Advanced Acquisition Strategies for Lab-Based Diffraction Contrast Tomography
Source abstract
Abstract
Three new advanced acquisition strategies for lab-based diffraction contrast tomography are presented. They are named Helical Phyllotaxis, Helical Phyllotaxis Raster, and Helical Phyllotaxis HART and enable grain mapping of longer, larger, high-aspect ratio samples. The implementation of these advanced acquisition strategies combines a golden angle rotation with vertical and horizontal translations to perform a seamless data collection that has a uniform sample illumination both angularly and spatially. Reconstruction of the corresponding data is equally seamless, simultaneously using all data to reconstruct the full illuminated volume without the need for registration or stitching of data subsets or sample subvolumes. Examples of performing Helical Phyllotaxis and Helical Phyllotaxis Raster scans on a selection of samples, which have either been mapped previously or come from the same batch of samples, show a substantial reduction in data collection time and/or a significant improvement in grain statistics. The Helical Phyllotaxis HART (high-aspect ratio tomography for plate-like samples) strategy enables investigations of a hitherto inaccessible class of sample geometries comprising industrially relevant materials like rolled metal sheets and electrical steels. The advanced acquisition strategies take lab-based non-destructive 3D grain mapping to the next level of throughput, grain statistics and versatility and hold great promise for integrated computational materials science and engineering applications. While the throughput warrants 4D studies of materials microstructural evolution, a representative sample volume is a prerequisite for successful model predictions of the evolution, and the versatility enables studies of samples or components under more realistic in situ or in operando conditions.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Microstructure and mechanical properties · Non-Destructive Testing Techniques · Mineral Processing and Grinding
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (32)
Show source-provided references
1. Schmidt S, Olsen UL, Poulsen HF et al (2008) Direct observation of 3-D grain growth in Al-0.1% Mn. Scr Mater 59:491–494. https://doi.org/10.1016/j.scriptamat.2008.04.04910.1016/j.scriptamat.2008.04.049 ↗
2. Pokharel R, Lind J, Li SF et al (2015) In situ observation of bulk 3D grain evolution during plastic deformation in polycrystalline Cu. Int J Plast 67:217–234. https://doi.org/10.1016/j.ijplas.2014.10.01310.1016/j.ijplas.2014.10.013 ↗
3. Menasche DB, Shade PA, Lind J et al (2016) Correlation of thermally induced pores with microstructural features using high energy X-rays. Metall Mater Trans A. https://doi.org/10.1007/s11661-016-3712-310.1007/s11661-016-3712-3 ↗
4. Naragani DP, Shade PA, Kenesei P et al (2019) X-ray characterization of the micromechanical response ahead of a propagating small fatigue crack in a Ni-based superalloy. Acta Mater 179:342–359. https://doi.org/10.1016/j.actamat.2019.08.00510.1016/j.actamat.2019.08.005 ↗
5. Ludwig W, Schmidt S, Lauridsen EM, Poulsen HF (2008) X-ray diffraction contrast tomography: a novel technique for three-dimensional grain mapping of polycrystals. I. Direct beam case. J Appl Crystallogr 41:302–309. https://doi.org/10.1107/S002188980800168410.1107/S0021889808001684 ↗
6. King A, Johnson G, Engelberg D et al (2008) Observations of intergranular stress corrosion cracking in a grain-mapped polycrystal. Science (80-) 321:382–385. https://doi.org/10.1126/science.115621110.1126/science.1156211 ↗
7. Zhang J, Zhang Y, Ludwig W et al (2018) Three-dimensional grain growth in pure iron. Part I. Statistics on the grain level. Acta Mater 156:76–85. https://doi.org/10.1016/j.actamat.2018.06.02110.1016/j.actamat.2018.06.021 ↗
8. King A, Reischig P, Adrien J et al (2014) Polychromatic diffraction contrast tomography. Mater Charact 97:1–10. https://doi.org/10.1016/j.matchar.2014.07.02610.1016/j.matchar.2014.07.026 ↗
9. McDonald SA, Reischig P, Holzner C et al (2015) Non-destructive mapping of grain orientations in 3D by laboratory X-ray microscopy. Sci Rep 5:14665. https://doi.org/10.1038/srep1466510.1038/srep14665 ↗
10. Holzner C, Lavery L, Bale H et al (2016) Diffraction contrast tomography in the laboratory—applications and future directions. Micros Today 24:34–43. https://doi.org/10.1017/S155192951600058410.1017/S1551929516000584 ↗
11. Oddershede J, Sun J, Gueninchault N et al (2019) Non-destructive characterization of polycrystalline materials in 3D by laboratory diffraction contrast tomography. Integr Mater Manuf Innov 8:217–225. https://doi.org/10.1007/s40192-019-00135-610.1007/s40192-019-00135-6 ↗
12. Bachmann F, Bale H, Gueninchault N et al (2019) 3D grain reconstruction from laboratory diffraction contrast tomography. J Appl Crystallogr 52:643–651. https://doi.org/10.1107/S160057671900544210.1107/S1600576719005442 ↗
13. Guinier A, Tennevin J (1949) Sur deux variantes de la méthode de laue et leurs applications. Acta Crystallogr 2:133–138. https://doi.org/10.1107/S0365110X4900037010.1107/S0365110X49000370 ↗
14. Kobayashi M, Zhang Y, Ishikawa H et al (2021) Investigation of relationships between grain structure and inhomogeneous deformation by means of laboratory-based multimodal X-ray tomography: strain accuracy analysis. Exp Mech. https://doi.org/10.1007/s11340-021-00701-010.1007/s11340-021-00701-0 ↗
15. Rothen F, Koch A-J (1989) Phyllotaxis, or the properties of spiral lattices. – I. Shape invariance under compression. J Phys 50:633–657. https://doi.org/10.1051/jphys:0198900500606330010.1051/jphys:01989005006063300 ↗
16. Gajjar P, Jørgensen JS, Godinho JRA et al (2018) New software protocols for enabling laboratory based temporal CT. Rev Sci Instrum 89:093702. https://doi.org/10.1063/1.504439310.1063/1.5044393 ↗
17. Keinan R, Bale H, Gueninchault N et al (2018) Integrated imaging in three dimensions: providing a new lens on grain boundaries, particles, and their correlations in polycrystalline silicon. Acta Mater 148:225–234. https://doi.org/10.1016/j.actamat.2018.01.04510.1016/j.actamat.2018.01.045 ↗
18. Patterson BR, Dehoff RT, Sahi CA et al (2019) Integral mean curvature analysis of 3D grain growth : Linearity of dV/dt and mean grain volume. IOP Conf Ser Mater Sci Eng 580:012020. https://doi.org/10.1088/1757-899X/580/1/01202010.1088/1757-899X/580/1/012020 ↗
19. Niverty S, Sun J, Williams J et al (2019) A forward modeling approach to high-reliability grain mapping by laboratory diffraction contrast tomography (LabDCT). JOM 71:2695–2704. https://doi.org/10.1007/s11837-019-03538-010.1007/s11837-019-03538-0 ↗
20. Sun J, Holzner C, Bale H et al (2019) 3D crystal orientation mapping of recrystallization in severely cold-rolled pure iron using laboratory diffraction contrast tomography. ISIJ Int 60:528–533. https://doi.org/10.2355/isijinternational.isijint-2019-40510.2355/isijinternational.isijint-2019-405 ↗
21. Sun J, Lyckegaard A, Zhang YB et al (2017) 4D study of grain growth in armco iron using laboratory X-ray diffraction contrast tomography. IOP Conf Ser Mater Sci Eng 219:012039. https://doi.org/10.1088/1757-899X/219/1/01203910.1088/1757-899X/219/1/012039 ↗
22. Juul NY, Winther G, Dale D et al (2016) Elastic interaction between twins during tensile deformation of austenitic stainless steel. Scr Mater 120:1–4. https://doi.org/10.1016/j.scriptamat.2016.03.02210.1016/j.scriptamat.2016.03.022 ↗
23. Sun J, Petryshynets I, Meng L et al (2021) 3D Non-destructive characterization of electrical steels for quantitative texture analysis with lab-based X-ray diffraction contrast tomography. Integr Mater Manuf Innov. https://doi.org/10.1007/s40192-021-00245-010.1007/s40192-021-00245-0 ↗
24. Lyckegaard A, Poulsen HF, Ludwig W et al (2012) Box-scan: a novel 3DXRD method for studies of recrystallization and grain growth. Mater Sci Forum 715–716:518–520. https://doi.org/10.4028/www.scientific.net/MSF.715-716.51810.4028/www.scientific.net/MSF.715-716.518 ↗
25. Wright J, Giacobbe C, Majkut M (2020) New opportunities at the Materials Science Beamline at ESRF to exploit high energy nano-focus X-ray beams. Curr Opin SOLID STATE Mater Sci 24:10081810.1016/j.cossms.2020.100818 ↗
26. Hayashi Y, Hirose Y, Seno Y (2015) Polycrystal orientation mapping using scanning three-dimensional X-ray diffraction microscopy. J Appl Crystallogr 48:1094–1101. https://doi.org/10.1107/S160057671500989910.1107/S1600576715009899 ↗
27. Hayashi Y, Setoyama D, Hirose Y et al (2019) Intragranular three-dimensional stress tensor fields in plastically deformed polycrystals. Science (80-) 366:1492–1496. https://doi.org/10.1126/science.aax916710.1126/science.aax9167 ↗
28. Hektor J, Hall SA, Henningsson NA et al (2019) Scanning 3DXRD measurement of grain growth, stress, and formation of Cu 6 Sn 5 around a tin whisker during heat treatment. Materials (Basel) 12:1–16. https://doi.org/10.3390/ma1203044610.3390/ma12030446 ↗
29. Henningsson NA, Hall SA, Wright P (2020) Reconstructing intragranular strain fields in polycrystalline materials from scanning 3DXRD data. J Appl Crystallogr 53:314–32510.1107/S1600576720001016 ↗
30. Bargmann S, Klusemann B, Markmann J et al (2018) Generation of 3D representative volume elements for heterogeneous materials: a review. Prog Mater Sci 96:322–384. https://doi.org/10.1016/j.pmatsci.2018.02.00310.1016/j.pmatsci.2018.02.003 ↗
31. Cerrone A, Stein C, Pokharel R et al (2015) Implementation and verification of a microstructure-based capability for modeling microcrack nucleation in LSHR at room temperature. Model Simul Mater Sci Eng 23:035006. https://doi.org/10.1088/0965-0393/23/3/03500610.1088/0965-0393/23/3/035006 ↗
32. Ozturk T, Stein C, Pokharel R et al (2016) Simulation domain size requirements for elastic response of 3D polycrystalline materials. Model Simul Mater Sci Eng 24:015006. https://doi.org/10.1088/0965-0393/24/1/01500610.1088/0965-0393/24/1/015006 ↗