Tuning the Permeability of Dense Membranes by Shaping Nanoscale Potentials

Abstract

The permeability is one of the most fundamental transport properties in soft matter physics, material engineering, and nanofluidics. Here we report by means of Langevin simulations of ideal penetrants in a nanoscale membrane made of a fixed lattice of attractive interaction sites, how the permeability can be massively tuned, even minimized or maximized, by tailoring the potential energy landscape for the diffusing penetrants, depending on the membrane attraction, topology, and density. Supported by limiting scaling theories we demonstrate that the observed non-monotonic behavior and the occurrence of extreme values of the permeability is far from trivial and triggered by a strong anti-correlation and substantial (orders of magnitude) cancellation between penetrant partitioning and diffusivity, especially within dense and highly attractive membranes.

Tuning the selective permeability of polydisperse polymer networks

“…1a). As described in our previous studies on penetrant partitioning in regular polymer networks, 69 and permeability of highly ordered membranes, 87 we used LAMMPS software 115 with the stochastic Langevin integrator. The iteration time step dt = 5 Â 10 À3 t was used with the time units t ¼ ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi…”

“…The LJ energy e pp = 0.1k B T of the LJ potential U pp LJ is fixed such that the mutual penetrant interaction is essentially repulsive 69,87 (see also the positive second virial coefficient of the LJ interaction in Table S1 in the ESI, † and the following sections including Fig. 4 for details of the virial coefficients).…”

“…The intra-network interaction e nn is interpreted as a measure of solvent quality, 69,87,119 thereby controlling the network volume fraction f n = (N m + N xlink )v 0 /V n , where v 0 = ps 3 /6 is the monomer volume with diameter s = s nn = s np , and V n is the network volume. As discussed in previous works, 69,87,119 small/ high e nn corresponds to a good/poor solvent leading to a small/ high volume fraction, respectively. The network-penetrant interaction e np governs the strength of attraction between the polymers and the penetrants.…”

“…[100][101][102][103][104][105][106][107][108][109][110] In this context, for instance, we recently presented a simple coarse-grained (CG) simulation model of penetrant transport across a rigid immobile lattice-based membrane, pursuing a better comprehension of permeability, particularly in dense and attractive systems. 87 Despite the simplicity of that model, we demonstrated a very intricate behavior of permeability: it varied over many orders of magnitude, and could even be minimized or maximized by tailoring the potential energy landscape for the diffusing penetrants through small variations of membrane attraction, structure, and density. Supported by limited scaling theories, we showed that the possible occurrence of extreme values is far from trivial, being evoked by a strong anti-correlation and substantial (orders of magnitude) cancellation between penetrant partitioning and diffusivity, especially in the case of dense and highly attractive membranes.…”

“…For this, we consider a polydisperse tetra-functional network, i.e., each cross-linker connects four polymer strands, which have a polydisperse length distribution. As considered previously, 69,87 the system includes the network region and the bulk reservoir region, enabling a direct calculation of partitioning, diffusivity, and thus permeability. We focus on two important control parameters: the polymer network density f n (volume fraction), tuned by internal interactions, and the interaction between the network monomers and the penetrants.…”