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Abstract

Scanning transmission electron microscopy (STEM) is one of the most powerful characterization tools in materials science research. Due to instrumentation developments such as highly coherent electron sources, aberration correctors, and direct electron detectors, STEM experiments can examine the structure and properties of materials at length scales of functional devices and materials down to single atoms. STEM encompasses a wide array of flexible operating modes, including imaging, diffraction, spectroscopy, and 3D tomography experiments. This review outlines many common STEM experimental methods with a focus on quantitative data analysis and simulation methods, especially those enabled by open source software. The hope is to introduce both classic and new experimental methods to materials scientists and summarize recent progress in STEM characterization. The review also discusses the strengths and weaknesses of the various STEM methodologies and briefly considers promising future directions for quantitative STEM research.

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2023-07-03
2024-05-03
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Literature Cited

  1. 1.
    Mullarkey T, Downing C, Jones L. 2021. Development of a practicable digital pulse read-out for dark-field STEM. Microsc. Microanal. 27:199–108
    [Google Scholar]
  2. 2.
    Tate MW, Purohit P, Chamberlain D, Nguyen KX, Hovden R et al. 2016. High dynamic range pixel array detector for scanning transmission electron microscopy. Microsc. Microanal. 22:1237–49
    [Google Scholar]
  3. 3.
    MacLaren I, Macgregor TA, Allen CS, Kirkland AI. 2020. Detectors—the ongoing revolution in scanning transmission electron microscopy and why this important to material characterization. Apl. Mater. 8:11110901
    [Google Scholar]
  4. 4.
    Nord M, Webster RW, Paton KA, McVitie S, McGrouther D et al. 2020. Fast pixelated detectors in scanning transmission electron microscopy. Part I: data acquisition, live processing, and storage. Microsc. Microanal. 26:4653–66
    [Google Scholar]
  5. 5.
    Krivanek OL, Dellby N, Hachtel JA, Idrobo JC, Hotz M et al. 2019. Progress in ultrahigh energy resolution EELS. Ultramicroscopy 203:60–67
    [Google Scholar]
  6. 6.
    Sawada H, Tomita T, Naruse M, Honda T, Hambridge P et al. 2005. Experimental evaluation of a spherical aberration-corrected TEM and STEM. Microscopy 54:2119–21
    [Google Scholar]
  7. 7.
    Kimoto K. 2014. Practical aspects of monochromators developed for transmission electron microscopy. J. Electron Microsc. 63:5337–44
    [Google Scholar]
  8. 8.
    McMorran BJ, Agrawal A, Anderson IM, Herzing AA, Lezec HJ et al. 2011. Electron vortex beams with high quanta of orbital angular momentum. Science 331:6014192–95
    [Google Scholar]
  9. 9.
    Ophus C, Ciston J, Pierce J, Harvey TR, Chess J et al. 2016. Efficient linear phase contrast in scanning transmission electron microscopy with matched illumination and detector interferometry. Nat. Commun. 7:10719
    [Google Scholar]
  10. 10.
    Yang H, Ercius P, Nellist PD, Ophus C. 2016. Enhanced phase contrast transfer using ptychography combined with a pre-specimen phase plate in a scanning transmission electron microscope. Ultramicroscopy 171:117–25
    [Google Scholar]
  11. 11.
    Verbeeck J, Béché A, Müller-Caspary K, Guzzinati G, Luong MA, Den Hertog M 2018. Demonstration of a 2 × 2 programmable phase plate for electrons. Ultramicroscopy 190:58–65
    [Google Scholar]
  12. 12.
    Harvey TR, Yasin FS, Chess JJ, Pierce JS, dos Reis RMS et al. 2018. Interpretable and efficient interferometric contrast in scanning transmission electron microscopy with a diffraction-grating beam splitter. Phys. Rev. Appl. 10:6061001
    [Google Scholar]
  13. 13.
    Zeltmann SE, Müller A, Bustillo KC, Savitzky B, Hughes L et al. 2020. Patterned probes for high precision 4D-STEM Bragg measurements. Ultramicroscopy 209:112890
    [Google Scholar]
  14. 14.
    Reed BW, Moghadam A, Bloom R, Park S, Monterrosa A et al. 2019. Electrostatic subframing and compressive-sensing video in transmission electron microscopy. Struct. Dyn. 6:5054303
    [Google Scholar]
  15. 15.
    Brown L. 1997. A synchrotron in a microscope. Electron Microscopy and Analysis 1997, Proceedings of the Institute of Physics Electron Microscopy and Analysis Group Conference, University of Cambridge, 2–5 September 1997 JM Rodenberg 17–22. Boca Raton, FL: CRC Press
    [Google Scholar]
  16. 16.
    Ramasse QM. 2017. Twenty years after: how “aberration correction in the STEM” truly placed a “a synchrotron in a microscope. .” Ultramicroscopy 180:41–51
    [Google Scholar]
  17. 17.
    Liu JJ. 2021. Advances and applications of atomic-resolution scanning transmission electron microscopy. Microsc. Microanal. 27:5943–95
    [Google Scholar]
  18. 18.
    De Graef M. 2003. Introduction to Conventional Transmission Electron Microscopy Cambridge, UK: Cambridge Univ. Press
  19. 19.
    Pennycook SJ, Nellist PD. 2011. Scanning Transmission Electron Microscopy: Imaging and Analysis New York: Springer
  20. 20.
    Ophus C, Ercius P, Sarahan M, Czarnik C, Ciston J. 2014. Recording and using 4D-STEM datasets in materials science. Microsc. Microanal. 20:S362–63
    [Google Scholar]
  21. 21.
    Spence J, Zuo J. 2013. Electron Microdiffraction New York: Springer
  22. 22.
    Ophus C. 2019. Four-dimensional scanning transmission electron microscopy (4D-STEM): from scanning nanodiffraction to ptychography and beyond. Microsc. Microanal. 25:3563–82
    [Google Scholar]
  23. 23.
    Swanson L, Schwind G. 2009. A review of the cold-field electron cathode. Adv. Imaging Electron Phys. 159:63–100
    [Google Scholar]
  24. 24.
    Egerton RF. 2011. Electron Energy-Loss Spectroscopy in the Electron Microscope New York: Springer
  25. 25.
    Ikeno H, Mizoguchi T. 2017. Basics and applications of ELNES calculations. Microscopy 66:5305–27
    [Google Scholar]
  26. 26.
    Watanabe M. 2011. X-ray energy-dispersive spectrometry in scanning transmission electron microscopes. Scanning Transmission Electron Microscopy: Imaging and Analysis SJ Pennycook, PD Nellist 291–351. New York: Springer
    [Google Scholar]
  27. 27.
    Kociak M, Zagonel L. 2017. Cathodoluminescence in the scanning transmission electron microscope. Ultramicroscopy 176:112–31
    [Google Scholar]
  28. 28.
    Miao J, Ercius P, Billinge SJ. 2016. Atomic electron tomography: 3D structures without crystals. Science 353:6306aaf2157
    [Google Scholar]
  29. 29.
    Elbaum M. 2018. Quantitative cryo-scanning transmission electron microscopy of biological materials. Adv. Mater. 30:411706681
    [Google Scholar]
  30. 30.
    Wang Z, Ke X, Sui M. 2022. Recent progress on revealing 3D structure of electrocatalysts using advanced 3D electron tomography: a mini review. Front. Chem. 10:872117
    [Google Scholar]
  31. 31.
    Olszta M, Hopkins D, Fiedler KR, Oostrom M, Akers S, Spurgeon SR. 2022. An automated scanning transmission electron microscope guided by sparse data analytics. Microsc. Microanal. 28:51611–21
    [Google Scholar]
  32. 32.
    Feng J, Somlyo AP, Somlyo AV, Shao Z. 2007. Automated electron tomography with scanning transmission electron microscopy. J. Microsc. 228:3406–12
    [Google Scholar]
  33. 33.
    Savitzky BH, Zeltmann SE, Hughes LA, Brown HG, Zhao S et al. 2021. py4DSTEM: a software package for four-dimensional scanning transmission electron microscopy data analysis. Microsc. Microanal. 27:4712–43
    [Google Scholar]
  34. 34.
    Spurgeon SR, Ophus C, Jones L, Petford-Long A, Kalinin SV et al. 2021. Towards data-driven next-generation transmission electron microscopy. Nat. Mater. 20:3274–79
    [Google Scholar]
  35. 35.
    Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M et al. 2016. The FAIR guiding principles for scientific data management and stewardship. Sci. Data 3:1160018
    [Google Scholar]
  36. 36.
    Kalinin SV, Ophus C, Voyles PM, Erni R, Kepaptsoglou D et al. 2022. Machine learning in scanning transmission electron microscopy. Nat. Rev. Methods Primers 2:111
    [Google Scholar]
  37. 37.
    Hovden R, Cueva P, Mundy JA, Muller DA. 2013. The open-source Cornell Spectrum Imager. Microsc. Today 21:140–44
    [Google Scholar]
  38. 38.
    de la Pema F, Prestat E, Fauske VT, Burdet P, Lahnemann J et al. 2022. hyperspy/hyperspy: Release v1.7.3. Zenodo. https://doi.org/10.5281/zenodo.7263263
    [Crossref] [Google Scholar]
  39. 39.
    Nord M, Vullum PE, MacLaren I, Tybell T, Holmestad R. 2017. Atomap: a new software tool for the automated analysis of atomic resolution images using two-dimensional Gaussian fitting. Adv. Struct. Chem. Imaging 3:19
    [Google Scholar]
  40. 40.
    O'Connell EN, Moore K, McFall E, Hennessy M, Moynihan E et al. 2022. TopoTEM: A python package for quantifying and visualizing scanning transmission electron microscopy data of polar topologies. Microsc. Microanal. 28:41444–52
    [Google Scholar]
  41. 41.
    Slater T, CameronGBell Mohsen. 2021. ePSIC-DLS/ParticleSpy: v0.5.2 Zenodo. https://zenodo.org/record/4668722/export/hx#.ZEmYF3bMKUk
  42. 42.
    Cautaerts N, Crout P, Ånes HW, Prestat E, Jeong J et al. 2022. Free, flexible and fast: orientation mapping using the multi-core and GPU-accelerated template matching capabilities in the python-based open source 4D-STEM analysis toolbox Pyxem. Ultramicroscopy 237:113517
    [Google Scholar]
  43. 43.
    Crout P, Johnstone DN, Hogas S, Martineau B, isabelwood100, et al. 2021. pyxem/diffsims: diffsims 0.4.2 Zenodo.. https://doi.org/10.5281/zenodo.4697299
    [Crossref]
  44. 44.
    Johnstone DN, Martineau BH, Crout P, Midgley PA, Eggeman AS. 2020. Density-based clustering of crystal (mis) orientations and the orix Python library. J. Appl. Crystallogr. 53:51293–98
    [Google Scholar]
  45. 45.
    Clausen A, Weber D, Ruzaeva K, Migunov V, Baburajan A et al. 2020. LiberTEM: software platform for scalable multidimensional data processing in transmission electron microscopy. J. Open Source Softw. 5:502006
    [Google Scholar]
  46. 46.
    Ophus C, Zeltmann SE, Bruefach A, Rakowski A, Savitzky BH et al. 2022. Automated crystal orientation mapping in py4DSTEM using sparse correlation matching. Microsc. Microanal. 28:2390–403
    [Google Scholar]
  47. 47.
    Mukherjee D, Unocic R. 2020. STEMtooL: an open source Python toolkit for analyzing electron microscopy datasets. Microsc. Microanal. 26:S22960–62
    [Google Scholar]
  48. 48.
    Somnath S, Smith CR, Laanait N, Vasudevan RK, Jesse S 2019. USID and pycroscopy – open source frameworks for storing and analyzing imaging and spectroscopy data. Microsc. Microanal. 25:S2220–21
    [Google Scholar]
  49. 49.
    Ziatdinov M, Ghosh A, Wong T, Kalinin SV. 2021. AtomAI: a deep learning framework for analysis of image and spectroscopy data in (scanning) transmission electron microscopy and beyond. arXiv:2105.07485 [physics.data-an]
  50. 50.
    Gürsoy D, De Carlo F, Xiao X, Jacobsen C 2014. TomoPY: a framework for the analysis of synchrotron tomographic data. J. Synchrotron Radiat. 21:51188–93
    [Google Scholar]
  51. 51.
    van Aarle W, Palenstijn WJ, De Beenhouwer J, Altantzis T, Bals S et al. 2015. The ASTRA toolbox: a platform for advanced algorithm development in electron tomography. Ultramicroscopy 157:35–47
    [Google Scholar]
  52. 52.
    Hanwell MD, Harris CJ, Genova A, Schwartz J, Jiang Y, Hovden R. 2019. Tomviz: open source platform connecting image processing pipelines to GPU accelerated 3D visualization. Microsc. Microanal. 25:S2408–9
    [Google Scholar]
  53. 53.
    Kremer JR, Mastronarde DN, McIntosh JR. 1996. Computer visualization of three-dimensional image data using IMOD. J. Struct. Biol. 116:171–76
    [Google Scholar]
  54. 54.
    Schaffer B 2016. Digital micrograph. Transmission Electron Microscopy: Diffraction, Imaging, and Spectrometry CB Carter, DB Williams 167–96. Cham, Switz: Springer
    [Google Scholar]
  55. 55.
    Jones L, Yang H, Pennycook TJ, Marshall MS, Van Aert S et al. 2015. Smart Align—a new tool for robust non-rigid registration of scanning microscope data. Adv. Struct. Chem. Imaging 1:18
    [Google Scholar]
  56. 56.
    Ophus C, Ciston J, Nelson CT. 2016. Correcting nonlinear drift distortion of scanning probe and scanning transmission electron microscopies from image pairs with orthogonal scan directions. Ultramicroscopy 162:1–9
    [Google Scholar]
  57. 57.
    Savitzky BH, El Baggari I, Clement CB, Waite E, Goodge BH et al. 2018. Image registration of low signal-to-noise cryo-STEM data. Ultramicroscopy 191:56–65
    [Google Scholar]
  58. 58.
    Berkels B, Liebscher CH. 2019. Joint non-rigid image registration and reconstruction for quantitative atomic resolution scanning transmission electron microscopy. Ultramicroscopy 198:49–57
    [Google Scholar]
  59. 59.
    Bárcena-González G, de la Paz Guerrero-Lebrero M, Guerrero E, Yañez A, Nuñez-Moraleda B et al. 2020. CDrift: an algorithm to correct linear drift from a single high-resolution STEM image. Microsc. Microanal. 26:5913–20
    [Google Scholar]
  60. 60.
    Kirkland EJ. 2020. Advanced Computing in Electron Microscopy Cham, Switz: Springer. , 3rd ed..
  61. 61.
    Cowley JM, Moodie AF. 1957. The scattering of electrons by atoms and crystals. I. A new theoretical approach. Acta Crystallogr. 10:10609–19
    [Google Scholar]
  62. 62.
    Pelz PM, Rakowski A, DaCosta LR, Savitzky BH, Scott MC, Ophus C. 2021. A fast algorithm for scanning transmission electron microscopy imaging and 4D-STEM diffraction simulations. Microsc. Microanal. 27:4835–48
    [Google Scholar]
  63. 63.
    Lobato I, Van Dyck D. 2014. An accurate parameterization for scattering factors, electron densities and electrostatic potentials for neutral atoms that obey all physical constraints. Acta Crystallogr. A Found. Adv. 70:6636–49
    [Google Scholar]
  64. 64.
    Mendis BG. 2018. Electron Beam-Specimen Interactions and Simulation Methods in Microscopy Hoboken, NJ: Wiley & Sons
  65. 65.
    Madsen J, Susi T. 2021. The abTEM code: transmission electron microscopy from first principles. Open Res. Eur. 1:24
    [Google Scholar]
  66. 66.
    Barthel J, Cattaneo M, Mendis BG, Findlay SD, Allen LJ. 2020. Angular dependence of fast-electron scattering from materials. Phys. Rev. B 101:18184109
    [Google Scholar]
  67. 67.
    Rossouw D, Botton GA. 2013. Plasmonic response of bent silver nanowires for nanophotonic subwavelength waveguiding. Phys. Rev. Lett. 110:6066801
    [Google Scholar]
  68. 68.
    Hébert C, Luitz J, Schattschneider P. 2003. Improvement of energy loss near edge structure calculation using Wien2k.. Micron 34:3–5219–25
    [Google Scholar]
  69. 69.
    Brown HG, Ciston J, Ophus C. 2019. Linear-scaling algorithm for rapid computation of inelastic transitions in the presence of multiple electron scattering. Phys. Rev. Res. 1:3033186
    [Google Scholar]
  70. 70.
    Rangel DaCosta L, Brown HG, Pelz PM, Rakowski A, Barber N et al. 2021. Prismatic 2.0 – simulation software for scanning and high resolution transmission electron microscopy (STEM and HRTEM). Micron 151:103141
    [Google Scholar]
  71. 71.
    Allen LJ, Findlay S. 2015. Modelling the inelastic scattering of fast electrons. Ultramicroscopy 151:11–22
    [Google Scholar]
  72. 72.
    Lobato I, Van Dyck D. 2015. MULTEM: A new multislice program to perform accurate and fast electron diffraction and imaging simulations using graphics processing units with CUDA. Ultramicroscopy 156:9–17
    [Google Scholar]
  73. 73.
    Barthel J. 2018. Dr. Probe: a software for high-resolution STEM image simulation. Ultramicroscopy 193:1–11
    [Google Scholar]
  74. 74.
    Forbes B, Martin A, Findlay S, D'alfonso A, Allen L 2010. Quantum mechanical model for phonon excitation in electron diffraction and imaging using a Born-Oppenheimer approximation. Phys. Rev. B 82:10104103
    [Google Scholar]
  75. 75.
    Pryor A, Ophus C, Miao J. 2017. A streaming multi-GPU implementation of image simulation algorithms for scanning transmission electron microscopy. Adv. Struct. Chem. Imaging 3:115
    [Google Scholar]
  76. 76.
    Ophus C. 2017. A fast image simulation algorithm for scanning transmission electron microscopy. Adv. Struct. Chem. Imaging 3:113
    [Google Scholar]
  77. 77.
    Mendis B. 2019. An inelastic multislice simulation method incorporating plasmon energy losses. Ultramicroscopy 206:112816
    [Google Scholar]
  78. 78.
    Dwyer C. 2005. Multislice theory of fast electron scattering incorporating atomic inner-shell ionization. Ultramicroscopy 104:2141–51
    [Google Scholar]
  79. 79.
    Zeiger PM, Rusz J. 2020. Efficient and versatile model for vibrational STEM-EELS. Phys. Rev. Lett. 124:2025501
    [Google Scholar]
  80. 80.
    Lugg N, Kothleitner G, Shibata N, Ikuhara Y 2015. On the quantitativeness of EDS STEM. Ultramicroscopy 151:150–59
    [Google Scholar]
  81. 81.
    Chen Z, Taplin D, Weyland M, Allen LJ, Findlay S. 2017. Composition measurement in substitutionally disordered materials by atomic resolution energy dispersive x-ray spectroscopy in scanning transmission electron microscopy. Ultramicroscopy 176:52–62
    [Google Scholar]
  82. 82.
    Yamamoto N, Araya K, Toda A, Sugiyama H. 2001. Light emission from surfaces, thin films and particles induced by high-energy electron beam. Surface Interface Anal. 31:279–86
    [Google Scholar]
  83. 83.
    Schaffer M, Schaffer B, Ramasse Q. 2012. Sample preparation for atomic-resolution STEM at low voltages by FIB. Ultramicroscopy 114:62–71
    [Google Scholar]
  84. 84.
    Egerton R, Watanabe M 2022. Spatial resolution in transmission electron microscopy. Micron 160:103304
    [Google Scholar]
  85. 85.
    Zhang Z, Wang W, Dong Z, Yang X, Liang F et al. 2022. The trends of in situ focused ion beam technology: toward preparing transmission electron microscopy lamella and devices at the atomic scale. Adv. Electron. Mater. 8:92101401
    [Google Scholar]
  86. 86.
    Egerton R. 2019. Radiation damage to organic and inorganic specimens in the TEM. Micron 119:72–87
    [Google Scholar]
  87. 87.
    Velazco A, Béché A, Jannis D, Verbeeck J. 2022. Reducing electron beam damage through alternative STEM scanning strategies, part I: experimental findings. Ultramicroscopy 232:113398
    [Google Scholar]
  88. 88.
    Kuei B, Gomez ED. 2021. Pushing the limits of high-resolution polymer microscopy using antioxidants. Nat. Commun. 12:1153
    [Google Scholar]
  89. 89.
    Kuipers J, Kalicharan RD, Wolters AH, van Ham TJ, Giepmans BN. 2016. Large-scale scanning transmission electron microscopy (nanotomy) of healthy and injured zebrafish brain. JoVE111e53635
    [Google Scholar]
  90. 90.
    Ke X, Zhang M, Zhao K, Su D. 2022. Moiré fringe method via scanning transmission electron microscopy. Small Methods 6:12101040
    [Google Scholar]
  91. 91.
    Gauquelin N, Van den Bos K, Béché A, Krause F, Lobato I et al. 2017. Determining oxygen relaxations at an interface: a comparative study between transmission electron microscopy techniques. Ultramicroscopy 181:178–90
    [Google Scholar]
  92. 92.
    Treacy MM. 2011. Z dependence of electron scattering by single atoms into annular dark-field detectors. Microsc. Microanal. 17:6847–58
    [Google Scholar]
  93. 93.
    Crewe AV, Wall J, Langmore J. 1970. Visibility of single atoms. Science 168:39371338–40
    [Google Scholar]
  94. 94.
    Singhal A, Yang J, Gibson J. 1997. STEM-based mass spectroscopy of supported Re clusters. Ultramicroscopy 67:1–4191–206
    [Google Scholar]
  95. 95.
    Voyles P, Muller D, Kirkland E. 2004. Depth-dependent imaging of individual dopant atoms in silicon. Microsc. Microanal. 10:2291–300
    [Google Scholar]
  96. 96.
    Allen JE, Hemesath ER, Perea DE, Lensch-Falk JL, Li Z et al. 2008. High-resolution detection of Au catalyst atoms in Si nanowires. Nat. Nanotechnol. 3:3168–73
    [Google Scholar]
  97. 97.
    Colliex C, Gloter A, March K, Mory C, Stéphan O et al. 2012. Capturing the signature of single atoms with the tiny probe of a STEM. Ultramicroscopy 123:80–89
    [Google Scholar]
  98. 98.
    Rosenauer A, Gries K, Müller K, Pretorius A, Schowalter M et al. 2009. Measurement of specimen thickness and composition in AlxGa1−xN/GaN using high-angle annular dark field images. Ultramicroscopy 109:91171–82
    [Google Scholar]
  99. 99.
    Krivanek OL, Chisholm MF, Nicolosi V, Pennycook TJ, Corbin GJ et al. 2010. Atom-by-atom structural and chemical analysis by annular dark-field electron microscopy. Nature 464:7288571–74
    [Google Scholar]
  100. 100.
    Yankovich AB, Berkels B, Dahmen W, Binev P, Sanchez SI et al. 2014. Picometre-precision analysis of scanning transmission electron microscopy images of platinum nanocatalysts. Nat. Commun. 5:4155
    [Google Scholar]
  101. 101.
    De Backer A, Martinez G, MacArthur K, Jones L, Béché A et al. 2015. Dose limited reliability of quantitative annular dark field scanning transmission electron microscopy for nano-particle atom-counting. Ultramicroscopy 151:56–61
    [Google Scholar]
  102. 102.
    Zou YC, Mogg L, Clark N, Bacaksiz C, Milovanovic S et al. 2021. Ion exchange in atomically thin clays and micas. Nat. Mater. 20:121677–82
    [Google Scholar]
  103. 103.
    Luo K, Liu B, Hu W, Dong X, Wang Y et al. 2022. Coherent interfaces govern direct transformation from graphite to diamond. Nature 607:7919486–91
    [Google Scholar]
  104. 104.
    LeBeau JM, Findlay SD, Allen LJ, Stemmer S. 2008. Quantitative atomic resolution scanning transmission electron microscopy. Phys. Rev. Lett. 100:20206101
    [Google Scholar]
  105. 105.
    Hartel P, Rose H, Dinges C. 1996. Conditions and reasons for incoherent imaging in STEM. Ultramicroscopy 63:293–114
    [Google Scholar]
  106. 106.
    Shi F, Li F, Ma Y, Zheng F, Feng R et al. 2019. In situ transmission electron microscopy study of nanocrystal formation for electrocatalysis. ChemNanoMat 5:121439–55
    [Google Scholar]
  107. 107.
    LeBeau JM, D'Alfonso AJ, Findlay SD, Stemmer S, Allen LJ 2009. Quantitative comparisons of contrast in experimental and simulated bright-field scanning transmission electron microscopy images. Phys. Rev. B 80:17174106
    [Google Scholar]
  108. 108.
    Okunishi E, Ishikawa I, Sawada H, Hosokawa F, Hori M, Kondo Y. 2009. Visualization of light elements at ultrahigh resolution by STEM annular bright field microscopy. Microsc. Microanal. 15:S2164–65
    [Google Scholar]
  109. 109.
    Ishikawa R, Okunishi E, Sawada H, Kondo Y, Hosokawa F, Abe E 2011. Direct imaging of hydrogen-atom columns in a crystal by annular bright-field electron microscopy. Nat. Mater. 10:4278–81
    [Google Scholar]
  110. 110.
    Byeon P, Hong Y, Bae HB, Shin J, Choi JW, Chung S-Y 2021. Atomic-scale unveiling of multiphase evolution during hydrated Zn-ion insertion in vanadium oxide. Nat. Commun. 12:14599
    [Google Scholar]
  111. 111.
    Findlay SD, Saito T, Shibata N, Sato Y, Matsuda J et al. 2010. Direct imaging of hydrogen within a crystalline environment. Appl. Phys. Express 3:11116603
    [Google Scholar]
  112. 112.
    Dekkers N, De Lang H. 1974. Differential phase contrast in a STEM. Optik 41:4452–56
    [Google Scholar]
  113. 113.
    Rose H. 1977. Nonstandard imaging methods in electron microscopy. Ultramicroscopy 2:251–67
    [Google Scholar]
  114. 114.
    Lubk A, Zweck J. 2015. Differential phase contrast: an integral perspective. Phys. Rev. A 91:2023805
    [Google Scholar]
  115. 115.
    Lazić I, Bosch EG, Lazar S. 2016. Phase contrast STEM for thin samples: integrated differential phase contrast. Ultramicroscopy 160:265–80
    [Google Scholar]
  116. 116.
    Shibata N, Findlay SD, Kohno Y, Sawada H, Kondo Y, Ikuhara Y. 2012. Differential phase-contrast microscopy at atomic resolution. Nat. Phys. 8:8611–15
    [Google Scholar]
  117. 117.
    Han B, Zhu R, Li X, Wu M, Ishikawa R et al. 2021. Two-dimensional room-temperature giant antiferrodistortive SrTiO3 at a grain boundary. Phys. Rev. Lett. 126:22225702
    [Google Scholar]
  118. 118.
    Shen B, Wang H, Xiong H, Chen X, Bosch EG et al. 2022. Atomic imaging of zeolite-confined single molecules by electron microscopy. Nature 607:7920703–7
    [Google Scholar]
  119. 119.
    MacLaren I, Wang L, McGrouther D, Craven AJ, McVitie S et al. 2015. On the origin of differential phase contrast at a locally charged and globally charge-compensated domain boundary in a polar-ordered material. Ultramicroscopy 154:57–63
    [Google Scholar]
  120. 120.
    Campanini M, Nasi L, Albertini F, Erni R. 2020. Disentangling nanoscale electric and magnetic fields by time-reversal operation in differential phase-contrast STEM. Appl. Phys. Lett. 117:15154102
    [Google Scholar]
  121. 121.
    Kohno Y, Seki T, Findlay SD, Ikuhara Y, Shibata N. 2022. Real-space visualization of intrinsic magnetic fields of an antiferromagnet. Nature 602:7896234–39
    [Google Scholar]
  122. 122.
    McMullan G, Faruqi A, Clare D, Henderson R 2014. Comparison of optimal performance at 300 keV of three direct electron detectors for use in low dose electron microscopy. Ultramicroscopy 147:156–63
    [Google Scholar]
  123. 123.
    Li X, Zheng SQ, Egami K, Agard DA, Cheng Y. 2013. Influence of electron dose rate on electron counting images recorded with the K2 camera. J. Struct. Biol. 184:2251–60
    [Google Scholar]
  124. 124.
    Gallagher-Jones M, Ophus C, Bustillo KC, Boyer DR, Panova O et al. 2019. Nanoscale mosaicity revealed in peptide microcrystals by scanning electron nanodiffraction. Commun. Biol. 2:26
    [Google Scholar]
  125. 125.
    Koch CT. 2011. Aberration-compensated large-angle rocking-beam electron diffraction. Ultramicroscopy 111:7828–40
    [Google Scholar]
  126. 126.
    LeBeau JM, Findlay SD, Wang X, Jacobson AJ, Allen LJ, Stemmer S. 2009. High-angle scattering of fast electrons from crystals containing heavy elements: simulation and experiment. Phys. Rev. B 79:21214110
    [Google Scholar]
  127. 127.
    LeBeau JM, D'Alfonso AJ, Wright NJ, Allen LJ, Stemmer S 2011. Determining ferroelectric polarity at the nanoscale. Appl. Phys. Lett. 98:5052904
    [Google Scholar]
  128. 128.
    Ophus C, Ercius P, Huijben M, Ciston J. 2017. Non-spectroscopic composition measurements of SrTiO3-La0.7Sr0.3MnO3 multilayers using scanning convergent beam electron diffraction. Appl. Phys. Lett. 110:6063102
    [Google Scholar]
  129. 129.
    Pennington RS, Van den Broek W, Koch CT. 2014. Third-dimension information retrieval from a single convergent-beam transmission electron diffraction pattern using an artificial neural network. Phys. Rev. B 89:20205409
    [Google Scholar]
  130. 130.
    Xu W, LeBeau JM. 2018. A deep convolutional neural network to analyze position averaged convergent beam electron diffraction patterns. Ultramicroscopy 188:59–69
    [Google Scholar]
  131. 131.
    Schnitzer N, Sung SH, Hovden R. 2019. Introduction to the Ronchigram and its calculation with Ronchigram.com. Microsc. Today 27:312–15
    [Google Scholar]
  132. 132.
    Liu Z, Zhang Q, Qin LC. 2005. Accurate determination of atomic structure of multiwalled carbon nanotubes by nondestructive nanobeam electron diffraction. Appl. Phys. Lett. 86:19191903
    [Google Scholar]
  133. 133.
    Rauch E, Véron M. 2014. Automated crystal orientation and phase mapping in TEM. Mater. Charact. 98:1–9
    [Google Scholar]
  134. 134.
    Sutter P, Wimer S, Sutter E. 2019. Chiral twisted van der Waals nanowires. Nature 570:7761354–57
    [Google Scholar]
  135. 135.
    Eggeman AS, Krakow R, Midgley PA. 2015. Scanning precession electron tomography for three-dimensional nanoscale orientation imaging and crystallographic analysis. Nat. Commun. 6:7267
    [Google Scholar]
  136. 136.
    Kazmierczak NP, Van Winkle M, Ophus C, Bustillo KC, Carr S et al. 2021. Strain fields in twisted bilayer graphene. Nat. Mater. 20:7956–63
    [Google Scholar]
  137. 137.
    Hayee F, Yu L, Zhang JL, Ciccarino CJ, Nguyen M et al. 2020. Revealing multiple classes of stable quantum emitters in hexagonal boron nitride with correlated optical and electron microscopy. Nat. Mater. 19:5534–39
    [Google Scholar]
  138. 138.
    Wu M, Harreiß C, Ophus C, Johnson M, Fink RH, Spiecker E. 2022. Seeing structural evolution of organic molecular nano-crystallites using 4D scanning confocal electron diffraction (4D-SCED). Nat. Commun. 13:12911
    [Google Scholar]
  139. 139.
    Ding Y, Choi Y, Chen Y, Pradel KC, Liu M, Wang ZL. 2020. Quantitative nanoscale tracking of oxygen vacancy diffusion inside single ceria grains by in situ transmission electron microscopy. Mater. Today 38:24–34
    [Google Scholar]
  140. 140.
    Pekin TC, Gammer C, Ciston J, Minor AM, Ophus C. 2017. Optimizing disk registration algorithms for nanobeam electron diffraction strain mapping. Ultramicroscopy 176:170–76
    [Google Scholar]
  141. 141.
    Rouviere JL, Béché A, Martin Y, Denneulin T, Cooper D. 2013. Improved strain precision with high spatial resolution using nanobeam precession electron diffraction. Appl. Phys. Lett. 103:24241913
    [Google Scholar]
  142. 142.
    Bustillo KC, Zeltmann SE, Chen M, Donohue J, Ciston J et al. 2021. 4D-STEM of beam-sensitive materials. Acc. Chem. Res. 54:112543–51
    [Google Scholar]
  143. 143.
    Panova O, Ophus C, Takacs CJ, Bustillo KC, Balhorn L et al. 2019. Diffraction imaging of nanocrystalline structures in organic semiconductor molecular thin films. Nat. Mater. 18:8860–65
    [Google Scholar]
  144. 144.
    Mu X, Wang D, Feng T, Kübel C. 2016. Radial distribution function imaging by STEM diffraction: phase mapping and analysis of heterogeneous nanostructured glasses. Ultramicroscopy 168:1–6
    [Google Scholar]
  145. 145.
    Treacy M, Borisenko K. 2012. The local structure of amorphous silicon. Science 335:6071950–53
    [Google Scholar]
  146. 146.
    Voyles P, Muller D. 2002. Fluctuation microscopy in the STEM. Ultramicroscopy 93:2147–59
    [Google Scholar]
  147. 147.
    Lu Z, Lu AKA, Zhang F, Tian Y, Jiang J et al. 2021. Crystal-like order stabilizing glasses: Structural origin of ultra-stable metallic glasses. arXiv:2111.02606 [cond-mat.dis-nn]
  148. 148.
    Liu A, Neish M, Stokol G, Buckley G, Smillie L et al. 2013. Systematic mapping of icosahedral short-range order in a melt-spun Zr36Cu64 metallic glass. Phys. Rev. Lett. 110:20205505
    [Google Scholar]
  149. 149.
    Cockayne DJ. 2007. The study of nanovolumes of amorphous materials using electron scattering. Annu. Rev. Mater. Res. 37:159–87
    [Google Scholar]
  150. 150.
    Schloz M, Pekin TC, Chen Z, Van den Broek W, Muller DA, Koch CT. 2020. Overcoming information reduced data and experimentally uncertain parameters in ptychography with regularized optimization. Opt. Express 28:1928306–23
    [Google Scholar]
  151. 151.
    Nellist P, McCallum B, Rodenburg JM. 1995. Resolution beyond the ‘information limit’ in transmission electron microscopy. Nature 374:6523630–32
    [Google Scholar]
  152. 152.
    Yang H, Rutte R, Jones L, Simson M, Sagawa R et al. 2016. Simultaneous atomic-resolution electron ptychography and Z-contrast imaging of light and heavy elements in complex nanostructures. Nat. Commun. 7:12532
    [Google Scholar]
  153. 153.
    Pelz PM, Johnson I, Ophus C, Ercius P, Scott MC. 2021. Real-time interactive 4D-STEM phase-contrast imaging from electron event representation data: less computation with the right representation. IEEE Signal Proc. Mag. 39:125–31
    [Google Scholar]
  154. 154.
    Chen Z, Jiang Y, Shao YT, Holtz ME, Odstrčil M et al. 2021. Electron ptychography achieves atomic-resolution limits set by lattice vibrations. Science 372:6544826–31
    [Google Scholar]
  155. 155.
    Humphry M, Kraus B, Hurst A, Maiden A, Rodenburg J. 2012. Ptychographic electron microscopy using high-angle dark-field scattering for sub-nanometre resolution imaging. Nat. Commun. 3:730
    [Google Scholar]
  156. 156.
    Jiang Y, Chen Z, Han Y, Deb P, Gao H et al. 2018. Electron ptychography of 2D materials to deep sub-ångström resolution. Nature 559:7714343–49
    [Google Scholar]
  157. 157.
    Hong X, Zeltmann SE, Savitzky BH, DaCosta LR, Müller A et al. 2021. Multibeam electron diffraction. Microsc. Microanal. 27:1129–39
    [Google Scholar]
  158. 158.
    Pelz PM, Qiu WX, Bücker R, Kassier G, Miller RD. 2017. Low-dose cryo electron ptychography via non-convex bayesian optimization. Sci. Rep. 7:19883
    [Google Scholar]
  159. 159.
    Hashimoto A, Shimojo M, Mitsuishi K, Takeguchi M. 2009. Three-dimensional imaging of carbon nanostructures by scanning confocal electron microscopy. J. Appl. Phys. 106:8086101
    [Google Scholar]
  160. 160.
    Etheridge J, Lazar S, Dwyer C, Botton GA. 2011. Imaging high-energy electrons propagating in a crystal. Phys. Rev. Lett. 106:16160802
    [Google Scholar]
  161. 161.
    Zheng C, Zhu Y, Lazar S, Etheridge J. 2014. Fast imaging with inelastically scattered electrons by off-axis chromatic confocal electron microscopy. Phys. Rev. Lett. 112:16166101
    [Google Scholar]
  162. 162.
    Inada H, Su D, Egerton R, Konno M, Wu L et al. 2011. Atomic imaging using secondary electrons in a scanning transmission electron microscope: experimental observations and possible mechanisms. Ultramicroscopy 111:7865–76
    [Google Scholar]
  163. 163.
    Krivanek OL, Ursin JP, Bacon NJ, Corbin GJ, Dellby N et al. 2009. High-energy-resolution monochromator for aberration-corrected scanning transmission electron microscopy/electron energy-loss spectroscopy. Philos. Trans. R. Soc. A 367:19033683–97
    [Google Scholar]
  164. 164.
    Zachman MJ, Tu Z, Choudhury S, Archer LA, Kourkoutis LF. 2018. Cryo-STEM mapping of solid–liquid interfaces and dendrites in lithium-metal batteries. Nature 560:7718345–49
    [Google Scholar]
  165. 165.
    Yang WCD, Wang C, Fredin LA, Lin PA, Shimomoto L et al. 2019. Site-selective Co disproportionation mediated by localized surface plasmon resonance excited by electron beam. Nat. Mater. 18:6614–19
    [Google Scholar]
  166. 166.
    Baldi A, Narayan TC, Koh AL, Dionne JA. 2014. In situ detection of hydrogen-induced phase transitions in individual palladium nanocrystals. Nat. Mater. 13:121143–48
    [Google Scholar]
  167. 167.
    Senga R, Suenaga K, Barone P, Morishita S, Mauri F, Pichler T. 2019. Position and momentum mapping of vibrations in graphene nanostructures. Nature 573:7773247–50
    [Google Scholar]
  168. 168.
    Yan X, Liu C, Gadre CA, Gu L, Aoki T et al. 2021. Single-defect phonons imaged by electron microscopy. Nature 589:784065–69
    [Google Scholar]
  169. 169.
    Bugnet M, Ederer M, Lazarov V, Li L, Ramasse Q et al. 2022. Imaging the spatial distribution of electronic states in graphene using electron energy-loss spectroscopy: prospect of orbital mapping. Phys. Rev. Lett. 128:11116401
    [Google Scholar]
  170. 170.
    Sheen M, Ko Y, Kim D-U, Kim J, Byun J-H et al. 2022. Highly efficient blue ingan nanoscale light-emitting diodes. Nature 608:792156–61
    [Google Scholar]
  171. 171.
    Varela M, Findlay S, Lupini A, Christen H, Borisevich A et al. 2004. Spectroscopic imaging of single atoms within a bulk solid. Phys. Rev. Lett. 92:9095502
    [Google Scholar]
  172. 172.
    Bosman M, Keast V, Garcia-Munoz J, D'Alfonso AJ, Findlay S, Allen L 2007. Two-dimensional mapping of chemical information at atomic resolution. Phys. Rev. Lett. 99:8086102
    [Google Scholar]
  173. 173.
    Castaing R. 1951. Application of electron probes to local chemical and crystallographic analysis. PhD Thesis, Univ. Paris
  174. 174.
    Watanabe M, Okunishi E, Aoki T. 2010. Atomic-level chemical analysis by EELS and XEDS in aberration-corrected scanning transmission electron microscopy. Microsc. Microanal. 16:S266–67
    [Google Scholar]
  175. 175.
    Watanabe M, Williams D. 1999. The new form of the zeta-factor method for quantitative microanalysis in AEM-XEDS and its evaluation. Microsc. Microanal. 5:S288–89
    [Google Scholar]
  176. 176.
    Watanabe M, Williams D. 2006. The quantitative analysis of thin specimens: a review of progress from the cliff-lorimer to the new ζ-factor methods. J. Microsc. 221:289–109
    [Google Scholar]
  177. 177.
    Kübel C, Voigt A, Schoenmakers R, Otten M, Su D et al. 2005. Recent advances in electron tomography: TEM and HAADF-STEM tomography for materials science and semiconductor applications. Microsc. Microanal. 11:5378–400
    [Google Scholar]
  178. 178.
    Hata S, Furukawa H, Gondo T, Hirakami D, Horii N et al. 2020. Electron tomography imaging methods with diffraction contrast for materials research. Microscopy 69:3141–55
    [Google Scholar]
  179. 179.
    Wolf SG, Shimoni E, Elbaum M, Houben L. 2018. STEM tomography in biology. Cellular Imaging E Hanssen 33–60. Cham, Switz: Springer
    [Google Scholar]
  180. 180.
    Ganeeva G, Altingövde O, Khac QO, Stellacci F, Fua P et al. 2022. Automatic 3D reconstruction by deep learning neural networks using images acquired via 4D-STEM stereo imaging. Microsc. Microanal. 28:S1218–20
    [Google Scholar]
  181. 181.
    Van den Broek W, Rosenauer A, Goris B, Martinez G, Bals S et al. 2012. Correction of non-linear thickness effects in HAADF STEM electron tomography. Ultramicroscopy 116:8–12
    [Google Scholar]
  182. 182.
    Zhong Z, Aveyard R, Rieger B, Bals S, Palenstijn WJ, Batenburg KJ. 2018. Automatic correction of nonlinear damping effects in HAADF–STEM tomography for nanomaterials of discrete compositions. Ultramicroscopy 184:57–65
    [Google Scholar]
  183. 183.
    Genc A, Kovarik L, Gu M, Cheng H, Plachinda P et al. 2013. XEDS STEM tomography for 3D chemical characterization of nanoscale particles. Ultramicroscopy 131:24–32
    [Google Scholar]
  184. 184.
    Segal-Peretz T, Winterstein J, Doxastakis M, Ramírez-Hernández A, Biswas M et al. 2015. Characterizing the three-dimensional structure of block copolymers via sequential infiltration synthesis and scanning transmission electron tomography. ACS Nano 9:55333–47
    [Google Scholar]
  185. 185.
    Vanrompay H, Bladt E, Albrecht W, Béché A, Zakhozheva M et al. 2018. 3D characterization of heat-induced morphological changes of Au nanostars by fast in situ electron tomography. Nanoscale 10:4822792–801
    [Google Scholar]
  186. 186.
    Leary R, Midgley PA, Thomas JM. 2012. Recent advances in the application of electron tomography to materials chemistry. Acc. Chem. Res. 45:101782–91
    [Google Scholar]
  187. 187.
    Gault B, Chiaramonti A, Cojocaru-Mirédin O, Stender P, Dubosq R et al. 2021. Atom probe tomography. Nat. Rev. Methods Primers 1:151
    [Google Scholar]
  188. 188.
    Van Aert S, Batenburg KJ, Rossell MD, Erni R, Van Tendeloo G. 2011. Three-dimensional atomic imaging of crystalline nanoparticles. Nature 470:7334374–77
    [Google Scholar]
  189. 189.
    Goris B, Bals S, Van den Broek W, Carbó-Argibay E, Gómez-Graña S et al. 2012. Atomic-scale determination of surface facets in gold nanorods. Nat. Mater. 11:11930–35
    [Google Scholar]
  190. 190.
    Scott M, Chen CC, Mecklenburg M, Zhu C, Xu R et al. 2012. Electron tomography at 2.4-ångström resolution. Nature 483:7390444–47
    [Google Scholar]
  191. 191.
    Chen CC, Zhu C, White ER, Chiu CY, Scott M et al. 2013. Three-dimensional imaging of dislocations in a nanoparticle at atomic resolution. Nature 496:744374–77
    [Google Scholar]
  192. 192.
    Haberfehlner G, Thaler P, Knez D, Volk A, Hofer F et al. 2015. Formation of bimetallic clusters in superfluid helium nanodroplets analysed by atomic resolution electron tomography. Nat. Commun. 6:18779
    [Google Scholar]
  193. 193.
    Wang C, Duan H, Chen C, Wu P, Qi D et al. 2020. Three-dimensional atomic structure of grain boundaries resolved by atomic-resolution electron tomography. Matter 3:61999–2011
    [Google Scholar]
  194. 194.
    Yang Y, Chen CC, Scott M, Ophus C, Xu R et al. 2017. Deciphering chemical order/disorder and material properties at the single-atom level. Nature 542:763975–79
    [Google Scholar]
  195. 195.
    Pelz PM, Griffin S, Stonemeyer S, Popple D, Devyldere H et al. 2022. Solving complex nanostructures with ptychographic atomic electron tomography. arXiv:2206.08958 [physics.app-ph]
  196. 196.
    Xu R, Chen CC, Wu L, Scott M, Theis W et al. 2015. Three-dimensional coordinates of individual atoms in materials revealed by electron tomography. Nat. Mater. 14:111099–103
    [Google Scholar]
  197. 197.
    Ren D, Ophus C, Chen M, Waller L. 2020. A multiple scattering algorithm for three dimensional phase contrast atomic electron tomography. Ultramicroscopy 208:112860
    [Google Scholar]
  198. 198.
    Whittaker ML, Ren D, Ophus C, Zhang Y, Waller L et al. 2022. Ion complexation waves emerge at the curved interfaces of layered minerals. Nat. Commun. 13:13382
    [Google Scholar]
  199. 199.
    Lee J, Lee M, Park Y, Ophus C, Yang Y. 2022. Multislice electron tomography using 4D-STEM. arXiv:2210.12636 [cond-mat.mtrl-sci]
  200. 200.
    Schwartz J, Di ZW, Jiang Y, Fielitz AJ, Ha DH et al. 2022. Imaging atomic-scale chemistry from fused multi-modal electron microscopy. NPJ Comput. Mater. 8:116
    [Google Scholar]
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