Computational Materials Science2022,Vol.20312.DOI:10.1016/j.commatsci.2021.111103

A multi-phase-field model of topological pattern formation during electrochemical dealloying of binary alloys

Li, Jie Hu, Shenyang Li, Yulan Shi, San-Qiang
Computational Materials Science2022,Vol.20312.DOI:10.1016/j.commatsci.2021.111103

A multi-phase-field model of topological pattern formation during electrochemical dealloying of binary alloys

Li, Jie 1Hu, Shenyang 2Li, Yulan 2Shi, San-Qiang1
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作者信息

  • 1. Hong Kong Polytech Univ
  • 2. Pacific Northwest Natl Lab
  • 折叠

Abstract

Porous metal structures produced by electrochemical dealloying have been extensively studied for use in various applications that require high surface areas. A new comprehensive multi-phase-field (MPF) model is proposed to study topological porous patterns formed by spontaneously etching a bulk binary alloy that involves electrochemical reactions, bulk and surface diffusion, ion transport, applied electrode potential, and charge conservation. The governing equations for the alloy-porous cluster-electrolyte system account for a generalized ButlerVolmer electrochemical reaction and are in accordance with the classical nucleation theory. Based on a quantitative examination of the effects of electrode potential and precursor composition, the simulation results reproduce typical phenomena including passive surface dealloying, active porosity evolution, critical potential, and characteristic length scale in two-dimension (2-D) and three-dimension (3-D). To consider more complicated dealloying systems, the evolutions of a bimodal porous metal structure, nanocomposite, and nested porous network with a structured hierarchy are investigated. The proposed model can be a useful tool for understanding and predicting the morphology evolution of diverse porous structures during electrochemical dealloying.

Key words

Multi-phase-field model/Topological porous pattern/Electrochemical dealloying/Hierarchical porous structure/NANOPOROUS GOLD FORMATION/CORROSION/METAL/AU/EVOLUTION/AG/CU/KINETICS/CRACKING

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出版年

2022
Computational Materials Science

Computational Materials Science

EISCI
ISSN:0927-0256
被引量3
参考文献量53
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