Applications of STEM-EELS to complex oxides

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Applications of STEM-EELS to complex oxides Jaume Gázquez a, Gabriel Sánchez-Santolino b,c, Neven Biškup d, Manuel A. Roldán b,e, M. Cabero b, Stephen J. Pennycook f, María Varela b,n a

Institute of Materials Science of Barcelona ICMAB-CSIC, Bellaterra, 08193 Barcelona, Spain Facultad de CC. Físicas & Instituto Pluridisciplinar, Universidad Complutense de Madrid, 28040 Madrid, Spain c Institute of Engineering Innovation, School of Engineering, The University of Tokyo, Yayoi 2-11-16, Bunkyo-ku, Tokyo 113-8656, Japan d Centro Nacional de Microscopía Electrónica, Universidad Complutense de Madrid, 28040 Madrid, Spain e King Abdullah University of Science and Technology (KAUST), 23955, Saudi Arabia f National University of Singapore, Department of Materials Science and Engineering, 9 Engineering Drive 1, Block EA, 07-14, 117575 Singapore b

art ic l e i nf o

a b s t r a c t

Article history: Received 1 March 2016 Received in revised form 19 May 2016 Accepted 9 June 2016

In this chapter we will review a few examples of applications of atomic resolution aberration corrected scanning transmission electron microscopy (STEM) and electron energy-loss spectroscopy (EELS) to complex oxide materials. These are most challenging systems where subtle changes in structure or chemistry may result in colossal responses in macroscopic physical behavior. Here, we will review how atomic resolution compositional mapping can be achieved in manganite thin films and single crystals, highlighting the importance of considering artifacts during quantification. Besides, minor changes in near edge fine structure may take place when the crystalline environment, and hence nearest neighbor configuration, is modified. These can also be tracked by atomic resolution EELS, as will be shown through the study of binary Fe oxides. Also, examples regarding the study of distributions of point defects such as O vacancies in cobaltite thin films will be discussed. In these materials, a combination of epitaxial strain and defects may promote physical behaviors not present in bulk, such as the stabilization of unexpected spin state superlattices. Last, a study of extended defects such as dislocation lines will be reviewed. In particular, we will show how chemical segregation at dislocation cores in yttria-stabilized zirconia grain boundaries results in the generation of static O vacancies that affect the local electrostatic potential and hence, the macroscopic ionic conduction properties. & 2016 Published by Elsevier Ltd.

Keywords: Electron microscopy STEM EELS Complex oxides Interfaces

1. Introduction With the advent of spherical aberration correction, both spatial resolution and sensitivity limits attainable in the scanning transmission electron microscope (STEM) have improved down to the single atom level. Atomic resolution in the STEM was demonstrated decades ago [1–8], but the correction of optical aberrations has resulted in unprecedented contrast and signal-to-noise ratio improvements in both imaging and electron energy-loss spectroscopy (EELS) [9–18]. A completely new perspective into the nanoworld is available now to scientists working at the forefront of materials science. Armed with STEM-EELS tools, we can extract a whole new dimension of information down to the level of light atoms, single dopants or isolated defects [19–22], be it in the study of cutting-edge novel materials or old systems revisited. Such capabilities bring a new spin to research into materials, which are n Corresponding author at: Universidad Complutense de Madrid, Facultad de CC. Físicas & Instituto Pluridisciplinar. Madrid 28040, Spain. E-mail address: [email protected] (M. Varela).

invaluable when analyzing systems whose physical properties are sensitive to subtle structural modifications or small changes in chemical doping, such as complex oxides. Oxides are very relevant systems from the point of view of both physical properties and technological relevance. Amongst complex oxides we can find insulators, semiconductors or metals, but also ferromagnets, ferroelectrics, multiferroics, superconductors and a wide list of families displaying the most disparate physical behaviors. Interestingly, most of these challenging properties can be extremely dependent on subtle changes in either structure or chemistry, sometimes triggering large macroscopic responses such as colossal magnetoresistance or high-Tc superconductivity. Therefore, harnessing the oxides that will become the building blocks of future devices is a fundamental task for materials scientists. Success necessarily rests on the availability of probes that can interrogate these systems in an atom-by-atom fashion in real space, specifically, aberration corrected STEM-EELS. In this chapter, we will review a few examples of applications of these techniques to cutting-edge oxides. We will focus on exploring three different fronts: i) examples (including

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quantification) of atomic resolution imaging and spectroscopy in oxides, ii) sensitivity to effects of minor variations in near edge fine structure (ELNES) in order to demonstrate that it can be used as a tool to identify different phases in the nanoscale and finally, iii) characterization of defects and arrays of defects (such as superstructures or grain boundaries). We will review these topics in an integrated fashion within actual examples of applications to oxide materials (bulk and thin films). In particular, Section 2 will deal with the atomic scale imaging and spectroscopy of complex oxides, including approaches to chemical quantification. Section 3 will describe the study of binary Fe oxides, and how minor changes in chemistry and coordination can affect the structure of EELS edges. An example of the study and characteristics of ordered arrays of point defects will be described in Section 4, which will deal with the characterization of O vacancy rich cobaltite thin films. Section 5 will explain how extended defects such as dislocation cores can be approached and even quantified in ionic conductors, and how the macroscopic physical properties can be explained in the light of microscopic findings. While this chapter cannot review every possible contribution to these fields, we hope to be able to convey a general flavor of what STEM-EELS can do for researchers working in complex oxides.

2. Atomic resolution imaging and quantification in oxides: manganite crystals and thin films Shortly after the first demonstrations of the success of aberration correction in the STEM, high angle annular dark field (HAADF) imaging combined with electron energy-loss spectroscopy (EELS) was applied to complex oxides [23]. Of particular interest have been the reports focused on the study of the family of manganite oxides. These perovskites exhibit quite intriguing behaviors still far from understood, such as colossal magnetoresistance (CMR) [24]. While the mechanisms underlying CMR are not completely clear yet, it is widely accepted that minor nanoscale fluctuations of chemical composition can trigger not just CMR but also other manifestations of strong electronic correlations such as orbital ordering or charge ordering [24]. In this scenario, STEM-EELS techniques have been extensively used to simultaneously study the structure, chemistry and electronic properties of perovskite oxides both in bulk and also in low dimensionality environments such as thin films, nanowires, nanostructures, etc [5,9,11,14,23,25–40]. In this section we will focus on two examples. First, atomic resolution mapping will be demonstrated in a multiferroic superstructure, composed of BiFeO3 (BFO)/La0.7Sr0.3MnO3 (LSMO) bilayers. We will show how both a qualitative measurement of elemental distribution and also chemical disorder can be studied at a glance. Then, we will address the quantification of atomic resolution EELS maps in a more simple bulk single crystal material, the double perovskite La2
2xSr1 þ 2xMn2O7. With the help of theoretical calculations, estimations of the local chemical composition with atomic resolution can be obtained. 2.1. Atomic resolution spectroscopic mapping in multiferroic oxide superlattices Doped manganites, such as LSMO, exhibit a wide range of interesting properties including ferromagnetism due to a strong interplay and competition between lattice, spin, and charge degrees of freedom [41–47], On the other hand, BFO is a single phase multiferroic material which displays magnetoelectric coupling between antiferromagnetic [48] and ferroelectric [49] order parameters up to temperatures hundreds of degrees above room temperature. When these materials are combined into a BFO/ LSMO heterostructure or superlattice, the interplay of these

Fig. 1. Atomic resolution HAADF image from a BFO/LSMO superstructure grown on a STO substrate (bottom). LSMO (BFO) layers are marked with blue (green) arrows, respectively. A green rectangle highlights the area where an EEL spectrum image was acquired. EELS maps for the different elements are shown on the right. From left to right, La M4,5 (green), Mn L2,3 (red), Fe L2,3 (blue) and Ti L2,3 (magenta) maps together with the overlay. Data acquired in an aberration corrected Nion UltraSTEM200 at Oak Ridge National Laboratory (ORNL), equipped with a cold field emission source and a fifth-order aberration corrector, operated at 200 kV. Adapted from reference [50] (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

phenomena can be tuned to produce a magnetoelectric multiferroic [50]. In particular, it has been shown that a state where an intimate coupling between the magnetization of LSMO with the uncompensated magnetization of BFO layers in a superlattice structure can be stabilized [50]. The size of this uncompensated magnetization suggests that when a very thin BFO film is sandwiched between LSMO layers, BFO can become ferromagnetic [50], but this behavior may be extremely sensitive to interface quality, sharpness and also to the presence of disorder. LSMO/BFO superlattices were deposited on a (001) SrTiO3 (STO) substrate by pulsed laser (KrF) deposition [50]. At a later stage, specimens for STEM observation were prepared by usual methods (just like most of the systems described in this chapter): mechanical polishing followed by ion milling to electron transparency. Fig. 1 shows a high angle annular dark field (HAADF) image, also known as a Z-contrast image, of a [(LSMO)6 u.c./(BFO)5 u.c.]  8 superlattice together with a series of atomic resolution EELS maps. A green rectangle marks the area where an EEL spectrum image was acquired. A number of chemical compositional maps related to different elements of interest were extracted from the La M4,5 (green), Mn L2,3 (red), Fe L2,3 (blue) and Ti L2,3 (magenta) absorption edges respectively. All of them exhibit atomic resolution contrast, and the interfaces can be clearly identified. An overlay is also shown for clarity, with the same color code, so the individual atomic columns for La, Fe, Mn and Ti can be visually identified. Interestingly, the BFO (top)/LSMO (bottom) interfaces seem atomically flat. However, the LSMO (top)/BFO (bottom) interfaces appear slightly disordered or intermixed, suggesting that BFO layer growth on LSMO takes place in a more ordered fashion than the opposite. Furthermore, some LSMO layers appear completely intermixed with Fe. This finding may be relevant when trying to explain the multiferroic properties of LSMO layers grown on top of BFO. As a matter of fact, finding some degree of chemical disorder as in this example raises a flag pointing towards the need for carrying out a more quantitative analysis of this kind of measurements. An example of this type of study is shown in the following section. 2.2. Quantitative approaches to local chemistry: analysis of EELS maps from bulk manganite crystals Well-characterized, single La2
2xSr1 þ 2xMn2O7 (LSMOx) crystals provide an ideal test system to measure and evaluate local

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composition via EELS imaging. Chemical doping in these double perovskites can be easily tuned by modifying x, which controls the ratio between La and Sr species. In this family of compounds La and Sr share the same atomic positions. Hence, controlled variations of x permit obtaining commensurate or incommensurate compositions. Atomic resolution STEM-EELS provides an outstanding tool to shed some light on the possibility of finding La/Sr chemical ordering at local length scales. In order to carry out this study different LSMOx compositions where chosen from each of the three regions within the phase diagram with different magnetic behaviors: x¼ 0.36, 0.50, and 0.56. For x¼ 0.36 (La1.28Sr1.72Mn2O7), the material exhibits ferromagnetic, metallic (FM) CMR behavior [45,46,51]. The second value, x¼ 0.50 (LaSr2Mn2O7), yields a composition within an A-type antiferromagnetic (AAFM) region, where charge ordering (CO) is found as the ground state [45]. Finally, the x ¼0.56 material (La0.88Sr2.12Mn2O7), lies in the high doping AAFM region, but no CO is reported. The single crystals were prepared for observation by crushing in methanol. Observations were carried out again in the ORNL Nion UltraSTEM200, equipped with a cold field emission electron source and a fifth-order aberration corrector, operated at 200 kV. STEM-EELS image simulations were performing using a Bloch wave method [52], with the ionization potentials calculated using Hartree-Fock ground states and Hartree-Slater continuum states [53]. High magnification HAADF images are shown in Fig. 2. From top to bottom, x ¼0.36, 0.50 and 0.56 compositions are displayed. Crystal quality is very high, with no major defects, such as secondary phase segregation, being observed. Since the LSMOx structure exhibits both rocksalt-like and also perovskite-like atomic positions, these have been labeled as R (red columns) and P (green), respectively, on the image in Fig. 2. Atomic resolution EELS maps corresponding to the Mn L2,3 (blue background rectangle), La M4,5 (green background rectangle) and Sr L2,3 (red background rectangle) edges for these samples are shown in the panels on the right side, along with an RGB overlay using the same color code. Principal component analysis (PCA) has been used to remove random noise [54]. While the Mn map exhibits an even contrast along the Mn atomic planes, both the La and Sr images exhibit noticeable fluctuations and uneven contrast when comparing P and R planes to each other, denoting a non-random distribution of La/Sr species in these positions. In fact, La intensities seem higher at the P planes, while Sr intensities appear higher on the R planes. Unfortunately, direct quantification of columnar compositions is by no means trivial, especially due to dechanneling of the electron probe, and sophisticated simulation procedures are required to accurately determine the degree of compositional ordering in such complex materials [55]. In order to quantify the degree of La/Sr chemical order, a full dynamical simulation of the EELS images must be performed. La and Sr fractional images can be simulated including different degrees of substitutional disorder into the P/R positions after producing a structural model sensitive to chemical disorder for the calculations. It is possible to define a disorder related parameter “α” as the actual occupancy of Sr atoms in the perovskite-like plane “P” (per unit cell). This way, the chemical formula for each compound with generic doping x can be rewritten in a fashion such that La/Sr occupations of both P and R planes can be distinguished while simultaneously taking account disorder: LaP1–α LaR2 P R (0.5
x þ 0.5α) SrαSr2(0.5 þ x
0.5α) Mn2O7. This way, for a composition of x¼ 0.50 the compound formula becomes LaP1–α LaRα SrPα SrR2–α Mn2O7. A value of α ¼0 would correspond to the 100% chemically ordered LaP SrR2 Mn2O7 structure, whereas α ¼2/3 would represent the randomly disordered LaP0.33LaR0.67SrP0.67SrR1.33Mn2O7. This way, for the x ¼0.36 (or the x ¼0.56) compound, with chemical formula

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Fig. 2. (Left) High angle annular dark field images for the x ¼ 0.36, 0.50, and 0.56 LSMOx samples, respectively from top to bottom, including a schematic of the crystal structure, with La/Sr columns in the P plane in green, La/Sr columns in the R plane in red and Mn columns depicted in blue. Green rectangles show the areas where electron energy-loss spectrum images were acquired. The colored panels on the right display atomic resolution EELS maps (after PCA denoising): from left to right, the Mn L2,3, La M4,5, and Sr L2,3 images (blue, green, and red boxes, respectively) and the corresponding RGB overlay (red ¼ Sr, green¼La, blue ¼Mn). Adapted from reference [55]. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) .

LaP1
αLaR0.28 þ αSrPαSrR1.72
αMn2O7 (LaP1
αLaRα
0.12SrPαSrR2.12
αMn2O7),

α ¼0 (0.12) represents 100% P site La- (R site Sr-) ordering while α ¼0.573 (0.707) will correspond to random disorder.

These formulas can be used as input in the theoretical model to simulate EELS images with different degrees of chemical disorder, as shown in Fig. 3 for the x ¼0.50 composition [55]. La and Sr images can be simulated and normalized in order to produce La or Sr fractional images, as shown in Fig. 3a and b. These can be forced to include different degrees of La/Sr chemical ordering by modifying the value of α, as shown in Fig. 3c for La fractional images in the x¼ 0.50 sample (Sr images display the inverse behavior). The higher the degree of order, the more intense La segregation into the P-like positions. On the contrary, La/Sr random disorder smears out the contrast up to the point of no clear differentiation between P and R atomic planes. The images normalized standard deviation (NSD) gives a good idea of the image contrast. From the inspection of the images, it is clear that higher degrees of La/Sr disorder give rise to lower contrast and, hence, lower values of the NSD. It is worth noting that specimen thickness will affect these quantifications so it must be taken into account [55,56]. By comparing the EELS image simulations and fractional intensities to the experimental ones, different values of the α parameter, and hence of chemical disorder, can be assigned to our LSMOx samples. Fig. 3d summarizes the α values obtained for the series of materials in Fig. 2 (black data points). These can be translated into an absolute percentage of ordering (red squares) assuming that 100% ordering corresponds to the case when α has the minimum

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Fig. 3. (a) For the x ¼0.50, fully ordered material the projected LSMO unit cell structure is shown, with the planes P and R labeled, together with simulated EELS images for La M4,5 and Sr L2,3 ionization edges. Also, the total image resulting from adding both La and Sr simulated maps is included. The specimen thickness used for these simulations was 300 Å. The c axis is marked with an arrow. (b) La (top) and Sr (bottom) fractional intensities, calculated from the simulated images in (a). The bottom panel shows the fractional intensities averaged over the width of the unit cell for both the La (green) and Sr (red). (c) Simulated fractional La M intensities as a function of α for the x ¼0.5, 300 Å thick sample. (d) Representation of the α value (black) and the corresponding degree of order (red), for the three compositions studied. Adapted from reference [55]. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

possible value for any given composition, while 0% ordering corresponds to the maximum possible value of α for each x (i.e., the La/Sr random alloy). In our case, we can conclude that samples x ¼0.36 and x ¼0.50 exhibit a non-negligible degree of chemical ordering (  35%). These findings are consistent with previous reports [45], which show that the underlying MnO framework seeks to maintain a relatively constant volume around the perovskite site. As the Sr content is increased the more Mn4 þ is added to the composition, therefore a surplus of Sr must be ‘pumped’ into this P site in order to maintain the volume. On the other hand, for the LSMO sample with x ¼0.56 we detect a significant degree of compositional ordering ( 50%), with an average composition of LaP0.59 LaR0.29 SrP0.41 SrR1.71 Mn2O7. In other words, type-P columns are occupied by 59% La and 41% Sr atoms on average, while type-R columns consist of 85% Sr and 15% La species [55]. Our findings suggest that the chemical background does not have a controlling role in the appearance of the CO phase in LSMOx with x ¼0.50. For higher dopings x (e.g., x¼ 0.56), a higher degree of chemical ordering develops, but no CO is present any more. These results rule out a simple chemical explanation for the extremely narrow stability field of the CO state near x ¼0.5. Other mechanisms will have to be invoked to understand this unique behavior in the bilayer manganite.

3. Column-dependent fine structure 3.1. Sensitivity of EELS to different coordination environments of iron in binary oxides Magnetoelectric multiferroics are a subject of interest due to their interesting and intriguing physics, as well as to the prospects of a novel generation of devices merging multiple functionalities. The realization of such applications demands materials with ample magnetization and electric polarization above room

temperature as well as strong coupling between the electric and magnetic orders. Interestingly, a simple binary oxide, the polar εFe2O3, meets these requirements [57]. ε-Fe2O3 is a robust roomtemperature insulating ferrimagnet with a Curie temperature near 500 K [58]. It exhibits typical ferroelectric switching with significant polarization (E 1 μC cm–2) and low switching voltages [57]. Although ε-Fe2O3 is an elusive metastable phase within the ample Fe-O phase diagram, it can be stabilized in the form of thin epitaxial films [59]. This fact, combined with the chemical simplicity of ε-Fe2O3 (it is also a single-valent oxide) represents a major advantage to overcome the challenges of stoichiometry and phase purity control that might be cumbersome in all other known room-temperature multiferroics, making of ε-Fe2O3 a good candidate for integration into future devices. ε-Fe2O3 is a metastable structural intermediate phase of maghemite (γ-Fe2O3) and hematite (α-Fe2O3) which presents a noncentrosymmetric structure (space group Pna21, a¼ 5.0885 Å , b ¼ 8.7802 Å , and c ¼9.4709 Å at 200 K). Fe occupies four distinct crystallographic sites, including one tetrahedral (Td:FeT) and three octahedral sites (Oh: one regular FeRO and two distorted FeDO1, FeDO2). Fig. 4a depicts the unit cell. The four Fe3 þ ions are antiferromagnetically coupled along the aaxis, resulting in a ferrimagnetic ordering [60]. Fig. 1b and c show both low and high magnification STEM Z-contrast images of an εFe2O3 film deposited on a (111) oriented SrTiO3 (STO) substrate. Fig. 4c demonstrates a sharp, coherent interface between the STO substrate and the ε-Fe2O3. Here, the ε-Fe2O3 is viewed down the [100] crystallographic direction, which exhibits those four different Fe crystallographic sites. As previously mentioned, one of the main advantages of STEM relies on the possibility of recording several signals simultaneously, such as the HAADF signal along with the in elastically scattered electrons to form EEL spectra. The energy lost by a fast electron resulting from interactions with the sample not only provides information about the chemistry of the material (as explained in the previous section) but also about the electronic

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Fig. 4. (a) ε-Fe2O3 unit cell. The tetrahedral (FeT) is represented in dark blue and three octahedral sites, one regular (FeRO), and two distorted (FeDO1) and (FeDO2) are represented in yellow, cyan and green, respectively. (b) Low magnification Z-contrast image of the ε-Fe2O3 film. (c) Atomic resolution Z-contrast STEM image of the ε-Fe2O3/ STO interface. The inset shows the ε-Fe2O3 structure viewed along the [100] crystallographic direction. Data acquired at 100 kV on the aberration-corrected Nion UltraSTEM. Specimen courtesy of M. Gich from Institute of Materials Science of Barcelona (ICMAB). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

properties and the unoccupied density of states. The onset and fine structure of the core-loss spectra (the overall shape) are highly dependent on the nearest neighbor environment in the solid and,

therefore, on the precise details of bonding, coordination and valence. In the particular case of ε-Fe2O3 the different metal-oxygen

Fig. 5. (a) EELS line-scan acquired along the direction marked with a yellow arrow in the Z-contrast image shown in panel (b). The inset represents the ε-Fe2O3 unit cell and shows the tetrahedral (FeT) and the three octahedral sites (FeRO, FeDO1, FeO2). (c) and (d) show the O K and the Fe L2,3 edges from the FeDO1 (cyan), the FeRO (yellow) and the FeT (blue) sites, respectively. The pre-peak intensities obtained from the octahedral iron (cyan and yellow) are smaller than that of the tetrahedral (dark blue), while the Fe L edges remain equal for all three. Data acquired at 100 kV with an acquisition time of 0.1 s per pixel in the aberration-corrected Nion UltraSTEM. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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atomic bonds result in electronic and physical properties that differ from ferrite counterparts; therefore a control of site occupancies is required for optimum response. Remarkably, this type of chemical bonding information can be obtained from combining atomic resolution STEM and EELS. Fig. 5 describes an example of this fact, displaying an EELS line scan (Fig. 5a) along the [001] εFe2O3 crystallographic direction, which is depicted in yellow in the Z-contrast image (Fig. 5b). The spectra energy range used allows for the simultaneous acquisition of both oxygen and iron edges. The O K edge stems from electron transitions between oxygen 1s core levels to unoccupied states in the 2p bands, and the intense narrow peaks of Fe L2,3 edge stem from iron 2p3/2 and 2p1/2 core levels to unoccupied states in the 3d bands, see Fig. 5c and d, respectively. The collected spectra from three different Fe sites reveal the variation of the O K edge fine structure, see Fig. 5c. The pre-peak in the very onset of the O K edge (∼ 525 eV) decreases in intensity when the beam is located on the distorted octahedral site (FeDO1), whereas the tetrahedral (FeT) and the octahedral (FeRO) sites show the same pre-peak intensity. However, large differences appear in the O K edge central peak (centered around 535 eV), which shows a much lower intensity when the beam is located on the tetrahedral site (dark blue line in Fig. 5c). On the contrary, no changes are observed in the corresponding Fe L2,3 edges. Since the intensity ratio of the Fe L3 and L2 white lines, known as L23 ratio, correlates with Fe valence [61], the even L23 ratio of the different Fe sites is an indication of single-valent iron, as expected for ε-Fe2O3. As a result, the variations observed in the O K edge can be assigned to the change in symmetry and Fe–O bonding lengths between different Fe species. In transition metal oxides, the O K-edge pre-peak accounts for the hybridization between the O 2p band and the transition metal 3d band [62,63]. Therefore, a different symmetry, translated in a different crystal field and Fe–O bonding lengths, may explain the difference in intensity of the O K edge pre-peak when compared with the central peak, as has been shown in a systematic study of several iron oxide phases carried on by Colliex et al. [61]. In the

particular case of ε-Fe2O3, the FeT presents a shorter O-Fe bonding length [60]. Besides, another factor that may explain the observed differences in the O K edge fine structure is the likely existence of a different spin state in the tetrahedral Fe site, as has been observed in other transition metal oxides in the presence of dissimilar symmetries [64]. Regarding the Fe L2,3 edge, it can also be used to test the quality of the ε-Fe2O3 films, as it can be compared with data obtained from highly crystalline ε-Fe2O3 nanoparticles synthesized by solgel methods [65]. Fig. 6a shows a Z-contrast image of such ε-Fe2O3 nanoparticles. The high resolution provided by the STEM-EELS technique may offer unique insights from single nanoparticles, as shown in the inset, which indicates the region from where a spectrum image was acquired. The characteristic L23 ratio values from a pure ε-Fe2O3 nanoparticle can be obtained as a reference. Maps of L23 ratio values from any single nanoparticle, shown in Fig. 6b and c can be produced using the so-called 2nd derivative method [66]. For this method, we first calculate the 2nd derivative of the raw spectra, and then use the signal at the maximum of the L3 and L2 peaks to obtain the L23 intensity ratio. In this case, both the film and the nanoparticles show similar values of the L23 ratio, around 6.3. This value can also be compared with those found in other ferrite phases, which all present different L23 ratios [61]. Salafranca et al. reported L23 ratios of 5 for magnetite (the Fe3O4 phase) nanoparticles [67], which contain two iron oxidation states, þ2 and þ3. This reference is particularly useful in order to distinguish if different iron oxide phases are present in a sample, as has been observed in ε-Fe2O3 films where two different phases may coexist at the interface. Fig. 7a exhibits a Z-contrast image of a region where different phases are present. Both are iron oxides. However, they exhibit a different contrast and also a different electronic structure, as can be deduced from the analysis of the Fe L and O K edge fine structures, see Fig. 7b and c. The ε-Fe2O3 phase presents a higher value of L23 ratio than the Fe3O4 phase, 6.3 vs. 5, and also a higher O K edge pre-peak intensity. As discussed above, the height of the O K edge pre-peak is related to the occupancy of the Fe 3d orbitals (and therefore the valence of Fe in the oxide).

Fig. 6. (a) Z-contrast image of ε-Fe2O3 nanoparticles. The inset shows the region where a spectrum image was acquired, along with a spectrum acquired during the scanning. (b) and (c) show the L23 ratio map (in false color) and the profiles along the direction of the yellow arrow in panel b, respectively. The averaged L23 value of the profile is 6.3, with a standard deviation of 0.3. Data acquired at 100 kV with an acquisition time of 0.1 s per pixel on the aberration-corrected Nion UltraSTEM. Specimen courtesy of M. Gich from Institute of Materials Science of Barcelona (ICMAB). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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The presence of Fe2 þ in the Fe3O4 phase reduces the hole population in the 3d band that hybridizes with the 2p state, which accounts for its lower pre-peak intensity. In summary, the

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methods described in this section can be utilized for further understanding of other oxide systems, allowing the local atomic and electronic structure changes to be unraveled.

Fig. 7. (a) Z-contrast image showing two different iron oxide phases, the ε-Fe2O3 and the Fe3O4. (b) and (c) show the Fe L2,3 and the O K edges of the two phases, respectively, the ε-Fe2O3 in black and the Fe3O4 in red. The Fe3O4 phase exhibits a smaller L23 ratio and a lower O K edge pre-peak intensity as well. Data acquired at 100 kV on the aberration-corrected Nion UltraSTEM. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 8. (a) High resolution Z-contrast STEM image of a Fe3O4 nanoparticle. The schematic represents the organic acid on the nanoparticle surface. (b) Color coded L2,3 ratio maps obtained from a Fe3O4 nanoparticle, acquired at two conjugate positions in the diffraction pattern (depicted as I þ and I
). (c) EEL spectra showing the Fe L2,3 edges from two conjugated spots (I þ in red and I− in black) in the nanodiffraction diagram, along with the dichroic signal (in blue), represented by the difference, which has been magnified by a factor of 5. The dichroic signal is five times bigger than the noise of the spectra. (d) L23 intensity ratio profiles along the nanoparticle, generated from the two L23 ratio maps acquired from the two symmetric positions in the diffraction pattern, and the resultant dichroic signal (in blue), represented by the difference. (e) Density of states (DOS) projected over the majority spin d orbitals in the octahedral iron site bonded to the organic acid. Adapted from reference [67]. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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3.2. Probing magnetism at the nanoscale So far we have only paid attention to the electronic properties of Fe oxides. However, EELS is also sensitive to other fundamental properties, such as magnetism. Iron oxides nucleate in a rich variety of phases exhibiting a wide range of magnetic behaviors. Of particular interest are magnetite Fe3O4 nanoparticles, which have received a great deal of attention due to their technological applications such as high-density magnetic recording media, sensors, catalysis and clinical uses [68]. Unfortunately, the magnetic properties of nanoparticles are commonly depressed by the presence of a magnetically inactive surface layer. However, magnetite nanoparticles capped with an organic acid exhibit the desired properties for the aforementioned applications: narrow size distribution in the proper range (1–50 nm), robust magnetization at room temperature, and super-paramagnetic behavior with little particle aggregation [69–71]. The nature of the capping in these particles is key to obtain bulk-like properties, pointing to a fundamental role of the bonding between the organic molecule and the surface. Hence, we carried out a real-space characterization at the sub-nanometer scale of magnetic and electronic properties, via aberration corrected STEM and EELS, which was used to probe the local magnetization of a single nanoparticle at room temperature [67]. Just like macroscopically averaged x-ray magnetic circular dichroism (XMCD), electron magnetic circular dichroism (EMCD) can be measured in transition metal oxides by studying the L2,3 edges of transition metals while illuminating nanometer-sized specimen areas [72–75]. As an example, Fig. 8a displays a high resolution Z-contrast STEM image of a Fe3O4 nanoparticle, showing high crystal quality. In this sample, EMCD was used to map the magnetization of single nanoparticles in real space with sub-nanometer spatial resolution. Following the procedures described by Schattschneider et al. [72], the Fe-L2,3 edges from two conjugated spots in the nanodiffraction diagram were obtained, which are equivalent to the two beam polarizations used in XMCD measurements (Fig. 8b). The dichroic signal is then given by the difference between these two spectra, see Fig. 8c, and it is proportional to the magnetization. Thus, EEL spectrum images allow probing the local magnetization of a nanoparticle. Indeed, the difference in L23 intensity ratio profiles in Fig. 8d show that the magnetization density within 1 nm of the particle surface is at most 30% lower than the magnetization of the core, but still the surface is magnetic. This behavior can be explained combining the results with density-functional theory calculations (Fig. 8e). These show that the resulting bond between the organic acid and the nanoparticles not only prevents further oxidation to Fe2O3, which could be detrimental for magnetization, but also results in O-Fe atomic configuration and distances close to the bulk values. This bulk-like surface structure results in magnetization being restored in the surface layer, which has a strong effect on the magnetic state of the nanoparticles.

4. Unusual effects of epitaxial strain in oxide thin films: oxygen vacancy ordering and spin state superlattices in cobaltite films Oxygen vacancies affect thin oxide film properties: they can control the structure and electronic properties. Furthermore, vacancy ordering can give rise to novel behaviors not present in bulk and, hence, oxygen vacancy ordering is a major controllable degree of freedom that can be used to engineer novel behavior in complex-oxide films. Here we will review examples where atomicallyresolved Z-contrast imaging is combined with EELS to demonstrate that oxygen vacancies combined with epitaxial strain in epitaxial cobaltite films may promote unexpected magnetic

behaviors. An example can be found in the long-range magnetism measured in non-magnetic LaCoO3 or the stabilization of spin state superlattices in Sr doped La0.5Sr0.5CoO3
x. We will show how epitaxial strain is relaxed through periodic or quasiperiodic local lattice expansion at oxygen-deficient atomic planes, while Co 3d electrons give rise to those unusual magnetic properties. 4.1. O vacancy ordering and Brownmillerite-like structures in doped cobaltite films Cobalt oxides are relevant for a vast array of materials applications ranging from batteries [76] to catalysts [77,78], thermoelectrics [79], electronics [80], spintronics [81], etc. In particular, Sr doped cobaltites, such as La1
xSrxCoO3 (LSCO) are ionic conductors and also exhibit bulk phase diagrams very similar to those of CMR manganites [24], in spite of the possibly different microscopic mechanism giving rise to magnetism. At low temperatures, ferromagnetism is found for doping levels of x Z0.18, and the highest Curie temperature value of TC ¼240 K is reached for the x¼ 0.5 compound [82]. In bulk LSCO it is well known that as divalent Sr þ 2 cations are inserted into the La sublattice, oxygen vacancies are introduced gradually as well, in such a fashion that the x ¼0.5 compound crystallizes into a Brownmillerite-like structure close to La0.5Sr0.5CoO2.5 [29,83–85]. It has been found that when LSCO is grown in the form of thin films a certain degree of O vacancy ordering is present as well, albeit a nano-domain phase related to the relaxation of epitaxial strain [86–89]. Depending on the degree and type of lattice mismatch between film and substrate, domains with different orientations of the ordering modulation vector can be observed. As an example, Fig. 9 shows the nature of oxygen vacancy ordering in LSCO (x ¼ 0.5) films grown on different single crystal substrates. Every other CoO2 atomic plane exhibits a darker contrast due to the presence of O vacancies [64]. All films are epitaxial and interfaces are coherent, but both the morphology and orientation of the O vacancy superstructures are determined by epitaxial mismatch. When LSCO is deposited on a tensile substrate such as SrTiO3 (STO) (100) the oxygen vacancy layers lie perpendicular to the substrate interface. However, they are found to rest parallel to the interface when grown under the compressive strain of LaAlO3 (LAO) (100) [89]. In the mixed (reduced) strain state derived from growth on the STO (110) plane, the vacancy superstructure is accommodated at domains that lie at 45° from the interface strain. No matter what the mismatch with the substrate is, superstructures will arrange themselves in a fashion that helps minimize lattice strain. Atomic resolution EELS gives proof that the dark stripes observed in the HAADF images of Fig. 9 are caused by the lack of O, i.e. the dark planes are indeed Co2
δ planes [64]. Fig. 10a exhibits a magnified atomic resolution HAADF image of a LSCO x ¼0.5 thin film where the vacancy rich planes and stoichiometric planes are marked with blue and red arrows respectively, with the different atomic columns marked on the sketch. The inset displays an atomic resolution O K-edge map measured from a region containing both a dark stripe and a regular CoO2 plane, for comparison. While the latter exhibits bright spots corresponding to the positions of O columns, the dark CoO2
δ stripe shows a clearly depressed O K signal. Simulations of the O K images in Fig. 10b were carried out for fully oxygenated LSCO structure (top), a further deoxygenated structure La0.5Sr0.5CoO2.25 (middle) as reported by Wang et al. [90], and a structure (bottom) which has the same stoichiometry than the previous but different location of oxygen vacancies. This tetragonal structure, shown on the right end of Figure 10b, was implicated by the match between the experimental data and density-functional theory (DFT) calculations. From these simulations it is obvious that the reduced contrast measured on the dark stripe atomic plane within the O K image

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Fig. 9. High resolution Z-contrast STEM images of the interface regions of La0.5Sr0.5CoO3
δ films grown on STO(001), STO(110), and LAO(001), respectively from left to right. Yellow lines mark the O deficient CoO2
δ planes. The scale bars represent 5 nm. Adapted from reference [89]. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 10. (a) High resolution HAADF image of a region within the LSCO film. Inset: area used for spectrum imaging of the O K edge (false color). (b) O K edge simulated images down the [010] zone axis. The right panel displays a sketch of the La0.5Sr0.5CoO2.25 structure used for the simulation on the bottom. Blue (red) arrows point to the dark (bright) stripes. (c). Averaged O K (top) and Co L2,3 (bottom) spectra from the bright stripe (red) and dark stripe (blue), scaled for presentation purposes. Data from an aberration corrected VG Microscopes HB501UX operated at 100 kV. Adapted from reference [64]. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

results directly from a lower local O content. Therefore, the bright/ dark contrast observed in alternating Co–O planes in the HAADF images denotes full/incomplete oxygenation, and EELS imaging confirms that the dark stripes are indeed CoO2
δ atomic planes. However, EELS is not only useful to study the local chemical composition. As already discussed, the fine structure correlates directly with electronic properties. In transition metal perovskite oxides, both the O K and the transition metal L2,3 fine structures correlates with the metal oxidation state, and cobaltites are not an exception [34,36,91]. Fig. 10c displays both the O K and the Co L2,3 edges averaged along the dark (blue), deoxygenated and bright (red), fully oxygenated Co–O atomic planes. The fact that the Co L2,3 edge fine structure does not change in a noticeable way when moving from bright to dark stripes denotes that the Co atoms in both types of planes exhibit similar valence states despite the O vacancy ordering (i.e., no modulation in Co oxidation state or charge ordering is detected). This result is nevertheless consistent with the fact that LSCO films are metallic [87]. However, important changes are detected in the fine structure of the O K edge, especially the pre-peak at the edge onset, pointing to some electronic ordering phenomenon of a different sort. Interestingly, previous studies in undoped LaCoO3 cobaltite (LCO) have found a similar behavior when the system undergoes a spin state transition [92]. Since in LCO the crystal field and Hund exchange energy scales are

comparable, electronic rearrangements within the d states (e.g. driven by temperature changes) may result in modifications of the overall Co spin state without changes in the metal oxidation state (more on this later). Remarkably, DFT calculations capable of examining the Co projected densities of states in our epitaxially strained LSCO films show a high spin state for our Co atoms in deoxygenated, O vacancy rich Co–O planes. Meanwhile, Co atoms in the fully oxygenated perovskite sites remain in a low spin state. This behavior gives rise to a spin state superstructure which is detected by atomic resolution EELS, since simulations confirm as well that the O K edge pre-peak must decrease when the Co spin state increases [64]. It is worth noting that this spin state superstructure is only stable under tensile epitaxial strain (i.e., when LSCO is clamped to a STO substrate), but cannot be found when the system is allowed to relax converging to a more bulk-like behavior [64]. In summary, for this system STEM/EELS combined with theory gives proof that the combination of O vacancy ordering with changes due to mismatch strain stabilize a novel magnetic state associated with a spin state superlattice which is not present in bulk. 4.2. Epitaxially strained LaCoO3 thin films So far we have discussed the example of Sr doped cobaltites, but the LaCoO3 (LCO) undoped parent compound is interesting on

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its own. LCO has been studied intensively over the last 60 years due to its unique magnetic behavior and its related nonmetalmetal transitions [93,94]. LCO in bulk is non-magnetic, with a magnetic susceptibility going to zero at low temperatures (T o100 K) [94]. Since no magnetic order is found in LCO [95], the magnetic transition at TC ¼85 K has been widely interpreted as the aforementioned high (or intermediate) spin state to low-spin, diamagnetic state transition [96]. Surprisingly, a clear ferromagnetic (FM) fingerprint has been reported at low temperatures in ultrathin films of LaCoO3 [97], suggesting that epitaxial strain may promote this unexpected behavior. One factor that strongly influences the physics of these systems is the stoichiometry of the thin films, especially since complex oxides are extremely sensitive to minor changes in doping. However, the actual film composition is often difficult to establish (particularly so when it comes to determining minor changes in O content). Atomic resolution STEM-EELS constitutes an ideal tool to probe any changes in the structure, electronic properties or chemical composition that may give rise to the unexpected behavior. Fig. 11a exhibits a high resolution HAADF image of a 15 nm thick LCO film, grown on a (001) oriented SrTiO3 (STO) substrate [98]. The film is epitaxial and the interface is coherent, but clear vertical dark stripes – running perpendicular to the interface – are observed. Such dark stripes, reminiscent of the LSCO example, correspond to CoO2
δ atomic planes (see the inset with the crystal structure). Actually, and just like LSCO, the darker contrast is due to an enlarged distance between some neighboring La atoms along the in-plane direction. In the LSCO case these dark stripes were observed every other Co-O plane, while they are detected every other third perovskite block in LCO. This effect can be observed in Fig. 11b, where the La-La in-plane distances are mapped (Δx) along the interface plane. Here it is clear that the dark stripes correspond to significantly dilated La-La distances (∼4.5 Å versus ∼3.6 Å for regular LCO blocks). The modulation vector of the superlattice lies in the plane of the interface, suggesting again a stabilization mechanism related to epitaxial strain. Indeed, if we take into account that one third of the in-plane blocks correspond to darker stripes, the film has an average in-plane lattice constant of 3.92 Å, which is a better match to STO (3.905 Å) than to LCO bulk (∼3.83 Å). The fact that for LCO the density of O deficient planes is lower than in LSCO suggests that the overall amount of O vacancies introduced during growth in this system is not as high [99]. It is worth noting that observations of such superstructures in epitaxial LCO were initially interpreted as an unconventional strain relaxation behavior in a chemically homogeneous material [100]. However, the atomic resolution EELS images again show that these dark stripes are related to a local deficiency of O [98]. Fig. 12a displays atomic resolution EELS maps of the LCO thin film corresponding to the O K and La M edges (red and green bottom panels, respectively), along with their averaged intensities. A quantification of the L23 intensity ratio is also displayed in the top inset. The oxygen signal decreases on the dark stripes, confirming the presence of O vacancies on these planes. Interestingly, in this case the Co L23 intensity ratio increases on these deoxygenated O planes, pointing to a modulation of the Co oxidation state. This behavior is opposite to the previously discussed example of LSCO, but it must be noticed that (unlike LSCO) LCO films are highly insulating. As already discussed, the L23 ratio in transition metals is well known to depend on the number of occupied d-orbitals [101,102], so the measured increment of the Co L23 ratio on the dark stripes is a direct fingerprint of a lower Co valence (Co þ 3Co þ 2) [103], possibly associated with the local accumulation of O vacancies in this insulating material. This finding points to the fact that charge ordering can be stabilized by self-organization of cobalt ions into oxygen deficient columns in epitaxially strained thin films of LCO.

Fig. 11. (a) High resolution, high angle annular dark field image of a LCO thin film 15 nm thick, grown on a (001) oriented STO substrate, showing the contrast resulting from O-vacancy ordering. The direction of the modulation vector, q, is marked with an arrow. The inset shows a 2D projection of the structure along the [011] direction ([100] in the pseudocubic setting), marking oxygen deficient (shaded blue) and stoichiometric (red) planes. Blue, red and green spheres are Co, O, and La atoms, respectively. (b) Map of the in-plane distance between first La neighbors (Δx) in (a), along the direction parallel to q. O-deficient planes are characterized by enlarged La-La distances. Adapted from reference [98]. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Again, in this case DFT resolves the puzzle of explaining the measured ferromagnetism in epitaxial thin films of LCO [98]. The structure model associated with minimum energy is shown in Fig. 12b. Calculations confirm that charge ordering takes place, indeed. Reduced cobalt ions (Co þ 2 ) sit in oxygen vacancy layers (blue – tetrahedral coordination), while Co atoms in stoichiometric blocks (red – octahedral coordination) are consistent both with the nominal Co þ 3 oxidation state and with reduced Co þ 2. Interestingly, Co þ 2 atoms are found to exhibit a high spin state (S¼2). Meanwhile, the octahedral Co þ 3 ions exhibit a low spin state (S¼0) and are ordered in a zig-zag matrix. High spin Co þ 2 atoms prefer to order antiferromagnetically with each other. Since some degree of blocking is unavoidable, a net ferromagnetic moment arises in the supercell of this overall ferrimagnetic structure. The calculations predict an average value of 1 μB/Co, which is in a good agreement with experimentally obtained values [104]. It is also worth noting that, although O vacancies typically dope a material n-type, our ordered vacancies induce Peierls-like minigaps which, combined with strain relaxation, trigger a nonlinear rupture of the energy bands, resulting in the measured insulating behavior. In conclusion, we have shown that LCO films under tensile strain relax by generating oxygen-vacancy superstructures that control the structural, electronic, and magnetic properties. These phenomena may occur in other materials providing a new, important degree of freedom to custom design thin-film properties.

5. Applications to the study of crystalline defects: origin of ionic conductivity barriers at Y2O3 stabilized ZrO2 grain boundaries As we have already seen, the high spatial resolution of aberration corrected STEM in combination with the analytical

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Fig. 12. (a) The top panel displays a high resolution Z-contrast image of the LCO film showing an average modulation length of three perovskite blocks. The inset shows the Co L23 intensity ratio map for the area. A schematic shows the pseudocubic unit cell (blue ¼ Co; green¼ La; red¼O). The bottom panels exhibit elemental chemical maps constructed by integrating the corresponding EEL spectra: O K (red) and La M5 (green) edges. Normalized intensity traces across the O K and La M5 images are also shown. Red and blue arrows point to the positions of fully oxygenated and O vacancy rich Co–O planes, respectively. The O intensity decreases on the latter planes as a result of the lower O content, which makes the La atoms move further apart from each other. (b) A 3D model of the structure found by DFT is shown here, including oxidation and spin states inferred from theoretical calculations. Oxygen ions (red spheres) form distorted tetrahedra (blue) around Co ions (dark blue spheres) in vacancy-rich planes, while bulk-like octahedra (red) can be observed around Co atoms in fully oxygenated planes. Large green arrows indicate a high spin state along with its relative direction (up or down). Adapted from reference [98]. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

capabilities of EELS allows the analysis of variations in the stoichiometry of a material at the atomic scale. This possibility is of great use to study systems where localized fluctuations in the composition may alter their physical properties, such as grain boundaries. It is well known that the structural and chemical changes present within the dislocation cores at grain boundaries strongly influence the properties of fuel cells based on polycrystalline solid oxide electrolytes [105,106] and nanoionics devices [107,108]. In the past years, there has been a growing interest in ionic conducting materials, principally motivated by their wide range of applications in solid-state electrochemical devices such as solid oxide fuel cells which are devices capable of converting chemical energy in electrical energy with a high efficiency and without the generation of any polluting emission [109]. The performance of these devices is largely determined by the presence of grain boundaries, the resistivity at grain boundaries being at least one order of magnitude higher than in the bulk [110–112]. The origin for the blocking of the ionic conductivity is therefore of a major importance for optimizing the physical properties of these materials, although the explanation of this effect is, surprisingly, still a subject of controversy [113–116]. A new theory [117] has been recently proposed based on the combinative analysis of experimental measurements and theoretical calculations of a single grain boundary of yttria stabilized zirconia, YSZ [x Y2O3: (1
x) ZrO2], one of the most extensively used materials for solid oxide electrolytes [109]. Contrary to previous reports, no positive charge accumulation at the YSZ grain boundary screened by a several nanometers thick oxygen vacancy depletion layer was found. Instead, atomic-scale STEM-EELS measurements along with ion transport measurements by nanoscale electrochemical strain microscopy (ESM), broadband dielectric spectroscopy measurements and density functional

calculations (DFT) show that the barrier for ionic transport arises from negatively charged acceptor electronic states screening the presence of structural oxygen vacancies within 1 nm of the grain boundary. The changes in stoichiometry in 9% mol yttria YSZ bi-crystals with a symmetrical 33° [001] tilt grain boundaries made by means of solid phase intergrowth were observed by aberration corrected STEM-EELS. For a more thorough study, both the low energy Y M4,5 and Zr M4,5 edges and the higher energy Y L2,3 and Zr L2,3 were used for quantification. The analysis of the M4,5 edges is shown in Fig. 13a. The HAADF image shows the region where the spectrum image was acquired. It is possible to observe the array of dislocation cores along the grain boundary, where neither disordered nor amorphous structures are present, indicating that the boundary is successfully joined at the atomic level. The spectrum image was acquired using a Nion UltraSTEM 100 operated at 100 kV and equipped with a Gatan Enfina spectrometer. Random noise was reduced using principal component analysis [54]. The resulting normalized integrated signal maps corresponding to the Y M4,5, Zr M4,5 and O K edges show large compositional changes with the periodicity of the grain boundary dislocation cores, as previously reported for grain boundaries [118–122]. There is a depletion of the oxygen content in the vicinity of the dislocation cores, accompanied by a reduction of Zr content and a strong increase of the Y signal, which could be explained by a segregation of Y cations into the dislocation cores, as reported previously for such grain boundaries in YSZ [123–126]. The same specimen was analyzed in a Nion UltraSTEM 200, operated at 200 kV and equipped with a Gatan Enfinium spectrometer and the resultant normalized chemical composition maps for Y L2,3, Zr L2,3, and O K edges are shown in Fig. 13b. It is worth noting that although the M4,5 edges occur at lower energy-losses and are less localized than the L2,3

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Fig. 13. Chemical quantification maps of a YSZ grain boundary. (a) Spectrum image of the grain boundary region obtained in a Nion UltraSTEM100 operated at 100 kV. From left to right: Z-contrast image of the grain boundary region where the EEL spectrum image was acquired; atomic resolution, normalized integrated signal maps of the Y M4,5 (red), Zr M4,5 (blue) and OK (green) edges, respectively. (b) Spectrum image of the grain boundary region obtained in a Nion UltraSTEM 200 operated at 200 kV. From left to right: Z-contrast image of the grain boundary region where the EEL spectrum image was acquired; atomic resolution, normalized integrated signal maps of Y L2,3 (red), Zr L2,3 (blue) and O K (green) edges, respectively. Scale bars represent 2 nm. Some spatial drift is observed in both spectrum images. Adapted from reference [117]. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

100 O K Edge

Normalized Integrated Signal

edges, their analysis yields similar trends regarding the elemental distribution within the dislocation cores. The profiles in Fig. 14 show the concentration changes of each atomic species near the grain boundary, obtained by averaging the intensity normalized maps in Fig. 13a and b. The full symbol profiles correspond to the quantification obtained from the analysis of the low-loss M4,5 edges, while the open symbols correspond to the high-loss L2,3 edges maps. The quantification results demonstrate a non-stoichiometric composition around the grain boundary dislocation cores. More specifically, there is an intense Y segregation to the dislocation cores, nearly doubling in relative concentration compared to the bulk region. A strong reduction in the oxygen concentration is also measured close to the grain boundary, even more than expected from the stoichiometric value calculated from the changes in the cation concentrations (black line in Fig. 14). These variations are more localized in the profiles obtained from the quantification of the higher energy-loss L2,3 edges. Furthermore, the length of these variations, especially in the case of the high-loss quantification, are in the range of one unit cell (5 Å), as obtained from the FWHM of the EELS compositional profiles. Interestingly, there is no evidence of a depletion of oxygen vacancies either side of the grain boundary, contrary to previous models for ionic transport through grain boundaries in ionic conducting materials [127–130]. It is well established that at lower resolutions, off-axis conditions are usually preferable for EELS quantification, but degrade the spatial resolution. In order to visualize the chemical variations found with atomic resolution, it is important to realize the chemical quantification in a zone-axis condition. In these “channeling” conditions, the relation between the intensity of the EELS signal and the composition is non-linear due to the multiple scattering of the beam along aligned atomic columns [131]. For thin specimens, the crystalline lattice produces a preferential focus on columns composed of heavier species and hence, the signal will be enhanced or reduced with respect to columns composed of lighter elements (depending on the thickness). On the other hand, in thick samples the beam may be scattered away from heavier columns, reducing their relative signal. However, several specimen thicknesses and orientations were

O K Edge Stochiometric O Content

80

60 Zr/(Zr+Y) L Edge

40

Zr / (Zr+Y) M Edge

20

Y/(Zr+Y) L Edge Y/(Zr+Y) M Edge

0

-3

-2

-1

0

1

2

3

d (nm) Fig. 14. Chemical quantification profiles of a YSZ grain boundary. Normalized integrated signal profiles averaged across the chemical maps in Fig. 13. Open symbols correspond to the results obtained using the Y and Zr L2,3 edges and solid symbols to the results obtained using the Y and Zr M4,5 edges. Zr and Y profiles have been normalized to the total cation concentration. The black line is the stoichiometric O content expected from Y L2,3 and Zr L2,3 edges signals. Adapted from reference [117].

analyzed and it was demonstrated that any difference in the quantification results between the “on-axis” and “off-axis” conditions lay within the experimental error, not affecting the final conclusions. Further experimental characterization presented by M.A. Frechero et al. [117] shows how the ionic conductivity is indeed depressed across the grain boundary, as depicted by dielectric spectroscopy measurements. Furthermore, the thickness for the ionic barrier was estimated to be of the order of 4 71 Å, in agreement with the EELS compositional variation ranges, and again, much smaller than previous estimates [127]. Moreover, ESM measurements allowed obtaining for the first time, direct images of ionic blocking at grain boundaries. To further understand the origin of the barrier for ionic conductivity, these experimental results served as a base for the realization of theoretical

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calculations by means of DFT. It was found that charge neutrality is achieved due to the presence of empty electronic states created by electronic reconstruction at the grain boundary, which capture the electrons donated by the structural oxygen vacancies. This reconstruction gives rise to an electrostatic potential dip that the mobile vacancies have to surpass while travelling across the boundary, resulting in a reduction of the ionic conductivity. These findings represent a further step in the understanding of ionic conductivity at grain boundaries, which will help optimizing the properties of solid-state electrochemical devices.

6. Concluding remarks Complex oxides constitute a hot field of materials physics, and they poise a most promising opportunity towards applications such as data storage, sensors, biomedical applications or spintronic devices. However, future technological developments will come hand-in-hand with new oxide materials or heterostructures including novel atomic arrangements or defect engineering at the atomic scale. In order to harness these systems, we need tools that can probe nature with atomic resolution, in real space. Electron microscopy combined with spectroscopy is an outstanding technique to analyze materials in an atom-by-atom fashion, especially after recent improvements in microscope performance ensuing from the correction of optical aberrations. Through the pages of this chapter we have reviewed a few examples of problems that can only be fully addressed using tools such as atomic resolution STEM-EELS combined with theoretical calculations and simulations. We have discussed how atomic resolution spectroscopic imaging is possible at a quantitative level, to the point that we can analyze chemical ordering down to a few percent units in complex crystal structures such as layered LSMOx manganites. Minor changes in atomic bonding and coordination can be detected not just from the analysis of images, but also from the near edge fine structure as we have shown in Fe-O binary oxides, where multiphase mapping at the nanoscale becomes feasible. We have also reviewed how new imaging modes sensitive to magnetic quantities are now a reality through the use of EMCD. In magnetite nanoparticles we not only find that the surface of the nanoparticles is ferromagnetic but it is possible to establish how magnetization is restored thanks to density-functional calculations. The sensitivity to STEM-EELS to point defects such as O vacancies has also been discussed and we have shown how in thin cobaltite films O vacancies combined with epitaxial strain can give rise to superstructures of ordered oxygen-deficient atomic planes. Such superstructures result in spin state superlattices stabilized in ferromagnetic LSCO thin films, which are not present in bulk. Also, ferromagnetism can arise in non-magnetic LCO films thanks to the fact that excess electrons result in ferromagnetic ordering. These examples show that oxygen vacancies complement strain as a major controllable degree of freedom that can be used to engineer novel behavior in complex-oxide films. Finally, we have also addressed the analysis of extended defects such as dislocation cores in ionic conductor YSZ grain boundaries. STEM-EELS analysis gives proof of depletion of oxygen and Y enrichment within a region of nanometric dimensions around the dislocation cores, which eventually gives rise to an electrostatic dip that determines ionic transport through interfaces. These are just a few examples of oxide materials problems where the combination of STEM and EELS with sub-Ångström resolution provides a unique approach to understanding microscopic mechanisms. Be it the analysis of minor chemical fluctuations, single dopants, point or extended defects, STEM-EELS plays (and will continue to do so) a pivotal role complementary to macroscopically averaged measurements when exploring the new properties of the oxide materials of the future.

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Acknowledgements The authors are deeply grateful to all our collaborators who have made this work possible, even if here we can only name a few of them: A.R. Lupini, M.F. Chisholm, W.H. Sides, M. Oxley, W. Luo, S.T. Pantelides, M. Watanabe, J. Santamaria, C. Leon, Z. Sefrioui, A. Rivera-Calzada, J. Garcia-Barriocanal, M. Fitzsimmons, J. Mitchell, C. Leighton, M. Torija, M. Sharma, S. Bose, Y. Suzuki, V. Mehta, M. Gich and many others. Research at Oak Ridge National Laboratory was sponsored by the Office of Basic Energy Sciences, Division of Materials Sciences and Engineering, U.S. Department of Energy. MR, NB and GSS were supported by the European Research Council Starting Investigator Award STEMOX # 239739. Research at Universidad Complutense sponsored by Fundación BBVA IN[15]_CBB_FIS_2805 and Spanish MINECO MAT2015-66888-C3-3-R. JG also acknowledges the Ramon Y Cajal Program (RYC-2012-11709).

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Please cite this article as: J. Gázquez, et al., Materials Science in Semiconductor Processing (2016), http://dx.doi.org/10.1016/j. mssp.2016.06.005i