We use vdW-corrected density functional theory (DFT) calculations with additional electron distribution correction to study the water binding chemistry of an Au nanoparticle supported on CeO2(111) with a linear step-edge. The initial structural model of Au/CeO2 used for DFT calculations is constructed by stabilizing a Au9 nanoparticle at the linear step-edge on a CeO2(111) slab. The calculated binding energy of a water molecule clearly shows that the interfacial site between Au and CeO2 binds water more strongly than the binding sites at the surface of Au nanoparticle. Subsequent water dissociation calculation result shows that the interface-bound water can be relatively easily dissociated into–OH and –H, providing a hydroxyl group that can be utilized as an oxygen source for CO oxidation. Based on the low dissociation energy of the interface bound water molecule, we suggest that the water at the Au-CeO2 interface can facilitate further oxidation of Au-bound CO. Our results point out that Au-CeO2 interface-bound water is beneficial for low-temperature oxidation reactions such as the water-gas shift reaction or preferential CO oxidation reaction.

The change in the open porosity of bulk graphite as a function of the uniaxial molding pressure during manufacturing is studied using artificial graphite powder. Subsequently, the graphite is impregnated to determine the effect of the open porosity on the impregnation efficiency and to improve the density of the final bulk graphite. Bulk graphite is manufactured with different uniaxial molding pressures after mixing graphite powder, which is the by-product of processing the final graphite products and phenolic resin. The bulk density and open porosity are measured using the Archimedes method. The bulk density and open porosity of bulk graphite increase as the molding pressure increases. The open porosity of molded bulk graphite is 25.35% at 30 MPa and 29.84% at 300 MPa. It is confirmed that the impregnation efficiency increases when the impregnation process is performed on a specimen with large open porosity. In this study, the bulk density of bulk graphite molded at 300 MPa is 11.06% higher than that before impregnation, which is the highest reported increase. Therefore, it is expected that the higher the uniaxial pressure, the higher the density of bulk graphite.

Predicting the quality of materials after they are subjected to plasma sintering is a challenging task because of the non-linear relationships between the process variables and mechanical properties. Furthermore, the variables governing the sintering process affect the microstructure and the mechanical properties of the final product. Therefore, an artificial neural network modeling was carried out to correlate the parameters of the spark plasma sintering process with the densification and hardness values of Ti-6Al-4V alloys dispersed with nano-sized TiN particles. The relative density (%), effective density (g/cm3), and hardness (HV) were estimated as functions of sintering temperature (oC), time (min), and composition (change in % TiN). A total of 20 datasets were collected from the open literature to develop the model. The high-level accuracy in model predictions (>80%) discloses the complex relationships among the sintering process variables, product quality, and mechanical performance. Further, the effect of sintering temperature, time, and TiN percentage on the density and hardness values were quantitatively estimated with the help of the developed model.

The charge transfer (CT) excitation energy calculations of H2N-(CH=CH)3-X and the H2N-H.....H-X structures with the various electron acceptors (-X) were performed with comparing the accuracy of various calculation methods, such as B3LYP, long-range corrected (LC)-BLYP, and EOM-CCSD. Both intra-molecular and inter-molecular systems showed a tendency for CT excitation energy to decrease as the electronic accepting property increases, and LC-BLYP showed the best accuracy in both inter- and intra-molecular CT excitation energy. In this study, it was confirmed that unexpectedly larger range separation parameter(μ) values of LC-BLYP showed better results of CT excitation energy.

본 연구에서는 운전 시뮬레이션을 이용하여 적응형 정속 주행(adaptive cruise control: ACC) 시스템에 대한 운전자의 신뢰 및 도로 혼잡도가 운전자의 작업부하와 상황인식에 미치는 효과를 알아보았다. ACC 시스템에 대한 운전자의 신뢰는 ACC 시스템이 정상 작동하는 조건과 시스템이 오작동하는 조건을 통해 신뢰상승 집단과 신뢰감소 집단으로 구분하였다. 도로 혼잡도는 운전자 차량 주변의 차량 수로 수준을 조작하였다. ACC 시스템에 대한 신뢰와 도로 혼잡도를 달리한 네 가지의 실험 조건 각각에 대해 운전자들의 작업부하와 상황인식을 측정하였다. 본 연구의 결과를 요약하면 다음과 같다. 먼저 ACC 시스템에 대한 신뢰감소 집단은 신뢰상승 집단에 비해 이 시스템의 사용으로 인한 운전부담 경감이나 안전운전 확보 등을 포함한 측정 항목 모두에서 시스템에 대한 신뢰 점수가 유의하게 더 낮았다. 둘째, ACC 시스템에 대한 신뢰감소 집단은 신뢰상승 집단에 비해 이차과제에서 더 느린 반응시간을 보였고, 시스템 사용에서의 주관적인 작업부하 수준도 더 높게 평정하였다. 셋째, 이와는 대조적으로 운전자들의 운전상황에 대한 상황인식은 ACC 시스템 신뢰감소 집단이 신뢰상승 집단보다 유의하게 더 우수하였다. 본 연구의 결과들은 ACC 시스템에 대한 신뢰가 운전 중에 수행하는 다양한 정보처리에 영향을 미칠 수 있음을 보였는데, 이것은 자동화된 운전보조 시스템의 설계에서 사용자의 시스템에 대한 신뢰가 중요한 변인으로 고려되어야 한다는 것을 시사한다.