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

Iaroslav Gaponenko, Loïc Musy, Neus Domingo, Nicolas Stucki, Albert Verdaguer, Nazanin Bassiri-Gharb, Patrycja Paruch

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

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.

Original languageEnglish
Article number163
Journalnpj Computational Materials
Volume7
Issue number1
DOIs
StatePublished - Dec 2021
Externally publishedYes

Funding

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.

FundersFunder number
Spanish GovernmentPID2019-110907GB-I00, CEX2019-000917-S, PID2019-109931GB-I00
National Science FoundationDMR-20269676
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung200021_178782

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