4.6 Article

Influence of crystallographic structure on polarization reversal in polycrystalline ferroelectric/ferroelastic materials

Journal

JOURNAL OF APPLIED PHYSICS
Volume 125, Issue 17, Pages -

Publisher

AMER INST PHYSICS
DOI: 10.1063/1.5081086

Keywords

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Funding

  1. Deutsche Forschungsgemeinschaft (DFG) [KO 5100/1-1]

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Polarization reversal is the most fundamental physical process in ferroelectrics and directly or indirectly influences all functional properties of these materials. While this process is influenced by various intrinsic material's properties and external boundary conditions, arguably one of the most dominant parameters is the material's crystallographic structure. In this work, the influence of the crystallographic structure on the polarization reversal was investigated on the model ferroelectric system Pb(Zr,Ti)O-3 using simultaneous time-dependent polarization and strain measurements. This method enabled one to extend the understanding beyond the widely investigated relationship between the structure and coercive fields. Polarization reversal was described by three regimes, which represent a sequence of well-defined non-180 degrees and 180 degrees switching events. The crystallographic structure was found to largely influence the mobility of the non-180 degrees domain walls during the first switching regime, the amplitude of negative strain, and the broadness of the transition between the first and the second switching regimes, as well as the speed of the second (main) switching regime. The observed changes could be related to the amount of possible polarization directions, distribution of the local electric fields, and strain mismatch at domain wall junctions influenced by the lattice distortion. Moreover, activation fields for the first and the second regimes were experimentally determined for the investigated series of Pb(Zr,Ti)O-3 samples. Besides providing insight into fundamental mechanisms of polarization reversal, these results can also be used as input parameters for micromechanical or stochastic models. Published under license by AIP Publishing.

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