Graphene oxide (GO) membranes with nanoconfined interlayer channels theoretically enable anomalous nanofluid transport for ultrahigh filtration performance. However, it is still a significant challenge for current GO laminar membranes to achieve ultrafast water permeation and high ion rejection simultaneously, because of the contradictory effect that exists between the water–membrane hydrogen-bond interaction and the ion–membrane electrostatic interaction. Here, we report a vertically aligned reduced GO (VARGO) membrane and propose an electropolarization strategy for regulating the interfacial hydrogen-bond and electrostatic interactions to concurrently enhance water permeation and ion rejection. The membrane with an electro-assistance of 2.5 V exhibited an ultrahigh water permeance of 684.9 L m −2 h −1 bar −1 , which is 1–2 orders of magnitude higher than those of reported GO-based laminar membranes. Meanwhile, the rejection rate of the membrane for NaCl was as high as 88.7%, outperforming most reported graphene-based membranes (typically 10 to 50%). Molecular dynamics simulations and density-function theory calculations revealed that the electropolarized VARGO nanochannels induced the well-ordered arrangement of nanoconfined water molecules, increasing the water transport efficiency, and thereby resulting in improved water permeation. Moreover, the electropolarization effect enhanced the surface electron density of the VARGO nanochannels and reinforced the interfacial attractive interactions between the cations in water and the oxygen groups and π-electrons on the VARGO surface, strengthening the ion-partitioning and Donnan effect for the electrostatic exclusion of ions. This finding offers an electroregulation strategy for membranes to achieve both high water permeability and high ion rejection performance.
In this paper, a novel algorithm is proposed for reducing a banded symmetric generalized eigenvalue problem to a banded symmetric standard eigenvalue problem, based on the sequentially semiseparable (SSS) matrix techniques. It is the first time that the SSS matrix techniques are used in such eigenvalue problems. The newly proposed algorithm only requires linear storage cost and O(n2) computation cost for matrices with dimension n, and is also potentially good for parallelism. Some experiments have been performed by using Matlab, and the accuracy and stability of algorithm are verified.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.