Probing Non-Gaussianity in Confined Diffusion of Nanoparticles

Nanoparticle Diffusion in Crowded Polymer Nanocomposite Melts

This study examines nanoparticle diffusion in crowded polymer nanocomposites by diffusing small Al2O3 nanoparticles (NPs) in SiO2-loaded P2VP matrices. Time-of-flight secondary ion mass spectroscopy (ToF-SIMS) measures Al2O3 NP diffusion coefficients within a homogeneous PNC background of larger, immobile SiO2 NPs. By developing a geometric model for the average interparticle distance in a system with two NP sizes, we quantify nanocomposite confinement relative to the Al2O3 NP size with a bound layer. At low SiO2 concentrations, Al2O3 NP diffusion aligns with the neat polymer results. In more crowded nanocomposites with higher SiO2 concentrations where the interparticle distance approaches the size of the mobile Al2O3 NP, the 6.5 nm Al2O3 NPs diffuse faster than predicted by both core-shell and vehicular diffusion models. Relative to our previous studies of NPs diffusing into polymers, these findings demonstrate that the local environment in crowded systems significantly complicates NP diffusion behavior and the bound layer lifetimes.

Viscoelasticity of diverse biological samples quantified by Acoustic Force Microrheology (AFMR)

In the context of soft matter and cellular mechanics, microrheology - the use of micron-sized particles to probe the frequency-dependent viscoelastic response of materials - is widely used to shed light onto the mechanics and dynamics of molecular structures. Here we present the implementation of active microrheology in an Acoustic Force Spectroscopy setup (AFMR), which combines multiplexing with the possibility of probing a wide range of forces ( ~ pN to ~nN) and frequencies (0.01-100 Hz). To demonstrate the potential of this approach, we perform active microrheology on biological samples of increasing complexity and stiffness: collagen gels, red blood cells (RBCs), and human fibroblasts, spanning a viscoelastic modulus range of five orders of magnitude. We show that AFMR can successfully quantify viscoelastic properties by probing many beads with high single-particle precision and reproducibility. Finally, we demonstrate that AFMR to map local sample heterogeneities as well as detect cellular responses to drugs.

Universal scaling of the diffusivity of dendrimers in a semidilute solution of linear polymers

The static and dynamic properties of dendrimers in semidilute solutions of linear chains of comparable size are investigated using Brownian dynamics simulations. The radius of gyration and diffusivity of a wide variety of low generation dendrimers and linear chains in solution follow universal scaling laws independent of their topology. Analysis of the shape functions and internal density of dendrimers shows that they are more spherical than linear chains and have a dense core. At intermediate times, dendrimers become subdiffusive, with an exponent higher than that previously reported for nanoparticles in semidilute polymer solutions. The long-time diffusivity of dendrimers does not follow theoretical predictions for nanoparticles. We propose a new scaling law for the long-time diffusion coefficients of dendrimers which accounts for the fact that, unlike nanoparticles, dendrimers shrink with an increase in background solution concentration. Analysis of the properties of a special case of a higher functionality dendrimer shows a transition from polymer-like to nanoparticle-like behaviour.

What determines sub-diffusive behavior in crowded protein solutions?

The aqueous environment inside cells is densely packed. A typical cell has a macromolecular concentration in the range 90-450 g/L, with 5%-40% of its volume being occupied by macromolecules, resulting in what is known as macromolecular crowding. The space available for the free diffusion of metabolites and other macromolecules is thus greatly reduced, leading to so-called excluded volume effects. The slow diffusion of macromolecules under crowded conditions has been explained using transient complex formation. However, sub-diffusion noted in earlier works is not well characterized, particularly the role played by transient complex formation and excluded volume effects. We have used Brownian dynamics simulations to characterize the diffusion of chymotrypsin inhibitor 2 in protein solutions of bovine serum albumin and lysozyme at concentrations ranging from 50 to 300 g/L. The predicted changes in diffusion coefficient as a function of crowder concentration are consistent with NMR experiments. The sub-diffusive behavior observed in the sub-microsecond timescale can be explained in terms of a so-called cage effect, arising from rattling motion in a local molecular cage as a consequence of excluded volume effects. By selectively manipulating the nature of interactions between protein molecules, we determined that excluded volume effects induce sub-diffusive dynamics at sub-microsecond timescales. These findings may help to explain the diffusion-mediated effects of protein crowding on cellular processes.

Temperature-mediated diffusion of nanoparticles in semidilute polymer solutions

The temperature is often a critical factor affecting the diffusion of nanoparticles in complex physiological media, but its specific effects are still to be fully understood. Here, we constructed a temperature-regulated model of semidilute polymer solution and experimentally investigated the temperature-mediated diffusion of nanoparticles using the particle tracking method. By examining the ensemble-averaged mean square displacements (MSDs), we found that the MSD grows gradually as the temperature increases while the transition time from sublinear to linear stage in MSD decreases. Meanwhile, the temperature-dependent measured diffusivity of the nanoparticles shows an exponential growth. We revealed that these temperature-mediated changes are determined by the composite effect of the macroscale property of polymer solution and the microscale dynamics of polymer chain as well as nanoparticles. Furthermore, the measured non-Gaussian displacement probability distributions were found to exhibit non-Gaussian fat tails, and the tailed distribution is enhanced as the temperature increases. The non-Gaussianity was calculated and found to vary in the same trend with the tailed distribution, suggesting the occurrence of hopping events. This temperature-mediated non-Gaussian feature validates the recent theory of thermally induced activated hopping. Our results highlight the temperature-mediated changes in diffusive transport of nanoparticles in polymer solutions and may provide the possible strategy to improve drug delivery in physiological media.

Multilayered noise model for transport in complex environments

Transport in complex fluidic environments often exhibits transient subdiffusive dynamics accompanied by non-Gaussian probability density profiles featuring a nonmonotonic non-Gaussian parameter. Such properties cannot be adequately explained by the original theory of Brownian motion. Based on an extension of kinetic theory, this study introduces a chain of hierarchically coupled random walks approach that effectively captures all these intriguing characteristics. If the environment consists of a series of independent white noise sources, then the problem can be expressed as a system of hierarchically coupled Ornstein-Uhlenbech equations. Due to the linearity of the system, the most essential transport properties have a closed analytical form.

Triggering Gaussian-to-Exponential Transition of Displacement Distribution in Polymer Nanocomposites via Adsorption-Induced Trapping

In many disordered systems, the diffusion of classical particles is described by a displacement distribution P(x, t) that displays exponential tails instead of Gaussian statistics expected for Brownian motion. However, the experimental demonstration of control of this behavior by increasing the disorder strength has remained challenging. In this work, we explore the Gaussian-to-exponential transition by using diffusion of poly(ethylene glycol) (PEG) in attractive nanoparticle-polymer mixtures and controlling the volume fraction of the nanoparticles. In this work, we find "knobs", namely nanoparticle concentration and interaction, which enable the change in the shape of P(x,t) in a well-defined way. The Gaussian-to-exponential transition is consistent with a modified large deviation approach for a continuous time random walk and also with Monte Carlo simulations involving a microscopic model of polymer trapping via reversible adsorption to the nanoparticle surface. Our work bears significance in unraveling the fundamental physics behind the exponential decay of the displacement distribution at the tails, which is commonly observed in soft materials and nanomaterials.

Universal to nonuniversal transition of the statistics of rare events during the spread of random walks

Through numerous experiments that analyzed rare event statistics in heterogeneous media, it was discovered that in many cases the probability density function for particle position, P(X,t), exhibits a slower decay rate than the Gaussian function. Typically, the decay behavior is exponential, referred to as Laplace tails. However, many systems exhibit an even slower decay rate, such as power-law, log-normal, or stretched exponential. In this study, we utilize the continuous-time random walk method to investigate the rare events in particle hopping dynamics and find that the properties of the hop size distribution induce a critical transition between the Laplace universality of rare events and a more specific, slower decay of P(X,t). Specifically, when the hop size distribution decays slower than exponential, such as e^{-|x|^{β}} (β>1), the Laplace universality no longer applies, and the decay is specific, influenced by a few large events, rather than by the accumulation of many smaller events that give rise to Laplace tails.

Non-Gaussian Diffusion Near Surfaces

We study the diffusion of particles confined close to a single wall and in double-wall planar channel geometries where the local diffusivities depend on the distance to the boundaries. Displacement parallel to the walls is Brownian as characterized by its variance, but it is non-Gaussian having a nonzero fourth cumulant. Establishing a link with Taylor dispersion, we calculate the fourth cumulant and the tails of the displacement distribution for general diffusivity tensors along with potentials generated by either the walls or externally, for instance, gravity. Experimental and numerical studies of the motion of a colloid in the direction parallel to the wall give measured fourth cumulants which are correctly predicted by our theory. Interestingly, contrary to models of Brownian-yet-non-Gaussian diffusion, the tails of the displacement distribution are shown to be Gaussian rather than exponential. All together, our results provide additional tests and constraints for the inference of force maps and local transport properties near surfaces.

Hopping Behavior Mediates the Anomalous Confined Diffusion of Nanoparticles in Porous Hydrogels

Diffusion is an essential means of mass transport in porous materials such as hydrogels, which are appealing in various biomedical applications. Herein, we investigate the diffusive motion of nanoparticles (NPs) in porous hydrogels to provide a microscopic view of confined diffusion. Based on the mean square displacement from particle tracking experiments, we elucidate the anomalous diffusion dynamics of the embedded NPs and reveal the heterogeneous pore structures in hydrogels. The results demonstrate that diffusive NPs can intermittently escape from single pores through void connective pathways and exhibit non-Gaussian displacement probability distribution. We simulate this scenario using the Monte Carlo method and clarify the existence of hopping events in porous diffusion. The resultant anomalous diffusion can be fully depicted by combining the hopping mechanism and the hydrodynamic effect. Our results highlight the hopping behavior through the connective pathways and establish a hybrid model to predict NP transport in porous environments.

Heterogeneous Nanostructures Cause Anomalous Diffusion in Lipid Monolayers

The diffusion and mobility in biomembranes are crucial for various cell functions; however, the mechanisms involved in such processes remain ambiguous due to the complex membrane structures. Herein, we investigate how the heterogeneous nanostructures cause anomalous diffusion in dipalmitoylphosphatidylcholine (DPPC) monolayers. By identifying the existence of condensed nanodomains and clarifying their impact, our findings renew the understanding of the hydrodynamic description and the statistical feature of the diffusion in the monolayers. We find a universal characteristic of the multistage mean square displacement (MSD) with an intermediate crossover, signifying two membrane viscosities at different scales: the short-time scale describes the local fluidity and is independent of the nominal DPPC density, and the long-time scale represents the global continuous phase taking into account nanodomains and increases with DPPC density. The constant short-time viscosity reflects a dynamic equilibrium between the continuous fluid phase and the condensed nanodomains in the molecular scale. Notably, we observe an "anomalous yet Brownian" phenomenon exhibiting an unusual double-peaked displacement probability distribution (DPD), which is attributed to the net dipolar repulsive force from the heterogeneous nanodomains around the microdomains. The findings provide physical insights into the transport of membrane inclusions that underpin various biological functions and drug deliveries.

Structural relaxation dynamics of colloidal nanotrimers

By Molecular Dynamics simulation, we investigate the dynamics of isotropic fluids of colloidal nanotrimers whose interactions are described by varying the strength of attractive and repulsive terms of the Mie potential. To provide a consistent comparison between the systems described by different force fields, we determine the phase diagram and critical points of each system, characterize the morphology of high-density liquid phases at the same reduced temperature and density, and finally investigate their long-time relaxation dynamics. In particular, we detect an especially complex dynamics that reveals the existence of slow and fast nanotrimers and the resulting occurrence of non-Gaussianity, which develops at intermediate timescales. Deviations from Gaussianity are temporary and vanish within the timescales of the system's density fluctuations decay, when a Fickian-like diffusion regime is eventually observed.

Diffusion of polymer-grafted nanoparticles with dynamical fluctuations in unentangled polymer melts

The dynamics of polymer-grafted nanoparticles (PGNPs) in melts of unentangled linear chains were investigated by means of coarse-grained molecular dynamics simulations. The results demonstrated that the graft monomers closer to the particle surface relax more slowly than those farther away due to the constraint of the grafted surface and the confinement of the neighboring chains. Such heterogeneous relaxations of the surrounding environment would perturb the particle motion, making them fluctuating around their centers before they can diffuse through the melt. During such intermediate-time stage, the dynamics is subdiffusive while the distribution of particle displacements is Gaussian, which can be described by the popular fractional Brownian motion model. For the long-time Fickian diffusion, we found that the diffusivity D decreases with increasing grafting density Σ_g, grafted chain length N_g, and matrix chain length N_m. This is due to the fact that the diffusivity is controlled by the viscous drag of an effective core, consisting of the NP and the non-draining layer of graft segments, and that of the free-draining graft layer outside the "core". With increasing Σ_g, the PGNPs become harder with greater effective size and thinner free draining layer, resulting in a reduction in D. At extremely high Σ_g, the diffusivity can even be estimated by the diameter-renormalized Stokes-Einstein (SE) relation. With increasing N_g, both the effective core size and the thickness of the free-draining layer increase, leading to a reduction in diffusivity by D ∼ N-γg with 0.5 < γ < 1. Increasing N_m would lead to the enlargement of the effective core size but meanwhile result in the reduction of the free-draining layer thickness due to autophobic dewetting. The counteraction between these two opposite effects leads to only a slight reduction in the diffusivity, significantly different from the typical SE behavior where D ∼ N_m^-1. These findings bear significance in unraveling the fundamental physics of the anomalous dynamics of PGNPs in various polymers, including biological and synthetic.

Motion of an active particle with dynamical disorder

We propose a model for investigating the motion of a single active particle in a heterogeneous environment where the heterogeneity may arise due to crowding, conformational fluctuations and/or slow rearrangement of the surroundings. Describing the active particle in terms of the Ornstein-Uhlenbeck process (OUP) and incorporating heterogeneity in a thermal bath using two separate models, namely "diffusing diffusivity" and "switching diffusion", we explore the essential dynamical properties of the particle for its one-dimensional motion. In addition, we show how the dynamical behavior is controlled by dynamical variables associated with active noise such as strength and persistence time. Our model is relevant in the context of single particle dynamics in a crowded environment, driven by activity.

Hydrodynamics induce superdiffusive jumps of passive tracers along critical paths of random networks and colloidal gels

We present a numerical study on the effect of hydrodynamic interactions (HI) on the diffusion of inert point tracer particles in several fixed random structures. As expected, the diffusion is hampered by the extra hydrodynamic friction introduced by the obstacle network. However, a non-trivial effect due to HI appears in the analysis of the van-Hove displacement probability close to the percolation threshold, where tracers diffuse through critical fractal paths. We show that the tracer dynamics can be split up into short and long jumps, the latter being ruled by either exponential or Gaussian van Hove distribution tails. While at short time HI slow down the tracer diffusion, at long times, hydrodynamic interactions with the obstacles increase the probability of longer jumps, which circumvent the traps of the labyrinth more easily. Notably, the relation between the anomalous diffusion exponent and the fractal dimension of the critical (intricate) paths is greater than one, which implies that the long-time (long-jump) diffusion is mildly superdiffuse. A possible reason for such a hastening of the diffusion along the network corridors is the hydrodynamically induced mobility anisotropy, which favours displacements parallel to the walls, an effect which has already been experimentally observed in collagen gels.

Three-dimensional localization refinement and motion model parameter estimation for confined single particle tracking under low-light conditions

Confined diffusion is an important model for describing the motion of biological macromolecules moving in the crowded, three-dimensional environment of the cell. In this work we build upon the technique known as sequential Monte Carlo - expectation maximization (SMC-EM) to simultaneously localize the particle and estimate the motion model parameters from single particle tracking data. We extend SMC-EM to handle the double-helix point spread function (DH-PSF) for encoding the three-dimensional position of the particle in the two-dimensional image plane of the camera. SMC-EM can handle a wide range of camera models and here we assume the data was acquired using a scientific CMOS (sCMOS) camera. The sensitivity and speed of these cameras make them well suited for SPT, though the pixel-dependent nature of the camera noise presents a challenge for analysis. We focus on the low signal setting and compare our method through simulation to more standard approaches that use the paradigm of localize-then-estimate. To localize the particle under the standard paradigm, we use both a Gaussian fit and a maximum likelihood estimator (MLE) that accounts for both the DH-PSF and the pixel-dependent noise of the camera. Model estimation is then carried out either by fitting the model to the mean squared displacement (MSD) curve, or through an optimal estimation approach. Our results indicate that in the low signal regime, the SMC-EM approach outperforms the other methods while at higher signal-to-background levels, SMC-EM and the MLE-based methods perform equally well and both are significantly better than fitting to the MSD. In addition our results indicate that at smaller confinement lengths where the nonlinearities dominate the motion model, the SMC-EM approach is superior to the alternative approaches.

Computationally efficient application of Sequential Monte Carlo expectation maximization to confined single particle tracking

Single Particle Tracking (SPT) plays a crucial role in biophysics through its ability to reveal dynamic mechanisms and physical properties of biological macromolecules moving inside living cells. Such molecules are often subject to confinement and important information can be revealed by understanding the mobility of the molecules and the size of the domain they are restricted to. In previous work, we introduced a method known as Sequential Monte Carlo-Expectation Maximization (SMC-EM) to simultaneously estimate particle trajectories and model parameters. In this paper, we describe three modifications to SMC-EM aimed at improving its computationally efficiency and demonstrate it through analysis of simulated SPT data of a particle in a three dimensional confined environment. The first two modifications use approximation methods to reduce the complexity of the original motion and measurement models without significant loss of accuracy. The third modification replaces the previous SMC methods with a Gaussian particle filter combined with a backward simulation particle smoother, trading off some level of generality for improved computational performance. In addition, we take advantage of the improved efficiency to investigate the effect of data length on performance in localization and parameter estimation.

Subtle changes in crosslinking drive diverse anomalous transport characteristics in actin-microtubule networks

Anomalous diffusion in crowded and complex environments is widely studied due to its importance in intracellular transport, fluid rheology and materials engineering. Specifically, diffusion through the cytoskeleton, a network comprised of semiflexible actin filaments and rigid microtubules that interact both sterically and via crosslinking, plays a principal role in viral infection, vesicle transport and targeted drug delivery. Here, we elucidate the impact of crosslinking on particle diffusion in composites of actin and microtubules with actin-actin, microtubule-microtubule and actin-microtubule crosslinking. We analyze a suite of transport metrics by coupling single-particle tracking and differential dynamic microscopy. Using these complementary techniques, we find that particles display non-Gaussian and non-ergodic subdiffusion that is markedly enhanced by cytoskeletal crosslinking, which we attribute to suppressed microtubule mobility. However, the extent to which transport deviates from normal Brownian diffusion depends strongly on the crosslinking motif - with actin-microtubule crosslinking inducing the most pronounced anomalous characteristics. Our results reveal that subtle changes to actin-microtubule interactions can have complex impacts on particle diffusion in cytoskeleton composites, and suggest that a combination of reduced filament mobility and more variance in actin mobilities leads to more strongly anomalous particle transport.

Dynamical heterogeneity in the gelation process of a polymer solution with a lower critical solution temperature

The gelation of a hydrophobically modified hyaluronic acid aqueous solution which shows a lower critical solution temperature of about 25 °C was investigated by multi-particle tracking microrheology. The linear viscoelasticity of the gelling system is converted from the microrheological data. The critical gelling temperature T_gel = 36.3 °C was determined from the loss tangent by the Winter-Chambon criterion. The critical exponent n = 0.62 was determined from the shift factors of the time-cure superposition. The length scales of the dynamic heterogeneity of the gelling system were analyzed using a proposed framework where single-particle and multi-particle non-Gaussian parameters were compared. The length scale of the dynamic heterogeneous regions monotonically decreases during the gelation process, consistent with the nucleation-and-growth mechanism of phase separation. Distributions of local viscosity in the gelling system were extracted from the observed distributions of particle displacement as a time-dependent fingerprint of the dynamic heterogeneity of the gelling system. The results and analyzing methods proposed in the present work can be applied to other microrheological studies.

Interfacial behaviour of β-lactoglobulin aggregates at the oil-water interface studied using particle tracking and dilatational rheology

During processing, proteins are easily self-assembled into different aggregates, such as nanoparticles and fibrils. Protein aggregates exhibit a strong interfacial activity due to their morphologies and functional groups on the surface. Their interfacial structure and rheological properties at the oil-water interface have a significant effect on the stability and fat digestion of emulsions in food. In this study, β-lactoglobulin (β-lg) aggregates including β-lg nanoparticles (β-lg NP) and β-lg fibrils (β-lg F) were prepared in solution by controlling the heating temperature and pH, and their surface properties including the electric potential, hydrophobicity, and density of free thiol groups were characterized. The adsorption kinetics, interfacial rheology, and displacement by bile salts (BSs) of native β-lg and its aggregates at the oil (decane)/water interfaces were studied using particle tracking microrheology and dilatational rheology. From the movement of tracer particles at the interface, β-lg NP and β-lg F were found to adsorb faster than native β-lg, and they were found to form interfacial films with a marginally higher elasticity. During the process of protein adsorption, the films of β-lg and its aggregates are not uniform. In the process of protein displacement, β-lg NP has the strongest ability while native β-lg has the weakest ability to resist BS substitution, which is consistent with the results from in vitro digestion experiments. The present study reveals the microrheological behaviour of protein aggregates at the oil-water interface and demonstrates that β-lg thermal aggregates exhibit an excellent emulsification ability and can be used to control fat digestion. The study also illustrates the applicability of microrheological methods to the study of interfacial rheology and its complementarity with dilatational rheological methods.

Short-time dynamics of a tracer in an ideal gas

A small tagged particle immersed in a fluid exhibits Brownian motion and diffuses on a long timescale. Meanwhile, on a short timescale, the dynamics of the tagged particle cannot be simply described by the usual generalized Langevin equation with Gaussian noise, since the number of collisions between the tagged particle and fluid particles is rather small. On such a timescale, we should explicitly consider individual collision events between the tagged particle and the surrounding fluid particles. In this study we analyze the short-time dynamics of a tagged particle in an ideal gas, where we do not have static or hydrodynamic correlations between fluid particles. We perform event-driven hard-sphere simulations and show that the short-time dynamics of the tagged particle is correlated even under such an idealized situation. Namely, the velocity autocorrelation function becomes negative when the tagged particle is relatively light and the fluid density is relatively high. This result can be attributed to the dynamical correlation between collision events. To investigate the physical mechanism which causes the dynamical correlation, we analyze the correlation between successive collision events. We find that the tagged particle can collide with the same ideal-gas particle several times and such collisions cause a strong dynamical correlation for the velocity.

Estimation of the probability density function of random displacements from images

We introduce an image-based algorithm to find the probability density function (PDF) of particle displacements from a sequence of images. Conventionally methods based on cross correlation (CC) of image ensembles estimate the standard deviation of an assumed Gaussian PDF from the width of the CC peak. These methods are subject to limiting assumptions that the particle intensity profile and distribution of particle displacements are both Gaussian. Here, we introduce an approach to image-based probability estimation of displacement (iPED) without making any assumptions about the shape of particles' intensity profile or the PDF of the displacements. In addition, we provide a statistical convergence criterion for iPED to achieve an accurate estimate of the underlying PDF. We compare iPED's performance with the previous CC method for both Gaussian and non-Gaussian particle intensity profiles undergoing Gaussian or non-Gaussian processes. We validate iPED using synthetic images and show that it accurately resolves the PDF of particle displacements with no underlying assumptions. Finally, we demonstrate the application of iPED to real experimental data sets and evaluate its performance. In conclusion, this work presents a method for the estimation of the probability density function of random displacements from images. This method is generalized and independent of any assumptions about the underlying process and is applicable to any moving objects of any arbitrary shape.

Getting around the cell: physical transport in the intracellular world

Eukaryotic cells face the challenging task of transporting a variety of particles through the complex intracellular milieu in order to deliver, distribute, and mix the many components that support cell function. In this review, we explore the biological objectives and physical mechanisms of intracellular transport. Our focus is on cytoplasmic and intra-organelle transport at the whole-cell scale. We outline several key biological functions that depend on physically transporting components across the cell, including the delivery of secreted proteins, support of cell growth and repair, propagation of intracellular signals, establishment of organelle contacts, and spatial organization of metabolic gradients. We then review the three primary physical modes of transport in eukaryotic cells: diffusive motion, motor-driven transport, and advection by cytoplasmic flow. For each mechanism, we identify the main factors that determine speed and directionality. We also highlight the efficiency of each transport mode in fulfilling various key objectives of transport, such as particle mixing, directed delivery, and rapid target search. Taken together, the interplay of diffusion, molecular motors, and flows supports the intracellular transport needs that underlie a broad variety of biological phenomena.

Diffusion of Anisotropic Colloids in Periodic Arrays of Obstacles

Colloidal suspensions in confined geometries exhibit rich diffusion dynamics governed by particle shapes and particle-confinement interactions. Here, we propose a colloidal system, consisting of ellipsoids in periodic array of obstacles, to investigate the confined diffusion of anisotropic colloids. From the obstacle density-dependent diffusion, we discover a decoupling of translational and rotational diffusion in which only rotational motion is localized while translational motion remains diffusive. Moreover, by evaluating the probability distributions of displacements, we found Brownian but non-Gaussian diffusion behaviors with increasing the obstacle densities, which originates from the shape anisotropy of the colloid and the multiplicity of the local configurations of the ellipsoids with respect to the obstacle. Our results suggest that the shape anisotropy and spatial confinements play a vital role in the diffusion dynamics. It is important for understanding the transportations of anisotropic objects in complex environments.

Tracer Diffusion in Tightly-Meshed Homogeneous Polymer Networks: A Brownian Dynamics Simulation Study

We report Brownian dynamics simulations of tracer diffusion in regularly crosslinked polymer networks in order to elucidate the transport of a tracer particle in polymer networks. The average mesh size of homogeneous polymer networks is varied by assuming different degrees of crosslinking or swelling, and the size of a tracer particle is comparable to the average mesh size. Simulation results show subdiffusion of a tracer particle at intermediate time scales and normal diffusion at long times. In particular, the duration of subdiffusion is significantly prolonged as the average mesh size decreases with increasing degree of crosslinking, for which long-time diffusion occurs via the hopping processes of a tracer particle after undergoing rattling motions within a cage of the network mesh for an extended period of time. On the other hand, the cage dynamics and hopping process are less pronounced as the mesh size decreases with increasing polymer volume fractions. The interpretation is provided in terms of fluctuations in network mesh size: at higher polymer volume fractions, the network fluctuations are large enough to allow for collective, structural changes of network meshes, so that a tracer particle can escape from the cage, whereas, at lower volume fractions, the fluctuations are so small that a tracer particle remains trapped within the cage for a significant period of time before making infrequent jumps out of the cage. This work suggests that fluctuation in mesh size, as well as average mesh size itself, plays an important role in determining the dynamics of molecules and nanoparticles that are embedded in tightly meshed polymer networks.

Local Confinement Controls Diffusive Nanoparticle Dynamics in Semidilute Polyelectrolyte Solutions

We investigate the mobility of polystyrene particles ranging from 100 to 790 nm in diameter in dilute and semidilute sodium polystyrene sulfonate (NaPSS) solutions using fluorescence microscopy. We tune the polymer conformations by varying the ionic strength of the solution. The nanoparticle mean-squared displacements evolve linearly with time at all time scales, indicating Fickian diffusive dynamics. In solutions of high ionic strength, chains adopt a random walk conformation and particle dynamics couple to the bulk zero-shear rate viscosity, according to the Stokes-Einstein picture. In solutions of low ionic strength, however, particle dynamics nonmonotonically deviate from bulk predictions as polymer concentration increases and are not accurately predicted by the available models. These nonmonotonic dynamics directly correlate with the non-Gaussianity in distributions of particle displacements, suggesting the emergence of a local confining length scale as polyelectrolyte concentration increases.

First-principles nonequilibrium deterministic equation of motion of a Brownian particle and microscopic viscous drag

We present a first-principles thermodynamic approach to provide an alternative to the Langevin equation by identifying the deterministic (no stochastic component) microforce F_{k,BP} acting on a nonequilibrium Brownian particle (BP) in its kth microstate m_{k}. (The prefix "micro" refers to microstate quantities and carry a suffix k.) The deterministic new equation is easier to solve using basic calculus. Being oblivious to the second law, F_{k,BP} does not always oppose motion but viscous dissipation emerges upon ensemble averaging. The equipartition theorem is always satisfied. We reproduce well-known results of the BP in equilibrium. We explain how the microforce is obtained directly from the mutual potential energy of interaction beween the BP and the medium after we average it over the medium so we only have to consider the particles in the BP. Our approach goes beyond the phenomenological and equilibrium approach of Langevin and unifies nonequilibrium viscous dissipation from mesoscopic to macroscopic scales and provides new insight into Brownian motion beyond Langevin's and Einstein's formulation.

Large Deviations for Continuous Time Random Walks

Recently observation of random walks in complex environments like the cell and other glassy systems revealed that the spreading of particles, at its tails, follows a spatial exponential decay instead of the canonical Gaussian. We use the widely applicable continuous time random walk model and obtain the large deviation description of the propagator. Under mild conditions that the microscopic jump lengths distribution is decaying exponentially or faster i.e., Lévy like power law distributed jump lengths are excluded, and that the distribution of the waiting times is analytical for short waiting times, the spreading of particles follows an exponential decay at large distances, with a logarithmic correction. Here we show how anti-bunching of jump events reduces the effect, while bunching and intermittency enhances it. We employ exact solutions of the continuous time random walk model to test the large deviation theory.

Diffusion of Nanoparticles with Activated Hopping in Crowded Polymer Solutions

A long-distance hop of diffusive nanoparticles (NPs) in crowded environments was commonly considered unlikely, and its characteristics remain unclear. In this work, we experimentally identify the occurrence of the intermittent hops of large NPs in crowded entangled poly(ethylene oxide) (PEO) solutions, which are attributed to thermally induced activated hopping. We show that the diffusion of NPs in crowded solutions is considered as a superposition of the activated hopping and the reptation of the polymer solution. Such activated hopping becomes significant when either the PEO molecular weight is large enough or the NP size is relatively small. We reveal that the time-dependent non-Gaussianity of the NP diffusion is determined by the competition of the short-time relaxation of a polymer entanglement strand, the activated hopping, and the long-time reptation. We propose an exponential scaling law τ_hop/τ_e ∼ exp(d/d_t) to characterize the hopping time scale, suggesting a linear dependence of the activated hopping energy barrier on the dimensionless NP size. The activated hopping motion can only be observed between the onset time scale of the short-time relaxation of local entanglement strands and the termination time scale of the long-time relaxation. Our findings on activated hopping provide new insights into long-distance transportation of NPs in crowded biological environments, which is essential to the delivery and targeting of nanomedicines.

Generalization of Langevin Dynamics from Spatio-Temporal Dressed Dynamics Perspective

Understanding multiscale dynamics characteristics has been the holy grail in a broad range of scientific disciplines from physics, chemistry, to biology, and beyond. The seminal Langevin equation successfully unravels remarkable details of Brownian motion dynamics involving stochastic collisions from the fluidic medium. However, extraordinary phenomena beyond the scope of Langevin dynamics were observed to exhibit a series of multiscale dynamic features in recent years. Here, an explicit spatio-temporal coupled kernel is developed to provide the microscopic account for delicate dynamic coupling between particle and medium in the dressed dynamics perspective. This methodology is applied to investigate an aqueous solvation shell model with an explicit spatial boundary to illustrate the significance of spatial and temporal coupling, leading to a general temporal profile of dressed dynamics over 12 orders of magnitude in time In particular, the time-resolved viscosity is formulated to address the remarkable enhancement of viscosity measured by the liquid cell electron microscopy. The understanding of dressed dynamics processes will be greatly enriched by further studies on the detailed dynamics that manifests the microscopic inhomogeneity of medium.

Breakup Dynamics of Semi-dilute Polymer Solutions in a Microfluidic Flow-focusing Device

Droplet microfluidics involving non-Newtonian fluids is of great importance in both fundamental mechanisms and practical applications. In the present study, breakup dynamics in droplet generation of semi-dilute polymer solutions in a microfluidic flow-focusing device were experimentally investigated. We found that the filament thinning experiences a transition from a flow-driven to a capillary-driven regime, analogous to that of purely elastic fluids, while the highly elevated viscosity and complex network structures in the semi-dilute polymer solutions induce the breakup stages with a smaller power-law exponent and extensional relaxation time. It is elucidated that the elevated viscosity of the semi-dilute solution decelerates filament thinning in the flow-driven regime and the incomplete stretch of polymer molecules results in the smaller extensional relaxation time in the capillary-driven regime. These results extend the understanding of breakup dynamics in droplet generation of non-Newtonian fluids and provide guidance for microfluidic synthesis applications involving dense polymeric fluids.

Packets of Diffusing Particles Exhibit Universal Exponential Tails

Brownian motion is a Gaussian process described by the central limit theorem. However, exponential decays of the positional probability density function P(X,t) of packets of spreading random walkers, were observed in numerous situations that include glasses, live cells, and bacteria suspensions. We show that such exponential behavior is generally valid in a large class of problems of transport in random media. By extending the large deviations approach for a continuous time random walk, we uncover a general universal behavior for the decay of the density. It is found that fluctuations in the number of steps of the random walker, performed at finite time, lead to exponential decay (with logarithmic corrections) of P(X,t). This universal behavior also holds for short times, a fact that makes experimental observations readily achievable.

Unraveling Dynamic Transitions in Time-Resolved Biomolecular Motions by A Dressed Diffusion Model

Recent experimental data reveal the complexity of diffusion dynamics beyond the scope of classical Brownian dynamics. The particles exhibit diverse diffusive motions from the anomalous toward classical diffusion over a wide range of temporal scales. Here a dressed diffusion model is developed to account for non-Brownian phenomena. By coupling the particle dynamics with a local field, the dressed diffusion model generalizes the Langevin equation through coupled damping kernels and generates the salient feature of time-dependent diffusion dynamics reported in the experimental measurements of biomolecules. The dressed diffusion model provides one quantitative aspect for future endeavors in this rapid-growing field.

Quantification of spatio-temporal scales of dynamical heterogeneity of water near lipid membranes above supercooling

A hydrated 1,2-dimyristoyl-sn-glycero-3-phosphorylcholine (DMPC) lipid membrane is investigated using an all atom molecular dynamics simulation at 308 K to determine the physical sources of universal slow relaxations of hydration layers and length-scale of the spatially heterogeneous dynamics. Continuously residing interface water (IW) molecules hydrogen bonded to different moieties of lipid heads in the membrane are identified. The non-Gaussian parameters of all classes of IW molecules show a cross-over from cage vibration to translational diffusion. A significant non-Gaussianity is observed for the IW molecules exhibiting large length correlations in translational van Hove functions. Two time-scales for the ballistic motions and hopping transitions are obtained from the self intermediate scattering functions of the IW molecules with an additional long relaxation, which disappears for bulk water. The long relaxation time-scales for the IW molecules obtained from the self intermediate scattering functions are in good accordance with the hydrogen bond relaxation time-scales irrespective of the nature of the chemical confinement and the confinement lifetime. Employing a block analysis approach, the length-scale of dynamical heterogeneities is captured from a transition from non-Gaussianity to Gaussianity in van Hove correlation functions of the IW molecules. The heterogeneity length-scale is comparable to the wave-length of the small and weak undulations of the membrane calculated by Fourier transforms of lipid tilts. This opens up a new avenue towards a possible correlation between heterogeneity length-scale and membrane curvature more significant for rippled membranes. Thus, our analyses provide a measure towards the spatio-temporal scale of dynamical heterogeneity of confined water near membranes.

Transport of probe particles in a polymer network: effects of probe size, network rigidity and probe-polymer interaction

Fundamental understanding of the effect of microscopic parameters on the dynamics of probe particles in different complex environments has wide implications. Examples include diffusion of proteins in biological hydrogels, porous media, polymer matrix, etc. Here, we use extensive molecular dynamics simulations to investigate the dynamics of the probe particle in a polymer network on a diamond lattice, which provides substantial crowding to mimic the cellular environment. Our simulations show that the dynamics of the probe increasingly becomes restricted, non-Gaussian and subdiffusive on increasing the network rigidity, binding affinity and probe size. In addition, the velocity autocorrelation functions show negative dips owing to the viscoelasticity and caging due to the surrounding network. These observations go with the general experimental findings. Importantly, for a probe particle of size comparable to the mesh size, unrestricted motion engulfing large length scales has been observed. This happens with a more flexible polymer network, which is easily pushed by the bigger probe. On increasing the rigidity of the network, the bigger probe can not efficiently push the network and as a result the long tail disappears. Our study gives a general qualitative picture of the transport of probes in a gel-like medium, as encountered in different contexts.

Filament Rigidity Vies with Mesh Size in Determining Anomalous Diffusion in Cytoskeleton

The diffusion of microscopic particles through the cell, important to processes such as viral infection, gene delivery, and vesicle transport, is largely controlled by the complex cytoskeletal network, comprised of semiflexible actin filaments and rigid microtubules, that pervades the cytoplasm. By varying the relative concentrations of actin and microtubules, the cytoskeleton can display a host of different structural and dynamic properties that, in turn, impact the diffusion of particles through the composite network. Here, we couple single-particle tracking with differential dynamic microscopy to characterize the transport of microsphere tracers diffusing through composite in vitro networks with varying ratios of actin and microtubules. We analyze multiple complementary metrics for anomalous transport to show that particles exhibit anomalous subdiffusion in all networks, which our data suggest arises from caging by networks. Further, subdiffusive characteristics are markedly more pronounced in actin-rich networks, which exhibit similarly more prominent viscoelastic properties compared to microtubule-rich composites. While the smaller mesh size of actin-rich composites compared to microtubule-rich composites plays an important role in these results, the rigidity of the filaments comprising the network also influences the anomalous characteristics that we observe. Our results suggest that as microtubules in our composites are replaced with actin filaments, the decreasing filament rigidity competes with increasing network connectivity to drive anomalous transport.

Spatial Dependence of Non-Gaussian Diffusion of Nanoparticles in Free-Standing Thin Polymer Films

The addition of nanoparticles (NPs) to a free-standing polymer film affects the properties of the film such as viscosity and glass transition temperature. Recent experiments, for example, showed that the glass transition temperature of thin polymer films was dependent on how NPs were distributed within the polymer films. However, the spatial arrangement of NPs in free-standing polymer films and its effect on the diffusion of NPs and polymers remain elusive at a molecular level. In this study, we employ generic coarse-grained models for polymers and NPs and perform extensive molecular dynamics simulations to investigate the diffusion of polymers and NPs in free-standing thin polymer films. We find that small NPs are likely to stay at the interfacial region of the polymer film, while large NPs tend to stay at the center of the film. On the other hand, as the interaction between a NP and a monomer becomes more attractive, the NP is more likely to be placed at the film center. The diffusion of monomers slows down slightly as more NPs are added to the film. Interestingly, the NP diffusion is dependent strongly on the spatial arrangement of the NPs: NPs at the interfacial region diffuse faster and undergo more non-Gaussian diffusion than NPs at the film center, which implies that the interfacial region would be more mobile and dynamically heterogeneous than the film center. We also find that the mechanism for non-Gaussian diffusion of NPs at the film center differs from that at the interfacial region and that the NP diffusion would reflect the local viscosity of the polymer films.

Effects of Hydrodynamic Interactions on the Near-Surface Diffusion of Spheroidal Molecules

We investigated diffusion of spheroidal molecules near a planar surface, accounting for spatially dependent translational and rotational mobilities of molecules resulting from their hydrodynamic interactions with the plane. Rigid-body Brownian dynamics simulations of prolate ellipsoids of revolution of an axial ratio in the range of 1.5 to 3.0, suspended in a viscous fluid, with a no-slip flat boundary confining the suspension were employed. Mobility tensor matrices of molecules were evaluated as functions of spheroids' distance and orientation with respect to the plane. Hydrodynamic interactions with the surface lead to substantial changes of spheroids' translational diffusion coefficients both in the direction perpendicular and parallel to the plane when compared with the values characterizing the bulk diffusion. Moreover, the short-time translational diffusion of molecules, measured in the laboratory frame, both in an unbounded fluid and under the confinement, is non-Gaussian, with much larger deviations from Gaussianity observed in the latter case. In an unbounded fluid, distributions of translational displacements of molecules deviate from those expected for a simple Brownian motion as a result of shape anisotropy. In the presence of the plane, spheroids experience an additional anisotropic drag, and consequently, their mobilities depend on their positions and orientations. Therefore, anomalies in the short-time dynamics observed under confinement can be explained in terms of the so-called diffusing-diffusivity mechanism. Our findings have implications for understanding of a wide range of biological and technological processes that involve diffusion of anisotropic molecules near surfaces of natural and model cell membranes, biosensors and nanosensors, and electrodes.

Nanoparticle Diffusion within Dilute and Semidilute Xanthan Solutions

We measured the translation diffusion coefficient ( D) of nanoparticles within dilute and semidilute solutions of a semiflexible polymer, xanthan. Our results showed that for particle diameters ( d) of 5 and 10 nm, the obstruction theory can explain the concentration ( c) dependence of D in the dilute regime. Diffusion in semidilute solutions is better explained by additionally considering the modified Darcy flow with the hydrodynamic screening length varying according to κ ≈ c^-0.76_. The depletion effect is operative for larger particles ( d = 30 nm) within semidilute solutions. We used a scaling relation for the depletion layer thickness δ ≈ ξ^ν, where ξ is the static correlation length and the exponent ν ≈ 0.42 that can explain our data. This is in contrast with a flat surface, where the exponent is expected to be 1. Our results showed that in the situation, when the polymer network relaxation is much slower compared to the diffusive time-scale of particles, no single theory is capable to describe the concentration and size dependence of particle mobility.

Anomalous Dynamics of Water in Polyamide Matrix

Water in polymer matrixes is likely to show anomalous dynamics, a problem that has not been well understood yet. Here, we performed atomistic molecular dynamics simulations to study the water dynamics in a polyamide (PA) matrix, the bulk phase of well-known reverse osmosis membranes. For time-dependent ensemble average, water molecules experienced ballistic diffusion at a shorter time scale, followed by a crossover from subdiffusion to Brownian diffusion at a time scale ∼10 ns, and non-Gaussian diffusion, an indication of anomalous dynamics, sticks on even in the Brownian diffusion region. The anomalous dynamics mainly originates from two distinct motions including small-step continuous diffusion and jumping diffusion. The jumping motion has a mean length of 3.08 ± 0.31 Å and characteristic relaxation time of 0.218 ± 0.040 ns, which dominates the water diffusion in a fully hydrated PA matrix. It comprised low- and high-frequency jumps; the former is almost unchanged, and the latter remarkably increases with the increase of the hydration level. Surrounding neighbors of water strongly affect the jumping frequency, which exponentially or linearly decays with the increase in the number of atoms from the PA matrix. Although the PA matrix is flexible, associated with the water dynamics, the translocation of water is mainly through either tracing the position of neighboring water or jumping into the adjacent accommodation space.

A general phenomenological relation for the subdiffusive exponent of anomalous diffusion in disordered media

This work numerically investigates the diffusion of finite inert tracer particles in different types of fixed gels. The mean square displacement (MSD) of the tracers reveals a transition to subdiffusive motion MSD ∼ tα as soon as the accessible volume fraction p in the gel decreases from unity. Individual tracer dynamics reveals two types of particles in the gels: mobile tracers cross the system through percolating pores following subdiffusive dynamics MSDmob ∼ tαmob, while a fraction ptrap(p) of the particles remain trapped in finite pores. Below the void percolation threshold p < pc all the particles get trapped and α → 0. By separately studying both populations we find a simple phenomenological law for the mobile tracers αmob(p) ≈ a ln p + c where c ≈ 1 and a ∼ 0.2 depends on the gel type. On the other hand, a cluster-analysis of the gel accessible volume reveals a power law for the trapping probability ptrap ∼ (p/pc)-γ, with γ ≃ 2.9. This yields a prediction for the ensemble averaged subdiffusion exponent α = αmob(1 - ptrap). Our predictions are successfully validated against the different gels studied here and against numerical and experimental results in the literature (silica gels, polyacrylamide gels, flexible F-actin networks and in different random obstacles). Notably, the parameter a ∼ 0.2 presents small differences amongst all these cases, indicating the robustness of the proposed relation.