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Title: To switch or not to switch – a machine learning approach for ferroelectricity


The introduced two-dimensional representation of two-parameter signal dependence allows for clear interpretation and classification of the measured signal upon using machine learning methods.

ORCiD logo [1];  [1];  [2]; ORCiD logo [3];  [1]; ORCiD logo [2]; ORCiD logo [1];  [1]
  1. Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, USA
  2. Department of Materials Science and Engineering, University of California, Berkeley, USA, Materials Sciences Division
  3. Department of Physics & CICECO – Aveiro Institute of Materials, University of Aveiro, Aveiro, Portugal, School of Natural Sciences and Mathematics
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES). Materials Sciences & Engineering Division; National Science Foundation (NSF); US Army Research Office (ARO); Fundação para a Ciência e a Tecnologia (FCT)
OSTI Identifier:
Alternate Identifier(s):
OSTI ID: 1615406; OSTI ID: 1637317; OSTI ID: 1659630
Grant/Contract Number:  
AC02-05CH11231; DMR-1708615; W911NF-14-1-0104; UIDB/50011/2020; UIDP/50011/2020; AC05-00OR22725
Resource Type:
Published Article
Journal Name:
Nanoscale Advances
Additional Journal Information:
Journal Name: Nanoscale Advances Journal Volume: 2 Journal Issue: 5; Journal ID: ISSN 2516-0230
Royal Society of Chemistry
Country of Publication:
United Kingdom

Citation Formats

Neumayer, Sabine M., Jesse, Stephen, Velarde, Gabriel, Kholkin, Andrei L., Kravchenko, Ivan, Martin, Lane W., Balke, Nina, and Maksymovych, Peter. To switch or not to switch – a machine learning approach for ferroelectricity. United Kingdom: N. p., 2020. Web. doi:10.1039/C9NA00731H.
Neumayer, Sabine M., Jesse, Stephen, Velarde, Gabriel, Kholkin, Andrei L., Kravchenko, Ivan, Martin, Lane W., Balke, Nina, & Maksymovych, Peter. To switch or not to switch – a machine learning approach for ferroelectricity. United Kingdom.
Neumayer, Sabine M., Jesse, Stephen, Velarde, Gabriel, Kholkin, Andrei L., Kravchenko, Ivan, Martin, Lane W., Balke, Nina, and Maksymovych, Peter. Tue . "To switch or not to switch – a machine learning approach for ferroelectricity". United Kingdom.
title = {To switch or not to switch – a machine learning approach for ferroelectricity},
author = {Neumayer, Sabine M. and Jesse, Stephen and Velarde, Gabriel and Kholkin, Andrei L. and Kravchenko, Ivan and Martin, Lane W. and Balke, Nina and Maksymovych, Peter},
abstractNote = {The introduced two-dimensional representation of two-parameter signal dependence allows for clear interpretation and classification of the measured signal upon using machine learning methods.},
doi = {10.1039/C9NA00731H},
journal = {Nanoscale Advances},
number = 5,
volume = 2,
place = {United Kingdom},
year = {2020},
month = {5}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Figures / Tables:

Fig. 1 Fig. 1: cKPFM on ferroelectric PZT. (a) Schematic of sequence of DC voltage pulses applied during cKPFM. Vwrite pulses are increasing and decreasing in a triangular envelope, whereas the Vread is applied between write pulses and sequentially increased with each cycle. (b) Traditional cKPFM diagram where response Dac is plottedmore » as a function of Vread with Vwrite steps color coded. (c) Hysteresis loop extracted from Vread = 0 as a function of Vwrite (top) and unfolded as a function of Vwrite step #. (d) Unfolded loops for all Vread stacked along a third dimension. These loops are projected on a 2D map where Dac is represented by the color scale, rows correspond to response during a certain Vread and columns correspond to Vwrite steps. (e) cKPFM with decreased Vread window as indicated in the green box in panel (d), (f) cKPFM map with a further decreased the probing window corresponding to the blue box in panel (e). The white dashed line in cKPFM maps in panels (d–f) indicate Vwrite.« less

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