On the fabrication of atom probe tomography specimens of Al alloys at room temperature using focused ion beam milling with liquid Ga ion source

电解抛光 材料科学 聚焦离子束 离子铣床 原子探针 制作 离子 离子束 蒸发 分析化学(期刊) 复合材料 微观结构 电解质 化学 电极 物理化学 病理 物理 有机化学 热力学 医学 替代医学 色谱法 图层(电子)
作者
Soumita Mondal,Ujjval Bansal,Surendra Kumar Makineni
出处
期刊:Microscopy Research and Technique [Wiley]
卷期号:85 (9): 3040-3049 被引量:1
标识
DOI:10.1002/jemt.24151
摘要

Abstract In this work, a simple rectangular milling technique was demonstrated to prepare needle shape atom probe tomography (APT) specimens from Al alloys by focused‐ion‐beam (FIB) milling using Ga + ions at room temperature. Ga has high miscibility in Al owing to which electropolishing technique is preferred over Ga + ion FIB instruments for the fabrication of APT specimens. Although, site specific sample preparation is not possible by the electropolishing technique. This led to the motivation to demonstrate a new rectangular milling technique using Ga + FIB instrument that resulted a significant reduction of Ga + ion impregnation into the specimens. This is attributed to the reduction of milling time (<30 s at 30 kV acceleration voltage) and the use of lower currents (<0.3 nA) compared to the conventional annular milling method. The yield of specimens during field evaporation in APT was also significantly increased from around 8 million ions to more than 86 million ions due to the avoidance of Ga + ion embrittlement. Therefore, the currently demonstrated rectangular milling technique can be used to prepare APT specimens from Al‐alloys and obtained accurate compositions of matrix, phases, and hetero‐phase interfaces with Ga < 0.1 at%. Research Highlights Feasibility of using Ga + ions for the preparation of needle shaped specimens at room temperature from aluminum alloys. Demonstration of using a rectangular milling technique instead of annular milling technique that led to a significant reduction in impregnation of Ga + ions into the specimen needles. Due to very low Ga + ion damage, the yield of the APT data increased by 10–12 times.
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