Quantifying the hydrophobic effect. 3. A computer simulation-molecular-thermodynamic model for the micellization of ionic and zwitterionic surfactants in aqueous solution

In this article, the validity and accuracy of the CS-MT model introduced in article 1 for oil aggregates and in article 2 for nonionic surfactants is further evaluated by using it to model the micellization behavior of ionic and zwitterionic surfactants in aqueous solution. In the CS-MT model, two separate free-energy contributions to the hydrophobic driving force for micelle formation are computed using hydration data obtained from computer simulation: gdehydr, the free-energy change associated with dehydration, and ghydr, the change in the hydration free energy. To enable straightforward estimation of gdehydr and ghydr for ionic and zwitterionic surfactants, a number of simplifying approximations were made. Reasonable agreement between the CMCs predicted using the CS-MT model and the experimental CMCs was obtained for sodium dodecyl sulfate (SDS), dodecylphophocholine (DPC), cetyltrimethylammonium bromide (CTAB), two 3-hydroxy sulfonate surfactants (AOS-12 and AOS-16), and a homologous series of four DCNA bromide surfactants with a dimethylammonium head attached to a dodecyl alkyl tail and to an alkyl side chain of length CN, having the chemical formula C12H25CNH2N+1N(CH3)2Br, with N = 1 (DC1AB), 2 (DC2AB), 4 (DC4AB), and 6 (DC6AB). For six of these nine surfactants, the CMCs predicted using the CS-MT model are closer to the experimental CMCs than the CMCs predicted using the traditional molecular-thermodynamic (MT) model. For DC2AB, DC4AB, and DC6AB, which are the most structurally complex of the ionic surfactants modeled, the CMCs predicted using the CS-MT model are in remarkably good agreement with the experimental CMCs, and the CMCs predicted using the traditional MT model are quite inaccurate. Our results suggest that the CS-MT model accurately quantifies the hydrophobic driving force for micelle formation for ionic and zwitterionic surfactants in aqueous solution. For complex ionic and zwitterionic surfactants where it is difficult to accurately quantify the hydrophobic driving force for micelle formation using the traditional MT modeling approach, the CS-MT model represents a very promising alternative.     

Experimental and theoretical investigation of the micellar-assisted solubilization of ibuprofen in aqueous media

Surfactants can be used to increase the solubility of poorly soluble drugs in water and to increase drug bioavailability. In this article, the aqueous solubilization of the nonsteroidal, antiinflammatory drug ibuprofen is studied experimentally and theoretically in micellar solutions of anionic (sodium dodecyl sulfate, SDS), cationic (dodecyltrimethylammonium bromide, DTAB), and nonionic (dodecyl octa(ethylene oxide), C12E8) surfactants possessing the same hydrocarbon "tail" length but differing in their hydrophilic headgroups. We find that, for these three surfactants, the aqueous solubility of ibuprofen increases linearly with increasing surfactant concentration. In particular, we observed a 16-fold increase in the solubility of ibuprofen relative to that in the aqueous buffer upon the addition of 80 mM DTAB and 80 mM C12E8 but only a 5.5-fold solubility increase upon the addition of 80 mM SDS. The highest value of the molar solubilization capacity (chi) was obtained for DTAB (chi = 0.97), followed by C12E8 (chi = 0.72) and finally by SDS (chi = 0.23). A recently developed computer simulation/molecular-thermodynamic modeling approach was extended to predict theoretically the solubilization behavior of the three ibuprofen/surfactant mixtures considered. In this modeling approach, molecular-dynamics (MD) simulations were used to identify which portions of ibuprofen are exposed to water (hydrated) in a micellar environment by simulating a single ibuprofen molecule at an oil/water interface (modeling the micelle core/water interface). On the basis of this input, molecular-thermodynamic modeling was then implemented to predict (i) the micellar composition as a function of surfactant concentration, (ii) the aqueous solubility of ibuprofen as a function of surfactant concentration, and (iii) the molar solubilization capacity (chi). Our theoretical results on the solubility of ibuprofen in aqueous SDS and C12E8 surfactant solutions are in good agreement with the experimental data. The ibuprofen solubility in aqueous DTAB solutions was somewhat overpredicted because of challenges associated with accurately modeling the strong electrostatic interactions between the anionic ibuprofen and the cationic DTAB. Our results indicate that computer simulations of ibuprofen at a flat oil/water interface can be used to obtain accurate information about the hydrated and the unhydrated portions of ibuprofen in a micellar environment. This information can then be used as input to a molecular-thermodynamic model of self-assembly to successfully predict the aqueous solubilization behavior of ibuprofen in the three surfactant systems studied.     

Expected improvement in efficient global optimization through bootstrapped kriging

This article uses a sequentialized experimental design to select simulation input combinations for global optimization, based on Kriging (also called Gaussian process or spatial correlation modeling); this Kriging is used to analyze the input/output data of the simulation model (computer code). This design and analysis adapt the classic ??expected improvement?? (EI) in ??efficient global optimization?? (EGO) through the introduction of an improved estimator of the Kriging predictor variance; this estimator uses parametric bootstrapping. Classic EI and bootstrapped EI are compared through various test functions, including the six-hump camel-back and several Hartmann functions. These empirical results demonstrate that in some applications bootstrapped EI finds the global optimum faster than classic EI does; in general, however, the classic EI may be considered to be a robust global optimizer.     

The Improvement of Superconductivity in PbxBi2-xSr2CaCu2Oy

In this paper we present the results of recent studies on the improvement of superconductivity in Pb_xBi_2-xSr₂CaCu₂O_y single crystals by preventing impurities incorporation, employing ZrO₂ crucible for crystal growth and post annealing the as-grown crystals in vacuum or argon. It is realized that the superconductivity of as-grown crystals is improved.     

Application-driven sequential designs for simulation experiments: Kriging metamodelling

This paper proposes a novel method to select an experimental design for interpolation in simulation. Although the paper focuses on Kriging in deterministic simulation, the method also applies to other types of metamodels (besides Kriging), and to stochastic simulation. The paper focuses on simulations that require much computer time, so it is important to select a design with a small number of observations. The proposed method is therefore sequential. The novelty of the method is that it accounts for the specific input/output function of the particular simulation model at hand; that is, the method is application-driven or customized. This customization is achieved through cross-validation and jackknifing. The new method is tested through two academic applications, which demonstrate that the method indeed gives better results than either sequential designs based on an approximate Kriging prediction variance formula or designs with prefixed sample sizes.     

A new synthetic method for controlled polymerization using a microfluidic system

While many parallel synthesis methods developed by the pharmaceutical and life science communities are being applied to polymer synthesis, there remains a need to construct "libraries" of polymeric materials that explore a wider range of polymer structures with accuracy, flexibility, and rapid, often small, changes. We report the use of microfluidics to create an environment for continuous controlled radical polymerization. Varying either the flow rate or the relative concentrations of reactants (i.e., stoichiometry) controls the molecular properties of the products. Molecular variables, here molecular weight, can then be varied continuously. Well-defined materials with narrow molecular weight distributions are produced inside the microfluidic reactor and are available for processing, such as further mixing, deposition, or coating on surfaces. Preliminary kinetic data appear to agree well with literature values reported for larger-scale reactions.     

Raman spectroscopic monitoring of droplet polymerization in a microfluidic device

Microfluidic methodologies are becoming increasingly important for rapid formulation and screening of materials, and development of analytical tools for multiple sample screening is a critical step in achieving a combinatorial 'lab on a chip' approach. This work demonstrates the application of Raman spectroscopy for analysis of monomer composition and degree of conversion of methacrylate-based droplets in a microfluidic device. Droplet formation was conducted by flow focusing on the devices, and a gradient of component composition was created by varying the flow rates of the droplet-phase fluids into the microchannels. Raman data were collected using a fiber optic probe from a stationary array of the droplets/particles on the device, followed by partial least squares (PLS) calibration of the first derivative (1600 cm(-1) to 1550 cm(-1)) allowing successful measurement of monomer composition with a standard error of calibration (SEC) of +/-1.95% by volume. Following photopolymerization, the percentage of double bond conversion of the individual particles was calculated from the depletion of the normalized intensity of the C[double bond, length as m-dash]C stretching vibration at 1605 cm(-1). Raman data allowed accurate measurement of the decrease in double bond conversion as a function of increasing crosslinker concentration. The results from the research demonstrate that Raman spectroscopy is an effective, on-chip analytical tool for screening polymeric materials on the micrometre scale.     

Synthesis and characterization of tapered copolymer brushes via surface-initiated atom transfer radical copolymerization

Tapered copolymer brushes of methyl methacrylate (MMA) and 2-hydroxyethyl methacrylate (HEMA) were synthesized via surface-initiated atom transfer radical polymerization (ATRP) by gradual addition of HEMA to a reaction mixture that originally only had MMA as monomer. The copolymer brush grew linearly with polymerization time. The tapered copolymer brushes responded to selective solvent treatments. For the same tapered copolymer brush, pretreating the surface with methylene chloride made the surface more hydrophobic; pretreating the surface with methanol increased the surface hydrophilicity. This change in surface properties was reversible and considered to be caused by the solvent induced rearrangement of the polymer brushes, which is supported by atomic force microscopy images of the surface. Our work demonstrates that the properties of the tapered copolymer brush could be finely tuned by careful control of the composition profile.     

On the shape of bottle-brush macromolecules: systematic variation of architectural parameters

We measured the form factor of bottle-brush macromolecules under good solvent conditions with small-angle neutron scattering and static light scattering. The systems under investigation are brushes, synthesized via the grafting-from route, built from a poly(alkyl methacrylate) backbone to which poly(n-butyl acrylate) side chains are densely grafted. The aim of our work is to study how the systematic variation of structural parameters such as the side chain length and backbone length change the conformation of the polymer brushes in solution. All spectra can be consistently described by a model, considering the bottle-brush polymers as flexible rods with internal density fluctuations. Parameters discussed are (1) the contour length per main chain monomer l(b), (2) the fractal dimension of the side chains Ds, as well as (3) the fractal dimension D, and (4) the Kuhn length lambdak of the overall brush. l(b)=0.253+/-0.008 nm is found to be independent of the side chain length and equal to the value found for the bare main chain, indicating a strongly stretched conformation for the backbone due to the presence of the side chains. The fractal dimension of the side chains is determined to be Ds=1.75+/-0.07 which is very close to the value of 10.588 approximately 1.70 expected for a three-dimensional self-avoiding random walk (3D-SAW) under good solvent conditions. On larger length scales the overall brush appears to be a 3D-SAW itself (D=1.64+/-0.08) with a Kuhn-step length of lambdak=70+/-4 nm. The value is independent of the side chain length and 46 times larger than the Kuhn length of the bare backbone (lambdak=1.8+/-0.2 nm). The ratio of Kuhn length to brush diameter lambda(k)d>or=20 determines whether lyotropic behavior can be expected or not. Since longer side chains do not lead to more persistent structures, lambda(k)d decreases from 8 to 4 with increasing side chain length and lyotropic behavior becomes unlikely.