Experimental Mechanics

, Volume 59, Issue 7, pp 1063–1073 | Cite as

A Robust Patterning Technique for Electron Microscopy-Based Digital Image Correlation at Sub-Micron Resolutions

  • C.B. Montgomery
  • B. Koohbor
  • N.R. SottosEmail author


Digital image correlation of scanning electron microscope images is a powerful technique for measuring full-field deformation at microstructural length scales. A major challenge in applying this technique is the fabrication of speckle patterns small enough to facilitate full-field measurements with high spatial resolutions and at high magnifications. Current approaches are inconsistent, damaging to the substrate, or highly substrate dependent, which requires researchers to recalibrate or develop new patterning approaches when changing materials systems. Here, multi-layered Au, Ti, and Ag sputtered coatings are reconfigured in a NaCl solution to quickly form DIC-appropriate speckle patterns. Our proposed technique is shown to be substrate independent, as demonstrated on neat epoxy, Ti-6Al-4V titanium alloy, and tetragonal zirconia polycrystal samples, and allows for controllable particle distributions by varying the sputtered Ag layer thickness. Patterns produced by the proposed technique enable the use of correlation window (subset) sizes smaller than 1 μm, small enough to capture highly localized deformation gradients at material discontinuities areas. Capabilities of this method in characterizing highly heterogeneous deformation conditions at sub-micron scales are demonstrated by measuring localized deformations in a single fiber model composite system.


Digital image correlation Scanning electron microscopy Speckle pattern Reconfiguration Composites 



This work has been supported through a grant No. FA9550-12-1-0445 to the Center of Excellence on Integrated Materials Modeling (CEIMM) at Johns Hopkins University, awarded by the AFOSR/ Aerospace Materials for Extreme Environments Program (Program Manager Dr. Ali Sayir) and AFRL/RX (Monitors Drs. C. Woodward and C. Przybyla). This work was carried out in part in the Frederick Seitz Materials Research Laboratory Central Research Facilities, University of Illinois. The authors also gratefully acknowledge Professor Scott R. White for his helpful insight and discussions.


  1. 1.
    Sutton MA, Li N, Joy DC, Reynolds AP, Li X (2007) Scanning electron microscopy for quantitative small and large deformation measurements part I: SEM imaging at magnifications from 200 to 10,000. Exp Mech 47:775–787CrossRefGoogle Scholar
  2. 2.
    Sutton MA, Li N, Garcia D, Cornille N, Orteu JJ, McNeill SR, Schreier HW, Li X, Reynolds AP (2007) Scanning electron microscopy for quantitative small and large deformation measurements part II: experimental validation for magnifications from 200 to 10,000. Exp Mech 47:789–804CrossRefGoogle Scholar
  3. 3.
    Li N, Sutton MA, Li X, Schreier HW (2007) Full-field thermal deformation measurements in a scanning electron microscope by 2D digital image correlation. Exp Mech 48:635–646CrossRefGoogle Scholar
  4. 4.
    Kammers AD, Daly S (2013) Digital image correlation under scanning electron microscopy: methodology and validation. Exp Mech 53:1743–1761CrossRefGoogle Scholar
  5. 5.
    Stinville JC, Echlin MP, Texier D, Bridier F, Bocher P (2016) Pollock. Sub-grain scale digital image correlation by electron microscopy for polycrystalline materials during elastic and plastic deformation. Exp Mech 56:197–216CrossRefGoogle Scholar
  6. 6.
    Maraghechi S, Hoefnagels JPM, Peerlings RHJ, Geers MGD (2018) Correction of scan line shift artifacts in scanning electron microscopy: an extended digital image correlation framework. Ultramicroscopy 187:144–163CrossRefGoogle Scholar
  7. 7.
    Jiang R, Pierron F, Octaviani S, Reed PAS (2017) Characterisation of strain localisation processes during fatigue crack initiation and early crack propagation by SEM-DIC in an advanced disc alloy. Mater Sci Eng A 699:128–144CrossRefGoogle Scholar
  8. 8.
    Di Gioacchino F, da Fonseca JQ (2015) An experimental study of the polycrystalline plasticity of austenitic stainless steel. Int J Plast 74:92–109CrossRefGoogle Scholar
  9. 9.
    Correlated Solutions, Incorporated (2016) 121 Dutchman Blvd, Irmo, SC 29063.
  10. 10.
    Scrivens WA, Luo Y, Sutton MA, Collette SA, Myrick ML, Miney P, Colavita PE, Reynolds AP, Li X (2007) Development of patterns for digital image correlation measurements at reduced length scales. Exp Mech 47:63–77CrossRefGoogle Scholar
  11. 11.
    Kammers AD, Daly S (2011) Small-scale patterning methods for digital image correlation under scanning electron microscopy. Meas Sci Technol 22:125501CrossRefGoogle Scholar
  12. 12.
    Berfield TA, Patel JK, Shimmin RG, Braun PV, Lambros J, Sottos NR (2007) Micro- and nanoscale deformation measurement of surface and internal planes via digital image correlation. Exp Mech 47:51–62CrossRefGoogle Scholar
  13. 13.
    Berfield TA, Patel JK, Shimmin RG, Braun PV, Lambros J, Sottos NR (2006) Fluorescent image correlation for nanoscale deformation measurements. Small 2:631–635CrossRefGoogle Scholar
  14. 14.
    Mehdikhani M, Aravand M, Sabuncuoglu B, Callens M, Lomov SV, Gorbatikh L (2016) Full-field strain measurements at the micro-scale in fiber-reinforced composites using digital image correlation. Compos Struct 140:192–201CrossRefGoogle Scholar
  15. 15.
    Canal LP, Gonzales C, Molina-Aldareguia JM, Sequrado J, Llorca J (2012) Application of digital image correlation at the microscale in fiber-reinforced composites. Compos Part A 43:1630–1638CrossRefGoogle Scholar
  16. 16.
    Tracy J, Daly S, Sevener K (2015) Multiscale damage characterization in continuous fiber ceramic matrix composites using digital image correlation. J Mater Sci 50:5286–5299CrossRefGoogle Scholar
  17. 17.
    LePage WS, Ahadi A, Lenthe WC, Sun QP, Pollock TM, Shaw JA, Daly SH (2018) Grain size effects on NiTi shape memory alloy fatigue crack growth. J Mater Res 33:91–107CrossRefGoogle Scholar
  18. 18.
    Chen Z, Daly SH (2017) Active slip system identification in polycrystalline metals by digital image correlation (DIC). Exp Mech 57:115–127CrossRefGoogle Scholar
  19. 19.
    Guery A, Hild F, Latourte F, Roux S (2016) Slip activities in polycrystals determined by coupling DIC measurements with crystal plasticity calculations. Int J Plast 81:249–266CrossRefGoogle Scholar
  20. 20.
    Guo SM, Sutton MA, Li N, Li XD, Wang LW, Rajan S (2017) Measurement of local thermal deformations in heterogeneous microstructures via SEM imaging with digital image correlation. Exp Mech 57:41–56CrossRefGoogle Scholar
  21. 21.
    Biery N, De Graef M, Pollock TM (2003) A method for measuring microstructural-scale strains using a scanning electron microscope: applications to γ-titanium aluminides. Metall Mater Trans A 34:2301–2313CrossRefGoogle Scholar
  22. 22.
    Ruggles TJ, Bomarito GF, Cannon AH, Hochhalter JD (2017) Selectively electron-transparent microstamping toward concurrent digital image correlation and high-angular resolution electron backscatter diffraction (EBSD) analysis. Microsc Microanal 23:1091–1095CrossRefGoogle Scholar
  23. 23.
    Githens A, Daly S (2016) Patterning corrosion-susceptible metallic alloys for digital image correlation in a scanning electron microscope. Strain 53:e12215CrossRefGoogle Scholar
  24. 24.
    Guery A, Latourte F, Hild F, Roux S (2014) Characterization of SEM speckle pattern marking and imaging distortion by digital image correlation. Meas Sci Technol 25:015401CrossRefGoogle Scholar
  25. 25.
    Shi Q, Roux S, Latourte F, Hild F, Loisnard D, Brynaert N (2018) On the use of SEM correlative tools for in situ mechanical tests. Ultramicroscopy 184:71–87CrossRefGoogle Scholar
  26. 26.
    Vitos L, Ruban AV, Skriver HL, Kollar J (1998) The surface energy of metals. Surf Sci 411:186–202CrossRefGoogle Scholar
  27. 27.
    Montgomery CB (2018) Multiscale characterization of carbon Fiber-reinforced epoxy composites. Dissertation, University of Illinois at Urbana-ChampaignGoogle Scholar
  28. 28.
    Koike K, Yamazaki F, Okamura T, Fukuda S (2007) Improvement of corrosion resistance of transparent conductive multilayer coating consisting of silver layers and transparent metal oxide layers. J Vac Sci Technol A 25:527–531CrossRefGoogle Scholar
  29. 29.
    Rajan VP, Rossol MN, Zok FW (2012) Optimization of digital image correlation for high strain mapping of ceramic composites. Exp Mech 52:1407–1421CrossRefGoogle Scholar
  30. 30.
    Koohbor B, Ravindran S, Kidane A (2017) Experimental determination of representative volume element (RVE) size in woven composites. Opt Lasers Eng 90:59–71CrossRefGoogle Scholar
  31. 31.
    Koike K, Fukuda S (2008) Multilayer transparent electrode consisting of silver alloy layer and metal oxide layers for organic luminescent electronic display device. J Vac Sci Technol A 26:444–454CrossRefGoogle Scholar
  32. 32.
    Repetto L, Batic BS, Firpo G, Piano E, Valbusa U (2012) Ion induced spinodal dewetting of thin solid films. Appl Phys Lett 100:223113CrossRefGoogle Scholar
  33. 33.
    Sutton MA, Orteu JJ, Schreier HW (2009) Image correlation for shape, motion and deformation measurements – basic concepts, theory and applications. Springer, New YorkGoogle Scholar
  34. 34.
    Efstathiou C, Sehitoglu H, Lambros J (2010) Multiscale strain measurements of plastically deforming polycrystalline titanium: role of deformation heterogeneities. Int J Plast 26:93–106CrossRefzbMATHGoogle Scholar
  35. 35.
    Orozco-Caballero A, Lunt D, Robson JD, da Fonseca JQ (2017) How magnesium accommodates local deformation incompatibility: a high-resolution digital image correlation study. Acta Mater 133:367–379CrossRefGoogle Scholar
  36. 36.
    Tasan CC, Hoefnagels JPM, Diehl M, Yan D, Roters F, Raabe D (2014) Strain localization and damage in dual phase steels investigated by coupled in-situ deformation experiments and crystal plasticity simulations. Int J Plast 63:198–210CrossRefGoogle Scholar
  37. 37.
    Bing P, Hui-min X, Bo-qin X, Fu-long D (2006) Performance of sub-pixel registration algorithms in digital image correlation. Meas Sci Technol 17:1615–1621CrossRefGoogle Scholar
  38. 38.
    Yang Q, Cox B (2005) Cohesive models for damage evolution in laminated composites. Int J Fract 133:107–137CrossRefzbMATHGoogle Scholar
  39. 39.
    Kusch VI, Shmegera SV, Brondsted P, Mishnaevsky L Jr (2011) Numerical simulation of progressive debonding in fiber reinforced composite under transverse loading. Int J Eng Sci 49:17–29CrossRefGoogle Scholar
  40. 40.
    Tavara L, Mantic V, Graciani E, Paris F (2011) BEM analysis of crack onset and propagation along fiber–matrix interface under transverse tension using a linear elastic–brittle interface model. Eng Anal Bound Elem 35:207–222MathSciNetCrossRefzbMATHGoogle Scholar
  41. 41.
    Totten KR, Kutub B, Carlsson LA (2016) In situ determination of the fiber–matrix interface tensile strength. J Compos Mater 50:589–599CrossRefGoogle Scholar
  42. 42.
    Gowrishankar S, Mei H, Liechti KM, Huang R (2012) A comparison of direct and interative methods for determining traction-separation relations. Int J Fract 177:109–128CrossRefGoogle Scholar
  43. 43.
    Svensson D, Alfredsson KS, Biel A, Stigh U (2014) Measurement of cohesive laws for interlaminar failure of CFRP. Compos Sci Technol 100:53–62CrossRefGoogle Scholar
  44. 44.
    Garcia IG, Mantic V, Graciani E (2015) Debonding at the fibre-matrix interface under remote transverse tension. One debond or two symmetric debonds? Eur J Mech A-Solid 53:75–88MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Society for Experimental Mechanics 2019

Authors and Affiliations

  1. 1.Department of Materials Science and EngineeringUniversity of Illinois at Urbana-ChampaignUrbanaUSA
  2. 2.Beckman Institute for Advanced Science and TechnologyUniversity of Illinois at Urbana-ChampaignUrbanaUSA

Personalised recommendations