Single-layer graphene oxide (SLGO) is emerging as a new-generation membrane material for high-flux, high-selectivity water purification, owing to its favorable two-dimensional morphology that allows facile fabrication of ultrathin membranes with subnanometer interlayer channels. However, reliable and precise molecular sieving performance still necessarily depends on thick graphene oxide (GO) deposition that usually leads to low water flux. This trade-off between selectivity and flux significantly impedes the development of ultrathin GO membranes. In this work, we demonstrate that the selectivity/flux trade-off can be broken by self-assembly of SLGO via simple deposition rate control. We find GO membranes, prepared by slow deposition of SLGO flakes, exhibit considerably improved salt rejection, while counterintuitively having 2.5-4 times higher water flux than that of membranes prepared by fast deposition. This finding has extensive implications of designing/tuning interlayer nanostructure of ultrathin GO membranes by simply controlling SLGO deposition rate and thus may greatly facilitate their development for high flux, high selectivity water purification.

While electric fields primarily result in migration of charged species in electrolytic solutions, the solutions are dynamically heterogeneous. Solvent molecules within the solvation shells of the cation will be dragged by the field while free solvent molecules will not. We combine electrophoretic NMR measurements of ion and solvent velocities under applied electric fields with molecular dynamics simulations to interrogate different solvation motifs in a model liquid electrolyte. Measured values of the cation transference number (𝑡 ! " ) agree quantitatively with simulation-based predictions over a range of electrolyte concentrations. Solvent-cation interactions strongly influence the concentration-dependent behavior of 𝑡 ! " . We identify a critical concentration at which most of the solvent molecules lie within solvation shells of the cations. The dynamic heterogeneity of solvent molecules is minimized at this concentration where 𝑡 ! " is approximately equal to 0.

Understanding the distribution of ionic species in electrolytes is important for predicting the ion-transport properties. Here, a quantitative analysis of wide-angle X-ray scattering (WAXS) profiles was conducted for the first time on a series of mixtures of poly­(ethylene oxide) (PEO) and lithium bis­(trifluoromethanesulfonyl)­imide salt (LiTFSI), PEO/LiTFSI, as a function of salt concentration in the melt state. Abnormal scattering signatures were observed: while WAXS data showed a single peak (Peak 1) in the absence of salt, a second peak (Peak 0) appeared at lower scattering angles with added salt. Molecular dynamics simulations with the standard TraPPE-UA force field were used to uncover the molecular origins of the WAXS peaks. Qualitative agreement was found between the experimental and simulated scattering profiles. Simulations indicated that Peak 1 arises from correlations between EO segments as well as correlations between TFSI– ions and EO segments, while Peak 0 arises from correlations between neighboring TFSI– ions. There were, however, quantitative disagreements between experiment and simulations, which were resolved by the introduction of a charge rescaling factor, R f, to account for the polarization of ions and polymers. Simulations with charge rescaling predicted that the formation of anion-rich clusters occurs at a higher salt concentration than the emergence of Peak 0. While the WAXS data did not directly reflect the presence of anion-rich clusters, they provided a basis for more refined calculation of short-range correlations between ions, correlations that directly affect clustering and ion-transport properties such as ionic conductivities and transference numbers.