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Gang Chen,Yu Jin,Jing Wang,Cheng Zhang,Qiang Chen,Hongming Zhang,Xingjian Zhao,Zhiyong Li,Changhai Xie,Zhiming Du 대한금속·재료학회 2022 METALS AND MATERIALS International Vol.28 No.9
Isothermal compression tests were carried out to study the hot deformation behavior of T2 copper under various conditions. The deformation parameters, such as temperature and strain rate, have strong influence on flow stress and microstructureevolution of the alloy. A unified dislocation density-based model considering dynamic recovery and recrystallization wasestablished. And material parameters of the developed model were optimized by genetic algorithm. Comparisons betweenthe experimental and model data demonstrates that the developed model can precisely describe the flow behavior at quitewide range of deformation conditions. Meanwhile, the designed iterative procedure allows the model to be applied in timevariantdeformation conditions. Processing map and microstructure examination were constructed to optimize the processingwindow of the studied alloy. According to the processing maps, flow instability mainly appeared at low temperatures of500–650 °C and strain rates higher than 0.1 s−1. The optimum deformation parameters of T2 copper was concluded as thetemperature range of 700–800 °C and the strain rate of 0.1–1 s−1.
Dang Mengyue,Li Ying,Xu Chaoxiang,He Yulin,Yu Chunpeng,Liu Wenbo,Jin Hongming,Zhu Mingyuan,Zhang Jiujun,Li Wenxian 한국물리학회 2021 Current Applied Physics Vol.32 No.-
The electrochemical performances of LiNi0.5Co0.2Mn0.3O2 (NCM523) layered cathode material, such as poor rate capacity and cycling stability caused by undesirable intrinsic conductivity and low rate of lithium ion transportation, are not fairly good especially at elevated rate and cut-off voltage. To improve these properties, in this study, the co-coating layer of graphene and TiO2 was constructed on NCM523 surface. The graphene/TiO2 coating layer could effectively prevent hydrofluoric acid (HF) attacks, suppress the side reaction, accelerate the lithium ion diffusion and facilitate the electron migration. The enhancement of cycle performance and rate capacity was contributed to the uniform co-modified surface, interacting each other and thus exhibiting synergistic effects.
산학연 협업 활성화를 위한 R&D 네트워크 연결 예측 연구
박미연(Mi-yeon Park),이상헌(Sangheon Lee),김국성(Guocheng Jin),심홍매(Hongme Shen),김우주(Wooju Kim) 한국지능정보시스템학회 2015 지능정보연구 Vol.21 No.3
The recent global trends display expansion and growing solidity in both cooperative collaboration between industry, education, and research and R&D network systems. A greater support for the network and cooperative research sector would open greater possibilities for the evolution of new scholar and industrial fields and the development of new theories evoked from synergized educational research. Similarly, the national need for a strategy that can most efficiently and effectively support R&D network that are established through the government’s R&D project research is on the rise. Despite the growing urgency, due to the habitual dependency on simple individual personal information data regarding R&D industry participants and generalized statistical data references, the policies concerning network system are disappointing and inadequate. Accordingly, analyses of the relationships involved for each subject who is participating in the R&D industry was conducted and on the foundation of an educational-industrial-research network system, possible changes within and of the network that may arise were predicted. To predict the R&D network transitions, Common Neighbor and Jaccard’s Coefficient models were designated as the basic foundational models, upon which a new prediction model was proposed to address the limitations of the two aforementioned former models and to increase the accuracy of Link Prediction, with which a comparative analysis was made between the two models. Through the effective predictions regarding R&D network changes and transitions, such study result serves as a stepping-stone for an establishment of a prospective strategy that supports a desirable educational-industrial-research network and proposes a measure to promote the national policy to one that can effectively and efficiently sponsor integrated R&D industries. Though both weighted applications of Common Neighbor and Jaccard’s Coefficient models provided positive outcomes, improved accuracy was comparatively more prevalent in the weighted Common Neighbor. An un-weighted Common Neighbor model predicted 650 out of 4,136 whereas a weighted Common Neighbor model predicted 50 more results at a total of 700 predictions. While the Jaccard’s model demonstrated slight performance improvements in numeric terms, the differences were found to be insignificant.