High Velocity, Low-Voltage Collective In-Plane Switching in (100) BaTiO3 Thin Films

Trygve M. Ræder*, Shuyu Qin, Rama K. Vasudevan, Tor Grande, Joshua C. Agar, Michael J. Zachman

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Ferroelectrics are being increasingly called upon for electronic devices in extreme environments. Device performance and energy efficiency is highly correlated to clock frequency, operational voltage, and resistive loss. To increase performance it is common to engineer ferroelectric domain structure with highly-correlated electrical and elastic coupling that elicit fast and efficient collective switching. Designing domain structures with advantageous properties is difficult because the mechanisms involved in collective switching are poorly understood and difficult to investigate. Collective switching is a hierarchical process where the nano- and mesoscale responses control the macroscopic properties. Using chemical solution synthesis, epitaxially nearly-relaxed (100) BaTiO3 films are synthesized. Thermal strain induces a strongly-correlated domain structure with alternating domains of polarization along the [010] and [001] in-plane axes and 90° domain walls along the [011] or [01 (Formula presented.)] directions. Simultaneous capacitance–voltage measurements and band-excitation piezoresponse force microscopy revealed strong collective switching behavior. Using a deep convolutional autoencoder, hierarchical switching is automatically tracked and the switching pathway is identified. The collective switching velocities are calculated to be ≈500 cm s−1 at 5 V (7 kV cm−1), orders-of-magnitude faster than expected. These combinations of properties are promising for high-speed tunable dielectrics and low-voltage ferroelectric memories and logic.

Original languageEnglish
Article number2201530
JournalAdvanced Science
Issue number29
Number of pages7
Publication statusPublished - 2022


  • Barium titanate
  • Capacitive hysteresis
  • Ferroelectric switching
  • Ferroelectrics
  • Neural network
  • Piezoresponse force microscopy


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