Charge-Induced (1 x 3) Reconstruction of Au(110): Mechanistic Insights from Potentiodynamic Scanning Tunneling Microscopy in Alkali Iodide Electrolytes

Abstract

The nature of the local atomic-level and nanoscale structural changes associated with the charge-induced (1 x 3) reconstruction on Au(110) in alkali iodide electrolytes is explored by means of potentiodynamic scanning tunneling microscopy, i.e. , with STM images obtained during electrode potential excursions where the surface transformations are triggered on a suitable (seconds) timescale. In potassium iodide electrolyte, the usual 'three-missing- row' (1 x 3) structure is seen to be generated by single gold atomic-row segments shifting both across and along the (110) direction. In cesium iodide, however, at least two spatially as well as potentiodynamically resolvable steps were observed, involving the intermediate local formation of one-missing-row (1 x 3) domains by removal of one-third of the top layer gold rows onto nearby terrace regions. Domains having (1 x 2) symmetry were also discerned. A subsequent transformation into the final 'three-missing-row' (1 x 3) structure is achieved by aggregation of the displaced monoatomic row segments. The mechanistic value of following atomic-level reconstruction processes by such coupled electrochemical-STM tactics is illustrated by these findings.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1994
Accession Number
ADA276632

Entities

People

  • Michael J. Weaver
  • Xiaoping Gao

Organizations

  • Purdue University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Alkali Metals
  • Chemistry
  • Electrochemical Cells
  • Electrodes
  • Electrolytes
  • Metals
  • Microscopy
  • Military Research
  • Phase Transformations
  • Potassium
  • Quantum Tunneling
  • Removal
  • Scanning
  • Sequences
  • Symmetry
  • Tunneling
  • X Ray Scattering

Fields of Study

  • Physics

Readers

  • Electrochemical Surface Science
  • Image Processing and Computer Vision.
  • Materials Science and Engineering.