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Atomistic Modelling and Simulation of Transmission Electron Microscopy Images: Application to Intrinsic Defects of Graphene

  • Cyril GuedjEmail author
  • Léonard Jaillet
  • François Rousse
  • Stéphane Redon
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 947)

Abstract

The characterization of advanced materials and devices in the nanometer range requires complex tools to understand the precise links between structure and properties. This paper demonstrates that the modelling of graphene-based defects can be obtained efficiently for various atomic arrangements using the Brenner module of the SAMSON software platform. The signatures of all kinds of defects are computed in terms of energy and simulated scanning transmission electron microscopy images. The results are in good agreement with the majority of the available theoretical and experimental data. This original methodology is an excellent compromise between the speed and the precision required by the semiconductor industry and opens the possibility of realistic in-silico research conjugated to the experimental nanocharacterization of these promising materials. We propose a novel approach to compare the agreement between experiment and simulation by using the projected radial distribution function. The maximum projected Euclidian distance between the model and the experiment is always better than 100 pm.

Keywords

Atomic modelling Electron microscopy STEM Graphene Defects Microstructure Image simulation Materials Characterization Atomistic 

Notes

Acknowledgements

The invaluable contribution from the platform of nanocharacterization (PFNC) at MINATEC, Grenoble, France is respectfully acknowledged (https://www.minatec.org/en/). We would like to gratefully acknowledge funding from the European Research Council through the ERC Starting Grant No. 307629.

References

  1. 1.
    Novoselov, K.S., et al.: Electric field effect in atomically thin carbon films. Science 306, 5696 (2004)CrossRefGoogle Scholar
  2. 2.
    Geim, A.K., Novoselov, K.S.: The rise of graphene. Nat. Mater. 6, 183–191 (2007)CrossRefGoogle Scholar
  3. 3.
    Lee, C., et al.: Measurement of the elastic properties and intrinsic strength of monolayer graphene. Science 321(5887), 385–388 (2008)CrossRefGoogle Scholar
  4. 4.
    Chen, H., et al.: Mechanically strong, electrically conductive, and biocompatible graphene paper. Adv. Mater. 20(18), 3557–3561 (2008)CrossRefGoogle Scholar
  5. 5.
    Pei, Q.X., et al.: A molecular dynamics study of the mechanical properties of hydrogen functionalized graphene. Carbon 48(3), 898–904 (2010)CrossRefGoogle Scholar
  6. 6.
    Scarpa, F., et al.: Effective elastic mechanical properties of single layer graphene sheets. Nanotechnology 20(6), 1–11 (2009)CrossRefGoogle Scholar
  7. 7.
    Park, S., et al.: The effect of concentration of graphene nanoplatelets on mechanical and electrical properties of reduced graphene oxide papers. Carbon 50(12), 4573–4578 (2012)CrossRefGoogle Scholar
  8. 8.
    Lee, E., et al.: Electrical properties and photoconductivity of stacked-graphene carbon nanotubes. Adv. Mater. 22(16), 1854–1857 (2010)CrossRefGoogle Scholar
  9. 9.
    Allen, B.L., et al.: Carbon nanotube field-effect-transistor-based biosensors. Adv. Mater. 19(11), 1439–1451 (2007)CrossRefGoogle Scholar
  10. 10.
    Sorkin, V., Zhang, Y.W.: Graphene-based pressure nano-sensors. J. Mol. Model. 17(11), 2825–2830 (2011)CrossRefGoogle Scholar
  11. 11.
    Qureshi, A., et al.: Review on carbon-derived, solid-state, micro and nano sensors for electrochemical sensing applications. Diam. Relat. Mater. 18(12), 1401–1420 (2009)CrossRefGoogle Scholar
  12. 12.
    Joh, H.-I., et al.: Synthesis and properties of an atomically thin carbon nanosheet similar to graphene and its promising use as an organic thin film transistor. Carbon 55, 299–304 (2013)CrossRefGoogle Scholar
  13. 13.
    Yao, J., et al.: In situ chemical synthesis of SnO2–graphene nanocomposite as anode materials for lithium-ion batteries. Electrochem. Commun. 11(10), 1849–1852 (2009)CrossRefGoogle Scholar
  14. 14.
    Stankovich, S., et al.: Graphene-based composite materials. Nature 442(7100), 282–286 (2006)CrossRefGoogle Scholar
  15. 15.
    Brenner, D.W.: Empirical potential for hydrocarbons for use in simulating the chemical vapor deposition of diamond films. Phys. Rev. B 42, 9458–9471 (1990)CrossRefGoogle Scholar
  16. 16.
    Brenner, D.W.: The art and science of an analytic potential. Phys. Stat. Sol. (b) 217, 23–40 (2000)CrossRefGoogle Scholar
  17. 17.
    Brenner, D.W., et al.: A second-generation reactive empirical bond order (REBO) potential energy expression for hydrocarbons. J. Phys. Condens. Mater. 14, 783–802 (2002)CrossRefGoogle Scholar
  18. 18.
    Dyson, A.J., Smith, P.V.: Extension of the Brenner empirical interatomic potential to C-Si-H systems. Surf. Sci. 355, 140–150 (1996)CrossRefGoogle Scholar
  19. 19.
    Los, J.H., Fasolino, A.: Intrinsic long-range bond-order potential for carbon: performance in Monte Carlo simulations of graphitization. Phys. Rev. B 68, 024107 (2003)CrossRefGoogle Scholar
  20. 20.
    Stuart, S.J., et al.: A reactive potential for hydrocarbons with intermolecular interactions. J. Chem. Phys. 112, 6472 (2000)CrossRefGoogle Scholar
  21. 21.
    Brenner, D.W., et al.: Simulated engineering of nanostructures. In: Fourth Foresight Conference on Molecular Nanotechnology (1996)CrossRefGoogle Scholar
  22. 22.
    Sinnott, S.B., et al.: Model of carbon nanotube growth through chemical vapor deposition. Chem. Phys. Lett. 315, 25–30 (1999)CrossRefGoogle Scholar
  23. 23.
    Brenner, D.W., et al.: Molecular dynamics simulations of the nanometer-scale mechanical properties of compressed Buckminsterfullerene. Thin Solid Films 206, 220–223 (1991)CrossRefGoogle Scholar
  24. 24.
    Lehtinen, O., et al.: Effect of ion bombardment on a two-dimensional target: atomistic simulations of graphene irradiation. Phys. Rev. B 81(15), 153401 (2010)CrossRefGoogle Scholar
  25. 25.
    Bosson, et al.: Interactive physically-based structural modeling of hydrocarbon systems. J. Comput. Phys. 231(6), 2581–2598 (2012)zbMATHCrossRefGoogle Scholar
  26. 26.
    Los, J.H., Fasolino, A.: Monte Carlo simulations of carbon-based structures based on an extended Brenner potential. Comput. Phys. Commun. 147, 178–181 (2002)zbMATHCrossRefGoogle Scholar
  27. 27.
    Redon, S., et al.: Adaptive dynamics of articulated bodies. ACM Trans. Graph. (TOG) 24(3), 936–945 (2005)CrossRefGoogle Scholar
  28. 28.
    Koch, C.: Determination of core structure periodicity and point defect density along dislocations. Ph.D. thesis, Arizona State University (2002)Google Scholar
  29. 29.
    Crewe, A.V., Wall, J., Langmore, J.: Science 168, 1338 (1970)CrossRefGoogle Scholar
  30. 30.
    Egerton, R.: Mechanisms of radiation damage in beam-sensitive specimens, for TEM accelerating voltages between 10 and 300 kV. Microsc. Res. Tech. 75(11), 1550–1556 (2012)CrossRefGoogle Scholar
  31. 31.
    Biskupek, J., et al.: Effects of residual aberrations explored on single-walled carbon nanotubes. Ultramicroscopy 116, 1–7 (2012)CrossRefGoogle Scholar
  32. 32.
    Barthel, J., Thust, A.: On the optical stability of high-resolution transmission electron microscopes. Ultramicroscopy 134, 6–17 (2013)CrossRefGoogle Scholar
  33. 33.
    Schramm, S., et al.: Intrinsic instability of aberration- corrected electron microscopes. Phys. Rev. Lett. 109(16), 163901 (2012)CrossRefGoogle Scholar
  34. 34.
    Uhlemann, S., et al.: Thermal magnetic field noise limits resolution in transmission electron microscopy. Phys. Rev. Lett. 111, 046101 (2013)CrossRefGoogle Scholar
  35. 35.
    Lee, Z., et al.: Electron dose dependence of signal-to-noise ratio, atom contrast and resolution in transmission electron microscope images. Ultramicroscopy 145, 3–12 (2014)CrossRefGoogle Scholar
  36. 36.
    LeBeau, J.M., et al.: Phys. Rev. Lett. 100, 206101 (2008)CrossRefGoogle Scholar
  37. 37.
    LeBeau, J.M., et al.: Phys. Rev. B 79, 214110 (2009)CrossRefGoogle Scholar
  38. 38.
    Hytch, M.J., et al.: Ultramicroscopy 53, 191 (1994)CrossRefGoogle Scholar
  39. 39.
    Howie, A.: Ultramicroscopy 98, 73 (2004)CrossRefGoogle Scholar
  40. 40.
    Mkhoyan, K.A., et al.: Phys. Rev. Lett. 100, 025503 (2008)CrossRefGoogle Scholar
  41. 41.
    Boothroyd, C.B.: J. Microsc. 190, 99 (1998)CrossRefGoogle Scholar
  42. 42.
    Du, K., et al.: Ultramicroscopy 107, 281 (2007)CrossRefGoogle Scholar
  43. 43.
    Meyer, R.R., et al.: Microsc. Res. Tech. 49, 269 (2000)CrossRefGoogle Scholar
  44. 44.
    Thust, A.: Phys. Rev. Lett. 102, 220801 (2009)CrossRefGoogle Scholar
  45. 45.
    Fasolino, A., et al.: Intrinsic ripples in graphene. Nat. Mater. 6, 858–861 (2007)CrossRefGoogle Scholar
  46. 46.
    Banhart, F., et al.: Irradiation effects in carbon nanostructures. Rep. Prog. Phys. 62, 1181 (1999)CrossRefGoogle Scholar
  47. 47.
    Smith, B.W., et al.: Electron irradiation effects in single wall carbon nanotubes. J. Appl. Phys. 90, 3509 (2001)CrossRefGoogle Scholar
  48. 48.
    Schindelin, et al.: Fiji: an open-source platform for biological-image analysis. Nat. Methods 9(7), 676 (2012)CrossRefGoogle Scholar
  49. 49.
    Stone, A.J., et al.: Theoretical Studies of Icosahedral C60 and some related species. Chem. Phys. Lett. 128, 501–503 (1986)CrossRefGoogle Scholar
  50. 50.
    Pauling, L.: The Nature of the Chemical Bond. Cornell University Press, Ithaca (1960)zbMATHGoogle Scholar
  51. 51.
    Meyer, J.C., et al.: Direct imaging of lattice atoms and topological defects in graphene membranes. Nano Lett. 8(11), 3582–3586 (2008)CrossRefGoogle Scholar
  52. 52.
    Kotakoski, J., et al.: From point defects in graphene to two-dimensional amorphous carbon. Phys. Rev. Lett. 106, 105505 (2011)CrossRefGoogle Scholar
  53. 53.
    Kotakoski, J., et al.: Stone-Wales-type transformations in carbon nanostructures driven by electron irradiation. Phys. Rev. B 83, 245420 (2011)CrossRefGoogle Scholar
  54. 54.
    Li, L., et al.: Defect energies of graphite: density-functional calculations. Phys. Rev. B 72, 184109 (2005)CrossRefGoogle Scholar
  55. 55.
    Ma, J., et al.: Stone-Wales defects in graphene and other planar sp2-bonded materials. Phys. Rev. B 80, 033407 (2009)CrossRefGoogle Scholar
  56. 56.
    Jensen, P., et al.: Catalysis of nanotube plasticity under tensile strain. Phys. Rev. B 66, 193403 (2002)CrossRefGoogle Scholar
  57. 57.
    Zhang, W., et al.: Tight-binding calculation studies of vacancy and adatom defects in graphene. J. Phys. Condens. Matter 28, 115001 (2016)CrossRefGoogle Scholar
  58. 58.
    Trevethan, T., et al.: Vacancy diffusion and coalescence in graphene directed by defect strain fields. Nanoscale 6, 2978–2986 (2014)CrossRefGoogle Scholar
  59. 59.
    Skowron, S., et al.: Energetics of atomic scale structure changes in graphene. Chem. Soc. Rev. 44, 3143 (2015)CrossRefGoogle Scholar
  60. 60.
    Gass, M.H., et al.: Free-Standing graphene at atomic resolution. Nat. Nanotechnol. 3, 676–681 (2008)CrossRefGoogle Scholar
  61. 61.
    Girit, Ç.Ö., et al.: Graphene at the edge: stability and dynamics. Science 27 323(5922), 1705–1708 (2009)CrossRefGoogle Scholar
  62. 62.
    El-Barbary, A.A., et al.: Structure and energetics of the vacancy in graphite. Phys. Rev. B 68, 144107 (2003)CrossRefGoogle Scholar
  63. 63.
    Robertson, A.W., Warner, J.H.: Atomic resolution imaging of graphene by transmission electron microscopy. Nanoscale 5, 4079–4093 (2013)CrossRefGoogle Scholar
  64. 64.
  65. 65.
    Lehtinen, O., et al.: Atomic scale study of the life cycle of a dislocation in graphene from birth to annihilation. Nat. Commun. 4, 3098 (2013)CrossRefGoogle Scholar
  66. 66.
    Ramasse, Q.M., et al.: Probing the bonding and electronic structure of single atom dopants in graphene with electron energy loss spectroscopy. Nano Lett. 13, 4989–4995 (2013)CrossRefGoogle Scholar
  67. 67.
    Warner, J.H., et al.: Dislocation-driven deformations in graphene. Science 337, 209 (2012)CrossRefGoogle Scholar
  68. 68.
    Saito, M., et al.: Magic numbers of graphene multivacancies. Jpn. J. Appl. Phys. 46(12L), L1185 (2007)CrossRefGoogle Scholar
  69. 69.
    Xu, C.H., et al.: Simulations of point-defect properties in graphite by a tight-binding-force model. Phys. Rev. B. 48(18), 13273 (1993)CrossRefGoogle Scholar
  70. 70.
    Dettori, R., et al.: Elastic fields and moduli in defected graphene. J. Phys. Condens. Matter 24, 104020 (2012)CrossRefGoogle Scholar
  71. 71.
    Robertson, A.W., et al.: Spatial control of defect creation in graphene at the nanoscale. Nat. Commun. 3, 1144–1151 (2012)CrossRefGoogle Scholar
  72. 72.
    Wu, L., et al.: First-principles study on migration and coalescence of point defects in monolayer graphene. J. Phys. Chem. C 117, 17066–17072 (2013)CrossRefGoogle Scholar
  73. 73.
    Song, B., et al.: Atomic-scale electron-beam sculpting of near-defect-free graphene nanostructures. Nano Lett. 11, 2247–2250 (2011)CrossRefGoogle Scholar
  74. 74.
    Tsetserisa, L., Pantelides, S.T.: Adatom complexes and self-healing mechanisms on graphene and single-wall carbon nanotubes. Carbon 47, 901–908 (2009)CrossRefGoogle Scholar
  75. 75.
    Hashimoto, A., et al.: Direct evidence for atomic defects in graphene layers. Nature 430, 870–873 (2004).  https://doi.org/10.1038/nature02817CrossRefGoogle Scholar
  76. 76.
    Bangert, U., et al.: Nanotopography of graphene. Phys. Status Solidi A 206, 2115–2119 (2009)CrossRefGoogle Scholar
  77. 77.
    Lee, Y.H., et al.: Catalytic growth of single-wall carbon nanotubes: an ab initio study. Phys. Rev. Lett. 78, 2393–2396 (1997)CrossRefGoogle Scholar
  78. 78.
    Lehtinen, O., et al.: Magnetic properties and diffusion of adatoms on a graphene sheet. Phys. Rev. Lett. 91, 017202 (2003)CrossRefGoogle Scholar
  79. 79.
    Crespi, V.H., et al.: Prediction of a pure-carbon planar covalent metal. Phys. Rev. B 53, R13303(R) (1996)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Cyril Guedj
    • 1
    Email author
  • Léonard Jaillet
    • 2
  • François Rousse
    • 2
  • Stéphane Redon
    • 3
  1. 1.Univ. Grenoble Alpes, CEA, LETIGrenobleFrance
  2. 2.Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LJKGrenobleFrance
  3. 3.OneAngstromGrenobleFrance

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