Hyperspectral X-ray imaging for nanometrology

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Resumo

A tool for X-ray hyperspectral imaging has been developed. It is based on a conventional CCD driven by an algorithm that allows resolution in both energy and position. A new algorithm has been developed that allows the real-time analysis of single photon events. The factors influencing the energy resolution, the formation of artifacts in the energy spectra, and the counting efficiency are analyzed. Furthermore, a method for achieving sub-pixel precision using the singular value decomposition is suggested. The algorithm has been tested on synthetic data and in a live experiment with the registration of X-ray fluorescence emission from a thin film structure. Applying hyperspectral imaging to grazing emission X-ray fluorescence opens up new possibilities in nanometrology.

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Sobre autores

А. Safonov

National Research Center “Kurchatov Institute”

Autor responsável pela correspondência
Email: Safonov_AIg@nrcki.ru
Rússia, Moscow

K. Nikolaev

National Research Center “Kurchatov Institute”; Moscow Institute of Physics and Technology (State University)

Email: Safonov_AIg@nrcki.ru
Rússia, Moscow; Moscow

S. Yakunin

National Research Center “Kurchatov Institute”

Email: Safonov_AIg@nrcki.ru
Rússia, Moscow

Bibliografia

  1. Zegenhagen J., Kazimirov A. X-ray Standing Wave Technique, The Principles And Applications. World Scientific, 2013. V. 7.
  2. Ковальчук М.В., Новикова Н.Н., Якунин С.Н. // Природа. 2012. № 12. С. 3.
  3. Kossel W., Loeck V., Voges H. // Z. Phys. 1935. B. 94. № 1. S. 139. https://doi.org/10.1007/BF01330803
  4. Baumann J., Kayser Y., Kanngießer B. // Phys. Status Solidi. B. 2021. V. 258. № 3. P. 2000471.
  5. Bergmann U., Glatzel P. // Photosynth. Res. 2009. V. 102. P. 255. Https://doi.org/10.1007/s11120-009-9483-6
  6. Лидер В.В. // Успехи физ. наук. 2018. Т. 188. № 10. С. 1081. https://doi.org/10.3367/UFNr.2017.07.038174
  7. Schioppa E.J. The Color of X-Rays: Spectral X-Ray Computed Tomography using Energy Sensitive Pixel Detectors. Amsterdam U., 2014. № CERN-THESIS-2014–179.
  8. Lazzari O., Jacques S., Sochi T., Barnes P. // Analyst. 2009. V. 134. № 9. P. 1802. https://doi.org/10.1039/B901726G
  9. Hönicke P., Kayser Y., Nikolaev K.V. et al. // Small. 2022. V. 18. P. 2105776. https://doi.org/10.1002/smll.202105776
  10. Staeck S., Andrle A., Hönicke P. et al. // Nanomaterials. 2022. V. 12. P. 3766. https://doi.org/10.3390/nano12213766
  11. Skroblin D., Herrero A.F., Siefke T. et al. // Nanoscale. 2022. V. 14. № 41. P. 15475. https://doi.org/10.1039/D2NR03046B
  12. Maiden A.M., Morrison G.R., Kaulich B. et al. // Nat. Commun. 2013. V. 4. № 1. P. 1669. https://doi.org/10.1038/ncomms2640
  13. Batey D.J., Cipiccia S., Van Assche F. et al. // Sci. Rep. 2019. V. 9. № 1. P. 12278. https://doi.org/10.1038/s41598-019-48642-y
  14. Fröjdh E. Hybrid Pixel Detectors: Characterization and Optimization: Thesis. Mid Sweden University, 2015.
  15. Pennicard D., Lange S., Smoljanin S. et al. // J. Phys. Conf. Ser. 2013. V. 425. № 6. P. 062010. https://doi.org/10.1088/1742-6596/425/6/062010
  16. Catura R.C., Smithson R.C. // Rev. Sci. Instrum. 1979. V. 50. № 2. P. 219. https://doi.org/10.1063/1.1135790
  17. Bailey R., Damerell C.J.S., English R.L. et al. // Nucl. Instrum. Methods. 1983. V. 213. № 2–3. P. 201. https://doi.org/10.1016/0167-5087(83)90413-1
  18. Walton D., Stem R.A., Catura R.C. et al. // Proc. SPIE. 1984. V. 501. P. 306. https://doi.org/10.1117/12.944675
  19. Pinotti E., Bräuninger H., Findeis N. et al. // Nucl. Instrum. Methods Phys. Res. A. 1993. V. 326. № 1–2. P. 85. https://doi.org/10.1016/0168-9002(93)90337-H
  20. Hynecek J. // IEEE Trans. Electron Devices. 1992. V. 39. № 8. P. 1972. https://doi.org/10.1109/16.144694
  21. Turner M.J.L., Abbey A., Arnaud M. et al. // Astron. Astrophys. 2001. V. 365. № 1. P. L27. https://doi.org/10.1051/0004-6361:20000087
  22. Gendreau K.C. X-Ray CCDS for Space Applications: Calibration, Radiation Hardness, and Use for Measuring the Spectrum of the Cosmic X-Ray Background: Thesis. Massachusetts Institute of Technology, 1995.
  23. Baumann J., Gnewkow R., Staeck S. et al. // J. Anal. At. Spectrom. 2018. V. 33. № 12. P. 2043. https://doi.org/10.1039/C8JA00212F
  24. Allen F.G., Gobeli G.W. // Phys. Rev. 1962. V. 127. № 1. P. 150. https://doi.org/10.1103/PhysRev.127.150
  25. Tamm I. // Z. Phys. 1932. B. 76. № 11–12. S. 849. https://doi.org/10.1007/BF01341581
  26. El Gamal A., Eltoukhy H. // IEEE Circuit. Devic. 2005. V. 21. № 3. P. 6. https://doi.org/10.1109/MCD.2005.1438751
  27. Белоус Д.А. // Изв. вузов России. Радиоэлектроника. 2017. № 3. С. 60.
  28. Ильин А.А., Виноградов А.Н., Егоров В.В. и др. // Современные проблемы дистанционного зондирования Земли из космоса. 2013. Т. 10. № 3. С. 106.
  29. Юшкин М.В., Клочкова В.Г. Комплекс программ обработки эшелле-спектров. Препринт САО. 2004. № 206.
  30. Ишханов Б.С., Капитонов И.М., Кэбин Э.И. Частицы и ядра. Эксперимент. М.: МАКС Пресс, 2013. С. 260.
  31. Jakubek J. // Nucl. Instrum. Methods Phys. Res. A. 2009. V. 607. № 1. P. 192. https://doi.org/10.1016/j.nima.2009.03.148
  32. Prigozhin G., Butler N.R., Kissel S.E., Ricker G.R. // IEEE Trans. Electron Devices. 2003. V. 50. № 1. P. 246. https://doi.org/10.1109/TED.2002.806470
  33. Abboud A., Send S., Pashniak N. et al. // J. Instrum. 2013. V. 8. № 05. P. P05005. https://doi.org/10.1088/1748-0221/8/05/P05005
  34. Blaj G., Chang C.E., Kenney C.J. // AIP Conf. Proc. 2019. V. 2054. № 1. P. 060077. https://doi.org/10.1063/1.5084708
  35. Hernández G., Fernández F. // Appl. Phys. B. 2018. V. 124. P. 1. https://doi.org/10.1007/s00340-018-6982-1
  36. Shustov A.E., Ulin S.E. // Phys. Proc. 2015. V. 74. P. 399. https://doi.org/10.1016/j.phpro.2015.09.210
  37. Dutton T.E., Woodward W.F., Lomheim T.S. // P. Soc. Photo. Opt. Ins. 1998. V. 3301. P. 52. https://doi.org/10.1117/12.304568
  38. Тучин М.С., Бирюков А.В., Захаров А.И., Прохоров М.Е. // Механика, управление и информатика. 2013. № 13. С. 249.
  39. Christen F., Kuijken K., Baade D. et al. // Scientific Detectors for Astronomy 2005: Explorers of the Photon Odyssey. Dordrecht: Springer Netherlands, 2006. P. 543.
  40. Fumo P., Waldron E., Laine J.P., Evans G. // J. Astron. Telesc. Instrum. Syst. 2015. V. 1. № 2. P. 028002. https://doi.org/10.1117/1.JATIS.1.2.028002
  41. Старовойтов В.В. // Информатика. 2017. № 2. С. 70.
  42. Narwaria M., Lin W. // IEEE Trans. Systems, Man, Cybernetics. B. 2011. V. 42. № 2. P. 347. https://doi.org/10.1109/TSMCB.2011.2163391
  43. Gerbrands J.J. // Pattern Recognit. 1981. V. 14. № 1–6. P. 375. https://doi.org/10.1016/0031-3203(81)90082-0
  44. Jha S.K., Yadava R.D.S. // IEEE Sens. J. 2010. V. 11. № 1. P. 35. https://doi.org/10.1109/JSEN.2010.2049351
  45. Feller W. Courant Anniversary Volume. New York, 1948. P. 105.
  46. Evans R.D., Evans R.D. The Atomic Nucleus. New York: McGraw-Hill, 1955. P. 582.
  47. Lee S.H., Gardner R.P. // Appl. Radiat. Isot. 2000. V. 53. № 4–5. P. 731. https://doi.org/10.1016/S0969-8043(00)00261-X
  48. Patil A., Usman S. // Nucl. Technol. 2009. V. 165. № 2. P. 249. https://doi.org/10.13182/NT09-A4090
  49. Fano U. // Phys. Rev. 1947. V. 72. № 1. P. 26. https://doi.org/10.1103/PhysRev.72.26
  50. Abboud A., Send S., Pashniak N. et al. // J. Instrum. 2013. V. 8. P. P05005. https://doi.org/10.1088/1748-0221/8/05/P05005
  51. Kondratev O.A., Makhotkin I.A., Yakunin S.N. // Appl. Surf. Sci. 2022. V. 574. P. 151573. https://doi.org/10.1016/j.apsusc.2021.151573
  52. Nikolaev K.V., Safonov A.I., Kondratev O.A. et al. // J. Appl. Cryst. 2023. V. 56. № 5. P. 1435. https://doi.org/10.1107/S1600576723007112
  53. Solé V.A., Papillon E., Cotte M. et al. // Spectrochim. Acta. B. 2007. V. 62. № 1. P. 63. https://doi.org/10.1016/j.sab.2006.12.002

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2. Рис. 1. Блок-схема алгоритма, реализующего позиционно-чувствительный энергодисперсионный анализатор.

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3. Fig. 2. Energy distribution of readout noise and the boron Kα line.

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4. Fig. 3. Dependence of the energy distribution of the Kα line (8047 eV) and Kβ line (8905 eV) of copper on the row number (a) and in the extreme rows (b).

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5. Fig. 4. Dependence of the registered photon flux (a) and counting efficiency (b) on the detector load.

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6. Fig. 5. Spectra obtained from a series of simulated frames (squares are overlap peaks).

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7. Fig. 6. Fluorescence spectrum of the W(3 nm)/Ti(16 nm)/W(3 nm) sample: asterisks are fluorescent lines of the experimental equipment, triangles are peaks of emission, squares are peaks of overlap.

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8. Fig. 7. Hyperspectral image (a) and spatial distributions of the titanium Kα line doublet (b) and tungsten Lα1 line (c) on a CCD matrix.

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