Advancement of capacitive deionization propelled by machine learning approach-Reference-Cited by-同舟云学术

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Advancement of capacitive deionization propelled by machine learning approach

Published:2025-02 Issue: Volume:354 Page:129423
ISSN:1383-5866
Container-title:Separation and Purification Technology
language:en
Short-container-title:Separation and Purification Technology

Author:

Wang Hao,Li Yuquan,Liu Yong,Xu Xingtao,Lu Ting,Pan Likun^ORCID

Publisher

Elsevier BV

Reference53 articles.

1. Heterointerface regulation of covalent organic framework-anchored graphene via a solvent-free strategy for high-performance supercapacitor and hybrid capacitive deionization electrodes;Xu;Mater. Horiz.,2024

2. Hydrogen-bonded organic framework derived 2D NO Co-doped carbon nanobelt with tunable pseudocapacitive contribution for efficient capacitive deionization;Meng;Small,2024

3. Solvent-free synthesis of covalent organic framework/graphene nanohybrids: High-performance faradaic cathodes for supercapacitors and hybrid capacitive deionization;Xu;Small,2024

4. In situ synthesis of ultrasmall NaTi2(PO4)3 nanocube decorated carbon nanofiber network enables ultrafast and superstable rocking-chair capacitive deionization;Wang;Chem. Eng. J.,2023

5. Tailoring the electrode material and structure of rocking-chair capacitive deionization for high-performance desalination;Wang;Mater. Horiz.,2024

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