Aromatic Peptide‐Enabled Cation‐π Engineering in Lamellar Nanochannels for Enhanced Cation Selectivity

ABSTRACT Ion selectivity is central to nanochannel membranes for ion separation, molecular recognition, and energy conversion. However, conventional membranes primarily rely on electrostatic repulsion to regulate ion selectivity; the short‐range and weak nature limits high selectivity. Herein, a cation‐π engineering strategy is proposed by intercalating aromatic peptides (APs) into sub‐nanometer graphene oxide (GO) channels. Systematic tuning of the π‐system with phenylalanine (F)‐, tyrosine (Y)‐, and tryptophan (W)‐based peptides reveals a dual role of cation‐π interactions, involving electrostatic attraction and cation confinement. Specifically, the Y‐based AP‐intercalated GO membrane achieves a cation transference number of 0.614, representing a 16.95% improvement over GO membrane, which is attributed to electrostatic attraction of π‐system toward cations. Significantly, experiments and simulations reveal a nonmonotonic relation between selectivity and π‐system density, excessive π‐system density strengthens confinement and compromises selectivity. Moreover, the W‐based AP‐intercalated GO membrane exhibits a maximum power density of 20.11 W/m 2 under a 50‐fold NaCl gradient through an optimized selectivity‐permeability balance. Notably, the power density is increased to 29.99 W/m 2 after introducing Mg 2+ , which competitively occupies indole π‐sites to facilitate Na + transport. This work uncovers the role of cation‐π interactions in confined channels, offering a chemical design principle for selective ion‐channel membranes.

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Journal
Small
Published
2026-11-05
DOI
https://doi.org/10.1002/smll.76673
Primary Topic
Nanopore and Nanochannel Transport Studies
Type
article
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article

Aromatic Peptide‐Enabled Cation‐π Engineering in Lamellar Nanochannels for Enhanced Cation Selectivity

Huimin Sun, Mingchen Jia, Shan Dan Zhou, Bo Yu et al.
Small
Nanopore and Nanochannel Transport Studies
article

Aromatic Peptide‐Enabled Cation‐π Engineering in Lamellar Nanochannels for Enhanced Cation Selectivity

Huimin Sun, Mingchen Jia, Shan Dan Zhou, Bo Yu, Hailin Cong, Qianqian Feng, Beibei Fu, Xiangyu He
article en

Abstract

ABSTRACT Ion selectivity is central to nanochannel membranes for ion separation, molecular recognition, and energy conversion. However, conventional membranes primarily rely on electrostatic repulsion to regulate ion selectivity; the short‐range and weak nature limits high selectivity. Herein, a cation‐π engineering strategy is proposed by intercalating aromatic peptides (APs) into sub‐nanometer graphene oxide (GO) channels. Systematic tuning of the π‐system with phenylalanine (F)‐, tyrosine (Y)‐, and tryptophan (W)‐based peptides reveals a dual role of cation‐π interactions, involving electrostatic attraction and cation confinement. Specifically, the Y‐based AP‐intercalated GO membrane achieves a cation transference number of 0.614, representing a 16.95% improvement over GO membrane, which is attributed to electrostatic attraction of π‐system toward cations. Significantly, experiments and simulations reveal a nonmonotonic relation between selectivity and π‐system density, excessive π‐system density strengthens confinement and compromises selectivity. Moreover, the W‐based AP‐intercalated GO membrane exhibits a maximum power density of 20.11 W/m 2 under a 50‐fold NaCl gradient through an optimized selectivity‐permeability balance. Notably, the power density is increased to 29.99 W/m 2 after introducing Mg 2+ , which competitively occupies indole π‐sites to facilitate Na + transport. This work uncovers the role of cation‐π interactions in confined channels, offering a chemical design principle for selective ion‐channel membranes.

Small
Qingdao University (CN), Shandong University of Technology (CN)
Openalex Percentile: Top 26%
Nanopore and Nanochannel Transport Studies
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Aromatic Peptide‐Enabled Cation‐π Engineering in Lamellar Nanochannels for Enhanced Cation Selectivity — Huimin Sun, Mingchen Jia, et al. · Small (2026) | TGRS Research Map | TGRS