Structure and Dynamics of Spherical and Rodlike Alkyl Ethoxylate Surfactant Micelles Investigated Using NMR Relaxation and Atomistic Molecular Dynamics Simulations.

Predicting and controlling the properties of amphiphile aggregate mixtures require understanding the arrangements and dynamics of the constituent molecules. To explore these topics, we study molecular arrangements and dynamics in alkyl ethoxylate nonionic surfactant micelles by combining NMR relaxation measurements with large-scale atomistic molecular dynamics simulations. We calculate parameters that determine relaxation rates directly from simulated trajectories, without introducing specific functional forms to describe the dynamics. NMR relaxation rates, which depend on relative motions of interacting atom pairs, are influenced by wide distributions of dynamic time scales. We find that relative motions of neighboring atom pairs are rapid and liquidlike but are subject to structural constraints imposed by micelle morphology. Relative motions of distant atom pairs are slower than nearby atom pairs because changes in distances and angles are smaller when the moving atoms are further apart. Large numbers of atom pairs undergoing these slow relative motions contribute to predominantly negative cross-relaxation rates. For spherical micelles, but not for cylindrical micelles, cross-relaxation rates are positive only for surfactant tail atoms connected to the hydrophilic headgroup. This effect is related to the lower packing density of these atoms at the hydrophilic-hydrophobic boundary in spherical vs cylindrical arrangements, with correspondingly rapid and less constrained motion of atoms at the boundary.

Characterisation of heterogeneity and spatial autocorrelation in phase separating mixtures using Moran's I.

In complex colloidal systems, particle-poor regions can develop within particle-rich phases during sedimentation or creaming. These particle-poor regions are overlooked by 1D profiles, which are typically used to assess particle distributions in a sample. Alternative methods to visualise and quantify these regions are required to better understand phase separation, which is the focus of this paper. Magnetic resonance imaging has been used to monitor the development of compositional heterogeneity in a vesicle-polymer mixture undergoing creaming. T2 relaxation time maps were used to identify the distribution of vesicles, with vesicle-poor regions exhibiting higher T2 relaxation times than regions richer in vesicles. Phase separated structures displayed a range of different morphologies and a variety of image analysis methods, including first-order statistics, Fourier transformation, grey level co-occurrence matrices and Moran's I spatial autocorrelation, were used to characterise these structures, and quantify their heterogeneity. Of the image analysis techniques used, Moran's I was found to be the most effective at quantifying the degree and morphology of phase separation, providing a robust, quantitative measure by which comparisons can be made between a diverse range of systems undergoing phase separation. The sensitivity of Moran's I can be enhanced by the choice of weight matrices used.

Efficient removal of unwanted signals in NMR spectra using the filter diagonalization method.

It is often desirable to selectively remove corrupting or uninteresting signals from complex NMR spectra without disturbing overlapping or nearby signals. For biofluids in particular, removal of solvent and urea signals is important for retaining quantitative accuracy in NMR-based metabonomics. This article presents a novel algorithm for efficient filtering of unwanted signals using the filter diagonalization method (FDM). Unwanted signals are modeled in the time domain using FDM. This modeled signal is subtracted from the original free induction decay. The resulting corrected signal is then processed using established workflow. The algorithm is found to be reliable and fast. By eliminating large, broad, uninteresting signals, many spectra can be subjected to fully automated absolute value processing, allowing objective preparation of spectra for pattern recognition analysis.

Molecular factor analysis applied to collections of NMR spectra.

It is often useful to identify and quantify mixture components by analyzing collections of NMR spectra. Such collections arise in metabonomics and many other applications. Many mixtures studied by NMR can contain hundreds of compounds, and it is challenging to analyze the resulting complex spectra. We have approached the problem of separating signals from different molecules in complex mixtures by using self-modeling curve resolution as implemented by the alternating least-squares algorithm. Alternating least squares uses nonnegativity criteria to generate spectra and concentrations from a collection of mixture spectra. Compared to previous applications of alternating least squares, NMR spectra of complex mixtures possess unique features, such as large numbers of components and sample-to-sample variability in peak positions. To deal with these features, we developed a set of data preprocessing methods, and we made modifications to the alternating least-squares algorithm. We use the term "molecular factor analysis" to refer to the preprocessing and modified alternating least-squares methods. Molecular factor analysis was tested using an artificial data set and spectra from a metabonomics study. The results show that the tools can extract valuable information on sample composition from sets of NMR spectra.

Preparation and physical characterization of pure beta-carotene.

Pure all-trans beta-carotene has been prepared on the 10's of grams scale by isothermal Fractional Dissolution (FD) of commercial laboratory samples in tetrahydrofuran (THF). beta-Carotene purified in this way is black, with a faint brownish tinge. The electronic spectra of black samples extend into the near infrared, with end-absorption past 750 nm. Black samples react directly with dioxygen under mild conditions to yield the familiar orange or red powders. Pure beta-carotene rigorously obeys Beer's Law in octane over the entire UV-Vis spectral range, while commercial laboratory samples and recrystallized samples do not. NMR self-diffusion coefficient data demonstrate that beta-carotene exists as simple molecular solutions in octane and toluene. The anomalously high crystallinity of beta-carotene can be attributed (from analysis using molecular mechanics) to the facts that: (1) the number of theoretically possible conformers of beta-carotene is extremely small, and (2) only a small fraction of these (ca. 12%, or 127) may actually exist in fluid phases.

Generalized correlation NMR spectroscopy.

The use of generalized correlation analysis (Noda, I. Appl. Spectrosc. 1993, 47, 1329-1336) for processing two-dimensional arrays of NMR data is described. This analysis produces complex two-dimensional spectra whose cross-peak intensities are related to correlations in the responses of pairs of signals to systematically incremented perturbations. The technique extends and generalizes the applicability of two-dimensional NMR by allowing model-independent analysis of nonperiodic signals as well as model-dependent analysis of such signals. When applied to diffusion-ordered NMR data, the processing scheme produces two-dimensional output spectra having two frequency axes. Relative diffusion coefficients are encoded in the signs and intensities of the cross-peaks. Key properties of the resulting spectra are model-independent, so the approach provides an alternative to traditional DOSY processing and offers advantages for data sets that do not provide pure exponential or Gaussian response curves. When data do conform well to a known response function, the technique provides a method for extracting descriptors in a two-dimensional plot having one axis corresponding to the descriptor and the other axis corresponding to the usual chemical shift scale. Finally, the technique may be used to identify differences in the response functions of closely related samples, generating a one-dimensional spectrum with signals at frequencies whose response functions differ between two samples.