The effects of surface cleaning to eliminate the surface oxides formed on Cu seed layer with dilute H2SO4 solution were investigated. Cu seed layer formed on Ti/Si（100） wafer by sputter deposition was exposed to air...The effects of surface cleaning to eliminate the surface oxides formed on Cu seed layer with dilute H2SO4 solution were investigated. Cu seed layer formed on Ti/Si（100） wafer by sputter deposition was exposed to air to grow native Cu oxide. Dilute H2SO4 solutions and/or TS-40A alkaline soak cleaner were used to remove the native Cu-oxide. After mainly carbon groups （such as C=O） on surface of Cu seed layer were removed by pretreatment of TS-40A alkaline solution, subsequently, dilute H2SO4 acid solution removed Cu-oxides （Cu20 and CuO） as well as a lot of O=C and Cu（OH）2.展开更多
The size effect of copper wire radius (0.04–0.82 mm) on the diffusion-limited current density of an oxygen reduction reaction in stagnant simulated seawater (naturally aerated 0.5 mol/L NaCl) is investigated by poten...The size effect of copper wire radius (0.04–0.82 mm) on the diffusion-limited current density of an oxygen reduction reaction in stagnant simulated seawater (naturally aerated 0.5 mol/L NaCl) is investigated by potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) and compared with the results obtained in 0.5 mol/L H2SO4. In the oxygen diffusion-limited range, size effect is found to occur independent of electrolytes, which is attributed to non-linear diffusion. Additionally, to satisfy application in a marine setting, an empirical equation correlating oxygen diffusion-limited current density to copper wire radius is proposed by fitting experimental data.展开更多
Spectrum sensing is one of the key issues in cognitive radio networks. Most of previous work concenates on sensing the spectrum in a single spectrum band. In this paper, we propose a spectrum sensing sequence predicti...Spectrum sensing is one of the key issues in cognitive radio networks. Most of previous work concenates on sensing the spectrum in a single spectrum band. In this paper, we propose a spectrum sensing sequence prediction scheme for cognitive radio networks with multiple spectrum bands to decrease the spectrum sensing time and increase the throughput of secondary users. The scheme is based on recent advances in computational learning theory, which has shown that prediction is synonymous with data compression. A Ziv-Lempel data compression algorithm is used to design our spectrum sensing sequence prediction scheme. The spectrum band usage history is used for the prediction in our proposed scheme. Simulation results show that the proposed scheme can reduce the average sensing time and improve the system throughput significantly.展开更多
In this paper,we consider a cognitive radio(CR) system with a single secondary user(SU) and multiple licensed channels.The SU requests a fixed number of licensed channels and must sense the licensed channels one by on...In this paper,we consider a cognitive radio(CR) system with a single secondary user(SU) and multiple licensed channels.The SU requests a fixed number of licensed channels and must sense the licensed channels one by one before transmission.By leveraging prediction based on correlation between the licensed channels,we propose a novel spectrum sensing strategy,to decide which channel is the best choice to sense in order to reduce the sensing time overhead and further improve the SU's achievable throughput.Since the correlation coefficients between the licensed channels cannot be exactly known in advance,the spectrum sensing strategy is designed based on the model-free reinforcement learning(RL).The experimental results show that the proposed spectrum sensing strategy based on reinforcement learning converges and outperforms random sensing strategy in terms of long-term statistics.展开更多
基金supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (No. 2012026094)
文摘The effects of surface cleaning to eliminate the surface oxides formed on Cu seed layer with dilute H2SO4 solution were investigated. Cu seed layer formed on Ti/Si（100） wafer by sputter deposition was exposed to air to grow native Cu oxide. Dilute H2SO4 solutions and/or TS-40A alkaline soak cleaner were used to remove the native Cu-oxide. After mainly carbon groups （such as C=O） on surface of Cu seed layer were removed by pretreatment of TS-40A alkaline solution, subsequently, dilute H2SO4 acid solution removed Cu-oxides （Cu20 and CuO） as well as a lot of O=C and Cu（OH）2.
基金Supported by the National Natural Science Foundation of China (No.50971118)
文摘The size effect of copper wire radius (0.04–0.82 mm) on the diffusion-limited current density of an oxygen reduction reaction in stagnant simulated seawater (naturally aerated 0.5 mol/L NaCl) is investigated by potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) and compared with the results obtained in 0.5 mol/L H2SO4. In the oxygen diffusion-limited range, size effect is found to occur independent of electrolytes, which is attributed to non-linear diffusion. Additionally, to satisfy application in a marine setting, an empirical equation correlating oxygen diffusion-limited current density to copper wire radius is proposed by fitting experimental data.
基金Supported by the National Natural Science Foundation of China（No.60832009）, the Natural Science Foundation of Beijing （No.4102044） and the National Nature Science Foundation for Young Scholars of China （No.61001115）
文摘Spectrum sensing is one of the key issues in cognitive radio networks. Most of previous work concenates on sensing the spectrum in a single spectrum band. In this paper, we propose a spectrum sensing sequence prediction scheme for cognitive radio networks with multiple spectrum bands to decrease the spectrum sensing time and increase the throughput of secondary users. The scheme is based on recent advances in computational learning theory, which has shown that prediction is synonymous with data compression. A Ziv-Lempel data compression algorithm is used to design our spectrum sensing sequence prediction scheme. The spectrum band usage history is used for the prediction in our proposed scheme. Simulation results show that the proposed scheme can reduce the average sensing time and improve the system throughput significantly.
基金supported by National Nature Science Foundation of China(NO.61372109)
文摘In this paper,we consider a cognitive radio(CR) system with a single secondary user(SU) and multiple licensed channels.The SU requests a fixed number of licensed channels and must sense the licensed channels one by one before transmission.By leveraging prediction based on correlation between the licensed channels,we propose a novel spectrum sensing strategy,to decide which channel is the best choice to sense in order to reduce the sensing time overhead and further improve the SU's achievable throughput.Since the correlation coefficients between the licensed channels cannot be exactly known in advance,the spectrum sensing strategy is designed based on the model-free reinforcement learning(RL).The experimental results show that the proposed spectrum sensing strategy based on reinforcement learning converges and outperforms random sensing strategy in terms of long-term statistics.
