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Oxidation Driven Thin-Film Solid-State Metal Dealloying Forming Bicontinuous Nanostructures

  • Cheng Chu Chung
  • , Charles Clark
  • , Chonghang Zhao
  • , Kim Kisslinger
  • , Fernando Camino
  • , Dmytro Nykypanchuk
  • , Hui Zhong
  • , Sanjit Ghose
  • , Ruipeng Li
  • , Chang Yong Nam
  • , Yu chen Karen Chen-Wiegart
  • Stony Brook University
  • Brookhaven National Laboratory

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Solid-state metal dealloying (SSMD) is a promising method for fabricating nanoscale metallic composites and nanoporous metals across a range of materials. Thin-film SSMD is particularly attractive due to its ability to create fine features via solid-state interfacial reactions within a thin-film geometry, which can be integrated into devices for various applications. This work examines a new dealloying couple, namely the Nb–Al alloy with the dealloying agent Sc, as previously predicted in the machine-learning (ML) models. Prior ML predictions aimed to guide the design of nanoarchitectured materials through dealloying, relying on intuition-driven discovery within a large parameter space. However, this work reveals that at the nanoscale, the involvement of oxygen in thin film processing may instead drive the dealloying process, resulting in the formation of bicontinuous nanostructures similar to those formed by metal-agent dealloying. The phase evolution, as well as chemical and morphological changes, are closely analyzed using a combination of X-ray absorption spectroscopy, diffraction, and scanning transmission electron microscopy to understand the mechanisms behind nanostructure formation. The findings suggest a potential pathway for utilizing oxygen to drive the formation of bicontinuous metal–metal oxide nanocomposites, paving the way for further development of functional nanoporous materials in diverse fields.

Original languageEnglish
Article number2300454
JournalAdvanced Materials Interfaces
Volume10
Issue number35
DOIs
StatePublished - Dec 13 2023

Keywords

  • SSID
  • machine-learning
  • metal dealloying
  • nanocomposites
  • synchrotron

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