A complete classification of shock waves in a van der Waals fluid is undertaken. This is in order to gain a theoretical understanding of those shock-related phenomena as observed in real fluids which cannot be accounted for by the ideal gas model. These relate to admissibility of rarefaction shock waves, shock-splitting phenomena, and shock-induced phase transitions. The crucial role played by the nature of the gaseous state before the shock (the unperturbed state), and how it affects the features of the shock wave are elucidated. A full description is given of the characteristics of shock waves propagating in a van der Waals fluid. The strength of these shock waves may range from weak to strong. The study is carried out by means of the theory of hyperbolic systems supported by numerical calculations.

Particulate matter (PM) is a primary contributor to air pollution, which is a serious threat to humans. It remains challenging to develop “green” high-performance air filters. Bio-based fibers as air-filtration materials are drawing much more attention. In this work, the first demonstration of applying absolutely ionic nanofibers derived from renewable phenylalanine methyl ester hydrochloride to produce high-performance air filters is successfully shown by employing a simple and convenient in situ ionic self-assembly approach. These bio-based filters exhibit exceptional comprehensive PM filtration performance, where the average PM removal efficiencies are above 99.5% and the pressure drops are 5 Pa resulting in record high quality factor (QF) values above 1 Pa⁻¹. Quantum-chemistry calculations were performed to evaluate the surface properties of the ionic fibers. The devised amino acid-based PM filter may be used as a high-efficiency “green” filter.

We reveal significant combined roles of chirality, anisotropic interactions and spatial confinement in regulating the collective behavior of active matter systems.

The anomalous diffusion dynamics of an active particle in polymer solutions is studied based on a Langevin Brownian dynamics simulation. Firstly, the mean-square displacement (MSD) is investigated under various system parameters of active force F_a, probe size σ_a, polymer volume fraction ϕ and polymer chain length N. A very novel transition between superdiffusion and subdiffusion is observed with varying F_a and ϕ, owing to the activity and crowding competition effect. The two anomalous diffusion regimes are identified in the parameter space diagram. The increment of the MSD under activity is examined on intermediate time scales, which manifests a power law relation with the particle's dynamical persistence length L, i.e., ΔMSD = 2L^m, where the exponent m decreases with ϕ. Secondly, we explicitly evaluate the long-time diffusion coefficients D⁰ _a in a pure solvent and D_a in polymer solutions. The dependence of relative diffusivity D_a/D⁰ _a on volume fraction ϕ reproduces the well-known Phillies' equation exp(−κϕ^μ). The fitting parameters show μ ≃ 1, but κ apparently increases with activity. More importantly, our simulation justifies a multi-length scaling relation in a very similar form to that for passive probes, depending on simple structural parameters of the probe–polymer system. With the aid of an activation energy model, we find a counterintuitive activity–crowding coupling effect: activity enhances the effective viscosity experienced by the probe and thus strengthens the crowding-induced slowing of diffusion.

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.