Zhang Yue, Lin Xiaoyu, Zhai Wenbo, Shen Yanran, Chen Shaojie, Zhang Yining, Yu Yi, He Xuming, Liu Wei
School of Physical Science and Technology, ShanghaiTech University, Shanghai 201210, China.
Shanghai Key Laboratory of High-resolution Electron Microscopy, ShanghaiTech University, Shanghai 201210, China.
Nano Lett. 2024 May 1;24(17):5292-5300. doi: 10.1021/acs.nanolett.4c00902. Epub 2024 Apr 22.
Understanding the structure-property relationship of lithium-ion conducting solid oxide electrolytes is essential to accelerate their development and commercialization. However, the structural complexity of nonideal materials increases the difficulty of study. Here, we develop an algorithmic framework to understand the effect of microstructure on the properties by linking the microscopic morphology images to their ionic conductivities. We adopt garnet and perovskite polycrystalline oxides as examples and quantify the microscopic morphologies via extracting determined physical parameters from the images. It directly visualizes the effect of physical parameters on their corresponding ionic conductivities. As a result, we can determine the microstructural features of a Li-ion conductor with high ionic conductivity, which can guide the synthesis of highly conductive solid electrolytes. Our work provides a novel approach to understanding the microstructure-property relationship for solid-state ionic materials, showing the potential to extend to other structural/functional ceramics with various physical properties in other fields.
理解锂离子传导固体氧化物电解质的结构与性能关系对于加速其发展和商业化至关重要。然而，非理想材料的结构复杂性增加了研究难度。在此，我们开发了一个算法框架，通过将微观形态图像与其离子电导率联系起来，以了解微观结构对性能的影响。我们以石榴石和钙钛矿多晶氧化物为例，通过从图像中提取确定的物理参数来量化微观形态。它直接可视化了物理参数对其相应离子电导率的影响。结果，我们可以确定具有高离子电导率的锂离子导体的微观结构特征，这可以指导高导电固体电解质的合成。我们的工作为理解固态离子材料的微观结构-性能关系提供了一种新方法，显示出扩展到其他领域具有各种物理性质的其他结构/功能陶瓷的潜力。
