Probing the polymer anomalous dynamics at solid/liquid interfaces at the single-molecule level

Non-Markovian Diffusion and Adsorption-Desorption Dynamics: Analytical and Numerical Results

The interplay of diffusion with phenomena like stochastic adsorption-desorption, absorption, and reaction-diffusion is essential for life and manifests in diverse natural contexts. Many factors must be considered, including geometry, dimensionality, and the interplay of diffusion across bulk and surfaces. To address this complexity, we investigate the diffusion process in heterogeneous media, focusing on non-Markovian diffusion. This process is limited by a surface interaction with the bulk, described by a specific boundary condition relevant to systems such as living cells and biomaterials. The surface can adsorb and desorb particles, and the adsorbed particles may undergo lateral diffusion before returning to the bulk. Different behaviors of the system are identified through analytical and numerical approaches.

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.

Tracking of Protein Adsorption on Poly(l-lactic acid) Film Surfaces: The Role of Molar Mass

Poly(l-lactic acid) (PLLA) has been extensively utilized as a biomaterial for various biomedical applications. The first and one of the most critical steps upon contact with biological fluids is the adsorption of proteins on the material's surface. Understanding the behavior of protein adsorption is vital for guiding the synthesis and preparation of PLLA for biomedical purposes. In this study, total internal reflection fluorescence microscopy was employed to investigate the adsorption of human serum albumin (HSA) on PLLA films with different molar masses. We found that molar mass affects HSA adsorption in such a way that it affects only the adsorption rate constants, but not the desorption rate constants. Additionally, we observed that HSA adsorption is spatially heterogeneous and exhibits many strong binding sites regardless of the molar mass of the PLLA films. We found that the free volume of PLLA plays a crucial role in determining its water uptake capacity and surface hydration, consequently impacting the adsorption of HSA.

Simulation Study on the Mechanism of Intermediate Subdiffusion of Diffusive Particles in Crowded Systems

The intermediate subdiffusion of diffusive particles in crowded systems is studied for two model systems: the continuous time random walk (CTRW) model and the obstruction-binding model. For the CTRW model with an arbitrarily given longest waiting time τmax, we find that the diffusive particle exhibits subdiffusion below τmax and recovers normal diffusion above τmax. For the obstruction-binding model with randomly distributed attractive obstacles, the diffusion of the diffusive particle is dependent on the binding energy and the density of obstacles. Interestingly, diffusion curves for different binding strengths can be overlapped by rescaling the simulation time, indicating that the diffusive particle in the obstruction-binding model can change from the intermediate subdiffusion to the normal diffusion at a long-term simulation scale. The results of the two model systems show that the diffusive particles only exhibit intermediate subdiffusion below the longest waiting time. Therefore, long timescale subdiffusion would only be observed in the CTRW model with an infinitely long waiting time and in the obstruction-binding model with an infinitely large binding strength.

Protein Desorption Kinetics Depends on the Timescale of Observation

The presence of so-called reversible and irreversible protein adsorption on solid surfaces is well documented in the literature and represents the basis for the development of nanoparticles and implant materials to control interactions in physiological environments. Here, using a series of complementary single-molecule tracking approaches appropriate for different timescales, we show that protein desorption kinetics is much more complex than the traditional reversible-irreversible binary picture. Instead, we find that the surface residence time distribution of adsorbed proteins transitions from power law to exponential behavior when measured over a large range of timescales (10^-2-10⁶ s). A comparison with macroscopic results obtained using a quartz crystal microbalance suggested that macroscopic measurements have generally failed to observe such nonequilibrium phenomena because they are obscured by ensemble-averaging effects. These findings provide new insights into the complex phenomena associated with protein adsorption and desorption.

A simulation study on the subdiffusion of polymer chains in crowded environments containing nanoparticles

Polymer chains in crowded environments often show subdiffusive behavior. We adopt molecular dynamics simulations to study the conditions for the subdiffusion of polymer chains in crowded environments containing randomly distributed, immobile, attractive nanoparticles (NPs). The attraction is strong enough to adsorb polymer chains on NPs. The results show that subdiffusion occurs at a low concentration of polymer chains (c_p). A transition from subdiffusion to normal diffusion is observed when c_p exceeds the transition concentration , which increases with increasing concentration of NPs while decreases with increasing size of NPs. The high concentration and small size of NPs exert a big effect on the subdiffusion of polymer chains. The subdiffusive behavior of polymer chains can be attributed to the strong adsorption of polymer chains on the attractive NPs. For the subdiffusion case, polymer chains are adsorbed strongly on multiple NPs, and they diffuse via the NP-exchange diffusion mechanism. However for the normal diffusion case, polymer chains are either free or weakly adsorbed on one or a few NPs, and they diffuse mainly via the adsorption-and-desorption diffusion mechanism.

Tracking of Nanoparticle Diffusion at a Liquid-Liquid Interface Adsorbed by Nonionic Surfactants

Emulsions stabilized by both nanoparticles and surfactants often display longer shelf life than those stabilized by nanoparticles or surfactants alone. Although numerous works have been conducted to understand the effect of nanoparticles and surfactants on the variation of interfacial tension, little is known about interfacial diffusion when both nanoparticles and surfactants are present at interfaces. In this work, we used single-particle fluorescence tracking to study the lateral diffusion of individual hydrophobic nanoparticles at hexane-glycerol interfaces adsorbed by different amounts of nonionic surfactants. When the surfactant concentration is over a threshold, we found that the nanoparticle diffusion exhibits a two-regime behavior involving short-time Brownian and the emergence of subdiffusive, non-Gaussian, and dynamically anticorrelated diffusion in the long lag time regime. A stepwise analysis rationalized diffusion in different lag time regimes, leading to a mechanistic interpretation regarding the two-regime behavior. These results could provide insight into the understanding of the synergistic effect for the surfactant-assistant Pickering emulsion.

Brownian Diffusion of Individual Janus Nanoparticles at Water/Oil Interfaces

Janus nanoparticles could exhibit a higher interfacial activity and adsorb stronger to fluid interfaces than homogeneous nanoparticles of similar sizes. However, little is known about the interfacial diffusion of Janus nanoparticles and how it compares to that of homogeneous ones. Here, we employed fluorescence correlation spectroscopy to study the lateral diffusion of ligand-grafted Janus nanoparticles adsorbed at water/oil interfaces. We found that the diffusion was significantly slower than that of homogeneous nanoparticles. We carried out dissipative particle dynamic simulations to study the mechanism of interfacial slowdown. Good agreement between experimental and simulation results has been obtained only provided that the flexibility of ligands grafted on the nanoparticle surface was taken into account. The polymeric ligands were deformed and oriented at an interface so that the effective radius of Janus nanoparticles is larger than the nominal one obtained by measuring the diffusion in bulk solution. These findings highlight further the critical importance of the ligands grafted on Janus nanoparticles for applications involving nanoparticle adsorption at an interface, such as oil recovery or two-dimensional self-assembly.

Three-Dimensional Bacterial Motions near a Surface Investigated by Digital Holographic Microscopy: Effect of Surface Stiffness

Surface stiffness plays a critical role in bacterial adhesion, but the mechanism is unclear since the bacterial motion before adhesion is overlooked. Herein, the three-dimensional (3D) motions of Escherichia coli and Pseudonomas sp. nov 776 onto poly(dimethylsiloxane) (PDMS) surfaces with varying stiffness before adhering were monitored by digital holographic microscopy (DHM). As Young's modulus (E) of the PDMS surface decreases from 278.1 to 3.4 MPa, the adhered E. coli and Pseudonomas sp. decrease in number by 40.4 and 34.9%, respectively. Atomic force microscopy (AFM) measurements show that the adhesion force of bacteria to the surface declines with the decreased surface stiffness. In contrast, a nontumbling mutant of adhered E. coli (HCB1414 with the adaptive function being partially deficient) decreases much less (by 18.4%). On the other hand, the tumble frequency (F_t) of E. coli HCB1 and flick frequency (F_f) of Pseudomonas sp. increase as the surface stiffness decreases, and the motion bias (B_θ) of Pseudomonas sp. also increases. These facts clearly indicate that the bacteria have adapted responses to the surface stiffness. RNA sequencing (RNA-seq) reveals that the downregulated Cph2 and CsrA as well as the upregulated GcvA of swimming E. coli HCB1 in bulk near the softer surface promote the bacterial motility.

Diffusive Escape of a Nanoparticle from a Porous Cavity

Narrow escape from confinement through a nanochannel is the critical step of complex transport processes including size-exclusion-based separations, oil and gas extraction from the microporous subsurface environment, and ribonucleic acid translocation through nuclear pore complex channels. While narrow escape has been studied using theoretical and computational methods, experimental quantification is rare because of the difficulty in confining a particle into a microscopic space through a nanoscale hole. Here, we studied narrow escape in the context of continuous nanoparticle diffusion within the liquid-filled void space of an ordered porous material. Specifically, we quantified the spatial dependence of nanoparticle motion and the sojourn times of individual particles in the interconnected confined cavities of a liquid-filled inverse opal film. We found that nanoparticle motion was inhibited near cavity walls and cavity escape was slower than predicted by existing theories and random-walk simulations. A combined computational-experimental analysis indicated that translocation through a nanochannel is barrier controlled rather than diffusion controlled.