In material science and engineering, obtaining a spectrum from a measurement is often time-consuming and its accurate prediction using data mining can also be difficult. In this work, we propose a machine learning strategy based on a deep neural network model to accurately predict the dielectric temperature spectrum for a typical multi-component ferroelectric system, i.e., (Ba_1−x−yCa_xSr_y)(Ti_{1−u−v−w}Zr_uSn_vHf_w)O₃. The deep neural network model uses physical features as inputs and directly outputs the full spectrum, in addition to yielding the octahedral factor, Matyonov–Batsanov electronegativity, ratio of valence electron to nuclear charge, and core electron distance (Schubert) as four key descriptors. Owing to the physically meaningful features, our model exhibits better performance and generalization ability in the broader composition space of BaTiO₃-based solid solutions. And the prediction accuracy is superior to traditional machine learning models that predict dielectric permittivity values at each temperature. Furthermore, the transition temperature and the degree of dispersion of the ferroelectric phase transition are easily extracted from the predicted spectra to provide richer physical information. The prediction is also experimentally validated by typical samples of (Ba_0.85Ca_0.15)(Ti_0.98–xZr_xHf_0.02)O₃. This work provides insights for accelerating spectra predictions and extracting ferroelectric phase transition information.

Ferroelectric (FE) phase transition with a large polarization change benefits to generate large electrocaloric (EC) effect for solid-sate and zero-carbon cooling application. However, most EC studies only focus on the single-physical factor associated phase transition. Herein, we initiated a comprehensive discussion on phase transition in Pb_0.99Nb_0.02[(Zr_0.6Sn_0.4)_1−xTi_x]_0.98O₃ (PNZST100x) antiferroelectric (AFE) ceramic system under the joint action of multi-physical factors, including composition, temperature, and electric field. Due to low energy barrier and enhanced zero-field entropy, the multi-phase coexistence point (x = 0.12) in the composition–temperature phase diagram yields a large positive EC peak of maximum temperature change (ΔT_max) = 2.44 K (at 40 kV/cm). Moreover, the electric field–temperature phase diagrams for four representative ceramics provide a more explicit guidance for EC evolution behavior. Besides the positive EC peaks near various phase transition temperatures, giant positive EC effects are also brought out by the electric field-induced phase transition from tetragonal AFE (AFE_T) to low-temperature rhombohedral FE (FE_R), which is reflected by a positive-slope boundary in the electric field–temperature phase diagram, while significant negative EC responses are generated by the phase transition from AFE_T to high-temperature multi-cell cubic paraelectric (PE_MCC) with a negative-slope phase boundary. This work emphasizes the importance of phase diagram covering multi-physical factors for high-performance EC material design.

For efficient solid-state refrigeration technologies based on electrocaloric effect (ECE), it is a great challenge of simultaneously obtaining a large adiabatic temperature change (ΔT) within a wide temperature span (T_span) in lead-free ferroelectric ceramics. Here, we studied the electrocaloric effect (ECE) in (1-x)(Na_0.5Bi_0.5)TiO₃-xCaTiO₃ ((1-x)NBT-xCT) and explored the combining effect of morphotropic phase boundary (MPB) and relaxor feature. The addition of CT not only constructs a MPB region with the coexistence of rhombohedral and orthorhombic phases, but also enhances the relaxor feature. The ECE peak appears around the freezing temperature (T_f), and shifts toward to lower temperature with the increasing CT amount. The directly measured ECE result shows that the ceramic of x = 0.10, which is in the MPB region, has an optimal ECE property of ΔT_max = 1.28 K @ 60 ℃ under 60 kV/cm with a wide T_span of 65 ℃. The enhanced ECE originates from the electric-field-induced transition between more types of polar nanoregions and long-range ferroelectric macrodomains. For the composition with more relaxor feature in the MPB region, such as x = 0.12, the ECE is relatively weak under low electric fields but it exhibits a sharp increment under a sufficiently high electric field. This work provides a guideline to develop the solid–state cooling devices for electronic components.

Introducing polarization field of piezoelectric materials is an effective strategy to improve photocatalytic performance. In this study, a new type of BaTiO₃/CuO heterostructure catalyst was designed and synthesized to achieve high piezo-photocatalytic activity through the synergy of heterojunction and piezoelectric effect. The BaTiO₃/CuO heterostructure shows a significantly enhanced piezo-photocatalytic degradation efficiency of organic pollutants compared with the individual BaTiO₃ nanowires (NWs) and CuO nanoparticles (NPs). Under the co-excitation of ultrasonic vibration and ultraviolet radiation, the optimal degradation reaction rate constant k of polarized BaTiO₃/CuO heterostructure on methyl orange (MO) dye can reach 0.05 min^-1, which is 6.1 times of photocatalytic rate and 7 times of piezocatalytic rate. The BaTiO₃/CuO heterostructure with remarkable piezo-photocatalytic behavior provides a promising strategy for the development of high-efficiency catalysts for wastewater purification, and it also helps understand the coupling mechanism between piezoelectric effect and photocatalysis.

Y-type hexagonal ferrite with planar magnetocrystalline anisotropy has ultrahigh cut-off frequency up to GHz and excellent magnetic properties in hyper frequency range, so that is regarded as the most suitable material in correpongding inductive devices and components. The technology of low temperature cofired ceramics for surface-mounted multilayer chip components needs ferrite to be sintered well under 900 ℃ to avoid the melting and diffusion of Ag inner electrode during the cofiring process. To lower the sintering temperature of Y-type hexagonal ferrite, there are several methods, (1) using nano-sized starting powders, (2) substitution by low-melting elements, (3) adding sintering additives, and (4) introducing lattice defect. In this paper, the effects of different methods on the sintering behavior and the magnetic properties were discussed in detail.