Energy Landscape Scheme for an Intuitive Understanding of Complex Domain Dynamics in Ferroelectric Thin Films

Abstract

Fundamental understanding of domain dynamics in ferroic materials has been a longstanding issue because of its relevance to many systems and to the design of nanoscale domain-wall devices. Despite many theoretical and experimental studies, a full understanding of domain dynamics still remains incomplete, partly due to complex interactions between domain-walls and disorder. We report domain-shape-preserving deterministic domain-wall motion, which directly confirms microscopic return point memory, by observing domain-wall breathing motion inferroelectric BiFeO3 thin film using stroboscopic piezoresponse force microscopy. Spatial energy landscape that provides new insights into domain dynamics is also mapped based on the breathing motion of domain walls. The evolution of complex domain structure can be understood by the process of occupying the lowest available energy states of polarization in the energy landscape which is determined by defect induced internal fields. Our result highlights a pathway for the novel design of ferroelectric domain wall devices through the engineering of energy landscape using defect-induced internal fields such as flexoelectric fields.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2015
Accession Number
AD1068042

Entities

People

  • Chang-Beom Eom
  • Jin-seok Chung
  • Jong-gul Yoon
  • Sang M Yang
  • Seung H. Baek
  • Seung Y Jang
  • Tae H. Kim
  • Tae W Noh
  • Taeyuun Min
  • Woong-kyu Park

Organizations

  • University of Wisconsin–Madison

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Capacitors
  • Domain Walls
  • Dynamics
  • Electric Fields
  • Energy
  • Engineering
  • Ferroelectric Domains
  • Films
  • Intensity
  • Magnetic Domains
  • Materials
  • Materials Science
  • Potential Energy
  • Shape
  • Spatial Distribution
  • Thin Films
  • Transitions

Fields of Study

  • Physics

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Materials Science and Engineering.
  • Theoretical Analysis.