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SrTiO₃의 미세구조의 대한 Nb 과 Cu 첨가제의 영향
조성걸,김대흥 국립경상대학교 공과대학 부설 첨단소재연구소 1992 尖端素材 Vol.2 No.-
Undoped, Nb-doped, and (Nb,Cu)-doped SrTiO₃specimens were made using oxide-mix process. Nb-doped specimens having Sr/(Ti+Nb)=0.986 showed grain size decrease as Nb concentration changed from 0.4 to 0.8 mol%. Dark blue color and low electrical resistivity were observed in all Nb-doped specimens. When 0.8 mol% Cu was added to 0.4 mol% Nb₂O?-doped composition, grain size decreased to 2 ㎛. However, grain growth inhibition was not found for specimens with 1.6 and 2.4 mol% Cu. Cu seemed to be distributed throughout the grains rather than segregated at grain boundaries and to be present as Cu⁴ion which compensated donor effect of Nb ions.
정대영(Dae Young Jung),김성우(Sung Woo Kim),박성우(Sung Woo Park),김대흥(Dae Hueng Kim) 한국에너지기후변화학회 2018 에너지기후변화학회지 Vol.13 No.1
The purpose of this study is to analyze the cases of small and medium-sized businesses that has a difficulty to apply in benchmark when establishing the GHG emission target and to provide a basis of GHG emission reduction by actual reduction efforts as predict the emission of industry and companies by using the credible economy indicators. Currently, GHG emissions targets are changing from grandfathering methods to benchmark-based methods as emissions trading is implemented, and plans to expand the target on industries is under consideration as well. However, since the benchmark coefficient is calculated based on a basic unit on each product, there is a risk of a the different opinion of small and medium enterprises when applying the consistent coefficient, because of the differences in facility investment and energy efficiency depending on the size of the corporate. Especially, in case of manufacturer in small business, they have characteristics of small quantity batch production. Thus, it is difficult to develop the coefficient of product benchmark by reason that the property of energy usage depending on the produced products is different even though they are in same industries. Therefore, we examined the possibility usage of the basic analysis data on GHG emission using statistics of GDP by economic activity, manufacturing production capacity and statistics of rate operation provided by the Statistical Korea. As a result of this study, when we further analyzed the error rate and correlation between regression analysis on specification emissions and expected emissions for the 130 companies that can analyze statistical data, we found out not only that the proportion of firms with a correlation coefficient of 0.7 or higher is 88% but also that proportion of companies with an error rate of less than 5% is 92%. It means that analysis by companies has a very high statistical significance with actual value. Based on this, we expect that similar results compared to the effects of benchmarking will be derived, if the methodologies can be applied in economic indicator are developed and reflected with characteristics by companies.