Porous carbons have been widely used as electrode material for supercapacitors. However, commercial porous carbons, such as activated carbons, have low electrochemical performance. Nitrogen-doping is one of the most promising strategies to improve electrochemical performance of porous carbons. In this study, nitrogen self-doped porous carbon (NPC) is prepared from melamine foam by carbonization to improve the supercapacitive performance. The prepared NPC is characterized in terms of the chemical structures and elements, morphology, pore structures, and electrochemical performance. The results of the N2 physisorption measurement, X-ray diffraction, and Raman analyses reveal that the prepared NPC has bimodal pore structures and pseudo-graphite structures with nitrogen functionality. The NPC-based electrode exhibits a gravimetric capacitance of 153 F g−1 at 1 A g−1, a rate capability of 73.2 % at 10 A g−1, and an outstanding cycling ability of 97.85% after 10,000 cycles at 10 A g−1. Thus, the NPC prepared in this study can be applied as electrode material for high-performance supercapacitors.

연구에서는 기술혁신 관점에서 창업기업 여부, 연구전담조직 보유, 국가연구개발사업 수혜 등의 특성이 한계기업의 정상기업 전환에 유의하게 기여하는지를 분석하였다. 분석결과, 한계기업 중 창업기업에게 국가연구개발사업을 지원하면, High-tech 산업을 중심으로 정상기업으로의 전환에 긍정적으로 기여하는 것으로 나타났다. 또한 한계기업의 연구전담조직의 보유여부가 정상기업으로의 전환에 긍정적으로 기여하였다. 이는 연구전담 조직이 체계적인 R&D를 수행할 수 있는 조직기반이 되고 있음을 시사한다. 상기 분석결과 는 한계기업에 대한 구조조정 위주의 기존 산업정책에서 정상기업으로의 전환 가능성이 높은 한계기업에 대한 선별적인 R&D 지원정책으로 패러다임 전환이 필요함과 동시에 한계기업의 정상기업으로의 전환을 지원하기 위한 국가연구개발사업의 전략성 강화가 필요함을 시사한다.

This study suggests a machine learning model for predicting the production quality of free-machining 303-series stainless steel small rolling wire rods according to the manufacturing process's operation condition. The operation condition involves 37 features such as sulfur, manganese, carbon content, rolling time, and rolling temperature. The study procedure includes data preprocessing (integration and refinement), exploratory data analysis, feature selection, machine learning modeling. In the preprocessing stage, missing values and outlier are removed, and variables for the interaction between processes and quality influencing factors identified in existing studies are added. Features are selected by variable importance index of lasso regression, extreme gradient boosting (XGBoost), and random forest models. Finally, logistic regression, support vector machine, random forest, and XGBoost is developed as a classifier to predict good or defective products with new operating condition. The hyper-parameters for each model are optimized using k-fold cross validation. As a result of the experiment, XGBoost showed relatively high predictive performance compared to other models with accuracy of 0.9929, specificity of 0.9372, F1-score of 0.9963 and logarithmic loss of 0.0209. In this study, the quality prediction model is expected to be able to efficiently perform quality management by predicting the production quality of small rolling wire rods in advance.

In this study, AlSi10Mg alloy powders are synthesized using gas atomization and sieving processes for powder bed fusion (PBF) additive manufacturing. The effect of nozzle diameter (ø = 4.0, 4.5, 5.0 and 8.0 mm) on the gas atomization and sieving size on the properties of the prepared powder are investigated. As the nozzle diameter decreases, the size of the manufactured powder decreases, and the uniformity of the particle size distribution improves. Therefore, the ø 4.0 mm nozzle diameter yields powder with superior properties. Spherically shaped powders can be prepared at a scale suitable for the PBF process with a particle size distribution of 10–45 μm. The Hausner ratio value of the powder is measured to be 1.24. In addition, the yield fraction of the powder prepared in this study is 26.6%, which is higher than the previously reported value of 10–15%. These results indicate that the nozzle diameter and the post-sieve process simultaneously influence the shape of the prepared powder as well as the satellite powder on its surface.

In this study, the high-temperature oxidation properties of austenitic 316L stainless steel manufactured by laser powder bed fusion (LPBF) is investigated and compared with conventional 316L manufactured by hot rolling (HR). The initial microstructure of LPBF-SS316L exhibits a molten pool ~100 μm in size and grains grown along the building direction. Isotropic grains (~35 μm) are detected in the HR-SS316L. In high-temperature oxidation tests performed at 700oC and 900oC, LPBF-SS316L demonstrates slightly superior high-temperature oxidation resistance compared to HR-SS316L. After the initial oxidation at 700oC, shown as an increase in weight, almost no further oxidation is observed for both materials. At 900oC, the oxidation weight displays a parabolic trend and both materials exhibit similar behavior. However, at 1100oC, LPBF-SS316L oxidizes in a parabolic manner, but HR-SS316L shows a breakaway oxidation behavior. The oxide layers of LPBF-SS316L and HR-SS316L are mainly composed of Cr2O3, Febased oxides, and spinel phases. In LPBF-SS316L, a uniform Cr depletion region is observed, whereas a Cr depletion region appears at the grain boundary in HR-SS316L. It is evident from the results that the microstructure and the hightemperature oxidation characteristics and behavior are related.