The diffusion of nanoparticles (NPs) in polymer solutions is studied by a combination of a mesoscale simulation method, multiparticle collision dynamics (MPCD), and molecular dynamics (MD) simulations. We investigate the long-time diffusion coefficient D as well as the subdiffusive behavior in the intermediate time region. The dependencies of both D and subdiffusion factor α on NP size and polymer concentration, respectively, are explicitly calculated. Particular attention is paid to the role of hydrodynamic interaction (HI) in the NP diffusion dynamics. Our simulation results show that the long-time diffusion coefficients satisfy perfectly the scaling relation found by experimental observations. Meanwhile, the subdiffusive factor decreases with the increase in polymer concentration but is of little relevance to the NP size. By parallel simulations with and without HI, we reveal that HI will generally enhance D, while the enhancement effect is non-monotonous with increasing polymer concentration, and it becomes most pronounced at semidilute concentrations. With the aid of a scaling law based on the diffusive activation energy model, we understand that HI affects diffusion through decreasing the diffusive activation energy on the one hand while increasing the effective diffusion size on the other. In addition, HI will certainly influence the subdiffusive behavior of the NP, leading to a larger subdiffusion exponent.

In the present work, we propose a new scaling form for the rotational diffusion coefficient of molecular probes in semi-dilute polymer solutions, based on a theoretical study. The mean-field theory for depletion effect and semi-empirical scaling equation for the macroscopic viscosity of polymer solutions are properly incorporated to specify the space-dependent concentration and viscosity profiles in the vicinity of the probe surface. Following the scheme of classical fluid mechanics, we numerically evaluate the shear torque exerted on the probes, which then allows us to further calculate the rotational diffusion coefficient Dr. Particular attention is given to the scaling behavior of the retardation factor Rrot ≡ Dr0/Dr with Dr0 being the diffusion coefficient in pure solvent. We find that Rrot has little relevance to the macroscopic viscosity of the polymer solution, while it can be well featured by the characteristic length scale rh/δ, i.e. the ratio between the hydrodynamic radius of the probe rh and the depletion thickness δ. Correspondingly, we obtain a novel scaling form for the rotational retardation factor, following Rrot = exp[a(rh/δ)b] with rather robust parameters of a ≃ 0.51 and b ≃ 0.56. We apply the theory to an extensive calculation for various probes in specific polymer solutions of poly(ethylene glycol) (PEG) and dextran. Our theoretical results show good agreements with the experimental data, and clearly demonstrate the validity of the new scaling form. In addition, the difference of the scaling behavior between translational and rotational diffusions is clarified, from which we conclude that the depletion effect plays a more significant role on the local rotational diffusion rather than the long-range translation diffusion.

Understanding the diffusion of proteins in polymer solutions is of ubiquitous importance for modeling processes in vivo. Here, we present a theoretical framework to analyze the decoupling of translational and rotational diffusion of globular proteins in semidilute polymer solutions. The protein is modeled as a spherical particle with an effective hydrodynamic radius, enveloped by a depletion layer. On the basis of the scaling formula of macroscopic viscosity for polymer solutions as well as the mean-field theory for the depletion effect, we specify the space-dependent viscosity profile in the depletion zone. Following the scheme of classical fluid mechanics, the hydrodynamic drag force as well as torque exerted to the protein can be numerically evaluated, which then allows us to obtain the translational and rotational diffusion coefficients. We have applied our model to study the diffusion of proteins in two particular polymer solution systems, i.e., poly(ethylene glycol) (PEG) and dextran. Strikingly, our theoretical results can reproduce the experimental results quantitatively very well, and fully reproduce the decoupling between translational and rotational diffusion observed in the experiments. In addition, our model facilitates insights into how the effective hydrodynamic radius of the protein changes with polymer systems. We found that the effective hydrodynamic radius of proteins in PEG solutions is nearly the same as that in pure water, indicating PEG induces preferential hydration, while, in dextran solutions, it is generally enhanced due to the stronger attractive interaction between protein and dextran molecules.

By means of a stochastic model suggested in this paper for the systems with local non-equilibrium excited thermal fluctuations, the famous Shannon entropy is extended to include the heat conduction processes controlled externally by boundary constraints of constant temperature gradients at two sides. Meanwhile, using the description of master equation for the continuous Markov processes a balance equation of stochastic entropy production valid for one dimension gaseous heat conduction systems with high values of Prandtl number has been also established. Based on it, a general expression for both the stochastic entropy production and the entropy production of fluctuations have been further deduced by the Ω-expansions. In this formalism, all kinds of stochastic contributions to the dissipation from the non-equilibrium thermal fluctuation and internal noise turn explicit.

A stochastic model of chemical reaction-heat conduction-diffusion for a one-dimensional gaseous system under Dirichlet or zero-fluxes boundary conditions is proposed in this paper. Based on this model, we extend the theory of the broadening exponent of critical fluctuations to cover the chemical reaction-heat conduction coupling systems as an asymptotic property of the corresponding Markovian master equation (ME), and establish a valid stochastic thermodynamics for such systems. As an illustration, the non-isothermal and inhomogeneous Schlögl model is explicitly studied. Through an order analysis of the contributions from both the drift and diffusion to the evolution of the probability distribution in the corresponding Fokker-Planck equation(FPE) in the approach to bifurcation, we have identified the critical transition rule for the broadening exponent of the fluctuations due to the coupling between chemical reaction and heat conduction. It turns out that the dissipation induced by the critical fluctuations reaches a deterministic level, leading to a thermodynamic effect on the nonequilibrium physico-chemical processes.