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Description
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(Zr$_{0.2}$Ti$_{0.8}$)O$_3$ thin films. We analyze the interaction of surface charges with ferroelectric domains through the framework of physically constrained unsupervised machine learning matrix factorization, 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.
