Seeing Cation Dopants in Gd-doped Ceria with STEM-EELS
Seeing Cation Dopants in Gd-doped Ceria with STEM-EELS
复制标题
使用 STEM-EELS 查看掺钆氧化铈中的阳离子掺杂剂
DOI：
10.1093/micmic/ozad067.195
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发表时间：
2023
影响因子：
2.8
通讯作者：
Crozier, Peter A
中科院分区：
文献类型：
--
作者：
Tan, Mai;Yang, Shize;Crozier, Peter A
Gd掺杂氧化铈（GDC）是中温低于700 ℃的固体氧化物燃料电池（SOFC）最有前途的材料之一。与其他候选材料相比，它在低温/中温下显示出高离子电导率和稳定性[1]。GDC是一种非化学计量的氧化物材料，已知其具有与周围环境交换晶格氧的能力。将异价掺杂剂Gd添加到纯二氧化铈中通过产生更多的外来氧空位来增强氧交换能力，这导致电导率改善[2]。掺杂剂分布和局部浓度可能在氧交换功能中起重要作用。然而，表面交换率和原子级缺陷的位置/分布之间的关系还没有很好地理解。为了了解点缺陷结构和位置对交换位点的可能影响，重要的是开发可视化方法来定位缺陷。原子级Gd缺陷浓度可以使用扫描透射电子显微镜结合电子能量损失谱（STEM-EELS）来测量。然而，对于元素标测，Gd EELS的信噪比（SNR）较低，这使得难以检测和定量。为了解决这一弱点，我们提出了一种混合方法，包括EELS和高角度环形暗场成像（HAADF）。使用基于溶液的水热方法合成了15% Gd掺杂的二氧化铈（原子重量%）纳米颗粒[3]。Gd阳离子点缺陷通过在像差校正的Nion UltraSTEM 100显微镜（在100 kV下操作）上进行的STEM-EELS光谱成像来检测和定量。将纳米颗粒倾斜到[110]区轴取向，并且在（110）表面附近收集EELS光谱图像。HAADF图像与光谱同时收集。为了计算Gd的局部浓度，采用了两种方法：Ce和Gd的传统EELS映射和混合HAADF/EELS方法。在传统的方法中，光谱处理涉及背景扣除和分离重叠的Ce M23和Gd M45峰以生成Gd M45元素图。图1显示了HAADF图像和同时采集的Ce和Gd元素图。Gd是不均匀分布的，通过比较Gd和Ce图观察到簇形成。注意，在元素图中，Gd和Ce信号之间存在反相关。然而，Gd图非常嘈杂，使得难以提供Gd分布的更详细信息。由于Gd信号较弱，我们开发了一种混合方法，主要依赖于较强的Ce EELS信号和HAADF信号来推断Gd含量。该方法假设Gd离子取代Ce，并且HAADF阳离子信号与柱中阳离子的总数成比例。图2是图1中所有柱的HAADF柱强度与来自EELS图的Ce+ Gd柱强度总和（总EELS阳离子信号）的图。图2表明，这两个积分强度之间存在线性关系。这意味着，对于特定的柱，Ce柱强度与相应的HAADF柱强度的比较应该允许推导Gd EELS信号。然后通过从合适的缩放的HAADF信号中减去Ce EELS信号来确定Gd信号。图3显示了用传统方法和混合方法测定的局部Gd柱浓度的结果。这两种方法都能成功地测定浓度的变化，并显示了其优越性。
Gd-doped ceria (GDC) is one of the most promising materials using in solid oxide fuel cell (SOFC) at median operating temperature below 700 C. It has shown high ion conductivity and stability at low/median temperatures compared with other candidate materials [1]. GDC is a non-stoichiometric oxide material that is known for its ability to exchange lattice oxygen with surrounding ambient environment. Adding the aliovalent dopant Gd to pure ceria enhances the oxygen exchange ability by creating more extrinsic oxygen vacancies, which results conductivity improvement [2]. The dopants distribution and local concentration may play an important role in oxygen exchange functionality. However, the relationship between the surface exchange rate and the atomic level defect location/distribution is not well understood. To understand a possible influence of point defect structures and location on exchange sites, it’s important to develop visualization methods to locate the defects. The atomic level Gd defect concentrations can be measured using scanning transmission electron microscopy coupled with electron energy-loss spectroscopy (STEM-EELS). However, for elemental mapping, the Gd EELS signal-to-noise ratio (SNR) is low, which making it difficult to detect and quantify. To address this weakness, we present a hybrid method involving EELS and high angle-annular dark-field imaging (HAADF).15% Gd-doped ceria (atomic weight%) nanoparticles were synthesized using a solution-based hydrothermal methods [3]. Gd cation point defects were detected and quantified via STEM-EELS spectrum imaging performed on an aberration-corrected Nion UltraSTEM 100 microscope (operated at 100kV). Nanoparticles were tilted into the [110] zone axis orientation, and EELS spectrum images were collected near (110) surfaces. HAADF image were collected simultaneous with the spectra. To calculate the local concentration of Gd, two approaches have been employed: traditional EELS mapping of Ce and Gd and, a hybrid HAADF/EELS approach. In the traditional approach, spectral processing involves background subtraction and separation of the overlapping Ce M23 and Gd M45 peaks to generate the Gd M45 elemental map. Figure 1 shows the HAADF image and the simultaneously acquired Ce and Gd elemental maps. Gd is not homogeneously distributed, and cluster formation is observed by comparing the Gd and Ce maps. Note that in elemental maps, there is an anti-correlation between the Gd and Ce signals. However, the Gd map is very noisy making it difficult to provide more detail information of the Gd distribution. Because the Gd signal is weak, we have developed a hybrid approach that relies primarily on the stronger Ce EELS signal and HAADF signals to deduce the Gd content. The method assumes that Gd ions substitute for Ce and that the HAADF cation signal is proportional to the total number of cations in the column. Figure 2 is a plot of the HAADF column intensity versus the sum of Ce+ Gd column intensity from the EELS maps (total EELS cation signal) for all the columns in Figure 1. Figure 2 shows that there is the linear relationship between these two integrated intensities. This implies that, for a particular column, a comparison of the Ce column intensity with the corresponding HAADF column intensity should allow the Gd EELS signal to be deduced. The Gd signal is then determined by subtracting Ce EELS signal from suitable scaled HAADF signal. Figure 3 shows results for local Gd column concentration determined with the traditional and hybrid methods. Both methods can successfully determine the concentration variation and showed the …