Dynamic Monte Carlo study on the polymer chain in random media filled with nanoparticles

Conformational and static properties of tagged chains in solvents: effect of chain connectivity in solvent molecules

Polymer chains immersed in different solvent molecules exhibit diverse properties due to multiple spatiotemporal scales and complex interactions. Using molecular dynamics simulations, we study the conformational and static properties of tagged chains in different solvent molecules. Two types of solvent molecules were examined: one type consisted of chain molecules connected by bonds, while the other type consisted of individual bead molecules without any bonds. The only difference between the two solvent molecules lies in the chain connectivity. Our results show a compression of the tagged chains with the addition of bead or chain molecules. Chain molecule confinement induces a stronger compression compared to bead molecule confinement. In chain solvent molecules, the tagged chain's radius of gyration reached a minimum at a monomer volume fraction of ∼0.3. Notably, the probability distributions of chain size remain unchanged at different solvent densities, irrespective of whether the solvent consists of beads or polymers. Furthermore, as solvent density increases, a crossover from a unimodal to a bimodal distribution of bond angles is observed, indicating the presence of both compressed and expanded regions within the chain. The effective monomer-solvent interaction is obtained by calculating the partial radial distribution function and the potential of the mean force. In chain solvents, the correlation hole effect results in a reduced number of nearest neighbors around tagged monomers compared to bead solvents. The calculation of pore size distribution reveals that the solvent nonhomogeneity induced by chain connectivity leads to a broader distribution of pore sizes and larger pore dimensions at low volume fractions. These findings provide a deeper understanding of the conformational behavior of polymer chains in different solvent environments.

Monte Carlo Simulation of Static and Dynamic Properties of Linear Polymer in a Crowded Environment

In this paper, we investigate the static and dynamic properties of linear polymer in the presence of obstacles. A Monte Carlo (MC) simulation method in two dimensions with a bond fluctuation model (BFM) was used to achieve this goal. To overcome the entropic barrier, we put the middle monomer of the polymer in the middle of the pore, which is placed between ordered and disordered obstacles. We probed the static properties of the polymer by calculating the mean square of the radius of gyration and the mean square end-to-end distance of the polymer, and we found that the scaling exponents of both the mean square end-to-end distance $〈R^2〉$ and the mean square radius of gyration $〈R_g^2〉$ as a function of the polymer length $N$ vary with the area fraction of crowding agents, $\varphi$ . The dynamic properties have also been studied by exploring the translocation of the polymer. Our current research shows that the escape time $\tau$ increases as $\varphi$ increases. Moreover, in the power-law relation of escape time $\tau$ as a function of polymer length $N$ , the scaling exponent ( $\alpha$ ) changes with $\varphi$ . Furthermore, the study has shown that the translocation of the polymer favors the disordered barriers.

A lattice kinetic Monte-Carlo method for simulating chromosomal dynamics and other (non-)equilibrium bio-assemblies

Biological assemblies in living cells such as chromosomes constitute large many-body systems that operate in a fluctuating, out-of-equilibrium environment. Since a brute-force simulation of that many degrees of freedom is currently computationally unfeasible, it is necessary to perform coarse-grained stochastic simulations. Here, we develop all tools necessary to write a lattice kinetic Monte-Carlo (LKMC) algorithm capable of performing such simulations. We discuss the validity and limits of this approach by testing the results of the simulation method in simple settings. Importantly, we illustrate how at large external forces Metropolis-Hastings kinetics violate the fluctuation-dissipation and steady-state fluctuation theorems and discuss better alternatives. Although this simulation framework is rather general, we demonstrate our approach using a DNA polymer with interacting SMC condensin loop-extruding enzymes. Specifically, we show that the scaling behavior of the loop-size distributions that we obtain in our LKMC simulations of this SMC-DNA system is consistent with that reported in other studies using Brownian dynamics simulations and analytic approaches. Moreover, we find that the irreversible dynamics of these enzymes under certain conditions result in frozen, sterically jammed polymer configurations, highlighting a potential pitfall of this approach.

Study on the interfacial properties of polymers around a nanoparticle

The interfacial properties of polymer chains on spherical nanoparticles are investigated using off-lattice Monte Carlo simulations.

Simulation on diffusivity and statistical size of polymer chains in polymer nanocomposites

The dynamical and conformational properties of polymer chains are affected significantly by strongly attractive nanoparticles. The adsorption of polymer chains on nanoparticles not only reduces the dynamics but also changes the conformation of polymer chains. For orderly distributed nanoparticles of size roughly the same as the radius of gyration of polymer chains, the variation of the diffusivity is highly related to that of the statistical size and can be explained mainly from the adsorption of polymers. In particular, both the polymer's size and diffusivity reach the minimum when the number of polymer chains matches the number of nanoparticles where polymer chains are mostly adsorbed on separate nanoparticles. The behavior of diffusivity can be explained from the cooperation of polymer adsorption and nanoparticle-exchange motion. Adsorption of the polymer chain slows down the diffusion, whereas the nanoparticle-exchange motion accelerates the diffusion of polymer chains.

Diffusivity and glass transition of polymer chains in polymer nanocomposites

The diffusivity and glass transition of polymer chains in polymer nanocomposites are studied by using dynamic Monte Carlo simulation. Nanoparticles are modeled as immobile and distributed in a cubic lattice in the system. The diffusion coefficient D of polymer chains is reduced, while the glass transition temperature Tg is increased by nanoparticles. Our results show that the effect of nanoparticles can be summarized as D = D0[1 - exp(-α·ID/2Rg)] and Tg = Tg,0[1 - exp(-α·ID/2Rg)]-1, with D0 and Tg,0 being the diffusion coefficient and the glass transition temperature in the absence of nanoparticles, Rg the radius of gyration of polymer chains, and ID the surface spacing between nearest-neighbor nanoparticles. The parameter α that governs the dynamics of polymer chains decreases with increasing nanoparticles' size or decreasing the temperature. Our results also show that smaller nanoparticles exert a stronger influence on the polymer dynamics at the same concentration of nanoparticles, whereas larger nanoparticles show a stronger effect at the same ID.

Monte Carlo Simulation Modeling of Nanoparticle-Polymer Cosuspensions

Creation of high-quality and novel polymer-particle nanocomposites to a large extent depends on understanding the behaviors of individual polymer chains and particles, especially at the mixing state in a liquid solvent. Simulations can help identify critical parameters and equations that govern the suspension behaviors. This study is the first attempt to understand the agglomeration processes of ZnO nanoparticle and poly(methyl methacrylate) polymer cosuspensions through a constant number Monte Carlo simulation. A modified Derjaguin-Landau-Verwey-Overbeek theory is used to describe the particle-particle interactions that lead to agglomeration. The average agglomerate size and number are measured as a function of suspension resting time, particle to polymer volume ratio, polymer chain length, and suspension drying. The agglomerate size increases persistently with the resting time and particle content increase, ranging from 1.2 μm for the 1 vol % particle content suspension to 4.6 μm for the 20 vol % particle content suspension after 30 min of suspension resting. The agglomerate size distribution for all of the particle contents follows a lognormal distribution. As the polymer chain length increases, agglomeration also becomes more severe. If drying is accounted for and thus the solids loading continually increases, the suspension becomes much more stable because of increases in viscosity and depletion stabilization.

Monte Carlo simulation on the dynamics of a semi-flexible polymer in the presence of nanoparticles

The dynamics of a semi-flexible polymer chain in the presence of periodically distributed nanoparticles is simulated by using off-lattice Monte Carlo simulations. For repulsive or weak attractive nanoparticles, the dynamics are slowed down monotonically by increasing the chain stiffness k_θ or decreasing the inter-particle distance d. For strong attractive nanoparticles, however, the dynamics show nonmonotonic behaviors with k_θ and d. An interesting result is that a stiff polymer may move faster than a flexible one. The underlying mechanism is that the nanoparticle's attraction is weakened by the chain stiffness. The nonmonotonic behavior of the polymer's dynamics with k_θ is explained by the competition between the weakening effect of the chain stiffness on the nanoparticle's attraction and the intrinsic effect of chain stiffness which reduces the dynamics of the polymer. In addition, the nonmonotonic behavior of the polymer's dynamics with d is explained by the competition between the nanoparticle-exchange motion of the polymer dominated at small d and the desorption-and-adsorption motion at large d. The excluded volume effect of the nanoparticles plays a more important role for stiffer polymers as the attraction of the nanoparticles is weakened by the chain stiffness.

Static and dynamic properties of a semiflexible polymer in a crowded environment with randomly distributed immobile nanoparticles

The dimensions, diffusivity, and relaxation of a polymer are dependent on the attraction strength and concentration of nanoparticles.

A study on the diffusivity of polymers in crowded environments with periodically distributed nanoparticles

Two novel diffusion behaviors of polymers at low temperature: a minimum at an intermediate inter-particle distance and oscillation with polymer length.

Translocation of polymers into crowded media with dynamic attractive nanoparticles

The translocation of polymers through a small pore into crowded media with dynamic attractive nanoparticles is simulated. Results show that the nanoparticles at the trans side can affect the translocation by influencing the free-energy landscape and the diffusion of polymers. Thus the translocation time τ is dependent on the polymer-nanoparticle attraction strength ɛ and the mobility of nanoparticles V. We observe a power-law relation of τ with V, but the exponent is dependent on ɛ and nanoparticle concentration. In addition, we find that the effect of attractive dynamic nanoparticles on the dynamics of polymers is dependent on the time scale. At a short time scale, subnormal diffusion is observed at strong attraction and the diffusion is slowed down by the dynamic nanoparticles. However, the diffusion of polymers is normal at a long time scale and the diffusion constant increases with the increase in V.

Polymer conformations in polymer nanocomposites containing spherical nanoparticles

We investigate the effect of various spherical nanoparticles on chain dimensions in polymer melts for high nanoparticle loading which is larger than the percolation threshold, using molecular dynamics simulations. We show that polymer chains are unperturbed by the presence of repulsive nanoparticles. In contrast polymer chains can be perturbed by the presence of attractive nanoparticles when the polymer radius of gyration is larger than the nanoparticle radius. At high nanoparticle loading, chains can be stretched and flattened by the nanoparticles, even oligomers can expand under the presence of attractive nanoparticles of very small size.

Equilibrium and dynamical properties of polymer chains in random medium filled with randomly distributed nano-sized fillers

The effect of randomly distributed nano-sized fillers on the equilibrium and dynamical properties of linear polymers is studied by using off-lattice Monte Carlo simulation.

Nonmonotonic diffusion of particles among larger attractive crowding spheres

We study the diffusive motion of particles among fixed spherical crowders. The diffusers interact with the crowders through a combination of a hard-core repulsion and a short-range attraction. The long-time effective diffusion coefficient of the diffusers is found to depend nonmonotonically on the strength of their attraction to the crowders. That is, for a given concentration of crowders, a weak attraction to the crowders enhances diffusion. We show that this counterintuitive fact can be understood in terms of the mesoscopic excess chemical potential landscape experienced by the diffuser. The roughness of this excess chemical potential landscape quantitatively captures the nonmonotonic dependence of the diffusion rate on the strength of crowder-diffuser attraction; thus, it is a purely static predictor of dynamic behavior. The mesoscopic view given here provides a unified explanation for enhanced diffusion effects that have been found in various systems of technological and biological interest.

Size and diffusion of polymer in media filled with periodic fillers

The effect of nanosized fillers on the equilibrium and dynamic properties of a single polymer chain has been studied by using off-lattice Monte Carlo (MC) simulation. Fillers of identical size are arranged periodically in the system and the Lennard-Jones (LJ) interaction is considered between the polymer and fillers. Our results show that the statistical size and dynamic diffusion properties of the polymer are not only dependent on the size of the polymer relative to the size of fillers and the distance between fillers, but also dependent on the interaction between the polymer and filler. The statistical size of the polymer can increase or decrease. Normal diffusion is always observed for long polymers and small fillers, whereas a transition from a desorbed state to an adsorbed state is observed for short polymers and large fillers. Finally, the size and diffusion of the polymer on an infinitely large surface are studied for comparison.