Order-in-disordered ultrathin carbon nanostructure with nitrogen-rich defects bridged by pseudographitic domains for high-performance ion capture

Mingxing Liang, Yifan Ren, Jun Cui, Xiaochen Zhang, Siyang Xing, Jingjing Lei, Mengyao He, Haijiao Xie, Libo Deng, Fei Yu and Jie Ma ()
Additional contact information
Mingxing Liang: Tongji University
Yifan Ren: Tongji University
Jun Cui: Beijing University of Chemical Technology
Xiaochen Zhang: Tongji University
Siyang Xing: Tongji University
Jingjing Lei: Tongji University
Mengyao He: Shenzhen University
Haijiao Xie: Hangzhou Yanqu Information Technology Co., Ltd.
Libo Deng: Shenzhen University
Fei Yu: Shanghai Ocean University
Jie Ma: Tongji University

Nature Communications, 2024, vol. 15, issue 1, 1-13

Abstract: Abstract Carbon materials with defect-rich structure are highly demanded for various electrochemical scenes, but encountering a conflict with the deteriorative intrinsic conductivity. Herein, we build a highway-mediated nanoarchitecture that consists of the ordered pseudographitic nanodomains among disordered highly nitrogen-doped segments through a supramolecular self-assembly strategy. The “order-in-disorder” nanosheet-like carbon obtained at 800 °C (O/D NSLC-800) achieves a tradeoff with high defect degree (21.9 at% of doped nitrogen) and compensated electrical conductivity simultaneously. As expected, symmetrical O/D NSLC-800 electrodes exhibit superior capacitive deionization (CDI) performance, including brackish water desalination (≈82 mgNaCl g−1 at a cell voltage of 1.6 V in a 1000 mg L−1 NaCl solution) and reusage of actual refining circulating cooling water, outperforming most of the reported state-of-the-art CDI electrodes. The implanted pseudographitic nanodomains lower the resistance and activation energy of charge transfer, which motivates the synergy of hosting sites of multiple nitrogen configurations. Our findings shed light on electrically conductive nanoarchitecture design of defect-rich materials for advanced electrochemical applications based on molecular-level modulation.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.nature.com/articles/s41467-024-50899-5 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-50899-5

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-024-50899-5

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().