a mixture of EtOH and silica sol. The diatomite support was coated by a dip-coating process. Silica coated diatomite filter was sintered at $1000{\sim}1200^{\circ}C$ for 1 hour. The largest pore size was decreased with increasing concentration ratio of coating sol. The gas and water permeability of silica coated diatomite decreased with increasing of concentration ratio of the coating sol.

• Proceedings of the Membrane Society of Korea Conference
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• 2003.07a
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• pp.129-132
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• 2003

Silica/SUS composite membranes were prepared for CO removal from products of methanol steam reforming. A support was prepared by coating Ni powder of sub-micron and SiO$_2$ sols of particle size of 500nm and 150nm in turns on a porous stainless steel (SUS) substrate. Silica top layer was coated on the modified support using colloidal sol with nanoparticle. As a result of mixture gas permeation test of silica composite membrane using H$_2$(99%)/CO(1%), CO concentration of 10000 ppm was reduced to under 81 ppm, which is acceptable in PEMFC anode gas specification. Permeation mechanism through the membrane was mainly molecular sieving.

• Membrane Journal
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• v.24 no.3
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• pp.177-184
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• 2014

Silica membranes with high permeability were prepared using colloidal and polymeric silica sols on a porous stainless steel-tube support by a DRFF and SRFF method. Silica sols were derived with tetraethylorthosilicate (TEOS) by sol-gel method and analyzed with DLS, FE-SEM, and $N_2$ adsorption. The coating of the intermediate layer with colloidal silica sol on the stainless steel-tube support led to a denser surface morphology of the membrane along with a considerable reduction in the number of surface defect. As the polymeric silica sol enclosed the colloidal silica sol with spherical particles during the SRFF method, the separation-layer-coated silica membrane showed a denser surface than the intermediate layer. Moreover, the silica membranes showed high hydrogen gas permeability of $(6.63-9.21){\times}10^{-5}mol{\cdot}m^{-2}{\cdot}s^{-1}{\cdot}Pa^{-1}$ with low $H_2/N_2$ perm-selectivity (2.9-3.1) at room temperatures.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.08a
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• pp.211-211
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• 2011

Nanostructures, with a diversity of shapes, built on substrates have been developed within many research areas. Lithography is one powerful, but complex, technique to make structures at the nanometer scale, such as platinum nanowires for studying CO catalytic reactions [1], or aluminum nanodisks for studying the plasmon effect [2]. In this work, we approach a facile method to construct nanostructures using noble metals on a titania thin film by using self-assembled structures as a pattern. Here, a large-scale silica monolayer is transferred to the titania thin film substrates using a Langmuir-Blodgett trough, followed by the deposition of a thin transition metal layer. Owing to the hexagonal close-packed structure of the silica monolayer, we would obtain a metal nanostructure that includes separated metallic triangles (islands) after removing the patterning silica beads. This nanostructure can be employed to investigate the role of metal-oxide interfaces in CO catalytic reactions by changing the patterning silica particles with different sizes or by replacing the oxide support. The morphology and chemical composition of the structure can be characterized by scanning electron microscopy, atomic force microscopy and X-ray photoelectron spectroscopy. In addition, we modify these islands to a connected island structure by reducing the silica size of the patterning monolayer, which is utilized to generating hot electron flow based on the localized surface plasmon resonance effect of the metal nanostructures.

• Structural Engineering and Mechanics
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• v.83 no.1
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• pp.79-92
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• 2022

In this paper, the impact of a vernacular pozzolanic kaolinite mine on concrete alkali-silica reaction and strength has been evaluated. For making the samples, kaolinite powder with various levels has been used in the quality specification test of aggregates based on the ASTM C1260 standard in order to investigate the effect of kaolinite particles on reducing the reaction of the mortar bars. The compressive strength, X-Ray Diffraction (XRD) and Scanning Electron Microscope (SEM) experiments have been performed on concrete specimens. The obtained results show that addition of kaolinite powder to concrete will cause a pozzolanic reaction and decrease the permeability of concrete samples comparing to the reference concrete specimen. Further, various machine learning methods have been used to predict ASR-induced expansion per different amounts of kaolinite. In the process of modeling methods, optimal method is considered to have the lowest mean square error (MSE) simultaneous to having the highest correlation coefficient (R). Therefore, to evaluate the efficiency of the proposed model, the results of the support vector machine (SVM) method were compared with the decision tree method, regression analysis and neural network algorithm. The results of comparison of forecasting tools showed that support vector machines have outperformed the results of other methods. Therefore, the support vector machine method can be mentioned as an effective approach to predict ASR-induced expansion.

• Particle and aerosol research
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• v.9 no.4
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• pp.209-219
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• 2013

We have used the modified diffusion flame burner to synthesize silica coated iron oxide nanoparticles having enhanced superparamagnetic property. Silica-encapsulated iron oxide particles were directly observed using a high resolution transmission electron microscope. From the energy dispersive X-ray spectroscopy (EDS) and zeta potential measurements, the iron oxide particles were found to be completely covered by a silica coating layer. X-ray photoelectron spectroscopy (XPS) and X-ray diffraction (XRD) measurements revealed that the iron oxide core consists of ${\gamma}-Fe_2O_3$ rather than ${\alpha}-Fe_2O_3$. Our magnetization measurements support this conclusion. Biocompatibility test of the silica-coated iron oxide nanoparticles is also conducted using the protein adsorption onto the coated particle.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5365-5369
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• 2011

Silica-gold composite particles were prepared by wet chemical route including impregnation method. The effect of precursor and solvent on the preparation of silica-gold particles was investigated. When spherical silica particles and PVP and hydrogentetrachloroaurate(III) hydrate aqueous solution were used as support material and precursor solution, silica-gold composite particles with light pink color successfully obtained. Obtained composite particles were characterized using FE-SEM, FE-TEM and XRD.

• Bulletin of the Korean Chemical Society
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• v.31 no.1
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• pp.157-161
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• 2010

A sensory element against carbaryl, as a widely used pesticide was prepared based on adsorbed acetylcholine esterase (AChE) from Torpedo california. Octadecyl was substituted on macro-porous silica, confirmed by infra-red (IR) spectroscopy and quantitatively estimated through thermo-gravimetric analysis (TGA). Immobilization of the enzyme was achieved by adsorption on this support. Activity of the immobilization product was measured as a function of the loaded enzyme concentration, and maximum binding capacity of the support was estimated to be 43.18 nmol.mg-1. The immobilized preparations were stable for more than two months at storage conditions and showed consistency in continuous operations. Possible application of the immobilized AChE for quantitative analysis of carbaryl is proposed in this study.

• Computers and Concrete
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• v.19 no.2
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• pp.217-226
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• 2017

This paper summarizes the results of experimental research, and artificial intelligence methods focused on determination of compressive strength of lightweight cement mortar with silica fume and fly ash after sulfate attack. The artificial neural network and the support vector machine were selected as artificial intelligence methods. Lightweight cement mortar mixtures containing silica fume and fly ash were prepared in this study. After specimens were cured in $20{\pm}2^{\circ}C$ waters for 28 days, the specimens were cured in different sulfate concentrations (0%, 1% $MgSO_4^{-2}$, 2% $MgSO_4^{-2}$, and 4% $MgSO_4^{-2}$ for 28, 60, 90, 120, 150, 180, 210 and 365 days. At the end of these curing periods, the compressive strengths of lightweight cement mortars were tested. The input variables for the artificial neural network and the support vector machine were selected as the amount of cement, the amount of fly ash, the amount of silica fumes, the amount of aggregates, the sulfate percentage, and the curing time. The compressive strength of the lightweight cement mortar was the output variable. The model results were compared with the experimental results. The best prediction results were obtained from the artificial neural network model with the Powell-Beale conjugate gradient backpropagation training algorithm.