High Electrocaloric Effect in Lead Scandium Tantalate Thin Films with Interdigitated Electrodes

Lead scandium tantalate, Pb(Sc,Ta)O₃, is an excellent electrocaloric material showing large temperature variations, good efficiency, and a broad operating temperature window. In form of multilayer ceramic capacitors integrated into a cooling device, the device can generate a temperature difference larger than 13 K. Here, we investigate Pb(Sc,Ta)O₃ in form of thin films prepared using the sol–gel chemical solution deposition method. We report the detailed fabrication process of high-quality films on various substrates such as c-sapphire and fused silica. The main originality of this research is the use of interdigitated top electrodes, enabling the application of very large electric fields in PST. We provide structural and electrical characterisation, as well as electrocaloric temperature variation, using the Maxwell relation approach. Films do not show a B-site ordering. The temperature variation from 7.2 to 15.7 K was measured on the Pb(Sc,Ta)O₃ film on a c-sapphire substrate under the electric field of 1330 kV/cm between 14.5 °C and 50 °C. This temperature variation is the highest reported so far in Pb(Sc,Ta)O₃ thin films. Moreover, stress seems to have an effect on the maximum permittivity temperature and thus electrocaloric temperature variation with temperature in Pb(Sc,Ta)O₃ films. Tensile stress induced by fused silica shifts the “transition” of Pb(Sc,Ta)O₃ to lower temperatures. This study shows the possibility for electrocaloric temperature variation tuning with stress conditions.

Machine-Learning-Enabled Prediction of Adiabatic Temperature Change in Lead-Free BaTiO3-Based Electrocaloric Ceramics

In this paper, we develop a data-driven machine learning (ML) approach to predict the adiabatic temperature change (ΔT) in BaTiO₃-based ceramics as a function of chemical composition, temperature, and applied electric field. The data set was curated from a survey of published electrocaloric measurements. Each chemical composition was represented by elemental descriptors of A-site and B-site elements. Pair-wise statistical correlation analysis was used to remove linearly correlated descriptors. We trained two separate regression-based ML models for indirect and direct measurements and found that both are capable of capturing the general trend of the temperature vs ΔT curve for various applied electric fields. We then complemented the regression models with a classification learning model that predicts the expected phase as a function of chemical composition and temperature. The combined regression and classification learning ML models predict a global maxima in ΔT near rhombohedral to cubic or tetragonal to cubic phase transition regions. An interactive, open source web application is developed to enable interested users to query our trained models and accelerate the design of novel BaTiO₃-based ceramics with targeted phase and ΔT properties for electrocaloric applications.

Mn-Doped BaTiO3Ceramics: Thermal and Electrical Properties for Multicaloric Applications

Multiferroic materials are widely used in microelectronics because they are sensitive to elastic, magnetic, and electric fields and there is an intrinsic coupling between them. In particular, transition metal-doped BaTiO₃ is considered as a viable multiferroic because of the simultaneous presence of ferroelectricity and magnetism. In this work, we study the electrical and thermal properties of Mn-doped BaTiO₃ ceramics that can be used for multicaloric applications. We found that Mn doping leads to the broadening and shifting of the phase transition accompanied with simultaneous decrease of latent heat and entropy. Mn doping causes a decrease in the bulk resistivity while contact resistance remains intact. Doped ceramics can withstand high electric fields (up to 40 kV/cm) and exhibit linear I-V characteristics followed by the Schottky limited current in contrast to earlier observations. As such, these ceramics are promising for multicaloric applications.