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Local and correlated studies of humidity-mediated ferroelectric thin film surface charge dynamics

Authors :
Nazanin Bassiri-Gharb
Patrycja Paruch
Albert Verdaguer
Neus Domingo
Iaroslav Gaponenko
Nicolas Stucki
Loïc Musy
Swiss National Science Foundation
Ministerio de Ciencia, Innovación y Universidades (España)
National Science Foundation (US)
Gaponenko, Iaroslav
Musy, Loïc
Domingo, Neus
Bassiri-Gharb, Nazanin
Gaponenko, Iaroslav [0000-0002-9694-7033]
Musy, Loïc [0000-0002-7741-6763]
Domingo, Neus [0000-0002-5229-6638]
Bassiri-Gharb, Nazanin [0000-0002-0183-5160]
Source :
npj Computational Materials, Vol 7, Iss 1, Pp 1-7 (2021), Digital.CSIC. Repositorio Institucional del CSIC, instname, npj computational materials, Vol. 7, No 1 (2021) P. 163
Publication Year :
2021
Publisher :
Nature Publishing Group, 2021.

Abstract

Electrochemical phenomena in ferroelectrics are of particular interest for catalysis and sensing applications, with recent studies highlighting the combined role of the ferroelectric polarisation, applied surface voltage and overall switching history. Here, we present a systematic Kelvin probe microscopy study of the effect of relative humidity and polarisation switching history on the surface charge dissipation in ferroelectric Pb(Zr0.2Ti0.8)O3 thin films. We analyse the interaction of surface charges with ferroelectric domains through the framework of physically constrained unsupervised machine learning matrix factorisation, Dictionary Learning, and reveal a complex interplay of voltage-mediated physical processes underlying the observed signal decays. Additional insight into the observed behaviours is given by a Fitzhugh–Nagumo reaction–diffusion model, highlighting the lateral spread and charge passivation process contributors within the Dictionary Learning analysis.<br />The authors acknowledge Dr Sergei V. Kalinin of Oak Ridge National Laboratory, for helpful discussions about machine learning and the initial suggestion to explore reaction–diffusion modelling. This work was supported by Division II of the Swiss National Science Foundation under project 200021_178782. A.V. acknowledges support by the Spanish Government under the project PID2019-110907GB-I00 and the “Severo Ochoa” Program for Centres of Excellence in R&D (CEX2019-000917-S). N.D. acknowledges support by the Spanish Government under the project PID2019- 109931GB-I00. N.B.G. acknowledges support by the National Science Foundation under the project DMR-20269676. The authors would like to thank S. Muller for technical support.<br />With funding from the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000917-S).

Details

Language :
English
ISSN :
20573960
Database :
OpenAIRE
Journal :
npj Computational Materials, Vol 7, Iss 1, Pp 1-7 (2021), Digital.CSIC. Repositorio Institucional del CSIC, instname, npj computational materials, Vol. 7, No 1 (2021) P. 163
Accession number :
edsair.doi.dedup.....526c46c746addc1bc6b0848bd6e80e35