Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-28T03:08:32.241Z Has data issue: false hasContentIssue false
  • English
  • Français

Building a Library of Simulated Atom Probe Data for Different Crystal Structures and Tip Orientations Using TAPSim

Published online by Cambridge University Press:  18 February 2019

Markus Kühbach Open the ORCID record for Markus Kühbach [Opens in a new window] ,
Andrew Breen ,
Michael Herbig  and
Baptiste Gault Open the ORCID record for Baptiste Gault [Opens in a new window]
Markus Kühbach*
Affiliation:
Max-Planck-Institut für Eisenforschung GmbH, Max-Planck-Str. 1, D-40237 Düsseldorf, Germany
Andrew Breen
Affiliation:
Max-Planck-Institut für Eisenforschung GmbH, Max-Planck-Str. 1, D-40237 Düsseldorf, Germany
Michael Herbig
Affiliation:
Max-Planck-Institut für Eisenforschung GmbH, Max-Planck-Str. 1, D-40237 Düsseldorf, Germany
Baptiste Gault
Affiliation:
Max-Planck-Institut für Eisenforschung GmbH, Max-Planck-Str. 1, D-40237 Düsseldorf, Germany
*
*Author for correspondence: Markus Kühbach, E-mail: [email protected]
Get access

Abstract

The process of building an open source library of simulated field desorption maps for differently oriented synthetic tips of the face-centered cubic, body-centered cubic, and hexagonal-close-packed crystal structures using the open source software TAPSim is reported. Specifically, the field evaporation of a total set of 4 × 101 single-crystalline tips was simulated. Their lattices were oriented randomly to sample economically the fundamental zone of crystal orientations. Such data are intended to facilitate the interpretation of low-density zone lines and poles that are observed on detector hit maps during Atom Probe Tomography (APT) experiments. The datasets and corresponding tools have been made publicly available to the APT community in an effort to provide better access to simulated atom probe datasets. In addition, a computational performance analysis was conducted, from which recommendations are made as to which key tasks should be optimized in the future to improve the parallel efficiency of TAPSim.

Keywords

atom probe crystallographyAtom Probe TomographyTAPSimmachine learningdata mining
Type
Data Analysis
Information
Microscopy and Microanalysis , Volume 25 , Special Issue 2: Atom Probe Tomography and Microscopy APT&M 2018 , April 2019 , pp. 320 - 330
Copyright
Copyright © Microscopy Society of America 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Amdahl, GM (1967). Validity of the single processor approach to achieving large-scale computer capabilities. AFIPS ‘67 (Spring) Proceedings of the April 18–20, 1967, Spring Joint Computer Conference, vol. 30, pp. 483–485.Google Scholar
Araullo-Peters, VJ, Breen, A, Ceguerra, AV, Gault, B, Ringer, SP & Cairney, JM (2015). A new systematic framework for crystallographic analysis of atom probe data. Ultramicroscopy 154, 7–14.Google Scholar
Araullo-Peters, VJ, Gault, B, Shrestha, SL, Yao, L, Moody, MP, Ringer, SP & Cairney, JM (2012). Atom probe crystallography: Atomic-scale 3-D orientation mapping. Scr Mater 66, 907–910.Google Scholar
Brannon, R M (2002). A review of useful theorems involving proper orthogonal matrices referenced to three-dimensional physical space. Tech. rep., Sandia National Laboratories. Available at https://www.mech.utah.edu/~brannon/public/rotation.pdf.Google Scholar
Breen, AJ, Babinsky, K, Day, AC, Eder, K, Oakman, CJ, Trimby, PW, Primig, S, Cairney, JM & Ringer, SP (2017). Correlating atom probe crystallographic measurements with Transmission Kikuchi Diffraction Data. Microsc Microanal 23, 279–290.Google Scholar
Ceguerra, AV, Breen, AJ, Stephenson, LT, Felfer, PJ, Araullo-Peters, VJ, Liddicoat, PV, Cui, XY, Yao, L, Haley, D, Moody, MP, Gault, B, Cairney, JM & Chang, CST (2013). The rise of computational techniques in Atom Probe Microscopy. Curr Opin Solid State Mater Sci 17, 224–235.10.1016/j.cossms.2013.09.006Google Scholar
Chandra, R, Dagum, L, Kohr, D, Maydan, D, Mcdonald, J & Menon, R (2001). Parallel Programming in OpenMP, 1st ed. San Francisco: Morgan Kaufmann.Google Scholar
de Cougny, HL, Devine, KD, Flaherty, JE, Loy, RM, Ozturan, C & Shephard, MS (1994). Load balancing for the parallel adaptive solution of partial-differential equations. Appl Numer Math 16, 157–182.Google Scholar
de Cougny, HL & Shephard, MS (1999). Parallel refinement and coarsening of tetrahedral meshes. Int J Numer Methods Eng 46, 1101–1125.10.1002/(SICI)1097-0207(19991110)46:7<1101::AID-NME741>3.0.CO;2-E3.0.CO;2-E>Google Scholar
Devaraj, A, Perea, DE, Liu, J, Gordon, LM, Prosa, TJ, Parikh, P, Diercks, DR, Meher, S, Kolli, RP, Meng, YS & Thevuthasan, S (2018). Three-dimensional nanoscale characterisation of materials by Atom Probe Tomography. Int Mater Rev 63, 68–101.Google Scholar
Downs, RT & Hall-Wallace, M (2003). The American mineralogist crystal structure database. Am Mineral 88, 247–250.Google Scholar
Eaton, HC & Lee, L (1982). The simulation of images in the field ion microscope: Specimens of arbitrary crystal structure and orientation. J Appl Phys 53, 988–994.10.1063/1.330579Google Scholar
Felfer, P, Scherrer, B, Demeulemeester, J, Vandervorst, W & Cairney, JM (2015). Mapping interfacial excess in atom probe data. Ultramicroscopy 159, 438–444.Google Scholar
Fryxell, B, Olson, K, Ricker, P, Timmes, FX, Zingale, M, Lamb, DQ, Macneice, P, Rosner, R, Truran, JW & Tufo, H (2000). Flash: An adaptive mesh hydrodynamics code for modeling astrophysical thermonuclear ashes. Astrophys J Suppl Ser 131, 273–334.Google Scholar
Gault, B, Haley, D, De Geuser, F, Moody, MP, Marquis, EA, Larson, DJ & Geiser, BP (2011 a). Advances in the reconstruction of Atom Probe Tomography data. Ultramicroscopy 111, 448–457.Google Scholar
Gault, B, Loi, ST, Araullo-Peters, VJ, Stephenson, LT, Moody, MP, Shrestha, SL, Marceau, RKW, Yao, L, Cairney, JM & Ringer, SP (2011 b). Dynamic reconstruction for Atom Probe Tomography. Ultramicroscopy 111, 1619–1624.10.1016/j.ultramic.2011.08.005Google Scholar
Gault, B, Moody, MP, Cairney, JM & Ringer, SP (2012). Atom Probe Microscopy, 1st ed. New York: Springer.10.1007/978-1-4614-3436-8Google Scholar
Geiser, BP, Larson, DJ, Gerstl, SSA, Reinhard, D, Kelly, TF, Prosa, TJ & Olson, JD (2009). A system for simulation of tip evolution under field evaporation. Microsc Microanal 15, 302–303.Google Scholar
Geuser, FD, Lefebvre, W, Danoix, F, Vurpillot, F, Forbord, B & Blavette, D (2007). An improved reconstruction procedure for the correction of local magnification effects in three-dimensional atom-probe. Surf Interface Anal 39, 268–272.Google Scholar
Gražulis, S, Chateigner, D, Downs, RT, Yokochi, AT, Quirós, M, Lutterotti, L, Manakova, E, Butkus, J, Moeck, P & Le Bail, A (2009). Crystallography Open Database—an open-access collection of crystal structures. J Appl Crystallogr 42, 726–729.Google Scholar
He, MR, Kim, SKSG, Felfer, PJ, Breen, AJ, Cairney, JM & Gianola, DS (2016). Linking stress-driven microstructural evolution in nanocrystalline aluminium with grain boundary doping of oxygen. Nat Commun 7, 11225.Google Scholar
Jägle, EA, Choi, PP & Raabe, D (2014). The maximum separation cluster analysis algorithm for atom-probe tomography: Parameter determination and accuracy. Microsc Microanal 20, 1662–1671.Google Scholar
Kelly, TF, Miller, MK, Rajan, K & Ringer, SP (2013). Atomic-scale tomography: A 2020 vision. Microsc Microanal 19, 652–664.10.1017/S1431927613000494Google Scholar
Kingham, DR (1982). The post-ionization of field evaporated ions: A theoretical explanation of multiple charge states. Surf Sci 116, 273–301.Google Scholar
Kühbach, M & Breen, A (2018 a). Milling of single-crystalline tips supplementary material: Zenodo open source data repository. Tech. rep. GmbH, Düsseldorf: Max-Planck-Institut für Eisenforschung. Available at https://zenodo.org/record/1466804.Google Scholar
Kühbach, M & Breen, A (2018 b). Milling of single-crystalline tips: Zenodo open source data repository. Tech. rep. Düsseldorf: Max-Planck-Institut für Eisenforschung, GmbH. Available at https://zenodo.org/record/1213680.Google Scholar
Kühbach, M & Breen, A (2018 c). Single-crystalline Al tips: Zenodo open source data repository. Tech. rep. Düsseldorf: Max-Planck-Institut für Eisenforschung, GmbH. Available at https://zenodo.org/record/1310632.Google Scholar
Kühbach, M & Breen, A (2018 d). Single-crystalline Mg tips: Zenodo open source data repository. Tech. rep. Düsseldorf: Max-Planck-Institut für Eisenforschung, GmbH. Available at https://zenodo.org/record/1311548.Google Scholar
Kühbach, M & Breen, A (2018 e). Single-crystalline W tips: Zenodo open source data repository. Tech. rep. Düsseldorf: Max-Planck-Institut für Eisenforschung, GmbH. Available at https://zenodo.org/record/1311617.Google Scholar
Kühbach, M & Breen, A (2018 f). Single-crystalline Zr tips: Zenodo open source data repository. Düsseldorf: Tech. rep. Max-Planck-Institut für Eisenforschung, GmbH. Available at https://zenodo.org/record/1311549.Google Scholar
Larson, DJ, Gault, B, Geiser, BP, De Geuser, F & Vurpillot, F (2013). Atom Probe Tomography spatial reconstruction: Status and directions. Curr Opin Solid State Mater Sci 17, 236–247.Google Scholar
Larson, DJ, Geiser, BP, Prosa, TJ, Gerstl, SSA, Reinhard, DA & Kelly, TF (2011). Improvements in planar feature reconstructions in atom probe tomography. J Microsc 243, 15–30.10.1111/j.1365-2818.2010.03474.xGoogle Scholar
Lefebvre, W, Vurpillot, F & Sauvage, X (2016). Atom Probe Tomography: Put Theory into Practice, 1st ed. Amsterdam: Academic Press.Google Scholar
Loseille, A, Menier, V & Alauzet, F (2015). Parallel generation of large-size adapted meshes. Procedia Eng 124, 57–69.Google Scholar
Marquis, EA & Hyde, JM (2010). Applications of atom-probe tomography to the characterisation of solute behaviours. Mater Sci Eng R 69, 37–62.Google Scholar
Miller, M (1996). Atom Probe Field Ion Microscopy. Oxford, UK: Clarendon Press.Google Scholar
Momma, K & Izumi, F (2008). VESTA: A three-dimensional visualization system for electronic and structural analysis. J Appl Crystallogr 41, 653–658.Google Scholar
Momma, K & Izumi, F (2011). VESTA 3 for three-dimensional visualization of crystal, volumetric and morphology data. J Appl Crystallogr 44, 1272–1276.10.1107/S0021889811038970Google Scholar
Momma, K & Izumi, F (2014). VESTA: a Three-Dimensional Visualization System for Electronic and Structural Analysis — The VESTA Manual, August 6, 2014. Tech. rep. Czech and Slovak Crystallographic Association (CSCA). Available at https://www.xray.cz/kryst/Vesta_manual.pdf.Google Scholar
Moody, MP, Tang, F, Gault, B, Ringer, SP & Cairney, JM (2011). Atom probe crystallography: Characterization of grain boundary orientation relationships in nanocrystalline aluminium. Ultramicroscopy 111, 493–499.Google Scholar
Moore, AJW (1981). The simulation of FIM desorption patterns. Philos Mag A 43, 803–814.Google Scholar
Müller, EW (1956). Field desorption. Phys Rev 102, 618–624.Google Scholar
Oberdorfer, C (2014 a). Numeric simulation of atom probe tomography. PhD Thesis, Westfälische Wilhelms-Universität Münster, Münster, Germany.Google Scholar
Oberdorfer, C (2014 b). TAPSim How-to. Tech. rep. Institute of Materials Physics, University of Münster.Google Scholar
Oberdorfer, C, Eich, SM, Lütkemeyer, M & Schmitz, G (2015). Applications of a versatile modelling approach to 3d atom probe simulations. Ultramicroscopy 159, 184–194.Google Scholar
Oberdorfer, C, Eich, SM & Schmitz, G (2013). A full-scale simulation approach for atom probe tomography. Ultramicroscopy 128, 55–67.Google Scholar
Oberdorfer, C, Withrow, T, Fisher, LJYK, Marquis, EA & Windl, W (2018). Influence of surface relaxation on solute atoms positioning within atom probe tomography reconstructions. Mater Charact 146, 324–335.Google Scholar
Owen, SJ, Brown, JA, Ernst, CD, Lim, H & Long, KN (2017). Hexahedral mesh generation for Computational Materials Modeling. 26th International Meshing Roundtable, (IMR26 2017), vol. 203, 167–179.Google Scholar
Sanchez, A (2018). Scatplot scatter plot with color indicating data density. Tech. rep. Available at https://de.mathworks.com/matlabcentral/fileexchange/8577-scatplot.Google Scholar
Shoemake, K (1992). Uniform random rotations. Graphics Gems III, Kirk D, ed., pp. 124–132. London: Academic Press.Google Scholar
Vurpillot, F, Bostel, A & Blavette, D (1999 a). The shape of field emitters and the ion trajectories in three-dimensional atom probes. J Microsc 196, 332–336.Google Scholar
Vurpillot, F, Bostel, A, Menand, A & Blavette, D (1999 b). Trajectories of field emitted ions in 3d atom-probe. The European Physics Journal 6, 217–221.Google Scholar
Wei, Y, Gault, B, Varanasi, RS, Raabe, D, Herbig, M & Breen, A (2018). Machine-learning-based atom probe crystallographic analysis. Ultramicroscopy 194, 15–24.Google Scholar
Yao, L (2016). A filtering method to reveal crystalline patterns from atom probe microscopy desorption maps. MethodsX 3, 268–273.10.1016/j.mex.2016.03.012Google Scholar
Yao, L, Ringer, SP, Cairney, JM & Miller, MK (2013). The anatomy of grain boundaries: Their structure and atomic-level solute distribution. Scr Mater 69, 622–625.Google Scholar
Supplementary material: PDF

Kühbach et al. supplementary material

Kühbach et al. supplementary material 1

Download Kühbach et al. supplementary material(PDF)
PDF 2.3 MB
Supplementary material: File

Kühbach et al. supplementary material

Kühbach et al. supplementary material 2

Download Kühbach et al. supplementary material(File)
File 31.7 KB
Supplementary material: File

Kühbach et al. supplementary material

Kühbach et al. supplementary material 3

Download Kühbach et al. supplementary material(File)
File 30.3 KB