journal article·2025-01

Enhanced energy storage performance of 0.85BaTiO3–0.15Bi(Mg0.5Hf0.5)O3 films via synergistic effect of defect dipole and oxygen vacancy engineering

Weijie Fu, Yi-qin Lu, Qiuyang Han, Tian-Yi Hu, Tingzhi Duan, Yupeng Liu, Shao-Dong Cheng, Yanzhu Dai, Ming Liu, Chunrui Ma

Acta Materialia· Volume 283
Publisher page

Abstract

Dielectric capacitors are widely used in electronic devices due to their ultra-fast charge/discharge rate and ultra-high power density, but their lower energy density and poor thermal stability limit their further application. In contrast to the traditional strategy of suppressing defects, this work combines oxygen vacancies with defect dipoles to improve the breakdown strength and polarization behavior of ferroelectric films. Low concentration of oxygen vacancies and defect dipoles can trap charge carriers and increase breakdown strength, but if the concentration is too high, it can easily make films prone to breakdown. Moreover, the defect dipoles can reduce Pr by providing intrinsic restoring force for polarization switching, while excessive defect dipoles and oxygen vacancies can pin domain walls and increase Pr. By delicately controlling the concentration of oxygen vacancies and defect dipoles in the film, the BT-BMH film deposited at 0.135 mbar achieved the maximum breakdown strength and slim P- E loops, inducing the energy density to reach 108.9 J·cm -3 with an efficiency of 79.6 % at room temperature and excellent thermal stability in the wide temperature range of -100∼350 °C with the energy density of 69.1 J·cm -3. This work reveals the important significance of reasonable defect control for improving energy storage performance and provides an effective method for developing high-performance dielectric capacitors.
Source: expertdata · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Ferroelectric and Piezoelectric Materials · Microwave Dielectric Ceramics Synthesis · Dielectric materials and actuators

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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