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 136 条
  • [1] Investigation of the ordering and atomic site occupancies of Nb-doped TiAl/Ti3Al intermetallics
    Al-Kassab, Tala'at
    Yuan, Yong
    Kluthe, Christian
    Boll, Torben
    Liu, Zhi-Guo
    [J]. SURFACE AND INTERFACE ANALYSIS, 2007, 39 (2-3) : 257 - 261
  • [2] Alam T., 2008, MATER FORUM, P1
  • [3] Precipitation and clustering in the early stages of ageing in Inconel 718
    Alam, Talukder
    Chaturvedi, Mahesh
    Ringer, Simon P.
    Cairney, Julie M.
    [J]. MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING, 2010, 527 (29-30): : 7770 - 7774
  • [4] Site occupation preference of Fe in Ni3Al: An atom-probe study
    Almazouzi, A
    Numakura, H
    Koiwa, M
    Hono, K
    Sakurai, T
    [J]. INTERMETALLICS, 1997, 5 (01) : 37 - 43
  • [5] Quantitative APT analysis of Ti(C,N)
    Angseryd, J.
    Liu, F.
    Andren, H-O.
    Gerstl, S. S. A.
    Thuvander, M.
    [J]. ULTRAMICROSCOPY, 2011, 111 (06) : 609 - 614
  • [6] [Anonymous], 1988, EXP HIGH RES EL MICR
  • [7] Microstructural evolution during ageing of Al-Cu-Li-x alloys
    Araullo-Peters, Vicente
    Gault, Baptiste
    de Geuser, Frederic
    Deschamps, Alexis
    Cairney, Julie M.
    [J]. ACTA MATERIALIA, 2014, 66 : 199 - 208
  • [8] A new systematic framework for crystallographic analysis of atom probe data
    Araullo-Peters, Vicente J.
    Breen, Andrew
    Ceguerra, Anna V.
    Gault, Baptiste
    Ringer, Simon P.
    Cairney, Julie M.
    [J]. ULTRAMICROSCOPY, 2015, 154 : 7 - 14
  • [9] Atom probe crystallography: Atomic-scale 3-D orientation mapping
    Araullo-Peters, Vicente J.
    Gault, Baptiste
    Shrestha, Sachin L.
    Yao, Lan
    Moody, Michael P.
    Ringer, Simon P.
    Cairney, Julie M.
    [J]. SCRIPTA MATERIALIA, 2012, 66 (11) : 907 - 910
  • [10] AURENHAMMER F, 1991, COMPUT SURV, V23, P345, DOI 10.1145/116873.116880