• Journal of the Korean Society for Precision Engineering
• /
• v.14 no.1
• /
• pp.101-107
• /
• 1997

Recently, as the raw water quality becomes to be polluted and the seasonal and local variation of water quality becomes to be severe, an exact control of coagulant dosing have been required in the water treat- ment plant. The amounts of coagulant is related to the raw water quality such as turbidity, alkalinity, water temperature, pH and edectrical conductivity. However the process of chemical reaction has not been clarified so far, so the dosing rate has been decided by jar-test, which is taken one or two hours. For the sake of this coagulant dosing control, fuzzy neural network to fuse fuzzy logic and neural network was proposed, and the scheme was applied to automatic determination of coagulant dosing rate. This controller can automatically identify the if-then rules and tune the membership functions by utilizing expert's cintrol data. It is shown that determination of coagulant dosing rate according to real time sensing of water quality is very effect.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 1999.11a
• /
• pp.475-478
• /
• 1999

The thermal properties of epoxy resin/siloxane for the electrical insulation were investigated by using dynamic DSC run method. As the heating rate increased, the peak temperature on dynamic DSC curve increased. From the linear relation on the Kissinger plot the curing reaction activation energy and pre-exponential factor could be obtained. The curing activation energy from the straight line of the Kissinger plot was 46.72 kJ/mol.

• Proceedings of the Membrane Society of Korea Conference
• /
• 2003.07a
• /
• pp.47-50
• /
• 2003

Carbon-silica membranes were Prepared by Pyrolyzing polyimide/silica composite obtained from ill-situ polymerization of alkoxy silanes via sol-gel reaction. In this study, effects of silica content and silica network in polyimide matrix were focused on the gas permeation and separation properties of the final carbon-silica membrane. The membranes prepared were characterized with a field emission scanning electron microscopy (FE-SEM), a solid state $^{29}$ Si nuclear magnetic resonance spectroscopy ($^{29}$ Si-NMR), an electron spectroscopy for chemical analysis (ESCA), a thermogravimetric analysis (TGA) and gas permeation tests.

• Polymer(Korea)
• /
• v.29 no.4
• /
• pp.344-349
• /
• 2005

Polyurethanes(PUs) were synthesized by reaction of isophorone diisocyanate, acetylbutyl citrate, and 3 types of polycaprolactone diol. Their structures were confirmed by FT-IR and NMR spectrometer. And, their thermal and mechanical properties were measured by TGA ud UTM. The effective network chain lengths ($\bar{M}_c$), measured by compressive modulus apparatus, were about $8000\~24000$ g/mol. As crosslinking density and amount of hard segment increased, tensile strength increased and elongation decreased. As the crosslinking density of PUs increased, thermal property inproved. When the ratio of NCO/OH is 1.1, maximum crosslinking density was achieved.

• Proceedings of the Korea Association of Crystal Growth Conference
• /
• 1996.06a
• /
• pp.494-496
• /
• 1996

The purpose of this study is to investigate the effect of process conditions on pore distribution in porous silicon layer prepared by electrochemical reaction. Porous silicon layers formed on p-type silicon wafer show the network structure of fine porse whose diameters are less than 100${\AA}$. In n-type porous silicon, selective growth was found on the pore surface by wet etching process after PR patterning. And numerical method showed high current density on the pore tip. With this result we confirmed that pore formation has two steps. First step is the initial attack on the surface and second step is the directional growth on the pore tip.

• IE interfaces
• /
• v.24 no.3
• /
• pp.187-195
• /
• 2011

The automatic radiopharmaceutical module consists of several 2-way valves, couple of syringes, gas supply unit, heating(cooling) unit and sensors to control the chemical reagents as well as to help the chemical reaction. In order to control the actuators of radiopharmaceutical module, the process is tabulated using spread sheet as like excel. Unlike the common program, a trivial error is too critical to allowed in the process because the error can lead to leak the radioactive reagent and to cause the synthesis equipment failure during synthesizing. Hence, the synthesis process has been validated using graphic simulation while the operator checks the whole process visually and undergoes trial and error. The verification of the synthesis process takes a long time and has a difficulty in finding the error. This study presents a methodology to verify the process algebraically while the radiopharmaceutical module is converted to the network model. The proposed method is validated using actual synthesis process.

• Journal of the Korean Ceramic Society
• /
• v.54 no.6
• /
• pp.535-538
• /
• 2017

Here we report the tunable electrical properties and chemical sensor of single-walled carbon nanotubes (SWCNTs) network-based devices with a functionalization technique. Formation of highly aligned SWCNT structures is made on $SiO_2/Si$ substrates using a template-based fluidic assembly process. We present a Platinum (Pt)-nanocluster decoration technique that reduces the resistivity of SWCNT network-based devices. This indicates the conversion of the semiconducting SWCNTs into metallic ones. In addition, we present the Hydrogen Sulfide ($H_2S$) gas detection by a redox reaction based on SWCNT networks functionalized with 2,2,6,6-Tetramethylpiperidine-1-oxyl (TEMPO) as a catalyst. We summarize current changes of devices resulting from the redox reactions in the presence of $H_2S$. The semiconducting (s)-SWCNT device functionalized with TEMPO shows high gas response of 420% at 60% humidity level compared to 140% gas response without TEMPO functionalization, which is about 3 times higher than bare s-SWCNT sensor at the same RH. These results reflect promising perspectives for real-time monitoring of $H_2S$ gases with high gas response and low power consumption.

• Journal of Institute of Control, Robotics and Systems
• /
• v.3 no.6
• /
• pp.652-658
• /
• 1997

Coagulant feeding control is very important in the water treatment process. Coagulant feeding is related to the raw water quality such as turbidity, alkalinity, water temperature, pH and so on. However, since the process of chemical reaction has not been clarified so far, coagulant dosing rate has been decided by jar-test. In order to overcome the difficulty mentioned above, Fuzzy Neural Network to fuse fuzzy logic and neural network was proposed, and the scheme was applied to the automatic determination of coagulant dosing rate. This algorithm can automatically identify the if-then rules, tune the membership functions by utilizing expert's experimental data. The proposed scheme is evaluated by computer simulation and interfaced with coagulant feeder operated by magnetic flowmeter, control valve and PLC. It is shown that coagulant feeding according to real time sensing of water quality is very effective.

• Proceedings of the Korean Vacuum Society Conference
• /
• 2010.02a
• /
• pp.137-137
• /
• 2010

Copper electroplating is a very popular and important technology for depositing high-quality conductor interconnections, especially in through silicon via (TSV). As this advanced packaging technique developing, a mass of copper and chemical solution are used, so attention to these chemical materials into the utilization and costs can not be ignored. An economical and practical real-time chemical solution monitoring has not been achieved yet. Either Red-green-blue (RGB) or optical emission spectroscopy (OES) color sensor can successfully monitor the color condition of solution during the process. The reaction rate, uniformity and quality can map onto the color changing. Hidden Semi Markov model (HSMM) can establish mapping from the color change to upper indicators, and artificial neural network (ANN) can be integrated to comprehensively determine its targets, whether the solution inside the container can continue to use.

• Journal of Institute of Control, Robotics and Systems
• /
• v.3 no.6
• /
• pp.644-651
• /
• 1997

In the water purification plant, chemicals are injected for quick purification of raw water. It is clear that the amount of chemicals intrinsically depends on water quality such as turbidity, temperature, pH and alkalinity. However, the process of chemical reaction to improve water quality (e.g., turbidity) by chemicals is not yet fully clarified nor quantified. The feedback signal in the process of coagulant dosage, which should be measured (through the sensor of the plant) to compute the appropriate amount of chemicals, is also not available. Most traditional methods focus on judging the conditions of purifying reaction and determine the amounts of chemicals through manual operation of field experts using Jar-test data. In this paper, a systematic control strategy is proposed to derive the optimum dosage of coagulant, PAC(Polymerized Aluminium Chloride), using Jar-test results. A neural network model is developed for coagulant dosing and purifying process by means of six input variables (turbidity, temperature, pH, alkalinity of raw water, PAC feed rate, turbidity in flocculation) and one output variable, while considering the relationships to the reaction of coagulation and flocculation. The model is utilized to derive the optimum coagulant dosage (in the sense of minimizing turbidity of water in flocculator). The ability of the proposed control scheme validated through the field test has proved to be of considerable practical value.