The critical adsorption of self-avoiding polymer chain in a simple cubic lattice onto a flat surface is studied with Monte Carlo simulations. The dependence of number of surface contacts M on chain length N and polymer-surface interaction ϵ is investigated by a finite-size scaling approach. We estimate the critical adsorption point ϵc=0.291±0.002 and the exponent ϕ=0.54±0.01. The asymptotic behaviors M∝N for ϵ⪢ϵc and M∝N0 for ϵ⪡ϵc are also obtained from the finite-size scaling relation. We have also estimated the critical adsorption point by using Binder’s cumulant method as well as configurational properties.

The effect of the loading of nanoparticles on the glass transition temperature, T_g, of polymer nanocomposites is studied by using molecular dynamics simulations. T_g is estimated from the variation of system volume with temperature and the temperature-dependent diffusion of the polymer described by the Vogel–Fulcher–Tammann law. The estimated values of T_g from the two methods are consistent with each other. Results show that T_g can be regulated by changing the volume fraction of nanoparticles, f_NP. A novel shift in T_g is observed, that is, T_g increases with f_NP at f_NP < , while it decreases with increasing f_NP at f_NP > . The basic mechanism behind the novel shift in T_g is the competition between the attraction of nanoparticles towards polymer chains and the fast diffusion of nanoparticles. The increase in T_g at low f_NP is due to the attraction of nanoparticles, whereas the decrease in T_g at high f_NP is attributed to the fast diffusion of nanoparticles. The diffusion of the polymer above T_g is also investigated. The diffusion of the polymer decreases with increasing f_NP below and increases with f_NP above , in agreement with the variation of T_g.

The translocation of a bond fluctuation polymer through an interacting nanopore is studied using dynamic Monte Carlo simulation. A driving force F is applied only for monomers inside the pore. The influence of polymer-pore interaction on the scaling relation $\tau${}$\sim${}N$\alpha${} is studied for both unbiased and biased translocations, with $\tau${} the translocation time and N the polymer length. Results show that the exponent $\alpha${} is dependent on the polymer-pore interaction. For a noninteracting pore, we find $\alpha${}=2.48 for unbiased translocation and $\alpha${}=1.35 for strong biased translocation; for strong attraction, we find $\alpha${}=2.35 for unbiased translocation and $\alpha${}=1.22 for strong biased translocation. The unbiased translocation corresponds to the low-NF regime whereas the strong biased translocation corresponds to the high-NF regime.

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 T_g is increased by nanoparticles. Our results show that the effect of nanoparticles can be summarized as D = D₀[1 − exp(−α·ID/2R_g)] and T_g = T_g,0[1 − exp(−α·ID/2R_g)]⁻¹, with D₀ and T_g,0 being the diffusion coefficient and the glass transition temperature in the absence of nanoparticles, R_g 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.

The glass transition temperature (T_g) of polymer nanocomposites is dependent on the size of nanoparticles. The behaviors of the diffusion constant and relaxation time of polymer chains at a temperature above T_g also support the results of T_g.