Local and correlated studies of humidity-mediated ferroelectric thin film surface charge dynamics
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 micro...
| Autores: | , , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universitat Autònoma de Barcelona |
| Repositorio: | Dipòsit Digital de Documents de la UAB |
| Idioma: | inglés |
| OAI Identifier: | oai:ddd.uab.cat:268432 |
| Acceso en línea: | https://ddd.uab.cat/record/268432 https://dx.doi.org/urn:doi:10.1038/s41524-021-00615-4 |
| Access Level: | acceso abierto |
| Palabra clave: | Applied surface Charge dynamics Dictionary learning Electrochemical phenomenon Ferroelectric polarization Ferroelectric thin-films Kelvin probe microscopy Sensing applications Surface voltages Thin film surfaces |
| Sumario: | 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(ZrTi)O 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. |
|---|