One-pot synthesis of α-aminonitriles using a highly efficient and recyclable silica-based scandium (III) interphase catalyst

Both aryl and alkyl imines, which formed in situ from aldehydes and amines undergo smooth nucleophilic addition with trimethylsilyl cyanide in the presence of a catalytic amount of a silica-based scandium (III) interphase catalyst under mild reaction condition to furnish the corresponding α-aminonitriles in good to excellent yields. The catalyst shows high thermal stability (up to 300 °C) and it could also be recovered and reused for at least 6 reaction cycles without considerable lose of its reactivity.     

Surfactant-polyelectrolyte complexes on the basis of chitin

The review is devoted to synthesis and study of interfacial properties of electrostatic complexes between oppositely charged chitin derivatives and surfactants, so-called surfactant-polyelectrolyte complexes (SPECs). The ordered nanostructure of insoluble SPEC found by small-angle X-ray scattering (SAXS) looks as a physical gel network formed by micelle-like aggregates interconnected by macro-molecular chains. Viscoelastic properties of such gels were studied by means of the Hertz method and interfacial dilational rheology. A new method based on the effect of diffusion-enhanced gelation at the interface of aqueous solutions of oppositely charged polyelectrolytes and surfactants was developed. This method makes it possible to produce microcapsules containing enzymes, i.e. microreactors for enzymatic catalysis.     

Precomputing strategy for Hamiltonian Monte Carlo method based on regularity in parameter space

Markov Chain Monte Carlo (MCMC) algorithms play an important role in statistical inference problems dealing with intractable probability distributions. Recently, many MCMC algorithms such as Hamiltonian Monte Carlo (HMC) and Riemannian Manifold HMC have been proposed to provide distant proposals with high acceptance rate. These algorithms, however, tend to be computationally intensive which could limit their usefulness, especially for big data problems due to repetitive evaluations of functions and statistical quantities that depend on the data. This issue occurs in many statistic computing problems. In this paper, we propose a novel strategy that exploits smoothness (regularity) in parameter space to improve computational efficiency of MCMC algorithms. When evaluation of functions or statistical quantities are needed at a point in parameter space, interpolation from precomputed values or previous computed values is used. More specifically, we focus on HMC algorithms that use geometric information for faster exploration of probability distributions. Our proposed method is based on precomputing the required geometric information on a set of grids before running sampling algorithm and approximating the geometric information for the current location of the sampler using the precomputed information at nearby grids at each iteration of HMC. Sparse grid interpolation method is used for high dimensional problems. Tests on computational examples are shown to illustrate the advantages of our method.     

Ellipsoidal Domains: Piecewise Nonuniform and Impotent Eigenstrain Fields

In association with multi-inhomogeneity problems, a special class of eigenstrains is discovered to give rise to disturbance stresses of interesting nature. Some previously unnoticed properties of Eshelby’s tensors prove useful in this accomplishment. Consider the set of nested similar ellipsoidal domains {Ω₁, Ω₂,⋯,Ω _N+1}, which are embedded in an infinite isotropic medium. Suppose that

Grain size,strain rate,and temperature dependence of flow stress in ultra-fine grained and nanocrystalline Cu and Al: Synthesis,experiment, and constitutive modeling

For the first time, high quality bulk nanocrystalline (nc) fcc metals, with least amounts of imperfections, exhibiting high strength and ductility at room and different temperatures, under quasi-static and dynamic types of loading, were prepared and a comprehensive study on their post-yield mechanical properties was performed. This investigation included study of the effect of temperature on stress–strain responses of mechanically milled bulk nc Cu and Al. The samples after preparation through mechanical milling and consolidation processes were subjected to uniaxial compressive loading at quasi-static and dynamic strain rates of 10⁻² s⁻¹ and 1840–3105 s⁻¹, respectively, at temperatures ranging from 223 to 523 K. In both materials strong dependency of flow stress to temperature was observed; this dependency was rather more pronounced when the materials were tested at the quasi-static strain rate. Further, a new grain size and temperature dependent viscoplastic phenomenological constitutive equation, Khan–Liang–Farrokh (KLF) model was developed based on the Khan–Huang–Liang (KHL) constitutive equation. The model was featured to correlate different characteristic behaviors of polycrystalline materials in the plastic regime, as the result of grain refinement. In addition, the viscoplastic responses of bulk Cu and Al of different grain sizes (from sub-micron to nanometer range), and those from bulk nc Cu and Al at different strain rates (quasi-static to dynamic), recently published (21 and 22), were simulated using the newly developed equation. The results confirmed reasonable capability of the developed model to correlate a wide spectrum of the viscoplastic responses of these fcc metals.     

Statistical methods for detecting activated regions in functional MRI of the brain

Two statistical tests for detecting activated pixels in functional MRI (fMRI) data are presented. The first test (t-test) is the optimal solution to the problem of detecting a known activation signal in Gaussian white noise. The results of this test are shown to be equivalent to the cross-correlation method that is widely used for activation detection in fMRI. The second test (F test) is the optimal solution when the measured data are modeled to consist of an unknown activation signal that lies in a known lower dimensional subspace of the measurement space with added Gaussian white noise. A model for the signal subspace based on a truncated trigonometric Fourier series is proposed for periodic activation–baseline imaging paradigms. The advantage of the second method is that it does not assume any information about the shape or delay of the activation signal, except that it is periodic with the same period as the activation–baseline pattern. The two models are applied to experimental echo-planar fMRI data sets and the results are compared.     

An image encryption approach using tuned Henon chaotic map and evolutionary algorithm

A new evolutionary-based image encryption method is proposed to protect the image content against adversary attacks from an insecure network throughout the Internet. Two-dimensional Henon chaotic map is the significant part of the encryption process, whereas its performance strongly depends on the fine tuning of its parameters, including α and β. Imperialist Competitive Algorithm (ICA) is applied to determine these parameters based on the input simple image, so that the pseudorandom number generated by the two-dimensional Henon map would be unique for each simple image, making it difficult to explore the encryption process. Experimental results assert that the proposed method is secure enough to resist against common attacks.

     

NiO/Porous Reduced Graphene Oxide as Active Hybrid Electrocatalyst for Oxygen Evolution Reaction

Russian Journal of Electrochemistry - At present, the graphene hybrid as electrode material demonstrates the efficient performance for oxygen evolution reaction (OER). OER influences some important...     

Distribution of fullerene nanomaterials between water and model biological membranes

Biological membranes are one of the important interfaces between cells and pollutants. Many polar and hydrophobic chemicals can accumulate within these membranes. For this reason, artificial biological membranes are appealing surrogates to complex organisms for assessing the bioaccumulation potential of engineered nanomaterials (ENMs). To our knowledge, this work presents the first quantitative study on the distribution of fullerene ENMs between lipid bilayers, used as model biological membranes, and water. We evaluated the lipid bilayer-water association coefficients (K(lipw)) of aqueous fullerene aggregates (nC(60)) and fullerol (C(60)(ONa)(x)(OH)(y), x + y = 24). Kinetic studies indicated that fullerol reached apparent equilibrium more rapidly than nC(60) (2 h versus >9 h). Nonlinear isotherms can describe the distribution behavior of nC(60) and fullerol. The lipid bilayer-water distributions of both nC(60) and fullerol were pH-dependent with the accumulation in lipid bilayers increasing systematically as the pH decreased from 8.6 (natural water pH) to 3 (the low end of physiologically relevant pH). This pH dependency varies with the zeta potentials of the ENMs and leads to patterns similar to those previously observed for the lipid bilayer-water distribution behavior of ionizable organic pollutants. The K(lipw) value for nC(60) was larger than that of fullerol at a given pH, indicating a greater propensity for nC(60) to interact with lipid bilayers. For example, at pH 7.4 and an aqueous concentration of 10 mg/L, K(lipw) was 3.5 times greater for nC(60) (log K(lipw) = 2.99) relative to fullerol (log K(lipw) = 2.45). Comparisons with existing aquatic organism bioaccumulation studies suggested that the lipid bilayer-water distribution is a potential method for assessing the bioaccumulation potentials of ENMs.