Finite-range viscoelastic subdiffusion in disordered systems with inclusion of inertial effects

TL;DR

This paper extends viscoelastic subdiffusion models to include inertial effects, explaining lipid subdiffusion in disordered biological membranes through various disorder models and matching experimental and simulation data.

Contribution

It introduces a modified model incorporating inertial effects into viscoelastic subdiffusion, explaining extended lipid subdiffusion beyond memory ranges in disordered systems.

Findings

Transient viscoelastic subdiffusion transitions to disorder-induced subdiffusion.

Subdiffusion exhibits a nonmonotonous, time-dependent power-law exponent.

Particle distributions are non-Gaussian and exponential power-shaped.

Abstract

This work justifies the paradigmatic importance of viscoelastic subdiffusion in random environments for cellular biological systems. This model displays several remarkable features, which makes it an attractive paradigm to explain the physical nature of biological subdiffusion. In particular, it combines viscoelasticity with distinct non-ergodic features. We extend this model to make it suitable for the subdiffusion of lipids in disordered biological membranes upon including the inertial effects. For lipids, the inertial effects occur in the range of picoseconds, and a power-law decaying viscoelastic memory extends over the range of several nanoseconds. Thus, in the absence of disorder, diffusion would become normal on a time scale beyond this memory range. However, both experimentally and in some molecular-dynamical simulations, the time range of lipid subdiffusion extends far beyond the viscoelastic memory range. We study three 1d models of correlated quenched Gaussian disorder to explain the puzzle: singular short-range (exponentially correlated), smooth short-range (Gaussian-correlated), and smooth long-range (power-law correlated) disorder. For a moderate disorder strength, transient viscoelastic subdiffusion changes into the subdiffusion caused by the randomness of the environment. It is characterized by a time-dependent power-law exponent of subdiffusion, which can show nonmonotonous behavior, in agreement with some recent molecular-dynamical simulations. Moreover, the spatial distribution of test particles in this disorder-dominated regime is shown to be a non-Gaussian, exponential power distribution, which also correlates well with molecular-dynamical findings and experiments. Furthermore, this subdiffusion is nonergodic with single-trajectory averages showing a broad scatter, in agreement with experimental observations for subdiffusion of various particles in living cells.