Graphene-based materials can have well-defined nanometer pores and can exhibit low frictional water flow inside them, making their properties of interest for filtration and separation. We investigate permeation through micrometer-thick laminates prepared by means of vacuum filtration of graphene oxide suspensions. The laminates are vacuum-tight in the dry state but, if immersed in water, act as molecular sieves, blocking all solutes with hydrated radii larger than 4.5 angstroms. Smaller ions permeate through the membranes at rates thousands of times faster than what is expected for simple diffusion. We believe that this behavior is caused by a network of nanocapillaries that open up in the hydrated state and accept only species that fit in. The anomalously fast permeation is attributed to a capillary-like high pressure acting on ions inside graphene capillaries.

Graphene oxide membranes show exceptional molecular permeation properties, with a promise for many applications. However, their use in ion sieving and desalination technologies is limited by a permeation cutoff of 9 Å, which is larger than hydrated ion diameters for common salts. The cutoff is determined by the interlayer spacing d 13.5 Å, typical for graphene oxide laminates that swell in water. Achieving smaller d for the laminates immersed in water has proved to be a challenge. Here we describe how to control d by physical confinement and achieve accurate and tuneable ion sieving. Membranes with d from  9.8 Å to 6.4 Å are demonstrated, providing the sieve size smaller than typical ions' hydrated diameters. In this regime, ion permeation is found to be thermally activated with energy barriers of 10-100 kJ/mol depending on d. Importantly, permeation rates decrease exponentially with decreasing the sieve size but water transport is weakly affected (by a factor of <2). The latter is attributed to a low barrier for water molecules entry and large slip lengths inside graphene capillaries. Building on these findings, we demonstrate a simple scalable method to obtain graphene-based membranes with limited swelling, which exhibit 97% rejection for NaCl.Selectively permeable membranes with sub-nm pores attract strong interest due to analogies with biological membranes and potential applications in water filtration, molecular separation and desalination [1][2][3][4][5][6][7][8] . Nanopores with sizes comparable to, or smaller than, the diameter D of hydrated ions are predicted to show enhanced ion selectivity 7,9-12 because of dehydration required to pass through such atomic-scale sieves. Despite extensive research on ion dehydration effects 3,7,9-13 , experimental investigation of the ion sieving controlled by dehydration has been limited because of difficulties in fabricating uniform membranes with well-defined sub-nm pores. The realisation of membranes with dehydration-assisted selectivity would be a significant step forward. So far, research into novel membranes has mostly focused on improving the water flux rather than ion selectivity. On the other hand, modelling of practically relevant filtration processes shows that an increase in water permeation rates above the rates currently achieved (2-3 L/m 2 ×h×bar) would not contribute greatly to the overall efficiency of desalination 8,14,15 . Alternative approaches based on higher water-ion selectivity may open new possibilities for improving filtration technologies, as the performance of state-of-the-art membranes is currently limited by the solution-diffusion mechanism, in which water molecules dissolve in the membrane material and then diffuses across the membrane 8 . Recently, carbon nanomaterials including carbon nanotubes (CNT)

In this article, we present coarse-grained potentials of ethylbenzene developed at 298 K and of amorphous polystyrene developed at 500 K by the pressure-corrected iterative Boltzmann inversion method. The potentials are optimized against the fully atomistic simulations until the radial distribution functions generated from coarse-grained simulations are consistent with atomistic simulations. In the coarse-grained polystyrene melts of different chain lengths, the Flory exponent of 0.58 is obtained for chain statistics. Both potentials of polystyrene and ethylbenzene are transferable over a broad range of temperature. The thermal expansion coefficients of the fully atomistic simulations are well reproduced in the coarse-grained models for both systems. However, for the case of ethylbenzene, the coarse-grained potential is temperature-dependent. The potential needs to be modified by a temperature factor of T / T 0 when it is transferred to other temperatures; T 0 = 298 K is the temperature at which the coarse-grained potential has been developed. For the case of polystyrene, the coarse-grained potential is temperature-independent. An optimum geometrical combination rule is proposed with the combination constant x = 0.4 for mutual interactions between the polystyrene monomer and ethylbenzene molecules in their mixtures at different composition and different temperature.

A key question for all coarse-graining methodologies is the degree of transferability of the resulting force field between various systems and thermodynamic conditions. Here we present a detailed study of the transferability over different thermodynamic states of a coarse-grained (CG) force field developed using the iterative Boltzmann inversion method. The force field is optimized against distribution functions obtained from atomistic simulations. We analyze the polymer case by investigating the bulk of polystyrene and polyamide-6,6 whose coarse-grained models differ in the chain length and in the number of atoms lumped in one bead. The effect of temperature and pressure on static, dynamic, and thermodynamic properties is tested by comparing systematically the coarse-grain results with the atomistic ones. We find that the CG model describing the polystyrene is transferable only in a narrow range of temperature and it fails in describing the change of the bulk density when temperature is 80K lower than the optimization one. Moreover the calculation of the self-diffusion coefficient shows that the CG model is characterized by a faster dynamics than the atomistic one and that it overestimates the isothermal compressibility. On the contrary, the polyamide-6,6 CG model turns out to be fully transferable between different thermodynamic conditions. The transferability is checked by changing either the temperature or the pressure of the simulation. We find that, in this case, the CG model is able to follow all the intra- and interstructural rearrangements caused by the temperature changes. In addition, while at low temperature the difference between the CG and atomistic dynamics is remarkable due to the presence of hydrogen bonds in the atomistic systems, for high temperatures, the speedup of the CG dynamics is strongly reduced, leading to a CG diffusion coefficient only six times bigger than the atomistic one. Moreover, the isothermal compressibility calculated at different temperatures agrees very well with the experimental one. We find that the polymer chain length does not affect the transferability of the force field and we attribute such transferability mainly to the finer model used in describing the polyamide-6,6 than the polystyrene.