Department of Materials Science and Engineering, Iowa State University, Ames, IA 50011, USA.
Ultramicroscopy. 2013 Sep;132:136-42. doi: 10.1016/j.ultramic.2013.02.013. Epub 2013 Feb 16.
The purpose of this work is to develop a methodology to estimate the APT reconstruction parameters when limited crystallographic information is available. Reliable spatial scaling of APT data currently requires identification of multiple crystallographic poles from the field desorption image for estimating the reconstruction parameters. This requirement limits the capacity of accurately reconstructing APT data for certain complex systems, such as highly alloyed systems and nanostructured materials wherein more than one pole is usually not observed within one grain. To overcome this limitation, we develop a quantitative methodology for calibrating the reconstruction parameters in an APT dataset by ensuring accurate inter-planar spacing and optimizing the curvature correction for the atomic planes corresponding to a single crystallographic orientation. We validate our approach on an aluminum dataset and further illustrate its capabilities by computing geometric reconstruction parameters for W and Al-Mg-Sc datasets.
这项工作的目的是开发一种方法来估计有限晶体学信息可用时的 APT 重建参数。目前,可靠的 APT 数据空间标度需要从场解吸图像中识别多个晶体极点来估计重建参数。这一要求限制了准确重建某些复杂系统(如高合金系统和纳米结构材料)的 APT 数据的能力,因为在一个晶粒内通常观察不到一个以上的极点。为了克服这一限制,我们开发了一种定量方法,通过确保准确的面间距和优化对应于单一晶体取向的原子面的曲率校正,来校准 APT 数据集的重建参数。我们在铝数据集上验证了我们的方法,并通过计算 W 和 Al-Mg-Sc 数据集的几何重建参数进一步说明了其能力。