Ceria has proven to be an excellent ion-transport and ion-exchange material when
used in polycrystalline form and with a high-concentration of aliovalent doped cations.
Despite its widespread application, the impact of atomic-scale defects in this material
are scarcely studied and poorly understood. In this article, using first-principles
simulations, we provide a fundamental understanding of the atomic-structure, thermodynamic stability and electronic properties of undoped grain-boundaries (GBs) and alkaline-earth metal (AEM) doped GBs in ceria. Using density-functional theory simulations, with a GGA+U functional, we find the 3 (111)/[101] GB is thermodynamically more stable than the 3 (121)/[101] GB due to the larger atomic coherency in the 3 (111)/[101] GB plane. We dope the GBs with 20% [M]GB (M=Be, Mg, Ca, Sr, and Ba) and find that the GB energies have a parabolic dependence on the size of solutes,the interfacial strain and the packing density of the GB. We see a stabilization of the GBs upon Ca, Sr and Ba doping whereas Be and Mg render them thermodynamically unstable. The electronic density of states reveal that no defect states are present in or above the band gap of the AEM doped ceria, which is highly conducive to maintain low electronic mobility in this ionic conductor. The electronic properties, unlike the thermodynamic stability, exhibit complex inter-dependence on the structure and chemistry of the host and the solutes. This work makes advances in the atomic-scale understanding of aliovalent cation doped ceria GBs serving as an anchor to future studies that can focus on understanding and improving ionic-transport.
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This content will become publicly available on April 25, 2025
Tuning grain boundary cation segregation with oxygen deficiency and atomic structure in a perovskite compositionally complex oxide thin film
Compositionally complex oxides (CCOs) are an emerging class of materials encompassing high entropy and entropy stabilized oxides. These promising advanced materials leverage tunable chemical bond structure, lattice distortion, and chemical disorder for unprecedented properties. Grain boundary (GB) and point defect segregation to GBs are relatively understudied in CCOs even though they can govern macroscopic material properties. For example, GB segregation can govern local chemical (dis)order and point defect distribution, playing a critical role in electrochemical reaction kinetics, and charge and mass transport in solid electrolytes. However, compared with conventional oxides, GBs in multi-cation CCO systems are expected to exhibit more complex segregation phenomena and, thus, prove more difficult to tune through GB design strategies. Here, GB segregation was studied in a model perovskite CCO LaFe0.7Ni0.1Co0.1Cu0.05Pd0.05O3−x textured thin film by (sub-)atomic-resolution scanning transmission electron microscopy imaging and spectroscopy. It is found that GB segregation is correlated with cation reducibility—predicted by an Ellingham diagram—as Pd and Cu segregate to GBs rich in oxygen vacancies (VO··). Furthermore, Pd and Cu segregation is highly sensitive to the concentration and spatial distribution of VO·· along the GB plane, as well as fluctuations in atomic structure and elastic strain induced by GB local disorder, such as dislocations. This work offers a perspective of controlling segregation concentration of CCO cations to GBs by tuning reducibility of CCO cations and oxygen deficiency, which is expected to guide GB design in CCOs.
more » « less- Award ID(s):
- 2011967
- PAR ID:
- 10506999
- Publisher / Repository:
- AIP Publishing
- Date Published:
- Journal Name:
- Applied Physics Letters
- Volume:
- 124
- Issue:
- 17
- ISSN:
- 0003-6951
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Interfaces such as grain boundaries (GBs) and heterointerfaces (HIs) are known to play a crucial role in structure-property relationships of polycrystalline materials. While several methods have been used to characterize such interfaces, advanced transmission electron microscopy (TEM) and scanning TEM (STEM) techniques have proven to be uniquely powerful tools, enabling quantification of atomic structure, electronic structure, chemistry, order/disorder, and point defect distributions below the atomic scale. This review focuses on recent progress in characterization of polycrystalline oxide interfaces using S/TEM techniques including imaging, analytical spectroscopies such as energy dispersive X-ray spectroscopy (EDXS) and electron energy-loss spectroscopy (EELS) and scanning diffraction methods such as precession electron nano diffraction (PEND) and 4D-STEM. First, a brief introduction to interfaces, GBs, HIs, and relevant techniques is given. Then, experimental studies which directly correlate GB/HI S/TEM characterization with measured properties of polycrystalline oxides are presented to both strengthen our understanding of these interfaces, and to demonstrate the instrumental capabilities available in the S/TEM. Finally, existing challenges and future development opportunities are discussed. In summary, this article is prepared as a guide for scientists and engineers interested in learning about, and/or using advanced S/TEM techniques to characterize interfaces in polycrystalline materials, particularly ceramic oxides.more » « less
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Abstract The interaction of alloying elements with grain boundaries (GBs) influences many phenomena, such as microstructural evolution and transport. While GB solute segregation has been the subject of active research in recent years, most studies focus on ground-state GB structures, i.e., lowest energy GBs. The impact of GB metastability on solute segregation remains poorly understood. Herein, we leverage atomistic simulations to generate metastable structures for a series of [001] and [110] symmetric tilt GBs in a model Al–Mg system and quantify Mg segregation to individual sites within these boundaries. Our results show large variations in the atomic Voronoi volume due to GB metastability, which are found to influence the segregation energy. The atomistic data are then used to train a Gaussian Process machine learning model, which provides a probabilistic description of the GB segregation energy in terms of the local atomic environment. In broad terms, our approach extends existing GB segregation models by accounting for variability due to GB metastability, where the segregation energy is treated as a distribution rather than a single-valued quantity.
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Abstract Polarization of ionic and electronic defects in response to high electric fields plays an essential role in determining properties of materials in applications such as memristive devices. However, isolating the polarization response of individual defects has been challenging for both models and measurements. Here the authors quantify the nonlinear dielectric response of neutral oxygen vacancies, comprised of strongly localized electrons at an oxygen vacancy site, in perovskite oxides of the form
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