Dynamics in crowded environments: is non-Gaussian Brownian diffusion normal?

The dynamics of colloids and proteins in dense suspensions is of fundamental importance, from a standpoint of understanding the biophysics of proteins in the cytoplasm and for the many interesting physical phenomena in colloidal dispersions. Recent experiments and simulations have raised questions about our understanding of the dynamics of these systems. Experiments on vesicles in nematic fluids and colloids in an actin network have shown that the dynamics of particles can be "non-Gaussian"; that is, the self-part of the van Hove correlation function, Gs(r,t), is an exponential rather than Gaussian function of r, in regimes where the mean-square displacement is linear in t. It is usually assumed that a linear mean-square displacement implies a Gaussian Gs(r,t). In a different result, simulations of a mixture of proteins, aimed at mimicking the cytoplasm of Escherichia coli, have shown that hydrodynamic interactions (HI) play a key role in slowing down the dynamics of proteins in concentrated (relative to dilute) solutions. In this work, we study a simple system, a dilute tracer colloidal particle immersed in a concentrated solution of larger spheres, using simulations with and without HI. The simulations reproduce the non-Gaussian Brownian diffusion of the tracer, implying that this behavior is a general feature of colloidal dynamics and is a consequence of local heterogeneities on intermediate time scales. Although HI results in a lower diffusion constant, Gs(r,t) is very similar to and without HI, provided they are compared at the same value of the mean-square displacement.

Monte Carlo simulation studies on the effect of entropic attraction on the electric conductivity in polymer nano-composites.

The effect of non-conductive nano-particles on the electrical percolating network formation and the electrical conductivity of conductive nano-particles in polymer matrices is investigated using Monte Carlo simulations and a percolation theory. Both conductive and non-conductive nano-particles are modeled as spheres but with different diameters. Non-conductive nano-particles are up to four times bigger than conductive nano-particles. Equilibrated configurations for mixtures of nano-particles are obtained via Monte Carlo simulations and are used to estimate the probability (P) of forming an electrical percolating network and the percolation threshold conductive nano-particle volume fraction (phi(c)). As the volume fraction (phi(nc)) of non-conductive nano-particles increases, phi(c) decreases significantly, thus increasing the electrical conductivity. When non-conductive nano-particles mix with conductive nano-particles, they make the effective interaction energy W(r) between conductive nano-particles attractive, which should facilitate the formation of the electrical percolating network. For a given phi(nc), phi(c) increases slightly with an increase in the non-conductive nano-particle diameter (sigma(nc)). We also carry out simulations with non-conductive nano-particles of different structures and find that phi(c) is relatively insensitive to the non-conductive nano-particle structure.

Dynamics and mechanism of flame retardants in polymer matrixes: experiment and simulation.

We investigate the dynamics and the mechanism of flame retardants in polycarbonate matrixes to explore for a way of designing efficient and environment-friendly flame retardants. The high phosphorus content of organic phosphates has been considered as a requirement for efficient flame retardants. We show, however, that one can enhance the efficiency of flame retardants even with a relatively low phosphorus content by tuning the dynamics and the intermolecular interactions of flame retardants. This would enable one to design bulkier flame retardants that should be less volatile and less harmful in indoor environments. UL94 flammability tests indicate that even though the phosphorus content of 2,4-di-tert-butylphenyl diphenyl phosphate (DDP) is much smaller with two bulky tertiary butyl groups than that of triphenyl phosphate (TPP), DDP should be as efficient of a flame retardant as TPP, which is a widely used flame retardant. On the other hand, the 2-tert-butylphenyl diphenyl phosphate (2-tBuDP), with a lower phosphorus content than TPP but with a greater phosphorus content than DDP, is less efficient as a flame retardant than both DDP and TPP. Dynamic secondary ion mass spectrometry and molecular dynamics simulations reveal that the diffusion of DDP is slower by an order of magnitude at low temperature than that of TPP but becomes comparable to that of TPP at the ignition temperature. This implies that DDP should be much less volatile than TPP at low temperature, which is confirmed by thermogravimetric analysis. We also find from Fourier transform infrared spectroscopy that Fries rearrangement and char formation are suppressed more by DDP than by TPP. The low volatility and the suppressed char formation of DDP suggest that the enhanced flame retardancy of DDP should be attributed to its slow diffusivity at room temperature and yet sufficiently high diffusivity at high temperature.

One-step peptide backbone dissociations in negative-ion free radical initiated peptide sequencing mass spectrometry.

Peptide dissociation behavior in TEMPO (2,2,6,6-tetramethylpiperidine-1-oxyl)-based FRIPS (free radical initiated peptide sequencing) mass spectrometry was analyzed in both positive- and negative-ion modes for a number of peptides including angiotensin II, kinetensin, glycoprotein IIb fragment (296-306), des-Pro(2)-bradykinin, and ubiquitin tryptic fragment (43-48). In the positive mode, the ·Bz-C(O)-peptide radical species was produced exclusively at the initial collisional activation of o-TEMPO-Bz-C(O)-peptides, and two consecutive applications of collisional activation were needed to observe peptide backbone fragments. In contrast, in the negative-ion mode, a single application of collisional activation to o-TEMPO-Bz-C(O)-peptides produced extensive peptide backbone fragmentations as well as ·Bz-C(O)-peptide radical species. This result indicates that the duty cycle in the TEMPO-based FRIPS mass spectrometry can be reduced by one-half in the negative-ion mode. In addition, the fragment ions observed in the negative-ion experiments were mainly of the a-, c-, x-, and z-types, indicating that radical-driven tandem mass spectrometry was mainly responsible for the TEMPO-based FRIPS even with a single application of collisional activation. Furthermore, the survival fraction analysis of o-TEMPO-Bz-C(O)-peptides was made as a function of the applied normalized collision energy (NCE). This helped us to better understand the differences in FRIPS behavior between the positive- and negative-ion modes in terms of dissociation energetics. The duty-cycle improvement made in the present study provides a cornerstone for future research aiming to achieve a single-step FRIPS in the positive-ion mode.

Effect of polydispersity on diffusion in random obstacle matrices.

The dynamics of tracers in disordered matrices is of interest in a number of diverse areas of physics such as the biophysics of crowding in cells and cell membranes, and the diffusion of fluids in porous media. To a good approximation the matrices can be modeled as a collection of spatially frozen particles. In this Letter, we consider the effect of polydispersity (in size) of the matrix particles on the dynamics of tracers. We study a two dimensional system of hard disks diffusing in a sea of hard disk obstacles, for different values of the polydispersity of the matrix. We find that for a given average size and area fraction, the diffusion of tracers is very sensitive to the polydispersity. We calculate the pore percolation threshold using Apollonius diagrams. The diffusion constant, D, follows a scaling relation D~(φ(c)-φ(m))(µ-ß) for all values of the polydispersity, where φ(m) is the area fraction and φ(c) is the value of φ(m) at the percolation threshold.

Electrical percolation networks of carbon nanotubes in a shear flow.

The effect of shear on the electrical percolation network of carbon nanotube (CNT)-polymer composites is investigated using computer simulations. Configurations of CNTs in a simple shear, obtained by using Monte Carlo simulations, are used to locate the electrical percolation network of CNTs and calculate the electric conductivity. When exposed to the shear, CNTs align parallel to the shear direction and the electrical percolation threshold CNT concentration decreases. Meanwhile, after a certain period of the shear imposition above a critical shear rate, CNTs begin to form an aggregate and the percolating network of CNTs is broken, thus decreasing the electric conductivity significantly. We also construct quasiphase diagrams for the aggregate formation and the electrical percolation network formation to investigate the effect of the shear rate and CNT concentration.

The structure and the percolation behavior of a mixture of carbon nanotubes and molecular junctions: a Monte Carlo simulation study.

The structure and the percolation behavior of the composite of carbon nanotubes (CNTs), CNT molecular junctions and polymers are studied using Monte Carlo (MC) simulations. We model a CNT as a rigid rod composed of hard spheres. "X" and "Y" molecular junctions of CNTs are constructed by joining four and three segments of CNTs, respectively. The model system consists of CNTs mixed with either "X" or "Y" molecular junctions. The system is equilibrated using Monte Carlo simulations and the equilibrated configurations are used to locate the clusters of connected molecules via a recursive algorithm. The fraction (P(perc)) of configurations with a percolating cluster is then estimated for a given total volume fraction (phi(t)) of molecules. When P(perc) reaches 0.5, phi(t) of the system is considered a percolation threshold concentration (phi(c)). The percolation behavior is found to be sensitive to the aspect ratio of CNTs and the concentration and the shape of molecular junctions. phi(c) is decreased with an increase in the aspect ratio of CNTs. As the mole fraction of molecular junctions is increased, phi(c) is decreased significantly, which suggests that molecular junctions could enhance the electric conductivity of CNT-polymer composites. X junctions are found to construct a percolating network more effectively than Y junctions. More interestingly, even though molecular junctions change the percolation behavior significantly, the site-site pair correlation functions of CNTs hardly show any difference as the mole fraction of molecular junctions is increased. This implies that the percolation of CNTs is determined by the subtle many-body correlation of CNTs that is not captured by the site-site pair correlation functions.