Mining information from atom probe data

被引:56
|
作者
Cairney, Julie M. [1 ,2 ]
Rajan, Krishna [3 ]
Haley, Daniel [4 ,5 ]
Gault, Baptiste [4 ]
Bagot, Paula. J. [4 ]
Choi, Pyuck-Pa [5 ]
Felfer, Peter J. [1 ,2 ]
Ringer, Simon P. [1 ,2 ]
Marceau, Ross K. W. [6 ]
Moody, Michael P. [4 ]
机构
[1] Univ Sydney, Sch Aerosp Mech Mechatron Engn, Sydney, NSW 2006, Australia
[2] Univ Sydney, Australian Ctr Microscopy & Microanal, Sydney, NSW 2006, Australia
[3] Iowa State Univ, Dept Mat Sci & Engn, Ames, IA 50011 USA
[4] Univ Oxford, Dept Mat, Oxford OX1 3PH, England
[5] Max Planck Inst Eisenforsch GmbH, D-40237 Dusseldorf, Germany
[6] Deakin Univ, Geelong Technol Precinct, Inst Frontier Mat, Waurn Ponds, Vic 3216, Australia
关键词
Atom probe tomography; Microscopy; Data mining; Clustering; Short range order; Crystallography; GRAIN-BOUNDARY SEGREGATION; SHORT-RANGE ORDER; SPECIMEN PREPARATION; INTERFACIAL EXCESS; FIELD EVAPORATION; SITE OCCUPATION; TOMOGRAPHIC RECONSTRUCTION; FOURIER-TRANSFORM; SOLUTE; MICROSCOPY;
D O I
10.1016/j.ultramic.2015.05.006
中图分类号
TH742 [显微镜];
学科分类号
摘要
Whilst atom probe tomography (APT) is a powerful technique with the capacity to gather information containing hundreds of millions of atoms from a single specimen, the ability to effectively use this information creates significant challenges. The main technological bottleneck lies in handling the extremely large amounts of data on spatial-chemical correlations, as well as developing new quantitative computational foundations for image reconstruction that target critical and transformative problems in materials science. The power to explore materials at the atomic scale with the extraordinary level of sensitivity of detection offered by atom probe tomography has not been not fully harnessed due to the challenges of dealing with missing, sparse and often noisy data. Hence there is a profound need to couple the analytical tools to deal with the data challenges with the experimental issues associated with this instrument. In this paper we provide a summary of some key issues associated with the challenges, and solutions to extract or "mine" fundamental materials science information from that data. (C) 2015 Published by Elsevier B.V.
引用
收藏
页码:324 / 337
页数:14
相关论文
共 50 条
  • [1] Data Mining and Informatics for Quantitative Atom Probe Tomography
    Rajan, Krishna
    Aluru, S.
    Ganapathysubramanian, B.
    MICROSCOPY AND MICROANALYSIS, 2009, 15 : 264 - 265
  • [2] Data mining for isotope discrimination in atom probe tomography
    Broderick, Scott R.
    Bryden, Aaron
    Suram, Santosh K.
    Rajan, Krishna
    ULTRAMICROSCOPY, 2013, 132 : 121 - 128
  • [3] Advanced volume reconstruction and data mining methods in atom probe tomography
    Vurpillot, F.
    Lefebvre, W.
    Cairney, J. M.
    Oberdorfer, C.
    Geiser, B. P.
    Rajan, K.
    MRS BULLETIN, 2016, 41 (01) : 46 - 51
  • [4] Advanced volume reconstruction and data mining methods in atom probe tomography
    F. Vurpillot
    W. Lefebvre
    J. M. Cairney
    C. Oberdorfer
    B. P. Geiser
    K. Rajan
    MRS Bulletin, 2016, 41 : 46 - 52
  • [5] Mining Information from the Data Clouds
    Orange, Erica
    FUTURIST, 2009, 43 (04) : 17 - 21
  • [6] ANALYSIS OF DATA FROM AN OPTICAL ATOM-PROBE
    COOPER, AS
    CEREZO, A
    HYDE, JM
    MACKENZIE, RAD
    SMITH, GDW
    APPLIED SURFACE SCIENCE, 1994, 76 (1-4) : 409 - 415
  • [7] On the retrieval of crystallographic information from atom probe microscopy data via signal mapping from the detector coordinate space
    Wallace, Nathan D.
    Ceguerra, Anna, V
    Breen, Andrew J.
    Ringer, Simon R.
    ULTRAMICROSCOPY, 2018, 189 : 65 - 75
  • [8] Interpreting atom probe data from chromium oxide scales
    La Fontaine, Alexandre
    Gault, Baptiste
    Breen, Andrew
    Stephenson, Leigh
    Ceguerra, Anna V.
    Yang, Limei
    Nguyen, Thuan Dinh
    Zhang, Jianqiang
    Young, David J.
    Cairney, Julie M.
    ULTRAMICROSCOPY, 2015, 159 : 354 - 359
  • [9] Mining citation information from CiteSeer data
    Dalibor Fiala
    Scientometrics, 2011, 86 : 553 - 562
  • [10] Mining citation information from CiteSeer data
    Fiala, Dalibor
    SCIENTOMETRICS, 2011, 86 (03) : 553 - 562