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The production of hydrogen, a favourable alternative to an unsustainable fossil fuel remains as a significant hurdle with the pertaining challenge in the design of proficient, highly productive and sustainable electrocatalyst for both oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). Herein, the dysprosium (Dy) doped copper oxide (Cu1-xDyxO) nanoparticles were synthesized via solution combustion technique and utilized as a non-noble metal based bi-functional electrocatalyst for overall water splitting. Due to the improved surface to volume ratio and conductivity, the optimized Cu1-xDyxO (x = 0.01, 0.02) electrocatalysts exhibited impressive HER and OER performance respectively in 1 M KOH delivering a current density of 10 mAcm?2 at a potential of ?0.18 V vs RHE for HER and 1.53 V vs RHE for OER. Moreover, the Dy doped CuO electrocatalyst used as a bi-functional catalyst for overall water splitting achieved a potential of 1.56 V at a current density 10 mAcm?2 and relatively high current density of 66 mAcm?2 at a peak potential of 2 V. A long term stability of 24 h was achieved for a cell voltage of 2.2 V at a constant current density of 30 mAcm?2 with only 10% of the initial current loss. This showcases the accumulative opportunity of dysprosium as a dopant in CuO nanoparticles for fabricating a highly effective and low-cost bi-functional electrocatalyst for overall water splitting.  相似文献   
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Hydrogen fuel is a promising alternative to fossil fuels because of its energy content, clean nature, and fuel efficiency. However, it is not readily available. Most current producion processes are very energy intensive and emit carbon dioxide. Therefore, this article reviews technological options for hydrogen production that are eco-friendly and generate clean hydrogen fuel. Biological methods, such different fermentation processes and photolysis are discussed together with the required substrates and the process efficiency.  相似文献   
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The electrochemical reduction of carbon dioxide (CO2) to hydrocarbons is a challenging task because of the issues in controlling the efficiency and selectivity of the products. Among the various transition metals, copper has attracted attention as it yields more reduced and C2 products even while using mononuclear copper center as catalysts. In addition, it is found that reversible formation of copper nanoparticle acts as the real catalytically active site for the conversion of CO2 to reduced products. Here, it is demonstrated that the dinuclear molecular copper complex immobilized over graphitized mesoporous carbon can act as catalysts for the conversion of CO2 to hydrocarbons (methane and ethylene) up to 60%. Interestingly, high selectivity toward C2 product (40% faradaic efficiency) is achieved by a molecular complex based hybrid material from CO2 in 0.1 m KCl. In addition, the role of local pH, porous structure, and carbon support in limiting the mass transport to achieve the highly reduced products is demonstrated. Although the spectroscopic analysis of the catalysts exhibits molecular nature of the complex after 2 h bulk electrolysis, morphological study reveals that the newly generated copper cluster is the real active site during the catalytic reactions.  相似文献   
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Burnishing is used increasingly as a finishing operation which gives additional advantages such as increased hardness, fatigue strength, and wear resistance. Experimental work based on 34 factorial design was carried out to establish the effects of ball burnishing parameters on the surface hardness of high-strength low alloy steels (HSLA) dual-phase (DP) steel specimens. Statistical analysis of the results shows that the speed, feed, lubricant and ball diameter have significant effect on surface hardness.  相似文献   
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Glenn  Richard R.  Suresh   《Computers & Security》2006,25(8):600-615
Network Denial-of-Service (DoS) attacks that disable network services by flooding them with spurious packets are on the rise. Criminals with large networks (botnets) of compromised nodes (zombies) use the threat of DoS attacks to extort legitimate companies. To fight these threats and ensure network reliability, early detection of these attacks is critical. Many methods have been developed with limited success to date. This paper presents an approach that identifies change points in the time series of network packet arrival rates. The proposed process has two stages: (i) statistical analysis that finds the rate of increase of network traffic, and (ii) wavelet analysis of the network statistics that quickly detects the sudden increases in packet arrival rates characteristic of botnet attacks.Most intrusion detections are tested using data sets from special security testing configurations, which leads to unacceptable false positive rates being found when they are used in the real world. We test our approach using data from both network simulations and a large operational network. The true and false positive detection rates are determined for both data sets, and receiver operating curves use these rates to find optimal parameters for our approach. Evaluation using operational data proves the effectiveness of our approach.  相似文献   
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