Carbon supported bimetallic Ru‐Co catalysts for H2 production through NaBH4 and NH3BH3 hydrolysis

This work investigates the effect of the addition of small amounts of Ru (0.5‐1 wt%) to carbon supported Co (10 wt%) catalysts towards both NaBH₄ and NH₃BH₃ hydrolysis for H₂ production. In the sodium borohydride hydrolysis, the activity of Ru‐Co/carbon catalysts was sensibly higher than the sum of the activities of corresponding monometallic samples, whereas for the ammonia borane hydrolysis, the positive effect of Ru‐Co systems with regard to catalytic activity was less evident. The performances of Ru‐Co bimetallic catalysts correlated with the occurrence of an interaction between Ru and Co species resulting in the formation of smaller ruthenium and cobalt oxide particles with a more homogeneous dispersion on the carbon support. It was proposed that Ru^°, formed during the reduction step of the Ru‐Co catalysts, favors the H₂ activation, thus enhancing the reduction degree of the cobalt precursor and the number of Co nucleation centers. A subsequent reduction of cobalt and ruthenium species also occurs in the hydride reaction medium, and therefore the state of the catalyst before the catalytic experiment determines the state of the active phase formed in situ. The different relative reactivity of the Ru and Co active species towards the two investigated reactions accounted for the different behavior towards NaBH₄ and NH₃BH₃ hydrolysis.     

The Role of Excitation Photons Energy in the Photoinduced Carrier Dynamics in InGaAs/InAlAs Superlattice Heterostructures

Technical Physics Letters - The influence of excitation photons energy on the relaxation times of photoexcited carriers is studied. The involved relaxation mechanisms are evaluated and the...     

On stochastic comparisons of finite mixtures for some semiparametric families of distributions

In this paper, we consider the classical finite mixture model, which is an effective tool for modeling lifetime distributions for random samples from heterogeneous populations. We discuss new results on stochastic comparison for two finite mixtures when each of them is drawn from one of the following semiparametric families, i.e., proportional hazards, accelerated lifetime and proportional reversed hazards.     

Peculiarities of Monitoring the State of a Flowing Medium by the Method of Nuclear Magnetic Resonance

Technical Physics Letters - Specific features of monitoring the state of a flowing medium by method of nuclear magnetic resonance (NMR) are considered. An approach to studying the state of a...     

Influence of the Chemical Composition and Local Atomic Packing of Nanostructured MoSx and MoSex Solid Lubricant Coatings on Their Tribological Properties under Complicated Conditions

Technical Physics Letters - We present the results of a comparative investigation of the friction and wear characteristics of MoSx and MoSex coatings in an oxidizing medium (argon–air...     

Detailed study on fusion characteristics of rigid poly(vinyl chloride) nanocomposites: The comparison of using multiple regression analysis and artificial neural network

Fusion behavior of poly(vinyl chloride) (PVC) compounds plays an important role in the development of physical properties of processed material. The fusion characteristics in PVC processing are governed by material variables that affect the fusion with some interactions. In this research, the aim was to characterize the effects of formulation ingredients on fusion characteristics of PVC. Four material parameters, including the contents of nanoclay (NC), azodicarbonamide, calcium stearate, and processing aid, are proposed as affecting variables. The fusion time (FT) as well as fusion factor (FF) are considered fusion indicators and are experimentally determined in some different levels of affecting parameters. The multivariable regression analysis (MRA) and the Artificial Neural Network (ANN) modeling are considered as two analytical methods. The regression analysis result for the FT denotes, in part, significant linear and quadratic effects of NC and also its significant interactions with azodicarbonamide and calcium stearate, whereas that of FF indicates only a linear effect of NC. ANN modeling is performed with a three‐layer (input, hidden, and output) neural network. The results of the comparison of the MRA and ANN predictions with experimental values are reported as the correlation coefficient (R²), mean‐square error, and mean absolute percentage error for both FF and FT parameters. The obtained values clearly denote that the ANN results are more precise and especially more general than those of MRA. However, in the case of FT, improvement of the ANN modeling is much greater than that of FF. J. VINYL ADDIT. TECHNOL., 21:147–155, 2015. © 2014 Society of Plastics Engineers