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Title: Rapid mapping of polarization switching through complete information acquisition

Journal Article · · Nature Communications
DOI:https://doi.org/10.1038/ncomms13290· OSTI ID:1334426

Polarization switching in ferroelectric and multiferroic materials underpins a broad range of current and emergent applications, ranging from random access memories to field-effect transistors, and tunnelling devices. Switching in these materials is exquisitely sensitive to local defects and microstructure on the nanometre scale, necessitating spatially resolved high-resolution studies of these phenomena. Classical piezoresponse force microscopy and spectroscopy, although providing necessary spatial resolution, are fundamentally limited in data acquisition rates and energy resolution. This limitation stems from their two-tiered measurement protocol that combines slow (~1 s) switching and fast (~10 kHz–1 MHz) detection waveforms. Here we develop an approach for rapid probing of ferroelectric switching using direct strain detection of material response to probe bias. This approach, facilitated by high-sensitivity electronics and adaptive filtering, enables spectroscopic imaging at a rate 3,504 times faster the current state of the art, achieving high-veracity imaging of polarization dynamics in complex microstructures.

Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Sciences (CNMS)
Sponsoring Organization:
USDOE Office of Science (SC)
Grant/Contract Number:
AC05-00OR22725
OSTI ID:
1334426
Journal Information:
Nature Communications, Vol. 7; ISSN 2041-1723
Publisher:
Nature Publishing GroupCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 17 works
Citation information provided by
Web of Science

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Full information acquisition in piezoresponse force microscopy
  • Somnath, Suhas; Belianinov, Alexei; Kalinin, Sergei
  • Oak Ridge Leadership Computing Facility; Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States) https://doi.org/10.13139/olcf/1464456
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Towards nanoscale electrical measurements in liquid by advanced KPFM techniques: a review journal July 2018
Materials science in the artificial intelligence age: high-throughput library generation, machine learning, and a pathway from correlations to the underpinning physics journal July 2019