Zero-valent iron particles embedded on the mesoporous silica–carbon for chromium (VI) removal from aqueous solution

Journal of Nanoparticle Research - The demand for metal nanoparticles is increasing strongly. Transferred arc synthesis is a promising process in this respect, as it shows high production rates,...     

Binding numbers for fractional ID-k-factor-critical graphs

LetG be a graph,and k≥2 be a positive integer.A graph G is fractional independentset-deletable k-factor-critical(in short,fractional ID-k-factor-critical),if G I has a fractional k-factor for every independent set I of G.The binding number bind(G)of a graph G is defined as bind(G)=min|NG(X)||X|:=X V(G),NG(X)=V(G).In this paper,it is proved that a graph G is fractional ID-k-factor-critical if n≥6k 9 and bind(G)(3k 1)(n 1)kn 2k+2.     

Network-based naive Bayes model for social network

Naive Bayes (NB) is one of the most popular classification methods. It is particularly useful when the dimension of the predictor is high and data are generated independently. In the meanwhile, social network data are becoming increasingly accessible, due to the fast development of various social network services and websites. By contrast, data generated by a social network are most likely to be dependent. The dependency is mainly determined by their social network relationships. Then, how to extend the classical NB method to social network data becomes a problem of great interest. To this end, we propose here a network-based naive Bayes (NNB) method, which generalizes the classical NB model to social network data. The key advantage of the NNB method is that it takes the network relationships into consideration. The computational effciency makes the NNB method even feasible in large scale social networks. The statistical properties of the NNB model are theoretically investigated. Simulation studies have been conducted to demonstrate its finite sample performance. A real data example is also analyzed for illustration purpose.     

Evaluation of approximations for concentration-dependent micropore diffusion in sorbent with bidisperse pore structure

Average diffusivity linear driving force (AD-LDF) and concentration-dependent diffusivity linear driving force (CDD-LDF) approximations are introduced to simplify the precise model describing the concentration-dependent micropore diffusion in bidisperse sorbents, and are compared with the precise model in predicting the dynamics of a sorption process under two different perturbations (i.e., step change perturbations and sinusoidal wave perturbation) with different concentrations imposed at the exterior surface of the bidisperse sorbent. The performance of the two approximations is validated by the precise model and experiments. The AD-LDF performs better in step adsorption and CDD-LDF does better in step desorption. Under sinusoidal wave perturbation, the CDD-LDF performs better. The different levels of consistency of the two approximations with the precise model are attributed to the different definitions of the diffusivities.     

Telaprevir fragments as organocatalysts in asymmetric direct aldol reactions of aldehydes

We have demonstrated that the fragments of Telaprevir can act as organocatalysts for asymmetric aldol reactions between aromatic aldehydes and acetone under mild conditions. The reaction conditions have been optimized in terms of the catalyst nature, choice of temperature, solvent, additive, and the catalyst loading. Under proper conditions, fairly good yield and enantioselectivity have been achieved.     

Dual‐responsive supramolecular self‐assembly of inclusion complex of an azobenzene‐ended poly(ε‐caprolactone) with a water‐soluble pillar[6]arene and its application in controlled drug release

Dual photo‐ and pH‐responsive polymeric vesicles are constructed from a host–guest complex between a water‐soluble pillar[6]arene and an azobenzene ended functionalized poly(ε‐caprolactone). Reversible morphological transitions between vesicles and solid aggregates are achieved upon repeated UV stimulus and pH stimulus. Moreover, the polymeric vesicles present excellent cytocompatibility toward HepG2 cells and can be further applied for controlled release of a hydrophilic model drug, DOX?HCl. © 2017 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2017 , 55 , 2477–2482     

Modeling the deformation behavior of nanocrystalline alloy with hierarchical microstructures

A mechanism-based plasticity model based on dislocation theory is developed to describe the mechanical behavior of the hierarchical nanocrystalline alloys. The stress–strain relationship is derived by invoking the impeding effect of the intra-granular solute clusters and the inter-granular nanostructures on the dislocation movements along the sliding path. We found that the interaction between dislocations and the hierarchical microstructures contributes to the strain hardening property and greatly influence the ductility of nanocrystalline metals. The analysis indicates that the proposed model can successfully describe the enhanced strength of the nanocrystalline hierarchical alloy. Moreover, the strain hardening rate is sensitive to the volume fraction of the hierarchical microstructures. The present model provides a new perspective to design the microstructures for optimizing the mechanical properties in nanostructural metals.