Immobilization of palladium on benzimidazole functionalized mesoporous silica nanoparticles: catalytic efficacy in Suzuki–Miyaura reaction and nitroarenes reduction

Journal of Porous Materials - Benzimidazole functionalized mesoporous silica nanoparticles immobilized Pd(0)/Pd(II) has been proposed as an efficient catalyst for the one-pot preparation of biaryls...     

Application of membrane separation processes in petrochemical industry: a review

In this paper a general review on different membrane processes and membrane reactors was done. As the main aim of this paper is to review the application of membrane processes in petrochemical industry, processes such as olefin/paraffin separation, light solvent separation, solvent dewaxing, phenol and aromatic recovery, dehydrogenation, oxidative coupling of methane and steam reforming of methane were discussed in detail. Besides, separation using polymer-inorganic nano composite membranes and wastewater treatment using membrane bio-reactors were reviewed.     

Contact dynamic modeling of a liquid droplet between two approaching porous materials

A computational fluid dynamics model based on a finite difference solution to mass and momentum conservation equations (Navier–Stokes equations) for a liquid droplet transport between two porous or nonporous contacting surfaces (CSs) is developed. The CS dynamic (equation of motion) and the spread of the incompressible liquid available on the primary surface for transfer are coupled with the Navier–Stokes equations. The topologies of the spread dynamic between and inside both surfaces (primary and CSs) are compared with experimental data. The amount of mass being transferred into the CS, predicted by the model, is also compared to the experimental measurements. The impact of the initial velocity on the spread topology and mass transfer into the pores is addressed. © 2014 American Institute of Chemical Engineers AIChE J, 60: 2346–2353, 2014     

Dy3Fe5O12 and DyFeO3 nanostructures: Green and facial auto-combustion synthesis,characterization and comparative study on electrochemical hydrogen storage

Although the technology of hydrogen energy heightened gradually, the application of binary metal oxides as a host for hydrogen sorption has not been widely established. Here we show, with a facial combustion method, the formation of Dy₃Fe₅O₁₂ and DyFeO₃ nanostructures with maximum average particle sizes ranging from 25 to 30 and 16–18 nm, respectively. The physical properties of the samples were served which further reflect in hydrogen storage properties. The discharge capacities of Dy₃Fe₅O₁₂ and DyFeO₃ nanoparticles were obtained at 2000 and 2100 mA h/g, respectively. The hydrogen storage properties were confirmed in their respective current-voltage cycles, prior to chronopotentiometry.     

Assessment of immobilized cell reactor and microbial fuel cell for simultaneous cheese whey treatment and lactic acid/electricity production

Two biological methods for treatment of cheese whey and concentrated cheese whey were investigated in this research. As the first method, fermentation of cheese whey for production of lactic acid, in an immobilized cell reactor (ICR) was successfully carried out. The immobilisation of Lactobacillus bulgaricus was performed by the enriched cells cultured media harvested at exponential growth phase. Furthermore, the FTIR analysis has been done to prove the production of lactic acid. The COD removal during the continuous process for both whey and concentrated whey was above 70% which showed the capability of reaction for wastewater treatment. The cells were immobilised by sodium alginate as a perfect polymer in this regard. The maximum produced lactic acid from whey was 10.7 g l^?1 at 0.125 h^?1 and 19.5 g l^?1 from concentrated whey at 0.063 h^?1. Finally it can be concluded that the process is efficient for lactic acid production and COD removal simultaneously. As the second studied method, whey and concentrated cheese whey were used as the sources of carbon in a microbial fuel cell. The power densities of 188.8 and 288.12 mW m^?2 were recorded for whey-fed and concentrated whey-fed MFCs while the COD removal were 95% and 86% respectively. Biological wastewater treatment can be a very efficient alternative for traditional wastewater treatment which selecting any and or integrating of them depends on specific applications needed to be achieved.     

Using backward elimination with a new model order reduction algorithm to select best double mixture model for document clustering

Probabilistic latent semantic analysis (PLSA) is a double structure mixture model which has got a wide application in text and web mining. This method is capable of establishing hidden semantic relations among the observed features, using a number of latent variables. In this approach, the selection of the correct number of latent variables is critical. In the most of the previous researches, the number of latent topics was selected based on the number of invoked classes. This paper presents a method, based on backward elimination approach, which is capable of unsupervised order selection in PLSA. This method starts with a model having a number of components more than the needed value, and then prunes the mixtures to reach their optimum size. During the elimination process, proper selection of some latent variables which must be deleted is the most essential problem, and its relation to the final performance of the pruned model is straightforward. To treat this problem, we introduce a new combined pruning method which selects the best options for removal, while keeping a low computational cost, at all. We conducted some experiments on two datasets from Reuters-21578 corpus. The obtained results show that this algorithm leads to an optimized number of latent variables and in turn achieves better clustering performance compared to the conventional model selection methods. It also shows superiority over the case in which a PLSA model with a fixed number of latent variables, equal to the real number of clusters, is exploited.