Dysprosium doped copper oxide (Cu1-xDyxO) nanoparticles enabled bifunctional electrode for overall water splitting

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 (Cu_1-xDy_xO) 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 Cu_1-xDy_xO (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.     

Graft copolymerization onto rubber. VII. Graft copolymerization of methyl methacrylate onto rubber using potassium peroxydisulfate catalyzed by silver ion

The graft copolymerization of methyl methacrylate onto natural rubber (NR) was carried out varying the concentration of monomer, initiator, thiourea, and silver nitrate over a wide range. The grafting reaction was temperature-dependent. From the Arrhenius plot, the overall energy of activation was computed. A suitable reaction scheme and rate expression for the rate of polymerization was suggested.     

Surface Hardening of High-Strength Low Alloy Steels (HSLA) Dual-Phase Steels by Ball Burnishing Using Factorial Design

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.     

Plastic Limit, Liquid Limit and Undrained Shear Strength of Soil—Reappraisal

The concept that plasticity index of soils can be defined as a range of water contents producing a 100-fold variation in undrained shear strength has been experimentally verified with the help of a large number of tests on soils of diverse nature. This has led to the redefinition of the plastic limit as the water content at which undrained shear strength is around 170 kN/m2. Undrained shear strength of a soil at the liquid limit can be considered to be around 1.7 kN/m2. Accordingly, both the liquid limit and the plastic limit have been determined in the present work by a single consistent method, i.e., the Swedish fall cone method. The undrained shear strength-water content relationship has been found to be log-linear for a wide range of water contents beginning from lower than the plastic limit to higher than the liquid limit. This resulted in the formulation of an expression for predicting undrained shear strength of a remolded soil at any water content based solely on its liquid limit and plastic limit.     

Wavelet based Denial-of-Service detection

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.