Ferroelectric BaTiO3 is widely used in capacitors, but the low Curie temperature limits a further use of BaTiO3. In this work we present an aqueous chemical solution deposition (CSD) route for BaTiO3 thin films, demonstrating that organic solvents are not required for CSD. Textured BaTiO3 thin films were deposited on SrTiO3 substrates. The in-plane dielectric properties were investigated using interdigitated electrodes and ferroelectric switching was observed up to 160±5 °C. The increased Curie temperature is proposed to result from thermal strain due to a mismatch in thermal expansion coefficient between the film and the substrate, and is in good agreement with the theory of strain engineering in BaTiO3. Finally, the decomposition and crystallization of BaTiO3 during thermal treatment were determined by the combination of thermal analysis, IR spectroscopy and X-ray diffraction of powder prepared from the solution.

Relaxor ferroelectrics exhibit superior properties for converting mechanical energy into electrical, and vice versa, but the structural disorder hampers an understanding of structureproperty relationships, and impedes rational design of new, lead-free materials. Bi0.5K0.5TiO3 (BKT) is a prototypical lead-free relaxor ferroelectric, but the microscopic origins of polarization, nature of the ferroelectric transition (TC) and structural changes across the tetragonal to pseudo-cubic transition (T2) are poorly understood. Here the local and intermediate structure of BKT is studied from room temperature to above TC by pair distribution functions (PDF) from synchrotron X-ray total scattering experiments and complemented by ab initio molecular dynamics (AIMD) simulations. The local structure varies smoothly across T2 as well as TC, in contrast to the abrupt changes at TC inferred from conventional diffraction.Ferroelectric distortions are larger on the local scale than in the average structure, with polar Ti 4+ displacements prevailing above TC. We find that local polar regions partly cancel each other below TC, while completely averaging out above, implying that BKT goes through a transition from partial to complete disorder across TC.

The accurate evaluation of ferroelectric thin films operated with interdigitated electrodes is quite a complex task. In this article, we show how to correct the electric field and the capacitance in order to obtain identical polarization and CV loops for all geometrical variants. The simplest model is compared with corrections derived from Schwartz-Christoffel transformations, and with finite element simulations. The correction procedure is experimentally verified, giving almost identical curves for a variety of gaps and electrode widths. It is shown that the measured polarization change corresponds to the average polarization change in the center plane between the electrode fingers, thus at the position where the electric field is most homogeneous with respect to the direction and size. The question of maximal achievable polarization in the various possible textures, and compositional types of polycrystalline lead zirconate titanate thin films is revisited. In the best case, a soft (110) textured thin film with the morphotropic phase boundary composition should yield a value of 0.95Ps, and in the worst case, a rhombohedral (100) textured thin film should deliver a polarization of 0.74Ps.

Ferroelectric domain walls are promising quasi-2D structures that can be leveraged for miniaturization of electronics components and new mechanisms to control electronic signals at the nanoscale. Despite the significant progress in experiment and theory, however, most investigations on ferroelectric domain walls are still on a fundamental level, and reliable characterization of emergent transport phenomena remains a challenging task. Here, we apply a neural-network-based approach to regularize local I(V)-spectroscopy measurements and improve the information extraction, using data recorded at charged domain walls in hexagonal (Er0.99,Zr0.01)MnO3 as an instructive example. Using a sparse long short-term memory autoencoder, we disentangle competing conductivity signals both spatially and as a function of voltage, facilitating a less biased, unconstrained and more accurate analysis compared to a standard evaluation of conductance maps. The neural-network-based analysis allows us to isolate extrinsic signals that relate to the tip-sample contact and separating them from the intrinsic transport behavior associated with the ferroelectric domain walls in (Er0.99,Zr0.01)MnO3. Our work expands machine-learning-assisted scanning probe microscopy studies into the realm of local conductance measurements, improving the extraction of physical conduction mechanisms and separation of interfering current signals.