Enhanced Luminescent Stability through Particle Interactions in Silicon Nanocrystal Aggregates.

Close-packed assemblies of ligand-passivated colloidal nanocrystals can exhibit enhanced photoluminescent stability, but the origin of this effect is unclear. Here, we use experiment, simulation, and ab initio computation to examine the influence of interparticle interactions on the photoluminescent stability of silicon nanocrystal aggregates. The time-dependent photoluminescence emitted by structures ranging in size from a single quantum dot to agglomerates of more than a thousand is compared with Monte Carlo simulations of noninteracting ensembles using measured single-particle blinking data as input. In contrast to the behavior typically exhibited by the metal chalcogenides, the measured photoluminescent stability shows an enhancement with respect to the noninteracting scenario with increasing aggregate size. We model this behavior using time-dependent density functional theory calculations of energy transfer between neighboring nanocrystals as a function of nanocrystal size, separation, and the presence of charge and/or surface-passivation defects. Our results suggest that rapid exciton transfer from "bright" nanocrystals to surface trap states in nearest-neighbors can efficiently fill such traps and enhance the stability of emission by promoting the radiative recombination of slowly diffusing excited electrons.

Ensemble brightening and enhanced quantum yield in size-purified silicon nanocrystals.

We report on the quantum yield, photoluminescence (PL) lifetime, and ensemble photoluminescent stability of highly monodisperse plasma-synthesized silicon nanocrystals (SiNCs) prepared though density-gradient ultracentrifugation in mixed organic solvents. Improved size uniformity leads to a reduction in PL line width and the emergence of entropic order in dry nanocrystal films. We find excellent agreement with the anticipated trends of quantum confinement in nanocrystalline silicon, with a solution quantum yield that is independent of nanocrystal size for the larger fractions but decreases dramatically with size for the smaller fractions. We also find a significant PL enhancement in films assembled from the fractions, and we use a combination of measurement, simulation, and modeling to link this "brightening" to a temporally enhanced quantum yield arising from SiNC interactions in ordered ensembles of monodisperse nanocrystals. Using an appropriate excitation scheme, we exploit this enhancement to achieve photostable emission.

Scattering intensity of bicontinuous microemulsions and sponge phases.

Monte Carlo simulations of dynamically triangulated surfaces of variable topology are used to investigate the scattering intensities of bicontinuous microemulsions. The bulk scattering intensity is shown to follow the Teubner-Strey expression. The domain size and the correlation length are extracted from the scattering peaks as a function of the bending rigidity, saddle-splay modulus, and surfactant density. The results are compared to earlier theories based on Ginzburg-Landau and Gaussian random field models. The ratio of the two length scales is shown to be well described by a linear combination of logarithmically renormalized bending rigidity and saddle-splay modulus with universal prefactors. This is in contrast to earlier theoretical predictions in which the scattering intensity is independent of the saddle-splay modulus. The equation of state, and the asymptotics of the bulk and film scattering intensities for high and low wave vectors are determined from simulations and compared with theoretical results.

Dynamics of thermally driven capillary waves for two-dimensional droplets.

Capillary waves have been observed in systems ranging from the surfaces of ordinary fluids to interfaces in biological membranes and have been one of the most studied areas in the physics of fluids. Recent advances in fluorescence microscopy and imaging enabled quantitative measurements of thermally driven capillary waves in lipid monolayers and bilayers, which resulted in accurate measurements of the line tension in monolayer domains. Even though there has been a considerable amount of work on the statics and dynamics of capillary waves in three dimensions, to the best of our knowledge, there is no detailed theoretical analysis for two-dimensional droplet morphologies. In this paper, we derive the dynamic correlation function for two-dimensional fluid droplets using linear response theory and verify our results using a novel particle-based simulation technique for binary mixtures.

Anterograde microtubule transport drives microtubule bending in LLC-PK1 epithelial cells.

Microtubules (MTs) have been proposed to act mechanically as compressive struts that resist both actomyosin contractile forces and their own polymerization forces to mechanically stabilize cell shape. To identify the origin of MT bending, we directly observed MT bending and F-actin transport dynamics in the periphery of LLC-PK1 epithelial cells. We found that F-actin is nearly stationary in these cells even as MTs are deformed, demonstrating that MT bending is not driven by actomyosin contractility. Furthermore, the inhibition of myosin II activity through the use of blebbistatin results in microtubules that are still dynamically bending. In addition, as determined by fluorescent speckle microscopy, MT polymerization rarely results, if ever, in bending. We suppressed dynamic instability using nocodazole, and we observed no qualitative change in the MT bending dynamics. Bending most often results from anterograde transport of proximal portions of the MT toward a nearly stationary distal tip. Interestingly, we found that in an in vitro kinesin-MT gliding assay, MTs buckle in a similar manner. To make quantitative comparisons, we measured curvature distributions of observed MTs and found that the in vivo and in vitro curvature distributions agree quantitatively. In addition, the measured MT curvature distribution is not Gaussian, as expected for a thermally driven semiflexible polymer, indicating that thermal forces play a minor role in MT bending. We conclude that many of the known mechanisms of MT deformation, such as polymerization and acto-myosin contractility, play an inconsequential role in mediating MT bending in LLC-PK1 cells and that MT-based molecular motors likely generate most of the strain energy stored in the MT lattice. The results argue against models in which MTs play a major mechanical role in LLC-PK1 cells and instead favor a model in which mechanical forces control the spatial distribution of the MT array.

Analysis of microtubule curvature.

The microtubule cytoskeleton in living cells generate and resist mechanical forces to mediate fundamental cell processes, including cell division and migration. Recent advances in digital fluorescence microscopy have enabled the direct observation of bending of individual microtubules in living cells, which has enabled quantitative estimation of the mechanical state of the microtubule array. Although a variety of mechanisms have been proposed, the precise origins of microtubule deformation in living cells remain largely obscure. To investigate these mechanisms and their relative importance in cellular processes, a method is needed to accurately quantify microtubule bending within living cells. Here we describe a method for quantification of bending, using digital fluorescence microscope images to estimate the distribution of curvature in the microtubule. Digital images of individual microtubules can be used to obtain a set of discrete x-y coordinates along the microtubule contour, which is then used to estimate the curvature distribution. Due to system noise and digitization error, the estimate will be inaccurate to some degree. To quantify the inaccuracy, a computational model is used to simulate both the bending of thermally driven microtubules and their observation by digital fluorescence microscopy. This allows for direct comparison between experimental and simulated images, a method which we call model convolution microscopy. We assess the accuracy of various methods and present a suitable method for estimating the curvature distribution for thermally driven semiflexible polymers. Finally, we discuss extensions of the method to quantify microtubule curvature in living cells.

Three-dimensional modeling of the brain's ECS by minimum configurational energy packing of fluid vesicles.

The extracellular space of the brain is the heterogeneous porous medium formed by the spaces between the brain cells. Diffusion in this interstitial space is the mechanism by which glucose and oxygen are delivered to the brain cells from the vascular system. It is also a medium for the transport of certain informational substances between the cells (called volume transmission), and for drug delivery. This work involves three-dimensional modeling of the extracellular space as void space in close-packed arrays of fluid membrane vesicles. These packings are generated by minimizing the configurational energy using a Monte Carlo procedure. Both regular and random packs of vesicles are considered. A random walk algorithm is then used to compute the geometric tortuosities, and the results are compared with published experimental data. For the random packings, it is found that although the absolute values for the tortuosities differ, the dependence of the tortuosity on pore volume fraction is very similar to that observed in experiment. The tortuosities we measure are larger than those computed in previous studies of packings of convex polytopes, and modeling improvements, which require higher resolution studies and an improved modeling of brain cell shapes and mechanical properties, could help resolve remaining discrepancies between model simulations and experiment. It is also shown that the specular reflection scheme is the appropriate technique for implementing zero-flux boundary conditions in random walk simulations commonly encountered in diffusion problems.

A combination of docking, QM/MM methods, and MD simulation for binding affinity estimation of metalloprotein ligands.

To alleviate the problems in the receptor-based design of metalloprotein ligands due to inadequacies in the force-field description of coordination bonds, a four-tier approach was devised. Representative ligand-metalloprotein interaction energies are obtained by subsequent application of (1) docking with metal-binding-guided selection of modes, (2) optimization of the ligand-metalloprotein complex geometry by combined quantum mechanics and molecular mechanics (QM/MM) methods, (3) conformational sampling of the complex with constrained metal bonds by force-field-based molecular dynamics (MD), and (4) a single point QM/MM energy calculation for the time-averaged structures. The QM/MM interaction energies are, in a linear combination with the desolvation-characterizing changes in the solvent-accessible surface areas, correlated with experimental data. The approach was applied to structural correlation of published binding free energies of a diverse set of 28 hydroxamate inhibitors to zinc-dependent matrix metalloproteinase 9 (MMP-9). Inclusion of steps 3 and 4 significantly improved both correlation and prediction. The two descriptors explained 90% of variance in inhibition constants of all 28 inhibitors, ranging from 0.08 to 349 nM, with the average unassigned error of 0.318 log units. The structural and energetic information obtained from the time-averaged MD simulation results helped understand the differences in binding modes of related compounds.

A comparison of the binding sites of matrix metalloproteinases and tumor necrosis factor-alpha converting enzyme: implications for selectivity.

MMPs and TACE (ADAM-17) assume independent, parallel, or opposite pathological roles in cancer, arthritis, and several other diseases. For therapeutic purposes, selective inhibition of individual MMPs and TACE is required in most cases due to distinct roles in diseases and the need to preserve activities in normal states. Toward this goal, we compared force-field interaction energies of five ubiquitous inhibitor atoms with flexible binding sites of 24 known human MMPs and TACE. The results indicate that MMPs 1-3, 10, 11, 13, 16, and 17 have at least one subsite very similar to TACE. S3 subsite is the best target for development of specific TACE inhibitors. Specific binding to TACE compared to most MMPs is promoted by placing a negatively charged ligand part at the bottom of S2 subsite, at the entrance of S1' subsite, or the part of S3' subsite that is close to catalytic zinc. Numerous other clues, consistent with available experimental data, are provided for design of selective inhibitors.

Processing multimode binding situations in simulation-based prediction of ligand-macromolecule affinities.

The linear response (LR) approximation and similar approaches belong to practical methods for estimation of ligand-receptor binding affinities. The approaches correlate experimental binding affinities with the changes upon binding of the ligand electrostatic and van der Waals energies and of solvation characteristics. These attributes are expressed as ensemble averages that are obtained by conformational sampling of the protein-ligand complex and of the free ligand by molecular dynamics or Monte Carlo simulations. We observed that outliers in the LR correlations occasionally exhibit major conformational changes of the complex during sampling. We treated the situation as a multimode binding case, for which the observed association constant is the sum of the partial association constants of individual states/modes. The resulting nonlinear expression for the binding affinities contains all the LR variables for individual modes that are scaled by the same two to four adjustable parameters as in the one-mode LR equation. The multimode method was applied to inhibitors of a matrix metalloproteinase, where this treatment improved the explained variance in experimental activity from 75% for the unimode case to about 85%. The predictive ability scaled accordingly, as verified by extensive cross-validations.

Simulation of ordered packed beds in chromatography.

A computer simulation of chromatographic dispersion in an ordered packed bed of spheres is conducted utilizing a detailed fluid flow profile provided by the Lattice Boltzmann technique. The ordered configurations of simple cubic, body-centered cubic, and face-centered cubic are employed in these simulations. It is found that zone broadening is less for the fcc structure than the sc and bcc structures and less than a random packed bed analyzed in a previous study in the low flow velocity region used for experimental chromatography. The factors which contribute to the performance of the ordered pack beds are analyzed in detail and found to be dependent both on the nearest surface to surface distance and on the distribution of velocities found in the various packing geometries. The pressure drops of the four configurations are compared and contrasted with the pressure drop from monolithic columns.

Advanced flicker spectroscopy of fluid membranes.

The bending elasticity of a fluid membrane is characterized by its modulus and spontaneous curvature. We present a new method, advanced flicker spectroscopy of giant nonspherical vesicles, which makes it possible to simultaneously measure both parameters for the first time. Our analysis is based on the generation of a large set of reference data from Monte Carlo simulations of randomly triangulated surfaces. As an example of the potential of the procedure, we monitor thermal trajectories of vesicle shapes and discuss the elastic response of zwitterionic membranes to transmembrane pH gradients. Our technique makes it possible to easily characterize membrane curvature as a function of environmental conditions.

Simulation of packed-bed chromatography utilizing high-resolution flow fields: comparison with models.

A computer simulation of a section of the interior region of a liquid chromatographic column is performed. The detailed fluid flow profile is provided from a microscopic calculation of low Reynolds number flow through a random packed bed of nonporous spherical particles. The fluid mechanical calculations are performed on a parallel processor computer utilizing the lattice Boltzmann technique. Convection, diffusion, and retention in this flow field are calculated using a stochastic-based algorithm. This computational scheme provides for the ability to reproduce the essential dynamics of the chromatographic process from the fundamental considerations of particle geometry, particle size, flow velocity, solute diffusion coefficient, and solute retention parameters when retention is utilized. The simulation data are fit to semiempirical models. The best agreement is found for the "coupling" model of Giddings and the four-parameter Knox model. These models are verified over a wide range of particle sizes and flow velocities at both low and high velocity. The simulations appear to capture the essential dynamics of the chromatographic flow process for non-dimensional flow velocities (Péclet number) less than 500. Since the same packing geometry is utilized for different particle size studies, the interpretation of the parameter estimates from these models can be extended to the physical column model. The simulations reported here agree very well with a number of experiments reported previously.