1932

Abstract

Dislocations play a vital role in the mechanical behavior of crystalline materials during deformation. To capture dislocation phenomena across all relevant scales, a multiscale modeling framework of plasticity has emerged, with the goal of reaching a quantitative understanding of microstructure–property relations, for instance, to predict the strength and toughness of metals and alloys for engineering applications. This review describes the state of the art of the major dislocation modeling techniques, and then discusses how recent progress can be leveraged to advance the frontiers in simulations of dislocations. The frontiers of dislocation modeling include opportunities to establish quantitative connections between the scales, validate models against experiments, and use data science methods (e.g., machine learning) to gain an understanding of and enhance the current predictive capabilities.

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2020-07-01
2024-03-28
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Literature Cited

  1. 1. 
    Sills RB, Bertin N, Bulatov VV, Cai W 2020. Multiscale modelling of plasticity. Model. Simul. Mater. Sci. Eng. 28:043001
    [Google Scholar]
  2. 2. 
    Cai W, Ghosh S. 2018. Recent advances in crystal plasticity. Handbook of Materials Modeling W Andreoni, S Yip Cham, Switz: Springer
    [Google Scholar]
  3. 3. 
    Woodward C, Trinkle DR, Hector LG Jr, Olmsted DL 2008. Prediction of dislocation cores in aluminum from density functional theory. Phys. Rev. Lett. 100:045507
    [Google Scholar]
  4. 4. 
    Xia S, El-Azab A. 2015. Computational modelling of mesoscale dislocation patterning and plastic deformation of single crystals. Model. Simul. Mater. Sci. Eng. 23:055009
    [Google Scholar]
  5. 5. 
    Ghosh S, Groeber MA. 2018. Developing virtual microstructures and statistically equivalent representative volume elements for polycrystalline materials. Handbook of Materials Modeling W Andreoni, S Yip Cham, Switz: Springer
    [Google Scholar]
  6. 6. 
    Sills RB, Bertin N, Aghaei A, Cai W 2018. Dislocation networks and the microstructural origin of strain hardening. Phys. Rev. Lett. 121:085501
    [Google Scholar]
  7. 7. 
    Sills RB, Boyce BL. 2020. Void growth by dislocation adsorption. Mater. Res. Lett. 8:103–9
    [Google Scholar]
  8. 8. 
    Pinna C, Lan Y, Kiu MF, Efthymiadis P, Lopez-Pedrosa M, Farrugia D 2015. Assessment of crystal plasticity finite element simulations of the hot deformation of metals from local strain and orientation measurements. Int. J. Plast. 73:24–38
    [Google Scholar]
  9. 9. 
    Mello AW, Nicolas A, Lebensohn RA, Sangid MD 2016. Effect of microstructure on strain localization in a 7050 aluminum alloy: comparison of experiments and modeling for various textures. Mater. Sci. Eng. A 661:187–97
    [Google Scholar]
  10. 10. 
    Rodney D, Ventelon L, Clouet E, Pizzagalli L, Willaime F 2017. Ab initio modeling of dislocation core properties in metals and semiconductors. Acta Mater 124:633–59
    [Google Scholar]
  11. 11. 
    Lüthi B, Ventelon L, Rodney D, Willaime F 2018. Attractive interaction between interstitial solutes and screw dislocations in bcc iron from first principles. Comput. Mater. Sci. 148:21–26
    [Google Scholar]
  12. 12. 
    Leyson GPM, Curtin WA, Hector LG Jr, Woodward CF 2010. Quantitative prediction of solute strengthening in aluminum alloys. Nat. Mater. 9:750–55
    [Google Scholar]
  13. 13. 
    Clouet E, Caillard D, Chaari N, Onimus F, Rodney D 2015. Dislocation locking versus easy glide in titanium and zirconium. Nat. Mater. 14:931–37
    [Google Scholar]
  14. 14. 
    Proville L, Rodney D, Marinica MC 2012. Quantum effect on thermally activated glide of dislocations. Nat. Mater. 11:845–49
    [Google Scholar]
  15. 15. 
    Freitas R, Asta M, Bulatov VV 2018. Quantum effects on dislocation motion from ring-polymer molecular dynamics. npj Comput. Mater. 4:55
    [Google Scholar]
  16. 16. 
    Borda EJL, Cai W, de Koning M 2016. Dislocation structure and mobility in hcp 4He. Phys. Rev. Lett. 117:045301
    [Google Scholar]
  17. 17. 
    Bulatov V, Cai W. 2006. Computer Simulations of Dislocations Oxford, UK: Oxford Univ. Press
  18. 18. 
    Cai W, Li J, Yip S 2012. Molecular dynamics. Comprehensive Nuclear Materials RJM Konings 249–65 Amsterdam: Elsevier
    [Google Scholar]
  19. 19. 
    Cai W, Bulatob VV, Chang J, Li J, Yip S 2003. Periodic image effects in dislocation modelling. Philos. Mag. 83:539–67
    [Google Scholar]
  20. 20. 
    Zhou X, Sills R, Ward D, Karnesky R 2017. Atomistic calculations of dislocation core energy in aluminium. Phys. Rev. B 95:054112
    [Google Scholar]
  21. 21. 
    Geslin PA, Gatti R, Devincre B, Rodney D 2017. Implementation of the nudged elastic band method in a dislocation dynamics formalism: application to dislocation nucleation. J. Mech. Phys. Solids 108:49–67
    [Google Scholar]
  22. 22. 
    Rao S, Dimiduk D, Parthasarathy T, El-Awady J, Woodward C, Uchic M 2011. Calculations of intersection cross-slip activation energies in fcc metals using nudged elastic band method. Acta Mater 59:7135–44
    [Google Scholar]
  23. 23. 
    Kang K, Yin J, Cai W 2014. Stress dependence of cross slip energy barrier for face-centered cubic nickel. J. Mech. Phys. Solids 62:181–93
    [Google Scholar]
  24. 24. 
    Singh CV, Mateos AJ, Warner DH 2011. Atomistic simulations of dislocation precipitate interactions emphasize importance of cross-slip. Scr. Mater. 64:398–401
    [Google Scholar]
  25. 25. 
    Saroukhani S, Nguyen LD, Leung KWK, Singh CV, Warner DH 2016. Harnessing atomistic simulations to predict the rate at which dislocations overcome obstacles. J. Mech. Phys. Solids 90:202–14
    [Google Scholar]
  26. 26. 
    Ryu S, Kang K, Cai W 2011. Entropic effect on the rate of dislocation nucleation. PNAS 108:5174–78
    [Google Scholar]
  27. 27. 
    Nguyen LD, Baker KL, Warner DH 2011. Atomistic predictions of dislocation nucleation with transition state theory. Phys. Rev. B 84:024118
    [Google Scholar]
  28. 28. 
    Stukowski A, Albe K. 2010. Extracting dislocations and non-dislocation crystal defects from atomistic simulation data. Model. Simul. Mater. Sci. Eng. 18:085001
    [Google Scholar]
  29. 29. 
    Stukowski A. 2014. A triangulation-based method to identify dislocations in atomistic models. J. Mech. Phys. Solids 70:314–19
    [Google Scholar]
  30. 30. 
    Zepeda-Ruiz LA, Stukowski A, Oppelstrup T, Bulatov VV 2017. Probing the limits of metal plasticity with molecular dynamics simulations. Nature 550:492–95
    [Google Scholar]
  31. 31. 
    Zepeda-Ruiz LA, Stukowski A, Oppelstrup T, Bertin N, Barton NR et al. 2019. Metal hardening in atomistic detail. arXiv:1909.02030 [cond-mat]
  32. 32. 
    Sills RB, Aubry A. 2018. Line dislocation dynamics simulations with complex physics. Handbook of Materials Modeling W Andreoni, S Yip Cham, Switz: Springer
    [Google Scholar]
  33. 33. 
    Arsenlis A, Cai W, Tang M, Rhee M, Oppelstrup T et al. 2007. Enabling strain hardening simulations with dislocation dynamics. Model. Simul. Mater. Sci. Eng. 15:553–95
    [Google Scholar]
  34. 34. 
    Sills RB, Aghaei A, Cai W 2016. Advanced time integration algorithms for dislocation dynamics simulations of work hardening. Model. Simul. Mater. Sci. Eng. 24:045019
    [Google Scholar]
  35. 35. 
    Bertin N, Aubry S, Arsenlis A, Cai W 2019. GPU-accelerated dislocation dynamics using subcycling time integration. Model. Simul. Mater. Sci. Eng. 27:075014
    [Google Scholar]
  36. 36. 
    Chen C, Aubry S, Oppelstrup T, Arsenlis A, Darve E 2018. Fast algorithms for evaluating the stress field of dislocation lines in anisotropic elastic media. Model. Simul. Mater. Sci. Eng. 26:045007
    [Google Scholar]
  37. 37. 
    Vattre A, Devincre B, Feyel F, Gatti R, Groh S et al. 2014. Modelling crystal plasticity by 3D dislocation dynamics and the finite element method: the discrete-continuous model revisited. J. Mech. Phys. Solids 63:491–505
    [Google Scholar]
  38. 38. 
    Bertin N, Upadhyay MV, Pradalier C, Capolungo L 2015. A FFT-based formulation for efficient mechanical fields computation in isotropic and anisotropic periodic discrete dislocation dynamics. Model. Simul. Mater. Sci. Eng. 23:065009
    [Google Scholar]
  39. 39. 
    Bertin N, Capolungo L. 2018. A FFT-based formulation for discrete dislocation dynamics in heterogeneous media. J. Comput. Phys. 355:366–84
    [Google Scholar]
  40. 40. 
    Bertin N. 2019. Connecting discrete and continuum dislocation mechanics: a non-singular spectral framework. Int. J. Plast. 122:268–84
    [Google Scholar]
  41. 41. 
    Weinberger CR, Cai W. 2007. Computing image stress in an elastic cylinder. J. Mech. Phys. Solids 55:2027–54
    [Google Scholar]
  42. 42. 
    Weinberger CR, Aubry S, Lee SW, Nix WD, Cai W 2009. Modeling dislocations in a free-standing thin film. Model. Simul. Mater. Sci. Eng. 17:075007
    [Google Scholar]
  43. 43. 
    Bertin N, Glavas V, Datta D, Cai W 2018. A spectral approach for discrete dislocation dynamics simulations of nanoindentation. Model. Simul. Mater. Sci. Eng. 28:055004
    [Google Scholar]
  44. 44. 
    Devincre B, Kubin L, Hoc T 2006. Physical analyses of crystal plasticity by DD simulations. Scr. Mater. 54:741–46
    [Google Scholar]
  45. 45. 
    Devincre B, Hoc T, Kubin L 2008. Dislocation mean free paths and strain hardening of crystals. Science 320:1745–48
    [Google Scholar]
  46. 46. 
    Queyreau S, Monnet G, Devincre B 2009. Slip systems interactions in α-iron determined by dislocation dynamics simulations. Int. J. Plast. 25:361–77
    [Google Scholar]
  47. 47. 
    Bertin N, Tomé C, Beyerlein I, Barnett M, Capolungo L 2014. On the strength of dislocation interactions and their effect on latent hardening in pure magnesium. Int. J. Plast. 62:72–92
    [Google Scholar]
  48. 48. 
    Messner MC, Rhee M, Arsenlis A, Barton NR 2017. A crystal plasticity model for slip in hexagonal close packed metals based on discrete dislocation simulations. Model. Simul. Mater. Sci. Eng. 25:044001
    [Google Scholar]
  49. 49. 
    Hussein AM, Rao SI, Uchic MD, Dimiduk DM, El-Awady JA 2015. Microstructurally based cross-slip mechanisms and their effects on dislocation microstructure evolution in fcc crystals. Acta Mater 85:180–90
    [Google Scholar]
  50. 50. 
    Rao SI, Woodward C, Akdim B, Antillon E, Parthasarathy TA et al. 2019. Large-scale dislocation dynamics simulations of strain hardening of Ni microcrystals under tensile loading. Acta Mater 164:171–83
    [Google Scholar]
  51. 51. 
    Zhou C, LeSar R. 2012. Dislocation dynamics simulations of plasticity in polycrystalline thin films. Int. J. Plast. 30:185–201
    [Google Scholar]
  52. 52. 
    Fan H, Aubry S, Arsenlis A, El-Awady JA 2015. The role of twinning deformation on the hardening response of polycrystalline magnesium from discrete dislocation dynamics simulations. Acta Mater 92:126–39
    [Google Scholar]
  53. 53. 
    Wei D, Zaiser M, Feng Z, Kang G, Fan H, Zhang X 2019. Effects of twin boundary orientation on plasticity of bicrystalline copper micropillars: a discrete dislocation dynamics simulation study. Acta Mater 176:289–96
    [Google Scholar]
  54. 54. 
    Xiang YGY, Quek SS, Srolovitz DJ 2015. Three-dimensional formulation of dislocation climb. J. Mech. Phys. Solids 83:319–37
    [Google Scholar]
  55. 55. 
    Niu X, Luoa T, Xiang JLY 2017. Dislocation climb models from atomistic scheme to dislocation dynamics. J. Mech. Phys. Solids 99:242–58
    [Google Scholar]
  56. 56. 
    Arsenlis A, Rhee M, Hommes G, Cook R, Marian J 2012. A dislocation dynamics study of the transition from homogeneous to heterogeneous deformation in irradiated body-centered cubic iron. Acta Mater 60:3748–57
    [Google Scholar]
  57. 57. 
    Sobie C, Bertin N, Capolungo L 2015. Analysis of obstacle hardening models using dislocation dynamics: application to irradiation-induced defects. Metall. Mater. Trans. A 46:3761–72
    [Google Scholar]
  58. 58. 
    Cui Y, Po G, Ghoniem NM 2018. A coupled dislocation dynamics–continuum barrier field model with application to irradiated materials. Int. J. Plast. 104:54–67
    [Google Scholar]
  59. 59. 
    Li Y, Robertson C. 2018. Irradiation defect dispersions and effective dislocation mobility in strained ferritic grains: a statistical analysis based on 3D dislocation dynamics simulations. J. Nucl. Mater. 504:84–93
    [Google Scholar]
  60. 60. 
    Sobie C, Capolungo L, McDowell DL, Martinez E 2017. Scale transition using dislocation dynamics and the nudged elastic band method. J. Mech. Phys. Solids 105:161–78
    [Google Scholar]
  61. 61. 
    Hofmann F, Keegan S, Korsunskuy AM 2012. Diffraction post-processing of 3D dislocation dynamics simulations for direct comparison with micro-beam Laue experiments. Mater. Lett. 89:66–69
    [Google Scholar]
  62. 62. 
    Balogh L, Capolungo L, Tomé CN 2012. On the measure of dislocation densities from diffraction line profiles: a comparison with discrete dislocation methods. Acta Mater 60:1467–77
    [Google Scholar]
  63. 63. 
    Upadhyay MV, Capolungo L, Balogh L 2014. On the computation of diffraction peaks from discrete defects in continuous media: comparison of displacement and strain-based methods. J. Appl. Crystallogr. 47:861–78
    [Google Scholar]
  64. 64. 
    Bertin N, Cai W. 2018. Computation of virtual X-ray diffraction patterns from discrete dislocation structures. Comput. Mater. Sci. 146:268–77
    [Google Scholar]
  65. 65. 
    El-Azab A, Po G. 2018. Continuum dislocation dynamics: classical theory and contemporary models. Handbook of Materials Modeling W Andreoni, S Yip Cham, Switz: Springer
    [Google Scholar]
  66. 66. 
    Acharya A. 2001. A model of crystal plasticity based on the theory of continuously distributed dislocations. J. Mech. Phys. Solids 49:761–84
    [Google Scholar]
  67. 67. 
    Acharya A. 2004. Constitutive analysis of finite deformation field dislocation mechanics. J. Mech. Phys. Solids 52:301–16
    [Google Scholar]
  68. 68. 
    Acharya A, Roy A. 2006. Size effects and idealized dislocation microstructure at small scales: predictions of a phenomenological model of mesoscopic field dislocation mechanics. Part I. J. Mech. Phys. Solids 54:1687–710
    [Google Scholar]
  69. 69. 
    Varadhan S, Beaudoin A, Acharya A, Fressengeas C 2006. Dislocation transport using an explicit Galerkin/least-squares formulation. Model. Simul. Mater. Sci. Eng. 14:1245
    [Google Scholar]
  70. 70. 
    Puri S, Das A, Acharya A 2011. Mechanical response of multicrystalline thin films in mesoscale field dislocation mechanics. J. Mech. Phys. Solids 59:2400–17
    [Google Scholar]
  71. 71. 
    Djaka KS, Taupin V, Berbenni S, Fressengeas C 2015. A numerical spectral approach to solve the dislocation density transport equation. Model. Simul. Mater. Sci. Eng. 23:065008
    [Google Scholar]
  72. 72. 
    Zhang X. 2017. A continuum model for dislocation pile-up problems. Acta Mater 128:428–39
    [Google Scholar]
  73. 73. 
    Hochrainer T, Zaiser M, Gumbsch P 2007. A three-dimensional continuum theory of dislocation systems: kinematics and mean-field formulation. Philos. Mag. 87:1261–82
    [Google Scholar]
  74. 74. 
    Sandfeld S, Hochrainer T, Gumbsch P, Zaiser M 2010. Numerical implementation of a 3D continuum theory of dislocation dynamics and application to micro-bending. Philos. Mag. 90:3697–728
    [Google Scholar]
  75. 75. 
    Hochrainer T, Sandfeld S, Zaiser M, Gumbsch P 2014. Continuum dislocation dynamics: towards a physical theory of crystal plasticity. J. Mech. Phys. Solids 63:167–78
    [Google Scholar]
  76. 76. 
    Hochrainer T. 2015. Multipole expansion of continuum dislocations dynamics in terms of alignment tensors. Philos. Mag. 95:1321–67
    [Google Scholar]
  77. 77. 
    Sandfeld S, Zaiser M. 2015. Pattern formation in a minimal model of continuum dislocation plasticity. Model. Simul. Mater. Sci. Eng. 23:065005
    [Google Scholar]
  78. 78. 
    Arora R, Acharya A. 2020. Dislocation pattern formation in finite deformation crystal plasticity. Int. J. Solids Struct. 184:114–35
    [Google Scholar]
  79. 79. 
    Roters F, Eisenlohr P, Hantcherli L, Tjahjanto DD, Bieler TR, Raabe D 2010. Overview of constitutive laws, kinematics, homogenization and multiscale methods in crystal plasticity finite-element modeling: theory, experiments, applications. Acta Mater 58:1152–211
    [Google Scholar]
  80. 80. 
    Arsenlis A, Parks DM. 2002. Modeling the evolution of crystallographic dislocation density in crystal plasticity. J. Mech. Phys. Solids 50:1979–2009
    [Google Scholar]
  81. 81. 
    Ma A, Roters F. 2004. A constitutive model for fcc single crystals based on dislocation densities and its application to uniaxial compression of aluminium single crystals. Acta Mater 52:3603–12
    [Google Scholar]
  82. 82. 
    Beyerlein I, Tomé C. 2008. A dislocation-based constitutive law for pure Zr including temperature effects. Int. J. Plast. 24:867–95
    [Google Scholar]
  83. 83. 
    Lee M, Lim H, Adams B, Hirth J, Wagoner R 2010. A dislocation density-based single crystal constitutive equation. Int. J. Plast. 26:925–38
    [Google Scholar]
  84. 84. 
    Bertin N, Capolungo L, Beyerlein I 2013. Hybrid dislocation dynamics based strain hardening constitutive model. Int. J. Plast. 49:119–44
    [Google Scholar]
  85. 85. 
    Payne MC, Robertson IJ, Thomson D, Heine V 1996. Ab initio databases for fitting and testing interatomic potentials. Philos. Mag. B 73:191–99
    [Google Scholar]
  86. 86. 
    Motamarri P, Gavini V. 2014. Subquadratic-scaling subspace projection method for large-scale Kohn–Sham density functional theory calculations using spectral finite-element discretization. Phys. Rev. B 90:115127
    [Google Scholar]
  87. 87. 
    Mi W, Shao X, Su C, Zhou Y, Zhang S et al. 2016. Atlas: a real-space finite-difference implementation of orbital-free density functional theory. Comput. Phys. Commun. 200:87–95
    [Google Scholar]
  88. 88. 
    Ponga M, Bhattacharya K, Ortiz M 2016. A sublinear-scaling approach to density-functional-theory analysis of crystal defects. J. Mech. Phys. Solids 95:530–56
    [Google Scholar]
  89. 89. 
    Olmsted DL, Hector LG Jr, Curtin W, Clifton R 2005. Atomistic simulations of dislocation mobility in Al, Ni and Al/Mg alloys. Model. Simul. Mater. Sci. Eng 13:371–88
    [Google Scholar]
  90. 90. 
    Groh S, Marin E, Horstemeyer M, Bammann D 2009. Dislocation motion in magnesium: a study by molecular statics and molecular dynamics. Model. Simul. Mater. Sci. Eng. 17:075009
    [Google Scholar]
  91. 91. 
    Kang K, Bulatov VV, Cai W 2012. Singular orientations and faceted motion of dislocations in body-centered cubic crystals. PNAS 109:15174–78
    [Google Scholar]
  92. 92. 
    Cereceda D, Stukowski A, Gilbert M, Queyreau S, Ventelon L et al. 2013. Assessment of interatomic potentials for atomistic analysis of static and dynamic properties of screw dislocations in W. J. Phys. Condens. Matter 25:085702
    [Google Scholar]
  93. 93. 
    Cho J, Molinari JF, Anciaux G 2017. Mobility law of dislocations with several character angles and temperatures in fcc aluminum. Int. J. Plast. 90:66–75
    [Google Scholar]
  94. 94. 
    Zhou S, Preston D, Lomdahl P, Beazley D 1998. Large-scale molecular dynamics simulations of dislocation intersection in copper. Science 279:1525–27
    [Google Scholar]
  95. 95. 
    Rodney D, Phillips R. 1999. Structure and strength of dislocation junctions: an atomic level analysis. Phys. Rev. Lett. 82:1704–7
    [Google Scholar]
  96. 96. 
    Spearot DE, Sangid MD. 2014. Insights on slip transmission at grain boundaries from atomistic simulations. Curr. Opin. Solid State Mater. Sci. 18:188–95
    [Google Scholar]
  97. 97. 
    Terentyev D, Bonny G, Domain C, Pasianot R 2010. Interaction of a 1/2 〈111〉 screw dislocation with Cr precipitates in bcc Fe studied by molecular dynamics. Phys. Rev. B 81:214106
    [Google Scholar]
  98. 98. 
    Singh C, Mateos A, Warner D 2011. Atomistic simulations of dislocation–precipitate interactions emphasize importance of cross-slip. Scr. Mater. 64:398–401
    [Google Scholar]
  99. 99. 
    Perez D, Uberuaga BP, Shim Y, Amar JG, Voter AF 2009. Accelerated molecular dynamics methods: introduction and recent developments. Annu. Rep. Comput. Chem. 5:79–98
    [Google Scholar]
  100. 100. 
    Uberuaga BP, Martínez E, Perez D, Voter AF 2018. Discovering mechanisms relevant for radiation damage evolution. Comput. Mater. Sci. 147:282–92
    [Google Scholar]
  101. 101. 
    Ghoniem NM, Tong SH, Sun LZ 2000. Parametric dislocation dynamics: a thermodynamics-based approach to investigations of mesoscopic plastic deformation. Phys. Rev. B 61:913–27
    [Google Scholar]
  102. 102. 
    Sills RB, Kuykendall WP, Aghaei AA, Cai W 2016. Fundamentals of dislocation dynamics simulations. Multiscale Materials Modeling for Nanomechanics CR Weinberger, GJ Tucker 53–87 Cham, Switz: Springer
    [Google Scholar]
  103. 103. 
    Cai W, Arsenlis A, Weinberger CR, Bulatov VV 2006. A non-singular continuum theory of dislocations. J. Mech. Phys. Solids 54:561–87
    [Google Scholar]
  104. 104. 
    Aubry S, Arsenlis A. 2013. Use of spherical harmonics for dislocation dynamics in anisotropic elastic media. Model. Simul. Mater. Sci. Eng. 21:065013
    [Google Scholar]
  105. 105. 
    Lemarchand C, Devincre B, Kubin LP 2001. Homogenization method for a discrete-continuum simulation of dislocation dynamics. J. Mech. Phys. Solids 49:1969–82
    [Google Scholar]
  106. 106. 
    Dehm G, Jaya BN, Raghavan R, Kirchlechner C 2018. Overview on micro- and nanomechanical testing: new insights in interface plasticity and fracture at small length scales. Acta Mater 142:248–82
    [Google Scholar]
  107. 107. 
    Nye J. 1953. Some geometrical relations in dislocated crystals. Acta Metall 1:153–62
    [Google Scholar]
  108. 108. 
    Xia S, Belak J, El-Azab A 2016. The discrete-continuum connection in dislocation dynamics. I. Time coarse graining of cross slip. Model. Simul. Mater. Sci. Eng. 24:075007
    [Google Scholar]
  109. 109. 
    Lebensohn RA, Tomé C. 1993. A self-consistent anisotropic approach for the simulation of plastic deformation and texture development of polycrystals: application to zirconium alloys. Acta Metall. Mater. 41:2611–24
    [Google Scholar]
  110. 110. 
    Lebensohn RA, Kanjarla AK, Eisenlohr P 2012. An elasto-viscoplastic formulation based on fast fourier transforms for the prediction of micromechanical fields in polycrystalline materials. Int. J. Plast. 32:59–69
    [Google Scholar]
  111. 111. 
    Li J, Wang CZ, Chang JP, Cai W, Bulatov VV et al. 2004. Core energy and Peierls stress of a screw dislocation in bcc molybdenum: a periodic-cell tight-binding study. Phys. Rev. B 70:104113
    [Google Scholar]
  112. 112. 
    Clouet E, Ventelon L, Willaime F 2009. Dislocation core energies and core fields from first principles. Phys. Rev. Lett. 102:055502
    [Google Scholar]
  113. 113. 
    Anderson PM, Hirth JP, Lothe J 2017. Theory of Dislocations Cambridge, UK: Cambridge Univ. Press
  114. 114. 
    Domain C, Monnet G. 2005. Simulation of screw dislocation motion in iron by molecular dynamics simulations. Phys. Rev. Lett. 95:215506
    [Google Scholar]
  115. 115. 
    Monnet G, Terentyev D. 2009. Structure and mobility of the 1/2 〈111〉 {112} edge dislocation in bcc iron studied by molecular dynamics. Acta Mater 57:1416–26
    [Google Scholar]
  116. 116. 
    Queyreau S, Marian J, Gilbert M, Wirth B 2011. Edge dislocation mobilities in bcc Fe obtained by molecular dynamics. Phys. Rev. B 84:064106
    [Google Scholar]
  117. 117. 
    Monnet G, Devincre B, Kubin L 2004. Dislocation study of prismatic slip systems and their interactions in hexagonal close packed metals: application to zirconium. Acta Mater 52:4317–28
    [Google Scholar]
  118. 118. 
    Wang Z, Beyerlein I. 2011. An atomistically-informed dislocation dynamics model for the plastic anisotropy and tension–compression asymmetry of bcc metals. Int. J. Plast. 27:1471–84
    [Google Scholar]
  119. 119. 
    Srivastava K, Gröger R, Weygand D, Gumbsch P 2013. Dislocation motion in tungsten: atomistic input to discrete dislocation simulations. Int. J. Plast. 47:126–42
    [Google Scholar]
  120. 120. 
    Po G, Cui Y, Rivera D, Cereceda D, Swinburne TD et al. 2016. A phenomenological dislocation mobility law for bcc metals. Acta Mater 119:123–35
    [Google Scholar]
  121. 121. 
    Geslin PA, Rodney D. 2018. Thermal fluctuations of dislocations reveal the interplay between their core energy and long-range elasticity. Phys. Rev. B 98:174115
    [Google Scholar]
  122. 122. 
    Anciaux G, Junge T, Hodapp M, Cho J, Molinari JF, Curtin W 2018. The coupled atomistic/discrete-dislocation method in 3D. Part I. Concept and algorithms. J. Mech. Phys. Solids 118:152–71
    [Google Scholar]
  123. 123. 
    Cho J, Molinari JF, Curtin WA, Anciaux G 2018. The coupled atomistic/discrete-dislocation method in 3D. Part III. Dynamics of hybrid dislocations. J. Mech. Phys. Solids 118:1–14
    [Google Scholar]
  124. 124. 
    Han J, Thomas SL, Srolovitz DJ 2018. Grain-boundary kinetics: a unified approach. Prog. Mater. Sci. 98:386–476
    [Google Scholar]
  125. 125. 
    Mughrabi H, Ungar T, Kienle W, Wilkens M 1986. Long-range internal stresses and asymmetric X-ray line-broadening in tensile-deformed [001]-orientated copper single crystals. Philos. Mag. A 53:793–813
    [Google Scholar]
  126. 126. 
    Sandfeld S, Po G. 2015. Microstructural comparison of the kinematics of discrete and continuum dislocations models. Model. Simul. Mater. Sci. Eng. 23:085003
    [Google Scholar]
  127. 127. 
    Sudmanns M, Stricker M, Weygand D, Hochrainer T, Schulz K 2019. Dislocation multiplication by cross-slip and glissile reactions in a dislocation based continuum formulation of crystal plasticity. J. Mech. Phys. Solids 132:103695
    [Google Scholar]
  128. 128. 
    Pollock TM, LeSar R. 2013. The feedback loop between theory, simulation and experiment for plasticity and property modeling. Curr. Opin. Solid State Mater. Sci. 17:10–18
    [Google Scholar]
  129. 129. 
    Mills MJ, Miracle DB. 1993. The structure of a 〈100〉 and a 〈110〉 dislocation cores in NiAl. Acta Metall. Mater. 41:85–95
    [Google Scholar]
  130. 130. 
    Gioacchnio FD, de Fonseca JQ 2015. An experimental study of the polycrystalline plasticity of austenitic stainless steel. Int. J. Plast. 74:92–109
    [Google Scholar]
  131. 131. 
    Chen Z, Daly SH. 2017. Active slip system identification in polycrystalline metals by digital image correlation (DIC). Exp. Mech. 57:115–27
    [Google Scholar]
  132. 132. 
    Rawat S, Chandra S, Chavan VM, Sharma S, Warrier M et al. 2014. Integrated experimental and computational studies of deformation of single crystal copper at high strain rates. J. Appl. Phys. 116:213507
    [Google Scholar]
  133. 133. 
    Ryu I, Nix WD, Cai W 2013. Plasticity of bcc micropillars controlled by competition between dislocation multiplication and depletion. Acta Mater 61:3233–41
    [Google Scholar]
  134. 134. 
    Guillonneau G, Mieszala M, Wehrs J, Schwiedrzik J, Grop S et al. 2018. Nanomechanical testing at high strain rates: new instrumentation for nanoindentation and microcompression. Mater. Des. 148:39–48
    [Google Scholar]
  135. 135. 
    Liu GS, House SD, Kacher J, Tanaka M, Higashida K, Robertson IM 2014. Electron tomography of dislocation structures. Mater. Charact. 87:1–11
    [Google Scholar]
  136. 136. 
    Larson BC, Levine LE. 2013. Submicrometre-resolution polychromatic three-dimensional X-ray microscopy. J. Appl. Crystallogr. 46:153–64
    [Google Scholar]
  137. 137. 
    Ramesh KT. 2008. High rates and impact experiments. Springer Handbook of Experimental Solid Mechanics WN Sharpe Jr 929–60 Boston: Springer
    [Google Scholar]
  138. 138. 
    Gilat A, Schmidt TE, Walker AL 2009. Full field strain measurement in compression and tensile split Hopkinson bar experiments. Exp. Mech. 49:291–302
    [Google Scholar]
  139. 139. 
    Chen W, Song B, Few DJ, Forrestal MJ 2003. Dynamic small strain measurements of a metal specimen with a split Hopkinson pressure bar. Exp. Mech. 43:20–23
    [Google Scholar]
  140. 140. 
    Drouet J, Dupuy L, Onimus F, Mompiou F 2016. A direct comparison between in-situ transmission electron microscopy observations and dislocation dynamics simulations of interaction between dislocation and irradiation induced loop in a zirconium alloy. Scr. Mater. 119:71–75
    [Google Scholar]
  141. 141. 
    Wang Z, McCabe RJ, Ghoniem NM, LeSar R, Misra A, Mitchell TE 2013. Dislocation motion in thin Cu foils: a comparison between computer simulations and experiment. Acta Mater 52:1535–42
    [Google Scholar]
  142. 142. 
    Hong C, Huang X, Winther G 2013. Dislocation content of geometrically necessary boundaries aligned with slip planes in rolled aluminum. Philos. Mag. 93:3118–41
    [Google Scholar]
  143. 143. 
    Saghi Z, Midgley PA. 2012. Electron tomography in the (S)TEM: from nanoscale morphological analysis to 3D atomic imaging. Annu. Rev. Mater. Res. 42:59–79
    [Google Scholar]
  144. 144. 
    Kacher J, Robertson IM. 2012. Quasi-four-dimensional analysis of dislocation interactions with grain boundaries in 304 stainless steel. Acta Mater 60:6657–72
    [Google Scholar]
  145. 145. 
    Guyon J, Mansour H, Gey N, Crimp M, Chalal S, Maloufi N 2015. Sub-micron resolution selected area electron channeling patterns. Ultramicroscopy 149:34–44
    [Google Scholar]
  146. 146. 
    Kriaa H, Guitton A, Maloufi N 2019. Modeling dislocation contrasts obtained by accurate-electron channeling contrast imaging for characterizing deformation mechanisms in bulk materials. Materials 12:1587
    [Google Scholar]
  147. 147. 
    Ben Haj Slama M, Maloufi N, Guyon J, Bahi S et al. 2019. In situ macroscopic tensile testing in SEM and electron channeling contrast imaging: pencil glide evidenced in a bulk β-Ti21s polycrystal. Materials 12:2479
    [Google Scholar]
  148. 148. 
    Swygenhoven HV, Petegem SV. 2013. In-situ mechanical testing during X-ray diffraction. Mater. Charact. 78:47–59
    [Google Scholar]
  149. 149. 
    Ulvestad A, Welland MJ, Cha W, Liu Y, Kim JW et al. 2017. Three-dimensional imaging of dislocation dynamics during the hydriding phase transformation. Nat. Mater. 16:565–73
    [Google Scholar]
  150. 150. 
    Dupraz M, Beutier G, Cornelius TW, Parry G, Ren Z et al. 2017. 3D imaging of a dislocation loop at the onset of plasticity in an indented nanocrystal. Nanoletters 17:6696–701
    [Google Scholar]
  151. 151. 
    Yau A, Cha W, Kanan MW, Stephenson GB, Ulvestad A 2017. Bragg coherent diffractive imaging of single-grain defect dynamics in polycrystalline films. Science 356:739–42
    [Google Scholar]
  152. 152. 
    Schülli TU, Leake SJ. 2018. X-ray nanobeam diffraction imaging of materials. Curr. Opin. Solid State Mater. Sci. 22:188–201
    [Google Scholar]
  153. 153. 
    Simons H, King A, Ludwig W, Detlefs C, Pantleon W et al. 2015. Dark-field X-ray microscopy for multiscale structural characterization. Nat. Commun. 6:6098
    [Google Scholar]
  154. 154. 
    Jakobsen AC, Simons H, Ludwig W, Yildirim C, Leemreize H et al. 2019. Mapping of individual dislocations with dark-field X-ray microscopy. J. Appl. Crystallogr. 52:122–32
    [Google Scholar]
  155. 155. 
    Bock FE, Aydin RC, Cyron CJ, Huber N, Kalidindi SR, Klusemann B 2019. A review of the application of machine learning and data mining approaches in continuum materials mechanics. Front. Mater. 6:110
    [Google Scholar]
  156. 156. 
    Kalidindi SR. 2015. Hierarchical Materials Informatics: Novel Analytics for Materials Data Amsterdam: Elsevier
  157. 157. 
    Behler J, Parrinello M. 2007. Generalized neural-network representation of high-dimensional potential-energy surfaces. Phys. Rev. Lett. 98:146401
    [Google Scholar]
  158. 158. 
    Behler J. 2016. Perspective: Machine learning potentials for atomistic simulations. J. Chem. Phys. 145:170901
    [Google Scholar]
  159. 159. 
    Yassar RS, AbuOmar O, Hansen E, Horstemeyer MF 2010. On dislocation-based artificial neural network modeling of flow stress. Mater. Des. 31:3683–89
    [Google Scholar]
  160. 160. 
    Zhang Y, Ngan AH. 2019. Extracting dislocation microstructures by deep learning. Int. J. Plast. 115:18–28
    [Google Scholar]
  161. 161. 
    Salmenjoki H, Alava MJ, Laurson L 2018. Machine learning plastic deformation of crystals. Nat. Commun. 9:5307
    [Google Scholar]
  162. 162. 
    Steinberger D, Song H, Sandfeld S 2019. Machine learning–based classification of dislocation micro-structures. Front. Mater. 6:141
    [Google Scholar]
  163. 163. 
    Kubin L, Devincre B, Hoc T 2008. Modeling dislocation storage rates and mean free paths in face-centered cubic crystals. Acta Mater. 56:6040–49
    [Google Scholar]
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