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  5. MXene Coatings: Novel Hydrogen Permeation Barriers for Pipe Steels

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Article
en
2021

MXene Coatings: Novel Hydrogen Permeation Barriers for Pipe Steels

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en
2021
Vol 11 (10)
Vol. 11
DOI: 10.3390/nano11102737

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Paul Kim Ho Chu
Paul Kim Ho Chu

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Kejun Shi
Xinyu Meng
Shu Xiao
+5 more

Abstract

MXenes are a new class of two-dimensional (2D) materials with promising applications in many fields because of their layered structure and unique performance. In particular, the physical barrier properties of two-dimensional nanosheets make them suitable as barriers against hydrogen. Herein, MXene coatings were prepared on pipe steel by a simple spin-coating process with a colloidal suspension. The hydrogen resistance was evaluated by electrochemical hydrogen permeation tests and slow strain rate tests, and the corrosion resistance was assessed by potentiodynamic polarization. The results reveal that MXene coatings offer excellent hydrogen resistance and corrosion protection by forming a barrier against diffusion. Experimentally, the hydrogen permeability of the MXene coating is one third of the substrate, and the diffusion coefficient decreases as well. The mechanistic study indicates that the hydrogen resistance of the MXene coatings is affected by the number of spin-coated layers, while the concentration of the d-MXene colloidal suspension determines the thickness of a single coating. However, damage to the sample surface caused by the colloidal suspension that contains H+ and F- may limit the improvement of the hydrogen resistance. This paper reveals a new application of 2D MXene materials as a novel efficient barrier against hydrogen permeation and the subsequent alleviation of hydrogen embrittlement in the steel substrate.

How to cite this publication

Kejun Shi, Xinyu Meng, Shu Xiao, Guohua Chen, Hao Wu, Chilou Zhou, Saihua Jiang, Paul Kim Ho Chu (2021). MXene Coatings: Novel Hydrogen Permeation Barriers for Pipe Steels. , 11(10), DOI: https://doi.org/10.3390/nano11102737.

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Publication Details

Type

Article

Year

2021

Authors

8

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.3390/nano11102737

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