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Material structure, properties, and dynamics through scanning transmission electron microscopy


Scanning transmission electron microscopy (STEM) has advanced rapidly in the last decade thanks to the ability to correct the major aberrations of the probe-forming lens. Now, atomic-sized beams are routine, even at accelerating voltages as low as 40 kV, allowing knock-on damage to be minimized in beam sensitive materials. The aberration-corrected probes can contain sufficient current for high-quality, simultaneous, imaging and analysis in multiple modes. Atomic positions can be mapped with picometer precision, revealing ferroelectric domain structures, composition can be mapped by energy-dispersive X-ray spectroscopy (EDX) and electron energy loss spectroscopy (EELS), and charge transfer can be tracked unit cell by unit cell using the EELS fine structure. Furthermore, dynamics of point defects can be investigated through rapid acquisition of multiple image scans. Today STEM has become an indispensable tool for analytical science at the atomic level, providing a whole new level of insights into the complex interplays that control material properties.


With the successful correction of lens aberrations, the STEM has become the dominant microscopy technique used today in material research, due to the availability of simultaneous, multiple, imaging and spectroscopic modes. While these benefits have long been appreciated in principle (Crewe 1966; Crewe et al. 1970; Rose 1974), before aberration correction, it was difficult to get sufficient current into the probe for good quality images, nor could spectroscopic signals be obtained at atomic resolution. Aberration correction, bringing smaller, brighter probes, has overcome the historic disadvantage of STEM, that of poor signal to noise ratio (Pennycook and Nellist 2011). In this review, we highlight some recent achievements and applications to materials. More detailed accounts can be found in a number of recent reviews (Pennycook 2015; Oxley et al. 2016; Varela et al. 2017; Gazquez et al. 2017; Li et al. 2017).

Figure 1 shows the principle of STEM. Like a scanning electron microscope, an incident probe is scanned across a sample, but it is thin enough so that the beam is transmitted, then several signals can be detected simultaneously and used to form images with complementary characteristics. The high-angle annular dark-field (HAADF) detector collects Rutherford scattering from the atomic nuclei, producing an image with strong sensitivity to atomic number Z, often called a Z-contrast image. Light columns such as O are only weakly visible in the Z-contrast image, but are seen clearly in a simultaneous bright-field (BF) image or annular bright-field (ABF) image. In perovskites and related materials, this allows the octahedral rotations to be determined, which are crucial to understanding their properties. If the bright-field detector is removed, electrons can be passed through a magnetic sector electron energy loss spectrometer to provide elemental maps and electronic structure information.

Fig. 1

Schematic showing the multiple imaging and analytical signals available in STEM. Top right is a HAADF image of BiFeO 3 ; the brightest atom columns are Bi and the less bright ones Fe, which are seen displaced slightly to the right due to the ferroelectric polarization. The center image is a bright-field image showing O columns, below is a color composite EELS image of LaMnO 3 in which the Mn is shown in red, O in green, showing displacements due to octahedral rotations, and La in blue. Adapted with premission from Borisevich et al. 2010 , copyrighted by the American Physical Society, and Varela et al. 2012

Imaging and spectroscopic modes

Imaging modes

The HAADF image is an incoherent image, that is, a direct image, of the columnar scattering power (Pennycook and Boatner 1988; Pennycook and Jesson 1990; Pennycook and Jesson 1991). It is least sensitive to crystal tilts, specimen thickness, and residual aberrations; therefore, it can provide positions of high-Z columns with high accuracy, as demonstrated in Fig. 2 showing BiFeO3 (BFO) viewed along the pseudocubic [110] direction (denoted [110]pc). However, for O columns, which scatter weakly to the HAADF detector, a bright-field image gives more accurate positions, although, being a phase-contrast image, the correct defocus and thickness combination must be determined by image simulation. Combining the positions from both (simultaneously acquired) images allows the octahedral rotations to be accurately measured (Wang et al. 2016; Kim et al. 2017).

Fig. 2

Measurement of oxygen octahedral tilts in BFO using HAADF and BF STEM images. a Schematic of the BFO structure observed along the [110] pc direction. b, c Simultaneously acquired HAADF and BF STEM images overlaid with peak finding results for the atomic columns. Bi (red) and Fe (blue) atomic columns can be defined from the HAADF STEM image (b) and oxygen columns from the BF STEM image (c). d A checkerboard pattern generated from the measurements of the projected tilt angles (±θ) of oxygen octahedra. Reproduced from Kim et al. 2017. Copyright 2017 with permission from Elsevier

The annular bright-field image, a phase-contrast image first proposed by Rose, (Rose 1974) has also become popular in the aberration-corrected era for imaging light atoms (Findlay et al. 2010; Ishikawa et al. 2011). However, the annular bright-field image may be more sensitive to crystal tilts than a normal bright-field image, as seen from the comparison in Fig. 3 (Kim et al. 2017). Figure 4 shows an example of the application to lead-free piezoelectric materials (Wu et al. 2016). It is known that good properties tend to result from an intimate phase mixture on the nanoscale. Engineering composition to have such phase transitions over the correct temperature range can produce high piezoelectric coefficients; therefore, it is of interest to be able to map local ferroelectric displacements cell by cell to track the polarization rotations. Figure 4 reveals a gradual polarization rotation from a rhombohedral phase (displacement along < 110>) to a tetragonal phase (displacement along < 100>). It is believed that this is indicative of a low-polarization anisotropy which leads to low-domain wall energy and enhanced piezoelectric coefficient (Zheng et al. 2017). There are many other examples of locating atomic columns to picometer accuracy (Borisevich et al. 2010; Borisevich et al. 2010; Kimoto et al. 2010; Chang et al. 2011; Kim et al. 2012; Yankovich et al. 2014; Tang et al. 2015; Dycus et al. 2015; He et al. 2015; Tang et al. 2016).

Fig. 3

Effect of specimen tilt in measuring oxygen octahedral tilts in BFO with 10.7 nm thickness. Oxygen octahedral tilt maps as a function of specimen tilt and defocus calculated from simulated a BF and c ABF images, respectively. b, d Line profiles of octahedral tilts averaged over vertical rows of the tilt maps shown in a and c, respectively. The dotted lines in the graphs indicate the tilt value (± 10.5°) of bulk BFO for the [110] pc projection. Simulations for 100 kV, spherical aberration coefficient − 0.037 mm, probe semiangle 31 mrad, and BF and ABF collection angles 0–1 and 8–20 mrad, respectively. Reproduced from Kim et al. 2017. Copyright 2017 with permission from Elsevier

Fig. 4

Local symmetry inside nanodomains of an alkali niobate lead-free ceramic. a STEM HAADF image at a domain boundary; b peak finding on a revealing rhombohedral (R) and tetragonal (T) regions; c enlarged image of the region in a within the blue box, showing T symmetry; d enlarged image of the region in b within the yellow box, showing R symmetry; e, f schematics showing projected atom displacements for T and R symmetry; g, h displacements along x- and y-axes; the region exhibiting displacement along only one axis reflects T symmetry, while the region exhibiting displacement along both x- and y-axes reflects R symmetry. i, j 2D and 3D images showing displacement along the diagonal direction, reflecting different regions with T and R symmetries. Reproduced from Wu et al. 2016. Copyright 2016 American Chemical Society

Besides accurate location of atomic column positions, much progress has also been made in quantifying crystal thickness down to the single-unit cell level, based on column intensity, often referred to as atom counting (Ortalan et al. 2010; Katz-Boon et al. 2013; Van Aert et al. 2013; De Backer et al. 2013; Martinez et al. 2014; Jones et al. 2014; Sang et al. 2014; De Backer et al. 2015). Figure 5 shows an example for a gold crystal (LeBeau et al. 2010). It is even possible to locate an impurity atom in depth with single-unit cell accuracy by accurate fitting of image intensity to simulations (Hwang et al. 2013; Ishikawa et al. 2014). The use of multiple annular detectors provides additional information (Zhang et al. 2015), and recently, it has even been possible to locate vacancies using such quantitative techniques (Kim et al. 2016).

Fig. 5

HAADF-STEM image of a wedge-shaped gold film viewed along110. The intensity maxima correspond to gold atom columns, and the white labels near the lower right of each atom column indicate the number of atoms contained in that column. The black box outlines the region from which the PACBED pattern shown in Fig. 3 was obtained. The image intensities are shown on an absolute scale relative to the incident beam intensity (see scale bar). Reproduced from LeBeau et al. 2010. Copyright 2010 American Chemical Society

More complex detector geometries are also becoming popular, particularly a segmented detector which allows a differential phase-contrast (DPC) mode (Shibata et al. 2012; Müller et al. 2014; Lazić et al. 2016). Forming the difference signal between opposite segments provides a measure of beam deflection, which can be used to form an image of electric or magnetic fields. Figure 6 shows the imaging of atomic electric fields in SrTiO3, where the fields are seen to point radially outwards from the centers of all the atomic columns, representing the field between the nuclei and the electrons projected along the viewing direction.

Fig. 6

Simultaneously acquired atomic-resolution STEM images of SrTiO 3 [001]. a ADF STEM image. b Projected electric field vector color map (left side) and electric field strength map (right side) constructed from the segmented-detector STEM images. The inset color wheel indicates how color and shade denote the electric field orientation and strength in the vector color map. It is seen that both heavy and light element columns are sensitively imaged. Intensity dips are clearly visible at the center of each atomic column position. Images taken with a JEOL ARM-300CF operating at 300 kV, adapted from Shibata et al. 2017

A pixelated detector provides another degree of freedom, in that the entire scattered electron distribution can be recorded for each point in the image. Often referred to as 4D STEM, there are several big advantages although at present, the detector readout severely limits the image speed. One major advantage is that the optimum detection angles can be decided after the image scan, not before as required with scintillator detectors. However, a more fundamental advantage is that not just annuli or segments can be used, but more complex detector patterns. This forms the basis of ptychography, where only those regions that give rise to a particular spatial frequency in the image are selected, as shown in Fig. 7. The method produces better signal to noise ratio and higher contrast than bright-field imaging since the electrons carrying no signal are excluded. Furthermore, no defocus or aberrations are needed to produce the image, so it is ideally complementary to the HAADF image, as shown in Fig. 8.

Fig. 7

Ptychographic reconstructions of phase and amplitude components for three spatial frequencies in graphene showing strong contribution from the regions of double overlap. Reproduced from Pennycook et al. 2015 . Copyright 2015 with permission from Elsevier

Fig. 8

Simultaneous Z-contrast and phase images of a double-wall carbon nanotube peapod. a Incoherent Z-contrast ADF image clearly shows the locations of the single iodine atoms indicated by the arrows. b The reconstructed phase image shows the presence of fullerenes inside the nanotube. c Annotated phase image with the fullerenes labeled using dotted circles and iodine atoms labeled using cross marks based on their locations in the ADF image. It is clear that the iodine atoms are located close to but outside the fullerenes. For comparison, conventional phase-contrast images including BF, ABF, DPC, and the DPC using the center of mass approach were synthesized from the data and shown in d h , respectively. The detector area of each imaging method is shown in white color in d g . The experiment was performed at an electron probe current of ~ 2.8 pA, pixel dwell time of 0.25 ms and a dose of ~ 1.3 10 4 e Å −2 . Scale bar, 1 nm; the gray scale of the phase in b is in units of radians reproduced from Rutte et al. 2016

Analytical modes

Analytical signals such as energy-dispersive X-ray spectroscopy (EDX) and electron energy loss spectroscopy (EELS) may be orders of magnitude weaker than imaging signals involving scattered electrons, as they typically involve inner shell excitation, which has a decreasing cross section with increasing energy loss. Nevertheless, aberration correction allows much larger currents to be focused into atomic-sized probes, as shown in Fig. 9. This fact, combined with major improvements in EDX collection efficiency, have made atomic resolution EDX mapping quite viable, see for example the near-atomically abrupt SrTiO3/LaAlO3 interface mapped in Fig. 10.

Fig. 9

Variation of probe current with probe size for uncorrected, third- and fifth-order-corrected 300 kV microscopes assuming a source brightness of 3 × 109 A sr1 cm2. Below the green line, the probe is predominantly coherent whereas above it is predominantly incoherent. Adapted from Pennycook 2016, with permission from Springer Nature. Copyright 2016

Fig. 10

EDX images of a near-atomically abrupt SrTiO 3 /LaAlO 3 interface showing atomic columns identified as labeled, with 10 min total acquisition using an Oxford X-Max 100TLE detector on a JEOL ARM200 equipped with ASCOR aberration corrector operated at 200 kV. The composite image includes all edges except O, top right is the HAADF image. Data courtesy Mengsha Li

EELS images generally have better statistics because EELS scattering is forward peaked, and for edges not too high in energy, all the inelastically scattered electrons can enter the spectrometer. Hence, it is possible to identify single impurity atoms embedded within a crystal. Figure 11 shows a 0.1% La-doped film of CaTiO3 grown on SrTiO3 by pulsed laser deposition. Using the La M edge, single La atoms can be located in specific columns of the CaTiO3 crystal.

Fig. 11

HAADF image of La-doped CaTiO 3 grown on a SrTiO 3 substrate with EELS images resolving the Ca, Ti, and O columns, and also revealing individual La atoms. The composite color image shows single La atoms in their respective columns. Data obtained with a Gatan Quantum ER on a JEOL ARM 200F equipped with ASCOR aberration corrector operated at 200 kV, recorded and processed by E. Okunishi

EELS edges also carry information on electronic structure since the transitions from the core level to the first available empty states depend on atomic valence and environment. This is particularly useful in transition metal oxides since the edge features are linearly related to transition metal valence. Hence, oxidation states can be directly extracted from atomic resolution images by comparison to standard spectra, for example, the O-K edge of a series of La x Ca1-xMnO3 compounds with varying x, is shown in Fig. 12 (Varela et al. 2009). The first and second peaks can be fitted by Gaussians and parameters such as their ratio or the relative distance between peaks linearly track the Mn oxidation state. This is especially useful for tracking charge transfer across interfaces as shown in Fig. 13, showing EELS data across a La0.7Ca0.3MnO3/YBa2Cu3O7-x/La0.7Ca0.3MnO3 (LCMO/YBCO/LCMO) trilayer (Varela et al. 2017). By quantifying the fine structure, the valence profile can be extracted, and it shows the LCMO layers have a hole concentration slightly higher than bulk while the YBCO layers have a depressed hole concentration, Fig. 14. Hence, electrons have transferred from the LCMO into the YBCO, which is consistent with their respective work functions and explains the depressed critical temperatures in the superconductor (Salafranca et al. 2014). Note also how the normalized pre-peak intensity is higher on the Cu-O planes than on the chains, reflecting directly that the holes responsible for superconductivity reside in the planes.

Fig. 12

a O K edges for a series of La x Ca 1- x MnO 3 compounds with x = 1, 0.7, 0.55, 0.33, and x = 0 from bottom to top. The energy scale has been shifted, so the pre-peaks are aligned, and the intensity normalized. The spectra have been displaced vertically for clarity. b O K EEL spectrum showing the Gaussian curves used to extract peak intensity and position (pre-peak in red and main peak in blue). c Normalized pre-peak intensity versus nominal oxidation state for the series of LCMO samples. The dashed line is a linear fit to the data. d Energy separation (calculated as the difference between positions of the second peak and the pre-peak) as a function of the Mn nominal oxidation state for the sample set of samples. Reprinted with permission from Varela et al. 2009. Copyright 2009 by the American Physical Society

Fig. 13

High-resolution Z-contrast image of a LCMO/YBCO/LCMO trilayer, obtained at 100 kV. b EELS linescan acquired along the direction marked with an arrow in (a). Principal component analysis (PCA) has been used to remove random noise. c Sample spectrum extracted from the linescan in (b), acquisition time is 2 s per spectrum. The data points are a raw spectrum while the red line is the same dataset after PCA. Reproduced from Varela et al. 2012. Copyright 2012 Oxford University Press

Fig. 14

a Top: For the O K edge, peak separation parameter, measured from the linescan in Fig.  13 b. Bottom: Mn oxidation state in the LCMO layers, derived from the data in a. b For the same linescan, O K edge pre-peak normalized integrated intensity. Reproduced from Varela et al. 2012. Copyright 2012 Oxford University Press

Another recent major advance is in higher energy resolution, achieved through monochromation, which is reaching into the meV range (Krivanek et al. 2014), opening the door to phonon spectroscopy (Lagos et al. 2017), and bandgap mapping (Lin et al. 2016). Such energy resolution is comparable to that of a synchrotron, but the microscope provides much better spatial resolution.

However, especially for low losses, the spatial resolution of EELS images may not be as high as for the HAADF or EDX image because electrons only need to pass close enough to the atom to cause an electronic transition, which can occur some distance away, an effect known as delocalization. Egerton (Egerton 2008) has introduced a measure of delocalization as the diameter containing 50% of the excitations, d50. However, it should be noted that this is not the same as image resolution, which is best defined as the full-width-half-maximum of the inelastic image (Oxley et al. 2016). Because of the delocalization effect, EELS images tend to have long tails more resembling a Lorentzian distribution than a Gaussian. The extended tails reduce image contrast more than they reduce resolution. Note also that delocalization is not a simple function of energy loss but depends on the actual electronic transitions. Recently, several examples have been found where low loss images show atomic resolution (Zhou et al. 2012; Zhou et al. 2012; Zhou et al. 2012). Quantum mechanical simulations show that such contrast arises from specific high momentum transfer transitions; hence, there is no violation of the uncertainty principle (Prange et al. 2012; Oxley et al. 2014; Kapetanakis et al. 2015; Kapetanakis et al. 2016).


The high-energy electron beam can cause ionization of the sample and direct knock-on events (displacement damage). Ionization damage increases as the beam energy is reduced, but knock-on damage decreases, until it disappears entirely below a certain threshold. Historically such processes have been viewed as undesirable damage events, but now that atomic resolution is possible at lower accelerating voltages, there have been many reports of watching atoms move under the beam, allowing insights into atomic motion and the energy landscape of small particles (Kurasch et al. 2012; Komsa et al. 2012; Komsa et al. 2013; Lin et al. 2014; Yang et al. 2014; Guo et al. 2014; Lehtinen et al. 2015; Jesse et al. 2015). Figure 15 shows a time-sequence of images of a Si6 cluster images at 60 keV beam energy. This is too low to knock atoms out of the cluster, but is sufficient to induce structural changes––one atom is repeatedly seen jumping from the left to right. Such studies reveal metastable configurations that would not be seen by simply heating the material.

Fig. 15

Sequential STEM Z-contrast images of a Si 6 cluster embedded in a graphene pore ( a h ). Scale bar, 0.2 nm. Reproduced from Lee et al. 2013

Another interesting insight into the dynamics of vacancies is revealed in Fig. 16, which shows beam-induced oxygen vacancy ordering in a LaCoO3/SrTiO3 (LCO/STO) superlattice (Jang et al. 2017). When O vacancies order into specific lattice planes, the strain energy is reduced since the lattice spacing of an entire plane can relax. The plane containing the vacancies expands, causing dark contrast in a Z-contrast image (Kim et al. 2012). Tracking planar spacings can therefore reveal this ordering process quantitatively. Since the average spacing in the LCO block in Fig. 16 does not change, the images show ordering of pre-existing vacancies rather than generation of new ones.

Fig. 16

Beam-induced oxygen vacancy ordering in a LaCoO 3 /SrTiO 3 superlattice grown on a SrTiO 3 substrate viewed along the [100] direction. a Sequential ADF images overlaid with corresponding maps of the out-of-plane interatomic La-La spacings. b Average spacings in the central V o layer (red curve), the adjacent (black curve), and peripheral (blue curve) layers within the top LCO block as a function of time; green (star) curve gives the overall average, suggesting that the beam primarily induces redistribution of existing vacancies rather than vacancy injection. c Comparison of the evolution of interatomic spacings in the oxygen-depleted planes of the top (T), middle (M), and bottom (B) LaCoO 3 blocks; the differences are attributed to differences in thickness due to the wedge geometry of the sample. d Atomic model of the ordering transition; La atoms are shown in green, CoO 6 octahedra in blue, and CoO 4 tetrahedra in purple. Reproduced from Jang et al. 2017. Copyright 2017 American Chemical Society

An example of the beam-induced diffusion of a heavy Ce atom is shown in Fig. 17. Quantification of image intensities matched to image simulations show that the atom jumps between next-neighbor sites inside the crystal, so the beam-induced motion is seeing the same diffusion processes that are normally induced thermally. Correlated vacancy/Ce atom motion and interstitial knock-out processes have also been seen (Ishikawa et al. 2014). The electron beam can even be used for solid-phase epitaxial crystallization of an amorphous material, as demonstrated by writing the letters ORNL in SrTiO3, see Fig. 18 (Jesse et al. 2015). Such beam-induced nanolithography should be achievable in three dimensions, due to the nanometer depth of focus of the aberration-corrected probe. Recently, it has been demonstrated that the STEM probe can be used to “push” single impurity atoms through the graphene lattice (Dyck et al. 2017). The potential for single atom fabrication with beams and probes is the subject of a recent issue of MRS Bulletin (Pennycook and Kalinin 2017).

Fig. 17

Atomic-resolution STEM images of Ce hopping from column A to B in AlN. Images are averages over ( a ) 19 frames before the jump and ( b ) 19 frames after the jump. Reproduced from Ishikawa et al. 2014 . Copyright 2014 American Chemical Society

Fig. 18

An example of crystalline oxide sculpting using an arbitrary graphical pattern (in this case, text “ORNL”): Fourier-filtered HAADF image of the ( a ) complete structure and ( b d ) magnified raw images of the regions at the top and at the base of the patterned letters. Note the same crystallographic orientation in b , c , and d , highlighting the epitaxial character of the growth. The widths of image b , c , and d are 12 nm. Reproduced from Jesse et al. 2015

Imaging, analysis, and nanofabrication in 3D

Ideally, we need atomic scale imaging, analysis, and nanofabrication not just in a two-dimensional projection but in three dimensions. In recent years, much progress has been made in tomography, combining views in multiple directions to reconstruct 3D structure (Goris et al. 2013; Bals et al. 2014; Goris et al. 2015; Miao et al. 2016; Bals et al. 2016). Figure 19 shows an example of the atomic scale reconstruction of an FePt nanoparticle revealing the presence of different ordered structures and different degrees of ordering (Yang et al. 2017). Grain boundaries and even point defects could be detected. Notable progress has also been made in EELS and EDX tomography, although atomic resolution remains far off due to the lower signal levels (Jarausch et al. 2009; Yedra et al. 2012; Haberfehlner et al. 2014; Collins and Midgley 2017).

Fig. 19

3D determination of atomic coordinates, chemical species, and grain structure of an FePt nanoparticle. a Overview of the 3D positions of individual atomic species with Fe atoms in red and Pt atoms in blue. b The nanoparticle consists of two large L12 grains, three small L12 grains, three small L10 grains, and a Pt-rich A1 grain. c Multislice image. Reproduced from Yang et al. 2017, by permission from Springer Nature. Copyright 2017

The example shown in Fig. 19 required many hours of data collection, which many samples could not withstand. An alternative method is optical sectioning. Aberration correctors achieve higher resolution through higher probe convergence angles. Lateral resolution increases linearly with increasing probe angle; however, depth resolution increases quadratically. So, with the latest generation of aberration correctors, the depth of focus has reduced to the nanometer scale, and the image comes from a thin section of the sample. Changing the focus gives a series of images at different depths which could also be reconstructed into a 3D image without the need to tilt the sample. At present, such optical sectioning has not achieved atomic resolution, but may with future generations of aberration corrector (Pennycook and Kalinin 2014; Pennycook 2015; Ishikawa et al. 2016). Figure 20 shows a simulated focal series of Ce atoms substituted in AlN for probe-forming angles of 30, 60, and 100 mrad (Ishikawa et al. 2015). For the larger probe angles, the two dopant atoms can be easily located at 2- and 8-nm depth. Although these simulations assume aberration-free conditions, simulations including chromatic aberration and the effects of electron shot noise suggest this approach should work under realistic conditions (Ishikawa et al. 2016). Optical sectioning can also be applied to analytical signals with nanoscale resolution, avoiding the need for specimen tilting (Pennycook et al. 2017). Alternatively, it may prove better to combine depth sectioning with discrete tomography (Alania et al. 2017).

Fig. 20

Simulated focal series of images of Ce atoms substituted in AlN for probe-forming angles of 30 (upper), 60 (center), and 100 (lower) mrad at 300 kV accelerating voltage, assuming aberration-free conditions. Ce atom locations are indicated by red rectangles. Reproduced from Ishikawa et al. 2015. Copyright 2014, with permission from Elsevier


STEM has developed dramatically in recent years, thanks to the development of aberration correctors which have allowed the advantages of multiple, simultaneous imaging and spectroscopic modes to be exploited with high sensitivity and precision. There are advantages also for in situ and operandi studies since STEM allows good control of dose rate and illumination area (Chang et al. 2011; Jungjohann et al. 2012; Mehdi et al. 2015; Wang et al. 2016). There are also major developments in mathematical image reconstruction techniques, learning from other fields such as computer vision, which are pushing towards lower dose imaging (Stevens et al. 2014; Meyer et al. 2014; Kovarik et al. 2016; Voyles 2017). It is certainly an exciting and rewarding time to be exploring the atomic world.


  1. Alania M, Altantzis T, De Backer A, et al. Depth sectioning combined with atom-counting in HAADF STEM to retrieve the 3D atomic structure. Ultramicroscopy. 2017;177:36–42.

    CAS  Article  Google Scholar 

  2. Bals S, Goris B, Altantzis T, et al. Seeing and measuring in 3D with electrons. Comptes Rendus Physique. 2014;15:140–50.

    CAS  Article  Google Scholar 

  3. Bals S, Goris B, De Backer A, et al. Atomic resolution electron tomography. MRS Bull. 2016;41:525–30.

    Article  Google Scholar 

  4. Borisevich A, Ovchinnikov OS, Chang HJ, et al. Mapping octahedral tilts and polarization across a domain wall in BiFeO3 from Z-contrast scanning transmission electron microscopy image atomic column shape analysis. ACS Nano. 2010;4:6071–9.

  5. Borisevich AY, Chang HJ, Huijben M, et al. Suppression of octahedral tilts and associated changes in electronic properties at epitaxial oxide heterostructure interfaces. Phys Rev Lett. 2010;105:087204.

    CAS  Article  Google Scholar 

  6. Chang H, Kalinin SV, Yang S, et al. Watching domains grow: in-situ studies of polarization switching by combined scanning probe and scanning transmission electron microscopy. J Appl Phys. 2011;110:052014–7.

    Article  Google Scholar 

  7. Chang HJ, Chang HJ, Kalinin SV, et al. Atomically resolved mapping of polarization and electric fields across ferroelectric/oxide interfaces by Z-contrast imaging. Adv Mater 2474–2479. 2011;

  8. Collins SM, Midgley PA. Progress and opportunities in EELS and EDS tomography. 1–9. 2017;

  9. Crewe AV. Scanning electron microscopes—is high resolution possible? Science. 1966;154:729–38.

    CAS  Article  Google Scholar 

  10. Crewe AV, Wall J, Langmore J. Visibility of single atoms. Science. 1970;168:1338–40.

    CAS  Article  Google Scholar 

  11. De Backer A, De Wael A, Gonnissen J, Van Aert S. Optimal experimental design for nano-particle atom-counting from high-resolution STEM images. Ultramicroscopy. 2015;151:46–55.

    CAS  Article  Google Scholar 

  12. De Backer A, Martinez GT, Rosenauer A, Van Aert S. Atom counting in HAADF STEM using a statistical model-based approach: methodology, possibilities, and inherent limitations. Ultramicroscopy. 2013;134:23–33.

    CAS  Article  Google Scholar 

  13. Dyck O, Kim S, Kalinin SV, Jesse S. Placing single atoms in graphene with a scanning transmission electron microscope. Appl Phys Lett. 2017;111:113104–6.

    Article  Google Scholar 

  14. Dycus JH, Harris JS, Sang X, et al. Accurate nanoscale crystallography in real-space using scanning transmission electron microscopy. Microsc Anal. 2015;21:946–52.

    CAS  Google Scholar 

  15. Egerton RF. Electron energy-loss spectroscopy in the TEM. Rep Prog Phys. 2008;72:016502x.

    Article  Google Scholar 

  16. Findlay SD, Shibata N, Sawada H, et al. Dynamics of annular bright field imaging in scanning transmission electron microscopy. Ultramicroscopy. 2010;110:903–23.

    CAS  Article  Google Scholar 

  17. Gazquez J, Sanchez-Santolino G, Biškup N, et al. Materials science in semiconductor processing. Mater Sci Semicond Process. 2017;65:49–63.

    CAS  Article  Google Scholar 

  18. Goris B, De Backer A, Van Aert S, et al. Three-dimensional elemental mapping at the atomic scale in bimetallic nanocrystals. Nano Lett. 2013;13:4236–41.

    CAS  Article  Google Scholar 

  19. Goris B, De Beenhouwer J, De Backer A, et al. Measuring lattice strain in three dimensions through electron microscopy. Nano Lett. 2015;15:6996–7001.

    Article  Google Scholar 

  20. Guo J, Lee J, Contescu CI, et al. Crown ethers in graphene. Nat Commun. 2014;5:1–6.

    CAS  Google Scholar 

  21. Haberfehlner G, Orthacker A, Albu M, et al. Nanoscale voxel spectroscopy by simultaneous EELS and EDS tomography. Nano. 2014;6:14563–9.

    CAS  Google Scholar 

  22. He Q, Ishikawa R, Lupini AR, et al. Towards 3D mapping of BO6 octahedron rotations at perovskite heterointerfaces, unit cell by unit cell. ACS Nano. 2015;9:8412–9.

  23. Hwang J, Zhang JY, D’Alfonso AJ, et al. Three-dimensional imaging of individual dopant atoms in SrTiO3. Phys Rev Lett. 2013;111:266101.

  24. Ishikawa R, Lupini AR, Findlay SD, et al (2014) Three-dimensional location of a single dopant with atomic precision by aberration-corrected scanning transmission electron microscopy. Nano Lett 1903−1908 doi:

  25. Ishikawa R, Lupini AR, Hinuma Y, Pennycook SJ. Large-angle illumination STEM: toward three-dimensional atom-by-atom imaging. Ultramicroscopy. 2015;151:122–9.

    CAS  Article  Google Scholar 

  26. Ishikawa R, Mishra R, Lupini AR, et al. Direct observation of dopant atom diffusion in a bulk semiconductor crystal enhanced by a large size mismatch. Phys Rev Lett. 2014;113:155501.

    Article  Google Scholar 

  27. Ishikawa R, Okunishi E, Sawada H, et al. Direct imaging of hydrogen-atom columns in a crystal by annular bright-field electron microscopy. Nat Mater. 2011;10:278–81.

    CAS  Article  Google Scholar 

  28. Ishikawa R, Pennycook SJ, Lupini AR, et al. Single atom visibility in STEM optical depth sectioning. Appl Phys Lett. 2016;109:163102.

    Article  Google Scholar 

  29. Jang JH, Kim Y-M, He Q, et al. In situ observation of oxygen vacancy dynamics and ordering in the epitaxial LaCoO3 system. ACS Nano. 2017;11:6942–9.

  30. Jarausch K, Thomas P, Leonard DN, et al. Four-dimensional STEM-EELS: enabling nano-scale chemical tomography. Ultramicroscopy. 2009;109:326–37.

    CAS  Article  Google Scholar 

  31. Jesse S, He Q, Lupini AR, et al. Atomic-level sculpting of crystalline oxides: toward bulk nanofabrication with single atomic plane precision. Small. 2015;11:5895–900.

    CAS  Article  Google Scholar 

  32. Jones L, MacArthur KE, Fauske VT, et al. Rapid estimation of catalyst nanoparticle morphology and atomic-coordination by high-resolution Z-contrast electron microscopy. Nano Lett. 2014;14:6336–41.

    CAS  Article  Google Scholar 

  33. Jungjohann KL, Evans JE, Aguiar JA, et al. Atomic-scale imaging and spectroscopy for in situ liquid scanning transmission electron microscopy. Microsc Anal. 2012;18:621–7.

    CAS  Google Scholar 

  34. Kapetanakis MD, Oxley MP, Zhou W, et al. Signatures of distinct impurity configurations in atomic-resolution valence electron-energy-loss spectroscopy: application to graphene. Phys Rev B. 2016;94:155449.

    Article  Google Scholar 

  35. Kapetanakis MD, Zhou W, Oxley MP, et al. Low-loss electron energy loss spectroscopy: an atomic-resolution complement to optical spectroscopies and application to graphene. Phys Rev B. 2015;92:125147.

    Article  Google Scholar 

  36. Katz-Boon H, Rossouw CJ, Dwyer C, Etheridge J. Rapid measurement of nanoparticle thickness profiles. Ultramicroscopy. 2013;124:61–70.

    CAS  Article  Google Scholar 

  37. Kim H, Zhang JY, Raghavan S, Stemmer S. Direct observation of Sr vacancies in SrTiO3 by quantitative scanning transmission electron microscopy. Phys Rev X. 2016;6:041063–7.

  38. Kim Y-M, He J, Biegalski MD, et al. Probing oxygen vacancy concentration and homogeneity in solid-oxide fuel-cell cathode materials on the subunit-cell level. Nat Mater. 2012;11:1–7.

    CAS  Article  Google Scholar 

  39. Kim Y-M, Pennycook SJ, Borisevich AY. Quantitative comparison of bright field and annular bright field imaging modes for characterization of oxygen octahedral tilts. Ultramicroscopy. 2017;181:1–7.

    CAS  Article  Google Scholar 

  40. Kimoto K, Asaka T, Yu X, et al. Local crystal structure analysis with several picometer precision using scanning transmission electron microscopy. Ultramicroscopy. 2010;110:778–82.

    CAS  Article  Google Scholar 

  41. Komsa H-P, Kotakoski J, Kurasch S, et al. Two-dimensional transition metal dichalcogenides under electron irradiation: defect production and doping. Phys Rev Lett. 2012;109:035503–5.

    Article  Google Scholar 

  42. Komsa H-P, Kurasch S, Lehtinen O, et al. From point to extended defects in two-dimensional MoS2: evolution of atomic structure under electron irradiation. Phys Rev B. 2013;88:035301–8.

  43. Kovarik L, Stevens A, Liyu A, Browning ND. Implementing an accurate and rapid sparse sampling approach for low-dose atomic resolution STEM imaging. Appl Phys Lett. 2016;109:164102–6.

    Article  Google Scholar 

  44. Krivanek OL, Lovejoy TC, Dellby N, et al. Vibrational spectroscopy in the electron microscope. Nature. 2014;514:209–12.

    CAS  Article  Google Scholar 

  45. Kurasch S, Kotakoski J, Lehtinen O, et al. Atom-by-atom observation of grain boundary migration in graphene. Nano Lett. 2012;12:3168–73.

    CAS  Article  Google Scholar 

  46. Lagos MJ, Trügler A, Hohenester U, Batson PE. Mapping vibrational surface and bulk modes in a single nanocube. Nature. 2017;543:529–32.

    CAS  Article  Google Scholar 

  47. Lazić I, Bosch EGT, Lazar S. Phase contrast STEM for thin samples: integrated differential phase contrast. Ultramicroscopy. 2016;160:265–80.

    Article  Google Scholar 

  48. LeBeau JM, Findlay SD, Allen LJ, Stemmer S. Standardless atom counting in scanning transmission electron microscopy. Nano Lett. 2010;10:4405–8.

    CAS  Article  Google Scholar 

  49. Lee J, Zhou W, Pennycook SJ, et al. Direct visualization of reversible dynamics in a Si6 cluster embedded in a graphene pore. Nat Commun. 2013;4:1650–7.

  50. Lehtinen O, Vats N, Algara-Siller G, et al. Implantation and atomic-scale investigation of self-interstitials in graphene. Nano Lett. 2015;15:235–41.

    CAS  Article  Google Scholar 

  51. Li C, Poplawsky J, Yan Y, Pennycook SJ. Understanding individual defects in CdTe thin-film solar cells via STEM: from atomic structure to electrical activity. Mater Sci Semicond Process. 2017;65:64–76.

    CAS  Article  Google Scholar 

  52. Lin J, Cretu O, Zhou W, et al. Flexible metallic nanowires with self-adaptive contacts to semiconducting transition-metal dichalcogenide monolayers. Nat Nanotechnol. 2014;9:436–42.

    CAS  Article  Google Scholar 

  53. Lin J, Gomez L, de Weerd C, et al. Direct observation of band structure modifications in nanocrystals of CsPbBr3 perovskite. Nano Lett. 2016;16:7198–202.

  54. Martinez GT, Rosenauer A, De Backer A, et al. Quantitative composition determination at the atomic level using model-based high-angle annular dark field scanning transmission electron microscopy. Ultramicroscopy. 2014;137:12–9.

    CAS  Article  Google Scholar 

  55. Mehdi BL, Qian J, Nasybulin E, et al (2015) Observation and quantification of nanoscale processes in Lithium batteries by operando electrochemical (S)TEM. Nano Lett 15:2168−2173 doi:

  56. Meyer JC, Kotakoski J, Mangler C. Atomic structure from large-area, low-dose exposures of materials: a new route to circumvent radiation damage. Ultramicroscopy. 2014;145:13–21.

    CAS  Article  Google Scholar 

  57. Miao J, Ercius P, Billinge S. Atomic electron tomography: 3D structures without crystals. Science. 2016;

  58. Müller K, Krause FF, Béché A, et al. Atomic electric fields revealed by a quantum mechanical approach to electron picodiffraction. Nat Commun. 2014;5:5653.

    Article  Google Scholar 

  59. Ortalan V, Uzun A, Gates BC, Browning ND. Towards full-structure determination of bimetallic nanoparticles with an aberration-corrected electron microscope. Nat Nanotechnol. 2010;5:843–7.

    CAS  Article  Google Scholar 

  60. Oxley MP, Kapetanakis MD, Prange MP, et al. Simulation of probe position-dependent electron energy-loss fine structure. Microsc Anal. 2014;20:784–97.

    CAS  Google Scholar 

  61. Oxley MP, Lupini AR, Pennycook SJ. Ultra-high resolution electron microscopy. Rep Prog Phys. 2016;80:026101–65.

    Article  Google Scholar 

  62. Pennycook SJ. Fulfilling Feynman’s dream: “make the electron microscope 100 times better”—are we there yet? MRS Bull. 2015;40:71–8.

    Article  Google Scholar 

  63. Pennycook SJ. Imaging in STEM. In: Carter CB, Williams DB, editors. Transmission electron microscopy. 1st ed. Cham: Springer; 2016. p. 283–342.

    Google Scholar 

  64. Pennycook SJ, Boatner LA. Chemically sensitive structure-imaging with a scanning transmission electron microscope. Nature. 1988;336:565–7.

    CAS  Article  Google Scholar 

  65. Pennycook SJ, Jesson DE. High-resolution incoherent imaging of crystals. Phys Rev Lett. 1990;64:938–41.

    CAS  Article  Google Scholar 

  66. Pennycook SJ, Jesson DE. High-resolution Z-contrast imaging of crystals. Ultramicroscopy. 1991;37:14–38.

    Article  Google Scholar 

  67. Pennycook SJ, Kalinin SV. Hasten high resolution. Nature. 2014;515:487–8.

    CAS  Article  Google Scholar 

  68. Pennycook SJ, Kalinin SV (2017) Single atom fabrication with beams and probes.

    Google Scholar 

  69. Pennycook SJ, Nellist PD, editors. Scanning transmission electron microscopy. New York, NY: Springer New York; 2011.

    Google Scholar 

  70. Pennycook TJ, Lupini AR, Yang H, et al. Efficient phase contrast imaging in STEM using a pixelated detector. Part 1: experimental demonstration at atomic resolution. Ultramicroscopy. 2015;151:160–7.

    CAS  Article  Google Scholar 

  71. Pennycook TJ, Yang H, Jones L, et al. 3D elemental mapping with nanometer scale depth resolution via electron optical sectioning. Ultramicroscopy. 2017;174:27–34.

    CAS  Article  Google Scholar 

  72. Prange MP, Oxley MP, Varela M, et al. Simulation of spatially resolved electron energy loss near-edge structure for scanning transmission electron microscopy. Phys Rev Lett. 2012;109:246101.

    CAS  Article  Google Scholar 

  73. Rose H. Phase-contrast in scanning transmission electron microscopy. Optik. 1974;39:416–36.

    Google Scholar 

  74. Rutte RN, Jones L, Simson M, et al. Simultaneous atomic-resolution electron ptychography and Z-contrast imaging of light and heavy elements in complex nanostructures. Nat Commun. 2016;7:1–8.

    Google Scholar 

  75. Salafranca J, Rincón J, Tornos J, et al. Competition between covalent bonding and charge transfer at complex-oxide interfaces. Phys Rev Lett. 2014;112:196802.

    Article  Google Scholar 

  76. Sang X, Oni AA, LeBeau JM. Atom column indexing: atomic resolution image analysis through a matrix representation. Microsc Anal. 2014;20:1764–71.

    CAS  Google Scholar 

  77. Shibata N, Findlay SD, Kohno Y, et al. Differential phase-contrast microscopy at atomic resolution. Nat Phys. 2012;8:611–5.

    CAS  Article  Google Scholar 

  78. Shibata N, Seki T, Sanchez-Santolino G, et al. Electric field imaging of single atoms. Nat Commun. 2017;8:15631.

    CAS  Article  Google Scholar 

  79. Stevens A, Yang H, Carin L, et al. The potential for Bayesian compressive sensing to significantly reduce electron dose in high-resolution STEM images. Microscopy. 2014;63:41–51.

    Article  Google Scholar 

  80. Tang YL, Zhu YL, Hong ZJ, et al. 3D polarization texture of a symmetric 4-fold flux closure domain in strained ferroelectric PbTiO3 films. J Mater Res. 2016;32:957–67.

  81. Tang YL, Zhu YL, Ma XL, et al. Observation of a periodic array of flux-closure quadrants in strained ferroelectric PbTiO3 films. Science. 2015;348:547–51.

  82. Van Aert S, De Backer A, Martinez G, et al. Procedure to count atoms with trustworthy single-atom sensitivity. Phys Rev B. 2013;87:064107.

    Article  Google Scholar 

  83. Varela M, Gazquez J, Pennycook SJ. STEM-EELS imaging of complex oxides and interfaces. MRS Bull. 2012;37:29–35.

    CAS  Article  Google Scholar 

  84. Varela M, Leon C, Santamaria J, Pennycook SJ. Scanning transmission electron microscopy of oxides. In: Tsymbal EY, Dagotto ERA, Eom C-B, Ramesh R, editors. Multifunctional oxide heterostructures. Oxford: Oxford University Press; 2017. p. 1–51.

  85. Varela M, Oxley MP, Luo W, et al. Atomic-resolution imaging of oxidation states in manganites. Phys Rev B. 2009;79:085117.

    Article  Google Scholar 

  86. Voyles PM. Informatics and data science in materials microscopy. Curr Opin Solid State Mater Sci. 2017;21:141–58.

    Article  Google Scholar 

  87. Wang Y, Salzberger U, Sigle W, et al. Ultramicroscopy. Ultramicroscopy. 2016;168:46–52.

    Article  Google Scholar 

  88. Wang Z, Santhanagopalan D, Zhang W, et al. In situ STEM-EELS observation of nanoscale interfacial phenomena in all-solid-state batteries. Nano Lett. 2016;16:3760–7.

    CAS  Article  Google Scholar 

  89. Wu B, Wu H, Wu J, et al. Giant piezoelectricity and high Curie temperature in nanostructured alkali niobate lead-free piezoceramics through phase coexistence. J Am Chem Soc. 2016;138:15459–64.

    CAS  Article  Google Scholar 

  90. Yang Y, Chen C-C, Scott MC, et al. Deciphering chemical order/disorder and material properties at the single-atom level. Nature. 2017;542:75–9.

    CAS  Article  Google Scholar 

  91. Yang Z, Yin L, Lee J, et al. Direct observation of atomic dynamics and silicon doping at a topological defect in graphene. Angew Chem Int Edit. 2014;53:8908–12.

    CAS  Article  Google Scholar 

  92. Yankovich AB, Berkels B, Dahmen W, et al. Picometre-precision analysis of scanning transmission electron microscopy images of platinum nanocatalysts. Nat Commun. 2014;5:1–7.

    Article  Google Scholar 

  93. Yedra L, Eljarrat A, Arenal R, et al. EEL spectroscopic tomography towards a new dimension in nanomaterials analysis. Ultramicroscopy. 2012;122:12–8.

    CAS  Article  Google Scholar 

  94. Zhang JY, Hwang J, Isaac BJ, Stemmer S. Variable-angle high-angle annular dark-field imaging: application to three-dimensional dopant atom profiling. Sci Rep. 2015:1–10.

  95. Zheng T, Wu H, Yuan Y, et al. The structural origin of enhanced piezoelectric performance and stability in lead free ceramics. Energy Environ Sci. 2017;10:528–37.

    CAS  Article  Google Scholar 

  96. Zhou W, Lee J, Nanda J, et al. Atomically localized plasmon enhancement in monolayer graphene. Nat Nanotechnol. 2012;7:161–5.

    CAS  Article  Google Scholar 

  97. Zhou W, Oxley MP, Lupini AR, et al. Single atom microscopy. Microsc Anal. 2012;18:1342–54.

    CAS  Google Scholar 

  98. Zhou W, Pennycook SJ, Idrobo J-C. Localization of inelastic electron scattering in the low-loss energy regime. Ultramicroscopy. 2012;119:51–6.

    CAS  Article  Google Scholar 

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All authors are grateful to their collaborators on the work cited here. SJP is grateful to the National University of Singapore for funding. CJL is supported by a Lee Kuan Yew Fellowship. Research at Universidad Complutense is sponsored by the European Research Council PoC-2016 POLAR-EM and Spanish MINECO-FEDER MAT2015-66888-C3-3-R. YMK was supported by the Institute for Basic Science (IBS-R011-D1) and Creative Materials Discovery Program through the NRF (National Research Foundation of Korea) grant (NRF-2015M3D1A1070672). J.H. Jang is supported by the Korea Basic Science Institute grant (T37210).


SJP is grateful to the National University of Singapore for funding. CJL is supported by a Lee Kuan Yew Fellowship. Research at Universidad Complutense is sponsored by the European Research Council PoC-2016 POLAR-EM and Spanish MINECO-FEDER MAT2015-66888-C3-3-R. YMK was supported by the Institute for Basic Science (IBS-R011-D1) and Creative Materials Discovery Program through the NRF (National Research Foundation of Korea) grant (NRF-2015M3D1A1070672) in Korea. J.H. Jang is supported by the Korea Basic Science Institute grant (T37210).

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Pennycook, S.J., Li, C., Li, M. et al. Material structure, properties, and dynamics through scanning transmission electron microscopy. J Anal Sci Technol 9, 11 (2018).

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  • Scanning transmission electron microscopy
  • Electron energy loss spectroscopy
  • Energy loss near-edge fine structure
  • Energy-dispersive X-ray spectroscopy
  • Ferroelectric domain structures
  • Lead-free piezoelectrics
  • Point defect dynamics
  • Nanofabrication