Automated voxelization of 3D atom probe data through kernel density estimation

被引：5

作者：

Srinivasan, Srikant ^{[1
]}

Kaluskar, Kaustubh ^{[1
]}

Dumpala, Santoshrupa ^{[1
]}

Broderick, Scott ^{[1
]}

Rajan, Krishna ^{[1
]}

机构：

[1] Iowa State Univ, Dept Mat Sci & Engn, Inst Combinatorial Discovery, Ames, IA 50011 USA

来源：

ULTRAMICROSCOPY | 2015年 / 159卷

关键词：

APT; Informatics; Kernel density estimation; Interfaces; Ni Alloy;

D O I：

10.1016/j.ultramic.2015.03.012

中图分类号：

TH742 [显微镜];

学科分类号：

摘要：

Identifying nanoscale chemical features from atom probe tomography (APT) data routinely involves adjustment of voxel size as an input parameter, through visual supervision, making the final outcome user dependent, reliant on heuristic knowledge and potentially prone to error. This work utilizes Kernel density estimators to select an optimal voxel size in an unsupervised manner to perform feature selection, in particular targeting resolution of interfacial features and chemistries. The capability of this approach is demonstrated through analysis of the gamma / gamma' interface in a Ni-Al-Cr superalloy. (C) 2015 Elsevier B.V. All rights reserved.

引用

页码：381 / 386

页数：6

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