970 resultados para orthogonal solvent


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In the biomimetic design two hydrophobic pentapetides Boc-Ile-Aib-Leu-Phe-Ala-OMe ( I) and Boc-Gly-Ile-Aib-Leu-Phe-OMe (II) (Aib: alpha-aminoisobutyric acid) containing one Aib each are found to undergo solvent assisted self-assembly in methanol/water to form vesicular structures, which can be disrupted by simple addition of acid. The nanovesicles are found to encapsulate dye molecules that can be released by the addition of acid as confirmed by fluorescence microscopy and UV studies. The influence of solvent polarity on the morphology of the materials generated from the peptides has been examined systematically, and shows that fibrillar structures are formed in less polar chloroform/petroleum ether mixture and vesicular structures are formed in more polar methanol/water. Single crystal X-ray diffraction studies reveal that while beta-sheet mediated self-assembly leads to the formation of fibrillar structures, the solvated beta-sheet structure leads to the formation of vesicular structures. The results demonstrate that even hydrophobic peptides can generate vesicular structures from polar solvent which may be employed in model studies of complex biological phenomena.

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Novel oxazoline-based comb-polymers possessing linoleyl or oleic side chains have been synthesized and used to produce low viscosity coatings. Inclusion of the polymers in model paint formulations results in coatings that exhibit faster drying times than commercially available alkyd resin formulations. The comb polymers were produced from diol substituted oxazoline monomers that were synthesized through a scalable, solvent free protocol and purified by simple recrystallisation. Co-polymerisation of the oxazolines with adipic acid at 160 °C in the bulk resulted in the targeted polyester comb type polymers. The polymers were soluble in a range of organic solvents and compatible with commercial alkyd resins. Model paint formulations containing up to 40 wt% of the linoleyl-based comb polymers exhibited a dramatic reduction in viscosity (from 35 to 13 Poise at 25 °C) with increasing quantities of polymer added. Dynamic mechanical analysis (DMA) studies revealed that the drying rate of the model paint formulations containing the comb polymers was enhanced when compared with that of commercial alkyd resins.

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Novel acid-terminated hyperbranched polymers (HBPs) containing adipic acid and oxazoline monomers derived from oleic and linoleic acid have been synthesized via a bulk polymerization procedure. Branching was achieved as a consequence of an acid-catalyzed opening of the oxazoline ring to produce a trifunctional monomer in situ which delivered branching levels of >45% as determined by 1H and 13C NMR spectroscopy. The HBPs were soluble in common solvents, such as CHCl3, acetone, tetrahydrofuran, dimethylformamide, and dimethyl sulfoxide and were further functionalized by addition of citronellol to afford white-spirit soluble materials that could be used in coating formulations. During end group modification, a reduction in branching levels of the HBPs (down to 12–24%) was observed, predominantly on account of oxazoline ring reformation and trans-esterification processes under the reaction conditions used. In comparison to commercial alkyd resin paint coatings, formulations of the citronellol-functionalized hyperbranched materials blended with a commercial alkyd resin exhibited dramatic decreases of the blend viscosity when the HBP content was increased. The curing characteristics of the HBP/alkyd blend formulations were studied by dynamic mechanical analysis which revealed that the new coatings cured more quickly and produced tougher materials than otherwise identical coatings prepared from only the commercial alkyd resins.

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In this paper a modified algorithm is suggested for developing polynomial neural network (PNN) models. Optimal partial description (PD) modeling is introduced at each layer of the PNN expansion, a task accomplished using the orthogonal least squares (OLS) method. Based on the initial PD models determined by the polynomial order and the number of PD inputs, OLS selects the most significant regressor terms reducing the output error variance. The method produces PNN models exhibiting a high level of accuracy and superior generalization capabilities. Additionally, parsimonious models are obtained comprising a considerably smaller number of parameters compared to the ones generated by means of the conventional PNN algorithm. Three benchmark examples are elaborated, including modeling of the gas furnace process as well as the iris and wine classification problems. Extensive simulation results and comparison with other methods in the literature, demonstrate the effectiveness of the suggested modeling approach.

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Quasi-uniform grids of the sphere have become popular recently since they avoid parallel scaling bottle- necks associated with the poles of latitude–longitude grids. However quasi-uniform grids of the sphere are often non- orthogonal. A version of the C-grid for arbitrary non- orthogonal grids is presented which gives some of the mimetic properties of the orthogonal C-grid. Exact energy conservation is sacrificed for improved accuracy and the re- sulting scheme numerically conserves energy and potential enstrophy well. The non-orthogonal nature means that the scheme can be used on a cubed sphere. The advantage of the cubed sphere is that it does not admit the computa- tional modes of the hexagonal or triangular C-grids. On var- ious shallow-water test cases, the non-orthogonal scheme on a cubed sphere has accuracy less than or equal to the orthog- onal scheme on an orthogonal hexagonal icosahedron. A new diamond grid is presented consisting of quasi- uniform quadrilaterals which is more nearly orthogonal than the equal-angle cubed sphere but with otherwise similar properties. It performs better than the cubed sphere in ev- ery way and should be used instead in codes which allow a flexible grid structure.

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Cyclic voltammetry and ultraviolet−visible/infrared (UV−vis/IR) spectroelectrochemistry were used to study the cathodic electrochemical behavior of the osmium complexes mer-[OsIII(CO) (bpy)Cl3] (bpy = 2,2′-bipyridine) and trans(Cl)-[OsII(CO) (PrCN)(bpy)Cl2] at variable temperature in different solvents (tetrahydrofuran (THF), butyronitrile (PrCN), acetonitrile (MeCN)) and electrolytes (Bu4NPF6, Bu4NCl). The precursors can be reduced to mer-[OsII(CO) (bpy•−)Cl3]2− and trans(Cl)-[OsII(CO)(PrCN) (bpy•−)Cl2]−, respectively, which react rapidly at room temperature, losing the chloride ligands and forming Os(0) species. mer-[OsIII(CO) (bpy)Cl3] is reduced in THF to give ultimately an Os−Os-bonded polymer, probably [Os0(CO) (THF)-(bpy)]n, whereas in PrCN the well-soluble, probably mononuclear [Os0(CO) (PrCN)(bpy)], species is formed. The same products were observed for the 2 electron reduction of trans(Cl)-[OsII(CO)(PrCN) (bpy)Cl2] in both solvents. In MeCN, similar to THF, the[Os0(CO) (MeCN)(bpy)]n polymer is produced. It is noteworthy that the bpy ligand in mononuclear [Os0(CO) (PrCN)(bpy)] is reduced to the corresponding radical anion at a significantly less negative potential than it is in polymeric [Os0(CO) (THF)(bpy)]n: ΔE1/2 = 0.67 V. Major differences also exist in the IR spectra of the Os(0) species: the polymer shows a broad ν(CO) band at much smaller wavenumbers compared to the soluble Os(0) monomer that exhibits a characteristic ν(Pr-CN) band below 2200 cm−1 in addition to the intense and narrow ν(CO) absorption band. For the first time, in this work the M0-bpy(M = Ru, Os) mono- and dicarbonyl species soluble in PrCN have been formulated as a mononuclear complex. Density functional theory (DFT) and time-dependent-DFT calculations confirm the Os(0) oxidation state and suggest that [Os0(CO)(PrCN)(bpy)] is a square planar moiety. The reversible bpy-based reduction of [Os0(CO) (PrCN)(bpy)] triggers catalytic reduction of CO2 to CO and HCOO−.

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An efficient two-level model identification method aiming at maximising a model׳s generalisation capability is proposed for a large class of linear-in-the-parameters models from the observational data. A new elastic net orthogonal forward regression (ENOFR) algorithm is employed at the lower level to carry out simultaneous model selection and elastic net parameter estimation. The two regularisation parameters in the elastic net are optimised using a particle swarm optimisation (PSO) algorithm at the upper level by minimising the leave one out (LOO) mean square error (LOOMSE). There are two elements of original contributions. Firstly an elastic net cost function is defined and applied based on orthogonal decomposition, which facilitates the automatic model structure selection process with no need of using a predetermined error tolerance to terminate the forward selection process. Secondly it is shown that the LOOMSE based on the resultant ENOFR models can be analytically computed without actually splitting the data set, and the associate computation cost is small due to the ENOFR procedure. Consequently a fully automated procedure is achieved without resort to any other validation data set for iterative model evaluation. Illustrative examples are included to demonstrate the effectiveness of the new approaches.

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tMelt-polycondensation of succinic acid anhydride with oxazoline-based diol monomers gave hyper-branched polymers with carboxylicacids terminal groups.1H NMR and quantitative13C NMRspectroscopy coupled with DEPT-13513C NMR experiment showed high degrees of branching (over 60%).Esterification of the acid end groups by addition of citronellol at 160◦C produced novel white spirit solubleresins which were characterized by Fourier transform-infrared (FTIR) spectroscopy, gel permeation chro-matography (GPC), differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). Blendsof the new hyperbranched materials with commercial alkyd resins resulted in a dramatic, concentrationdependent drop in viscosity. Solvent-borne coatings were formulated containing the hyperbranchedpolymers. Dynamic mechanical analysis studies revealed that the air drying rates of the new coatingsystems were enhanced compared with identical formulations containing only commercial alkyd resins.

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An efficient data based-modeling algorithm for nonlinear system identification is introduced for radial basis function (RBF) neural networks with the aim of maximizing generalization capability based on the concept of leave-one-out (LOO) cross validation. Each of the RBF kernels has its own kernel width parameter and the basic idea is to optimize the multiple pairs of regularization parameters and kernel widths, each of which is associated with a kernel, one at a time within the orthogonal forward regression (OFR) procedure. Thus, each OFR step consists of one model term selection based on the LOO mean square error (LOOMSE), followed by the optimization of the associated kernel width and regularization parameter, also based on the LOOMSE. Since like our previous state-of-the-art local regularization assisted orthogonal least squares (LROLS) algorithm, the same LOOMSE is adopted for model selection, our proposed new OFR algorithm is also capable of producing a very sparse RBF model with excellent generalization performance. Unlike our previous LROLS algorithm which requires an additional iterative loop to optimize the regularization parameters as well as an additional procedure to optimize the kernel width, the proposed new OFR algorithm optimizes both the kernel widths and regularization parameters within the single OFR procedure, and consequently the required computational complexity is dramatically reduced. Nonlinear system identification examples are included to demonstrate the effectiveness of this new approach in comparison to the well-known approaches of support vector machine and least absolute shrinkage and selection operator as well as the LROLS algorithm.

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We show how two linearly independent vectors can be used to construct two orthogonal vectors of equal magnitude in a simple way. The proof that the constructed vectors are orthogonal and of equal magnitude is a good exercise for students studying properties of scalar and vector triple products. We then show how this result can be used to prove van Aubel's theorem that relates the two line segments joining the centres of squares on opposite sides of a plane quadrilateral.

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Liquid-liquid equilibrium experimental data for refined sunflower seed oil, artificially acidified with commercial oleic acid or commercial linoleic acid and a solvent (ethanol + water), were determined at 298.2 K. This set of experimental data and the experimental data from Cuevas et al.,(1) which were obtained from (283.2 to 333.2) K, for degummed sunflower seed oil-containing systems were correlated using NRTL and UNIQUAC models with temperature-dependent binary parameters. The deviation between experimental and calculated compositions presented average values of (1.13 and 1.41) % for NRTL and UNIQUAC equations, respectively, indicating that the models were able to correctly describe the behavior of compounds under different temperature and solvent hydration.

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This work presents liquid-liquid experimental data for systems composed of sunflower seed oil, ethanol and water from 10 to 60 degrees C. The influence of process variables (temperature (T) and water concentration in the solvent (W)) on both the solvent content present in the raffinate (S(RP)) and extract (S(EP)) phases and the partition of free fatty acids (k(2)) was evaluated using the response surface methodology, where flash calculations were performed for each trial using the UNIQUAC equation. Water content in the solvent was the most important factor on the responses of S(EP) and k(2). Additionally, statistical analysis showed that the S(RP) was predominantly affected by temperature factor for low water content in the solvent. (c) 2009 Elsevier Ltd. All rights reserved.

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The main goal of this work was to evaluate thermodynamic parameters of the soybean oil extraction process using ethanol as solvent. The experimental treatments were as follows: aqueous solvents with water contents varying from 0 to 13% (mass basis) and extraction temperature varying from 50 to 100 degrees C. The distribution coefficients of oil at equilibrium have been used to calculate enthalpy, entropy and free energy changes. The results indicate that oil extraction process with ethanol is feasible and spontaneous, mainly under higher temperature. Also, the influence of water level in the solvent and temperature were analysed using the response surface methodology (RSM). It can be noted that the extraction yield was highly affected by both independent variables. A joint analysis of thermodynamic and RSM indicates the optimal level of solvent hydration and temperature to perform the extraction process.

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We address the effect of solvation on the lowest electronic excitation energy of camphor. The solvents considered represent a large variation in-solvent polarity. We consider three conceptually different ways of accounting for the solvent using either an implicit, a discrete or an explicit solvation model. The solvatochromic shifts in polar solvents are found to be in good agreement with the experimental data for all three solvent models. However, both the implicit and discrete solvation models are less successful in predicting solvatochromic shifts for solvents of low polarity. The results presented suggest the importance of using explicit solvent molecules in the case of nonpolar solvents. (C) 2009 Elsevier B.V. All rights reserved.