Apr 23, 2024
3:30pm - 4:00pm
Room 440, Level 4, Summit
Aiping Chen1,Di Zhang1,Nicholas Cucciniello1,2,Alessandro Mazza1,Quanxi Jia2,Michael Zachman3,Rod McCabe1,James LeBeau4
Los Alamos National Laboratory1,University at Buffalo, The State University of New York2,Oak Ridge National Laboratory3,Massachusetts Institute of Technology4
Aiping Chen1,Di Zhang1,Nicholas Cucciniello1,2,Alessandro Mazza1,Quanxi Jia2,Michael Zachman3,Rod McCabe1,James LeBeau4
Los Alamos National Laboratory1,University at Buffalo, The State University of New York2,Oak Ridge National Laboratory3,Massachusetts Institute of Technology4
Dielectric materials, holding charges as capacitors, are vital energy storage components of electronics and power systems. Dielectric capacitors distinguish themselves in features of ultrafast charging/discharging rates, high voltage endurance, and good reliability. Enhancing the relatively low energy densities of dielectric capacitors is essential for their applications in pulsed power equipment. Relaxor ferroelectrics are promising candidates for applications in energy storage. Therefore, considerable effort has been devoted to enhancing the energy storage via composition optimization, defect engineering, and architectural design.<br/>In this talk, I will discuss the strategies of designing interface and domain structure in doped BaTiO<sub>3</sub> to achieve relaxor ferroelectrics. In the first part, I will discuss the design of (Ba<sub>0.7</sub>Ca<sub>0.3</sub>)TiO<sub>3</sub> (BCT) and Ba(Ti<sub>0.8</sub>Zr<sub>0.2</sub>)O<sub>3</sub> (BZT) superlattices via a high-throughput combinatorial approach. Well-controlled compositional gradient, superlattice geometry and domain size are explored by scanning transmission electron microscopy (STEM). Ferroelectric and dielectric properties identified the “optimal property point” achieved near the morphotropic phase boundary. Our results have found that relaxor-like ferroelectric behavior enhances and the leakage slightly increases with reducing the superlattice periodicity (or with more interfaces). In the second part of the talk, I will discuss strategies to further optimize domain structures and suppress the leakage current in BZT-BCT films via a machine learning approach. Sn has been identified as an ideal dopant to maintain the rhombohedral /tetragonal phase boundary, reduce leakage current and reduce the domain size below 10 nm for BZT-BCT systems and greatly enhanced relaxor ferroelectric behavior has been achieved. The large polarization and the delayed polarization saturation lead to greatly enhanced energy density of 80 J/cm<sup>3</sup> and transfer efficiency of 85% over a wide temperature range. Such a data-driven design recipe for a slush-like polar state is generally applicable to quickly optimize functionalities of ferroelectric materials.