• Bulletin of the Korean Chemical Society
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• v.28 no.9
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• pp.1477-1484
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• 2007

Artificial neural networks (ANNs), for a first time, were successfully developed for the prediction partial molar heat capacity of aqueous solutions at infinite dilution for various polar aromatic compounds over wide range of temperatures (303.55-623.20 K) and pressures (0.1-30.2 MPa). Two three-layered feed forward ANNs with back-propagation of error were generated using three (the heat capacity in T = 303.55 K and P = 0.1 MPa, temperature and pressure) and six parameters (four theoretical descriptors, temperature and pressure) as inputs and its output is partial molar heat capacity at infinite dilution. It was found that properly selected and trained neural networks could fairly represent dependence of the heat capacity on the molecular descriptors, temperature and pressure. Mean percentage deviations (MPD) for prediction set by the models are 4.755 and 4.642, respectively.

• Biotechnology and Bioprocess Engineering:BBE
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• v.8 no.3
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• pp.205-209
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• 2003

Solubilization of domestic household waste through Steam explosion with Subsequent ethanol production by the microbial saccharifitation and fermentation of the exploded product was studied. The effects of steam explosion on the changes of the density, viscosity, pH, and amounts of extractive components in artificial household waste were determined. The composition of artificial waste used was similar to leftover waste discharged from a typical home in Japan. Consecutive microbial saccharification and fermentation, and simultaneous microbial saccharification and fermentation of the Steam-exploded product were attempted using Aspergillus awamori, Trichoderma viride, and Saccharomyces cerevisiae; the ethanol yields of each process were compared. The highest ethanol yield was obtained with simultaneous microbial saccharification and fermentation of exploded product at a steam pressure of 2 MPa and a steaming time of 3 min.

• Bulletin of the Korean Chemical Society
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• v.21 no.11
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• pp.1115-1118
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• 2000

Specimens were cured by using a 1 mm (thickness) ${\times}$5 mm (diameter) teflon mold, and were immersed in artificial saliva and in 75% ethanol for 1, 7, 14, 21 and 28 days in order to quantify and to identify toxic components and to determine any degra dation byproducts of Bis-GMA that might be released from five commercially available resin-based dental sealants. In artificial saliva, the only released component was triethylene glycol dimethacylate (TEGDMA). In 75% ethanol, TEGDMA, 2,2-bis[4-(2-hydroxy-3-methacryloyloxypropoxy) phenyl]propane (Bis-GMA) and urethane dimethacrylate (UDMA) were released highly at the initial stage, indicating that the amount of component released is not linearly correlated with the immersion time. The amount of released TEGDMA was found to be much higher in 75% ethanol than in artificial saliva. Importantly, bisphenol-A (BPA) was detected from all the uncured sealants tested, suggesting that all the sealants tested contain BPA as a contaminant.

• 한국생물공학회:학술대회논문집
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• 2005.04a
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• pp.225-225
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• 2005

• Carbon letters
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• v.16 no.3
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• pp.135-146
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• 2015

Graphite can be classified into natural graphite from mines and artificial graphite. Due to its outstanding properties such as light weight, thermal resistance, electrical conductivity, thermal conductivity, chemical stability, and high-temperature strength, artificial graphite is used across various industries in powder form and bulk form. Artificial graphite of powder form is usually used as anode materials for secondary cells, while artificial graphite of bulk form is used in steelmaking electrode bars, nuclear reactor moderators, silicon ingots for semiconductors, and manufacturing equipment. This study defines artificial graphite as bulk graphite, and provides an overview of bulk graphite manufacturing, including isotropic and anisotropic materials, molding methods, and heat treatment.

• 보존과학연구
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• s.30
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• pp.125-136
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• 2009

Stone cultural heritages in Korea have a severe damages from chemical and biological weathering because most of them have been situated in outdoors without any suitable protection systems, and this in turn causes deformation and structural damage. To counteract these problems and increase durability, various kinds of conservation materials are used in the conservation and restoration treatments. However until now there are not many practical and technological experiments on this subject. This paper attempts quantitative evaluation of effectiveness about chemical of ethylsilicate based resin for sandstone in Yeongyang-gun. It takes a long time to evaluate durability and side effect after conservation materials treatment. So we use artificial weathering through freezing§ thawing experimental method. As a result of this experiment, porosity and absorptance increased, and elastic wave speed, elastic modules, unconfined compression strength and tensile strength decreased more than before. This study plans to make a scientific method study about weathering factor and mechanism, and to deduce correlation between artificial weathering and natural weathering.

• Imaging Science in Dentistry
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• v.33 no.2
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• pp.91-95
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• 2003

Purpose : To compare the diagnostic accuracy of proximal caries detection between Kodak Insight film and the Biomedisys CDX2000HQ digital (CCD) sensor. Materials and Methods: 156 proximal surfaces of extracted teeth, 78 of which had chemical artificial caries, were used in this study. Four observers interpreted the radiographs using a five-point confidence rating scale to record their diagnoses. The results were analyzed by receiver operating characteristic curves, ANOVA and Kappa values. Result: Analysis using receiver operating characteristic curves revealed the areas under each curve which indicated a diagnostic accuracy of 0.951 in Insight and 0.952 in CDX2000HQ digital sensor. ANOVA revealed no significant differences between the two images with respect to caries detection. Kappa values indicated that the mean intra-observer agreement was 0.85 and inter-observer agreement 0.71 in conventional radiography. In digital radiography, the mean intra-observer agreement was 0.84 and inter-observer agreement 0.72. Conclusion: The results suggest that no significant difference exists between the two modalities for artificial caries detection and that CDX2000HQ was as good as Insight film for this purpose.

• Bulletin of the Korean Chemical Society
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• v.26 no.1
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• pp.139-145
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• 2005

Artificial neural networks (ANNs), for a first time, were successfully developed for the modeling and prediction of solvent effects on rate constant of [2+2] cycloaddition reaction of diethyl azodicarboxylate with ethyl vinyl ether in various solvents with diverse chemical structures using quantitative structure-activity relationship. The most positive charge of hydrogen atom (q$^+$), dipole moment ($\mu$), the Hildebrand solubility parameter (${\delta}_H^2$) and total charges in molecule (q$_t$) are inputs and output of ANN is log k$_2$ . For evaluation of the predictive power of the generated ANN, the optimized network with 68 various solvents as training set was used to predict log k$_2$ of the reaction in 16 solvents in the prediction set. The results obtained using ANN was compared with the experimental values as well as with those obtained using multi-parameter linear regression (MLR) model and showed superiority of the ANN model over the regression model. Mean square error (MSE) of 0.0806 for the prediction set by MLR model should be compared with the value of 0.0275 for ANN model. These improvements are due to the fact that the reaction rate constant shows non-linear correlations with the descriptors.

• Tribology and Lubricants
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• v.38 no.4
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• pp.152-161
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• 2022

Chemical mechanical planarization (CMP) is a technology that planarizes the surfaces of semiconductor devices using chemical reaction and mechanical material removal, and it is an essential process in manufacturing highly integrated semiconductors. In the CMP process, a conditioning process using a diamond conditioner is applied to remove by-products generated during processing and ensure the surface roughness of the CMP pad. In previous studies, prediction of pad wear by CMP conditioning has depended on numerical analysis studies based on mathematical simulation. In this study, using an artificial neural network, the ratio of conditioner coverage to the distance between centers in the conditioning system is input, and the average conditioning density, standard deviation, nonuniformity (NU), and conditioning density distribution are trained as targets. The result of training seems to predict the target data well, although the average conditioning density, standard deviation, and NU in the contact area of wafer and pad and all areas of the pad have some errors. In addition, in the case of NU, the prediction calculated from the training results of the average conditioning density and standard deviation can reduce the error of training compared with the results predicted through training. The results of training on the conditioning density profile generally follow the target data well, confirming that the shape of the conditioning density profile can be predicted.

• Current Photovoltaic Research
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• v.6 no.2
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• pp.62-67
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• 2018

Multi-wire busbar-type bifacial n-type Si solar cells have been used for the fabrication of monofacial and bifacial photovoltaic (PV) module, where bifacial module was equipped with transparent backsheet while monofacial module was prepared using white backsheet. The comparison of six-day accumulated power production obtained from outdoor test under gray cement ground conditions using 60cell monofacial and bifacial PV modules suggested the bifacial gain of over 20% could be achieved. Furthermore, the outdoor evaluation tests of bifacial modules with different ground conditions such as cement (reference), green paint, white paint and green artificial grass, were performed. It turned out white paint showed the best albedo and thus the highest power production, while green paint and artificial grass showed less power generation than cement ground.