Making unilamellar liposomes using focused ultrasound

Several techniques are available for making large unilamellar vesicles (LUV) with an average diameter of approximately 100 nm, widely employed as model biomembranes as well as vehicles for drug delivery. Here we describe the use of adaptive focused ultrasound (AFU) for the preparation of LUV from multilamellar vesicles (MLV) and studied the effects of ultrasound intensity and number of cycles per burst (CPB) on the average size of vesicles produced. CPB determines the duration of the intermittent pressure wavetrains emitted by the transducer, and the corresponding relaxation periods. Preliminary experiments indicated that CPB controls the size of vesicles assembling after the disruption of MLV by ultrasound and optimum values for obtaining LUV could be iterated. The sizes and lamellarity of LUV were assessed by dynamic light scattering (DLS), cryogenic transmission electron microscopy (cryo-TEM), and fluorescence quenching. AFU provides a simple and easy to use approach for making liposomes with several advantages: it is minimally invasive and involves no loss of material. Precisely controlled wavelengths are employed with a significant reduction in the presence of hot spots, which could destroy some biological materials of interest.     

Effect of electron beam irradiation on physico-chemical properties of pullulan

Many widely used polymers undergo main chain scission or crosslinking when exposed to radiation. Effects of electron beam irradiation at different doses up to 500?kGy on the biodegradable pullulan polymer films have been investigated by ultraviolet?Cvisible (UV?CVIS), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and thermogravimetric analysis (TGA) techniques. UV?CVisible study shows increase of optical absorbance with increase of doses, attributing to the formation some groups or radicals. FTIR and TGA results reveal the processes of both crosslinking and degradation of polymer taking place depending upon the dose of e-beam radiation. The surface morphology of the film is found to be altered by the e-beam radiation as indicated by SEM micrographs.     

Novel carbon materials for thermal energy harvesting

To decrease the consumption of fossil fuels, research has been done on utilizing low grade heat, sourced from industrial waste streams. One promising thermoenergy conversion system is a thermogalvanic cell; it consists of two identical electrodes held at different temperatures that are placed in contact with a redox-based electrolyte [1, 2]. The temperature dependence of the direction of redox reactions allows power to be extracted from the cell [3, 4]. This study aims to increase the power conversion efficiency and reduce the cost of thermogalvanic cells by optimizing the electrolyte and utilizing a carbon based electromaterial, reduced graphene oxide, as electrodes. Thermal conductivity measurements of the K₃Fe(CN)₆/K₄Fe(CN)₆ solutions used, indicate that the thermal conductivity decreases from 0.591 to 0.547?W/m?K as the concentration is increased from 0.1 to 0.4?M. The lower thermal conductivity allowed a larger temperature gradient to be maintained in the cell. Increasing the electrolyte concentration also resulted in higher power densities, brought about by a decrease in the ohmic overpotential of the cell, which allowed higher values of short circuit current to be generated. The concentration of 0.4?M K₃Fe(CN)₆/K₄Fe(CN)₆ is optimal for thermal harvesting applications using R-GO electrodes due to the synergistic effect of the reduction in thermal flux across the cell and the enhancement of power output, on the overall power conversion efficiency. The maximum mass power density obtained using R-GO electrodes was 25.51?W/kg (three orders of magnitude higher than platinum) at a temperature difference of 60?°C and a K₃Fe(CN)₆/K₄Fe(CN)₆ concentration of 0.4?M.     

A novel oxidative transformation of alcohols to nitriles: an efficient utility of azides as a nitrogen source

An efficient methodology to oxidize benzylic and cinnamyl alcohols to their corresponding nitriles in excellent yields has been developed. This methodology employs DDQ as an oxidant and TMSN(3) as a source of nitrogen in the presence of a catalytic amount of Cu(ClO(4))(2)·6H(2)O.     

Physicochemical study of spiropyran-terthiophene derivatives: photochemistry and thermodynamics

The photochemistry and thermodynamics of two terthiophene (TTh) derivatives bearing benzospiropyran (BSP) moieties, 1-(3,3″-dimethylindoline-6'-nitrobenzospiropyranyl)-2-ethyl 4,4″-didecyloxy-2,2':5',2″-terthiophene-3'-acetate (BSP-2) and 1-(3,3″-dimethylindoline-6'-nitrobenzospiropyranyl)-2-ethyl 4,4″-didecyloxy-2,2':5',2″-terthiophene-3'-carboxylate (BSP-3), differing only by a single methylene spacer unit, have been studied. The kinetics of photogeneration of the equivalent merocyanine (MC) isomers (MC-2 and MC-3, respectively), the isomerisation properties of MC-2 and MC-3, and the thermodynamic parameters have been studied in acetonitrile, and compared to the parent, non-TTh-functionalised, benzospiropyran derivative, BSP-1. Despite the close structural similarity of BSP-2 and BSP-3, their physicochemical properties were found to differ significantly; examples include activation energies (E(a(MC-2)) = 75.05 kJ mol(-1), E(a(MC-3)) = 100.39 kJ mol(-1)) and entropies of activation (ΔS = 43.38 J K(-1) mol(-1), ΔS = 37.78 J K(-1) mol(-1)) for the thermal relaxation from MC to BSP, with the MC-3 value much closer to the unmodified MC-1 value (46.48 J K(-1) mol(-1)) for this latter quantity. The thermal relaxation kinetics and solvatochromic behaviour of the derivatives in a range of solvents of differing polarity (ethanol, dichloromethane, acetone, toluene and diethyl ether) are also presented. Differences in the estimated values of these thermodynamic and kinetic parameters are discussed with reference to the molecular structure of the derivatives.     

Micromechanical cohesion force measurements to determine cyclopentane hydrate interfacial properties

Hydrate aggregation and deposition are critical factors in determining where and when hydrates may plug a deepwater flowline. We present the first direct measurement of structure II (cyclopentane) hydrate cohesive forces in the water, liquid hydrocarbon and gas bulk phases. For fully annealed hydrate particles, gas phase cohesive forces were approximately twice that obtained in a liquid hydrocarbon phase, and approximately six times that obtained in the water phase. Direct measurements show that hydrate cohesion force in a water-continuous bulk may be only the product of solid-solid cohesion. When excess water was present on the hydrate surface, gas phase cohesive forces increased by a factor of three, suggesting the importance of the liquid or quasi-liquid layer (QLL) in determining cohesive force. Hydrate-steel adhesion force measurements show that, when the steel surface is coated with hydrophobic wax, forces decrease up to 96%. As the micromechanical force technique is uniquely capable of measuring hydrate-surface forces with variable contact time, the present work contains significant implications for hydrate applications in flow assurance.     

Raman investigations of Zn1−xCoxO nanocrystals: role of starting precursors on vibrational properties

The Raman spectra of sol–gel derived Co‐doped ZnO nanoparticles (NPs) in the spectral range 100–1500 cm⁻¹ were investigated. In the sol–gel method, three different series of Co‐doped ZnO particles, i.e. Zn_1−xCo_xO (x = 0.05, 0.10, 0.15, and 0.20), were obtained using three different starting precursors, viz. cobalt chloride hexahydrate, cobalt acetate tetrahydrate, and cobalt nitrate hexahydrate, respectively. It has been observed that cobalt acetate is a better precursor in comparison to cobalt chloride and cobalt nitrate to obtain single‐phase Co‐doped ZnO NPs. As for cobalt acetate‐derived NPs, no hidden secondary phase of Co₃O₄ was observed for the lower (x = 0.05) Co concentration. The Fröhlich interaction associated with the longitudinal modes was found to be destroyed with increasing Co concentration due to structural disorder and defects induced by the dopant. In addition to ZnO and Co₃O₄ vibrational modes, a few additional modes near 550 and 715 cm⁻¹ were also observed in all cases, which could be attributed to the modes due to Co doping in ZnO. Copyright © 2011 John Wiley & Sons, Ltd.     

Dynamical stability and phase transition of ZrC under pressure

A comprehensive first principles study of structural, elastic, electronic, and phonon properties of zirconium carbide (ZrC) is reported within the density functional theory scheme. The aim is to primarily focus on the vibrational properties of this transition metal carbide to understand the mechanism of phase transition. The ground state properties such as lattice constant, elastic constants, bulk modulus, shear modulus, electronic band structure, and phonon dispersion curves (PDC) of ZrC in rock-salt (RS) and high-pressure CsCl structures are determined. The pressure-dependent PDCs are also reported in NaCl phase. The phonon modes become softer and finally attain imaginary frequency with the increase of pressure. The lattice degree of freedom is used to explain the phase transition. Static calculations predict the RS to CsCl phase transition to occur at 308?GPa at 0?K. Dynamical calculations lower this pressure by about 40?GPa. The phonon density of states, electron–phonon interaction coefficient, and Eliashberg's function are also presented. The calculated electron–phonon coupling constant λ and superconducting transition temperature agree reasonably well with the available experimental data.     

A first principles lattice dynamics and Raman spectra of the ferroelastic rutile to CaCl2 phase transition in SnO2 at high pressure

A first principles calculation of the lattice dynamical properties of rutile SnO₂ has been performed using density functional perturbation theory at ambient and high‐pressure conditions to understand the pressure‐induced phase transition. The calculated zone centre phonon modes at ambient and high pressures have been compared with Raman scattering and infrared measurements. Full phonon dispersion curves and phonon densities of states and Raman intensities at high pressures are calculated and given for the first time in literature. The ferroelastic transition from the rutile to the CaCl₂‐type structure was confirmed. It is clearly illustrated that the first transition is associated with macroscopic shear instability which arises from the strong coupling between elastic constants and softening of Raman active B_1g mode. The observed pressure of phase transition in experimental measurements was reproduced more accurately than in previous calculations, and the difference between observed and calculated transition pressure is only of the order of 2%. The mode Grüneisen parameter is quantitatively as well as qualitatively different from the earlier reported values. Copyright © 2013 John Wiley & Sons, Ltd.     

A sequential predictor retraining algorithm and its application to market prediction

In many applications, there are a large number of predictors, designed manually or trained automatically, to predict the same outcome. Much research has been devoted to the design of algorithms that can effectively select/combine these predictors to generate a more accurate ensemble predictor. The collaborative training algorithms from attribute distributed learning provide batch-processing solutions for scenarios in which the individual predictors are heterogeneous, taking different inputs and employing different models. However, in some applications, for example financial market prediction, it is desirable to use an online approach. In this paper, an innovative online algorithm is proposed, stemming from the collaborative training algorithms developed for attribute distributed learning. It sequentially takes new observations, simultaneously adjusting the way that the individual predictors are combined, and provides feedback to the individual predictors for them to be retrained in order to achieve a better ensemble predictor in real time. The efficacy of this new algorithm is demonstrated by extensive simulations on both artificial and real data, and particularly for financial market data. A trading strategy constructed from the ensemble predictor shows strong performance when applied to financial market prediction.