journal article·2021-04

Development of Wide Field of View Three-Dimensional Field Ion Microscopy and High-Fidelity Reconstruction Algorithms to the Study of Defects in Nuclear Materials

Benjamin Klaes, Rodrigue Lardé, Fabien Delaroche, Constantinos Hatzoglou, Stefan Parvianien, Jonathan Houard, Gérald Da Costa, Antoine Normand, Martin Brault, Bertrand Radiguet, François Vurpillot

Microscopy and Microanalysis· Volume 27· Issue 2
Publisher page

Abstract

This article presents a fast and highly efficient algorithm developed to reconstruct a three-dimensional (3D) volume with a high spatial precision from a set of field ion microscopy (FIM) images, and specific tools developed to characterize crystallographic lattice and defects. A set of FIM digital images and image processing algorithms allow the construction of a 3D reconstruction of the sample at the atomic scale. The capability of the 3D FIM to resolve the crystallographic lattice and the finest defects in metals opens a new way to analyze materials. This spatial precision was quantified on tungsten, analyzed at different analyzing conditions. A specific data mining tool, based on Fourier transforms, was also developed to characterize lattice distortions in the reconstructed volumes. This tool has been used in simulated and experimental volumes to successfully locate and characterize defects such as dislocations and grain boundaries.
Source: openalex_inverted_index · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Advanced Materials Characterization Techniques · Ion-surface interactions and analysis · Fusion materials and technologies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (41)

Show source-provided references
1. 10.1088/0965-0393/18/8/08500110.1088/0965-0393/18/8/085001 ↗
2. 10.1017/S143192760707094810.1017/S1431927607070948 ↗
3. 10.1088/0965-0393/20/8/08500710.1088/0965-0393/20/8/085007 ↗
4. 10.1016/j.ultramic.2015.02.01710.1016/j.ultramic.2015.02.017 ↗
5. 10.1016/j.ultramic.2010.11.01610.1016/j.ultramic.2010.11.016 ↗
6. 10.1103/PhysRevE.83.02670410.1103/PhysRevE.83.026704 ↗
7. 10.1017/S143192761700387710.1017/S1431927617003877 ↗
8. 10.1016/j.susc.2006.10.01910.1016/j.susc.2006.10.019 ↗
10. 10.1007/978-1-4615-4281-010.1007/978-1-4615-4281-0 ↗
11. 10.1103/PhysRevB.57.755610.1103/PhysRevB.57.7556 ↗
12. Lefebvre-Ulrikson · 2016
13. 10.1088/0965-0393/18/1/01501210.1088/0965-0393/18/1/015012 ↗
14. 10.1002/sia.249010.1002/sia.2490 ↗
15. 10.1038/ncomms650110.1038/ncomms6501 ↗
16. 10.1007/978-1-4899-7430-310.1007/978-1-4899-7430-3 ↗
17. 10.1063/1.12654510.1063/1.126545 ↗
18. 10.1016/j.cossms.2013.09.00210.1016/j.cossms.2013.09.002 ↗
19. 10.1016/j.matt.2020.09.00310.1016/j.matt.2020.09.003 ↗
20. 10.1046/j.1365-2818.2001.00923.x10.1046/j.1365-2818.2001.00923.x ↗
21. Beckey · 1977
22. 10.1016/j.cpc.2015.07.01210.1016/j.cpc.2015.07.012 ↗
23. 10.1007/BF0132965110.1007/BF01329651 ↗
24. Gomer · 1961
25. 10.1119/1.235090110.1119/1.2350901 ↗
26. 10.1016/0039-6028(78)90057-210.1016/0039-6028(78)90057-2 ↗
27. Interpreting nanovoids in atom probe tomography data for accurate local compositional measurements
28. 10.1080/1478644510856131010.1080/14786445108561310 ↗
29. 10.1088/0959-5309/52/1/30410.1088/0959-5309/52/1/304 ↗
30. 10.1017/S143192761700027710.1017/S1431927617000277 ↗
31. 10.1051/epjap:199917310.1051/epjap:1999173 ↗
32. 10.1063/1.169868110.1063/1.1698681 ↗
33. 10.1039/C7NR02656K10.1039/C7NR02656K ↗
34. 10.1016/0029-554X(81)90718-710.1016/0029-554X(81)90718-7 ↗
35. A model to predict image formation in the three-dimensional field ion microscope
36. 10.1016/0039-6028(92)91063-H10.1016/0039-6028(92)91063-H ↗
37. 10.1016/0039-6028(71)90114-210.1016/0039-6028(71)90114-2 ↗
38. 10.1016/0169-4332(94)00561-310.1016/0169-4332(94)00561-3 ↗
40. 10.1080/0141861990821033210.1080/01418619908210332 ↗
41. 10.1017/S143192761501518410.1017/S1431927615015184 ↗