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Abstract
Auger electron spectroscopy (AES) as a method to characterize the ferroelectric polarization domains in magnesium-doped lithium niobate crystals is demonstrated. Preliminary measurements on a test sample show a clearly identifiable relative shift in the energy of the Auger oxygen KLL transition peak between poled (inverted) and un-poled domains. Auger electrons detected from the negative polarization domains (-Z) have a higher energy than those from the positive domains indicating a lower ionization energy at the -Z domain surface. The degree of electron energy separation between the −Z and +Z domains was found to be dependent on proximity to the domain boundary and was potentially diminished by the accumulated charge under the incident primary beam. Polarization domain resolution is demonstrated on both the micron and millimeter scale, suggesting potential applicability of this technique to surface investigation and domain structure characterization of nonlinear optical devices such as periodically poled lithium niobate.
© 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
1. Introduction
Ferroelectricity is a unique material property of a built-in electric polarization field that is maintained in the absence of an external field. The orientation of this spontaneous polarization can be switched by the application of a sufficiently strong external electric field that overcomes the material’s coercive field [1]. Lithium niobate (LN) is one such ferroelectric crystal of interest due to its nonlinear optical properties and uniaxial ferroelectricity [2]. Ferroelectric crystals have found numerous applications in nonlinear optics [2–7]. Periodically poled lithium niobate is especially noteworthy for its ability to maintain quasi-phase matching and therefore high nonlinear conversion efficiency [8–17]. Furthermore, by adding magnesium doping to lithium niobate (MgLN), the coercive field can be substantially lowered to facilitate polarization switching [18,19], and the threshold for optical damage due to the photo-refractive effect substantially increased [20], thus making magnesium-doped lithium niobate crystals of particular interest for nonlinear optics applications. However, the periodic poling process requires precise manipulation of the crystal’s polarization orientation.
In order to form a stable state, a depolarization field is present on LN’s ferroelectric surface [8,21,22]. The depolarization field is polarization dependent and is accomplished by spontaneous atomic desorption, adsorption of environmental contaminants, different surface terminations, or other processes, which are not completely understood [21,23,24]. These complex surface interactions require further investigation in order to enable the growing number of novel applications of LN. Developing new techniques for studying the crystal’s surface properties and characterizing the polarization and crystal domains of LN and MgLN will also help to better understand and mitigate the challenges of poling [25]. In the present work a new characterization method is developed using Auger electron spectroscopy (AES). Polarization domains in MgLN crystals are differentiated by a relative shift in the energy of Auger spectral peaks. While AES has been used to depth profile ion-exchanged waveguides in LN and LiTaO$_3$ [26], AES has not been used to study the surface potential or characterize polarization domains. This novel technique is non-destructive and offers unique insight into the crystal surface when compared with other methods of characterization.
Currently, polarization selective domain etching in hydrofluoric acid (HF) is the most dependable method for ferroelectric domain characterization in MgLN. HF selectively etches -Z domains of lithium niobate crystal species and leaves the +Z face essentially unaffected [27–33], so that after a sufficiently long immersion in HF, the domain pattern is topographically etched into the crystal’s surface. The domain pattern can then be characterized as a relief image with scanning electron microscopy (SEM), scanning probe microscopy (SPM), or optically. While selective etching in HF is a common method [34,35] and is useful for characterizing large areas of poled materials, it has the disadvantage of being destructive to LN and MgLN surface applications.
Other methods of characterizing MgLN ferroelectric domains include piezo-response force microscopy (PFM), SEM imaging of secondary electrons (SE), and Raman spectroscopy (RS) [21,36]. PFM is a novel SPM technique where a conducting probe is brought into contact with a ferroelectric surface and an AC voltage applied to the tip. The sample’s oscillating response from the converse piezoelectric effect will either be in phase or out of phase with the applied voltage and, because there is a linear relationship between piezoelectricity and ferroelectricity, the direction of the ferroelectric domains can be determined [37,38]. It has been noted that the domain contrast mechanism with PFM is not well understood due to the complexity of the tip-surface interaction [39,40].
SEM imaging is a useful method of characterization that allows for imaging large areas. SEM images detect the contrast in secondary electron yield between MgLN domains of opposite polarization with certain primary beam parameters [41–43]. Focusing on detection of secondary electrons through the use of an in-lens detector also gives information about the material’s work function, although the information about the work function and image contrast can be complicated by “beam parameters, beam-induced contamination, specimen electric potential, SE collection efficiency, etc.” [44]. Similar to PFM, the contrast mechanism from SEM is not well understood and there are different theories on whether the domain contrast originates primarily from beam-induced pyroelectric effects [45] or differential charging when the SEM is operated in the regime where primary beam current and surface emitted current are roughly equal [41] or create a positive surface [42].
Raman spectroscopy has proven to be a useful technique for probing lithium niobate domain walls, internal fields, and defect structures. By exciting atomic vibrational modes with an incident laser, the inelastically scattered laser photons are shifted up or down in energy, which can then be detected by a spectrometer to probe material properties. Domain walls in lithium niobate can be detected by a modulation in the intensity of the A$_1$(LO4) phonon mode [46,47], or a shift in frequency of the E(TO8) phonon mode [48–50]. Similarly, opposite domains can be detected relative to each other by a modulation in the E(TO1) intensity, or a shift in the frequency of the A$_1$(LO4) phonon mode [47–49,51]. RS also has the especially useful ability to non-destructively probe dopant distribution and the ion-implanted waveguide structure in the bulk of nonlinear optical materials [48,52]. As an optical technique, spatial resolution of RS is set by the diffraction limit of the laser and generally on the order of 0.3 $\mathrm{\mu}$m, a relatively small value but large when compared with the size of domain walls, that are only a few lattice constants wide in LN [53]. In non-stoichiometric MgLN or LN samples, a single phonon mode’s detected shift in intensity, frequency, or width may be affected by a combination of factors such as impurities, lattice inhomogeneity, strain, point defects, and internal fields [21,48,54,55], though it has been demonstrated that domain walls can be studied independent of these factors in annealed, defect free, stoichiometric LiTaO$_3$ and near-stoichiometric LiNbO$_3$ [53].
Cherenkov second harmonic generation (CSHG) microscopy is another demonstrated technique for imaging domain walls in ferroelectric crystals, including LN [56–58]. It has been demonstrated that a laser focused on a ferroelectric domain wall generates a CSHG signal that is absent in the homogeneous bulk of the crystal [59,60]. Thus, by monitoring the CSHG signal while scanning the sample with a laser beam, domain walls can be mapped out. This non-destructive optical method has the added benefit of being able to probe the crystal volume and has been employed in-situ while poling in order to probe the 3D domain growth process in a 40$\times$60$\times$60 $\mathrm{\mu}$m$^3$ volume of strontium barium niobate crystals [61]. The origin of the CSHG signal at the domain walls is not fully understood, but has been attributed to either the broad range of reciprocal vectors perpendicular to the domain wall, a strong local electric field at the domain wall [59], or to lattice distortions from the poling process [62]. While super-resolution methods can be employed to precisely determine domain wall position with sub-micron resolution [60], CSHG microscopy’s imaging resolution is still restrained by the primary laser beam’s diffraction limit. Furthermore, a domain’s polarization direction cannot be determined from CSHG without prior knowledge.
In order to develop a non-destructive technique for characterizing ferroelectric domain patterns and study the surface of MgLN crystals, Auger electron spectroscopy (AES) is used to characterize the domains of in-house poled magnesium-doped lithium niobate crystals. AES is a technique that analyzes the characteristic Auger electrons ejected from a sample under primary electron beam irradiation. The kinetic energies of the detected Auger electrons are specific to the atomic species that emits them, enabling material characterization. AES is a highly surface sensitive method due to the short mean free path of the low energy Auger electrons in solids and thus only probes to depths of approximately 1-5 nm of a material [63], much less than other techniques such as SEM and CSHG. Oppositely polarized MgLN domains are found to be differentiable by a relative shift in the energy of the Auger O KLL peak, with -Z domains having a higher peak energy, in agreement with the literature where -Z domains have a lower electron affinity [23,64,65]. This technique has the potential to non-destructively characterize polarization domains on both the sub-micron and millimeter scale, benefits of PFM and SEM, respectively; have higher spatial resolution than diffraction limited RS and CSHG techniques; and study the material’s surface and origin of its work function without the complexity of PFM’s tip-surface interaction. We demonstrate the feasibility of AES characterization of ferroelectric domain with samples that have been etched in HF first in order to facilitate finding domains of opposite polarization. However, the AES domain characterization technique could in theory be employed on samples with unknown polarization domains as a non-destructive means of characterizing poled crystals.
2. Experiment
Samples of single crystal, Z-cut, optical grade magnesium doped (5% molar) lithium niobate with dimensions of 10$\times$10$\times$0.5 mm$^3$ were obtained from MTI Corp. MgLN was chosen in order to facilitate poling due to its lower coercive field of 4.45 kV$/$mm [66], compared to 21 kV$/$mm for congruent un-doped lithium niobate [67,68] and because of its preferred use for nonlinear optics applications. Upon receiving the crystal, the +Z face is determined using the compression method from Weis [69], which detects differences in the piezoelectric voltage generated when an electrode is pressed on the crystal surface due to the converse piezoelectric effect. Poling is performed using an in-house contact poling system shown in Fig. 1, which consists of millimeter-scale metal contact electrodes, and a Trek 610B High Voltage Power Supply Amplifier coupled with an Agilent 33220A arbitrary waveform generator (AWG) for controlling the poling voltage amplitude as a function of time. Samples were poled using a +3.9 kV, 4.0 s square pulse applied to the crystal’s original +Z face. After poling, samples are placed in room temperature 40% HF acid for 100 min, which results in etching the sample to a depth of approximately 0.5 $\mathrm{\mu}$m in the -Z regions (the switched regions on the original +Z face). An SEM image of the MgLN sample is shown in Fig. 2. A roughly triangular poled area, corresponding to a region of etched −Z domain, is visible in the left side of the image. Examining the other side of the MgLN sample shows a complementary set of domains were etched, indicating that the samples were through-poled.
Fig. 1. Contact poling system. Ferroelectric MgLN is placed between a flat HV electrode and a smaller ground electrode, the shape and size of which spatially defines the poled area. The HV amplifier is controlled by the AWG, which sets the pulse duration and voltage. The force applied by the springs is controlled by vertical position of XYZ stage.
Fig. 2. SEM image of MgLN sample. The roughly triangular region on the left side of the image corresponds to the poled region, made visible under SEM by HF-etching of the −Z domain. The FOV is 500 $\mathrm{\mu}$m and primary beam voltage and current are 1 kV and 1 nA, respectively. The sample is tilted 75° in the SEM, with the bottom of the image being closest to the observer.
The Auger electron spectroscopy analysis process begins by placing a sample of interest on a metal stage with a 30° tilt and securing it with a copper clip. The stage is transferred into the UHV main chamber of the Scanning Auger Electron Nanoprobe (Physical Electronics 710) and tilted 45° such that the sample’s total tilt is 75°. The use of a high tilt is an important technique to mitigate charging of the insulating sample because the primary beam is more likely to be reflected off of the sample surface rather than penetrating deeper into the material, lowering the amount of embedded charge [70]. The area of interest is located using the Nanoprobe’s SEM at low magnification and the primary beam at 1 kV and 1 nA.
In order to calibrate the spectrometer, the SEM’s field of view (FOV) is first moved laterally to the side (away from the area of interest) to an area that is roughly the same height on the tilted sample in order to avoid excess beam exposure to the area of interest during calibration. The FOV is reduced to 50 $\mathrm{\mu}$m and the spectrometer scans a narrow range of electron energies surrounding 1 kV, the primary beam voltage. The sample generally needs to be raised up in order to ensure electrons at the elastic peak energy (1 kV) are focused onto the detector. This process brings the sample into the focal point of the detector, which also ensures the strongest signal. After spectrometer calibration, the primary beam analysis parameters are set to 5 kV and 10 nA, and the focus and stigmation are adjusted at high magnification to give the clearest image. The SEM magnification is decreased and the SEM’s FOV is moved back to the area of interest.
The Auger peak from the oxygen KLL transition (O KLL, nominally at 531 eV) is chosen to differentiate domains due to the larger peak amplitude when compared with other peaks. For insulating ferroelectric samples, the initial position of various Auger spectral peaks is often shifted by tens of eV due to charging and sample history. In order to focus a survey on the Auger O KLL transition, an initial survey is performed with a wider range of 5-605 eV in order to find the O KLL peak’s initial position. An example of this is given in Fig. 3, where the O KLL peak is seen around 525 eV. This AES survey consisted of scans of survey areas 1-6 in Fig. 3(a), which places odd areas inside the etched −Z domain (on the left side of the image) and even numbered areas in the original +Z domain. The survey was a single cycle from 5-605 eV with 1.0 eV steps, 20 ms$/$step, and primary beam settings of 5 kV and 10 nA. Survey areas are scanned in an alternating manner inside and outside of the poled area (Fig. 3(a)) to increase spacing between most subsequent scans and allow more charge relaxation. Once the O KLL transition’s initial peak position is identified, subsequent scans can use a narrower survey energy range.
Fig. 3. An example of an AES survey of MgLN with six survey areas. a) 500 $\mathrm{\mu}$m wide SEM image of MgLN sample with the roughly triangular area on the left side of the image corresponding to the poled and etched -Z domain. The labeling of the six AES survey areas corresponds to the order in which the surveys were performed. Odd numbered AES survey areas are located inside the poled (−Z) domain region. b) Auger spectra for the 6 survey areas taken with a relatively wide energy range in order to find the O KLL peaks’ initial position (highlighted by the green stripe), located at approximately 525 eV in this instance. Niobium MNN and carbon KLL transitions are also noted. These surveys were taken on a separate day from the rest of the surveys shown in Figs. 4−9.
3. Results and discussion
AES scans are performed with a narrower range of energies to demonstrate how a relative shift in the O KLL transition’s peak energy can be used to differentiate polarization domains in MgLN. An SEM image of an MgLN sample is shown in Fig. 4(a), with a roughly triangular poled and etched −Z domain on the left side of the image. An AES survey is performed on the ten areas indicated by the numbered and colored boxes in Fig. 4(a). The scans are performed sequentially in numerical order. The odd-numbered areas are in the -Z domain and even-numbered areas are in the unmodified +Z domain. Each area has a side dimension of approximately 24.4 $\mathrm{\mu}$m.
Fig. 4. a) 500 $\mathrm{\mu}$m wide SEM image of MgLN sample with poled$/$etched −Z domain on left side of image. Selected AES survey areas are located across middle of image with numbering showing their sequential order. Note the alternating order in and out of the poled region. b) AES spectra corresponding to color-coded survey areas in SEM image. Survey has relatively low time$/$step (2 ms) but poled$/$un-poled spectra are still clearly differentiable. c) Spectra with higher time$/$step (100 ms) to improve signal to noise. d) Gaussian fit curves corresponding to spectra in 4-b (solid lines) and 4-c (dashed lines) shown above. Blue colored spectra are in −Z domain and are well separated due to their higher peak energies, even for the two survey areas closest to the domain boundary. 4-b and 4-c are surveys #39 and #40 in Figs. 6 and 7.
Figures 4(b) and 4(c) shows the results of two individual surveys, consisting of ten color-coded spectra corresponding to each of the areas. There is a clear trend with the odd-numbered spectra from survey areas inside the -Z poled region (various shades of blue) having a higher peak energy than the even-numbered spectra positioned outside in the +Z region (colored red or orange). This shift in the spectral peak demonstrates that domains of opposite polarization can be differentiated using this method. Figure 4(c) utilized a relatively long 100 ms per step, however the much faster measurement of 2 ms per step shown in 4(b) still provides the differentiable shift in peak energies between domains of opposite polarization.
Auger electron spectroscopy data is analyzed in MATLAB. The Auger O KLL energy peaks are treated as approximately following a normal distribution. The uneven background is ignored, and the top half of each peak is fit with a Gaussian in order to determine the peak energy. Figure 4(d) shows the Gaussian curves fit to the spectra in 4(b) and 4(c) (dashed lines), and emphasizes the separation between spectra inside and outside of the poled and etched −Z domain.
The degree of relative peak separation is partially dependent on the distance from the domain boundary. This is notable in Figs. 4(b) and 4(c) when looking at the two areas located nearest to the domain boundary, areas 9 and 10 are just inside and outside of the poled region, respectively. Their corresponding spectra have a smaller relative separation when compared with the rest of the areas that lie further from the domain boundary.
Next, a series of AES scans is performed at higher magnification, resulting in smaller scan areas with side dimensions of roughly 4.9 $\mathrm{\mu}$m. Figure 5(a) shows an SEM image with survey areas and the corresponding spectra similar to Fig. 4(a), except that the FOV is lowered to 100 $\mathrm{\mu}$m. Figures 5(b) and 5(c) are surveys with relatively low 2ms per step, and higher 100 ms per step (which increases survey time), respectively. The fitted Gaussian curves shown in 5(d) correspond to the spectra in 5(b) and 5(c) (dashed curves) and show the clear separation and differentiation of peak energies between poled (blue colors, left side of SEM image) and un-poled (red/orange colors, right side of SEM image) regions. At this smaller FOV the relative peak separation is more apparent for faster surveys (5(b)). The measured peak energy of areas 9 and 10 both exhibit unique behavior, likely due to their proximity to the domain boundary, and it must also be noted that these areas may not be wholly inside/outside of the domain due to both image drift at this smaller FOV and imprecision in positioning the FOV.
Fig. 5. a) 100 $\mathrm{\mu}$m wide SEM image with triangular poled$/$etched −Z domain on left side of image. AES survey areas across center of image with alternating order in and out of poled region, with numbering showing temporal order of survey areas. b) Fast AES spectra with 0.1 eV steps and low time/step (2 ms); blue spectra for areas that are located in poled −Z domain have higher energies and are well separated from red spectra for areas that are located in original +Z domain. c) Slower AES spectra with 0.1 eV steps and relatively high dwell time (100 ms/step) with higher signal to noise. Peak energies of poled and un-poled regions are still separable but energy separation is smaller relative to larger FOV shown in Fig. 4(d). Gaussian fit curves for surveys from 5-b and 5-c (dashed lines), demonstrating peaks are well separable and domain resolution of approximately 9 $\mathrm{\mu}$m. 5-b and 5-c are surveys #24 and #29 in Figs. 6 and 7.
To confirm these results, a number of additional surveys are conducted and the peak energies of all 10 survey areas are plotted for each survey in Fig. 6. Surveys are performed comparing poled/etched and un-poled regions of the sample at three different FOV settings: 500 $\mathrm{\mu}$m FOV (surveys 1–10, 31–40), 200 $\mathrm{\mu}$m FOV (surveys 11–20), and 100 $\mathrm{\mu}$m FOV (surveys 21–30). Additional surveys are conducted in an un-poled, un-etched region of the sample nearby (meaning all 10 scan areas are in un-poled regions) at each FOV setting: 500 $\mathrm{\mu}$m FOV (surveys 41–50), 200 $\mathrm{\mu}$m FOV (surveys 51–60), and 100 $\mathrm{\mu}$m FOV (surveys 61–70). As described above, a curve-fitting process is performed on the results of each survey to determine the peak energy value. For surveys 1–40, odd-numbered survey areas are located in -Z domains and are color-coded shades of blue, while even-numbered survey areas are located in +Z domains and are color-coded shades of red or orange. For surveys 41–70, the same color code is used, but all areas are located in +Z domains. In Fig. 6, the results shown in Figs. 4(b) and 4(c) correspond to surveys 39 and 40, respectively, while the results shown in Figs. 5(b) and 5(c) correspond to surveys 24 and 29, respectively.
Fig. 6. Peak energies for numerous surveys with changing FOVs. The studied FOVs are indicated by color-coded background, with FOVs given in microns. Surveys 1-40 have odd areas [1,3,5,7,9] in poled −Z domain, which have higher average energy. Surveys 41-70 are located in a control region on the MgLN sample and all 10 survey areas are located in a region of un-poled original +Z domain. The figure shows why relative peak energy shifts in an individual survey are used for domain characterization, because the average peak energy of an individual survey drifts more than the relative peak separation on any single survey. Surveys 29 and 40 were taken with 100ms/step, all other surveys utilize a faster 2ms/step.
For each survey including both poled and un-poled areas (1–40), in almost all cases there is a separation between the measured peak energy value for poled areas and un-poled areas. Surveys 21, 22 and 30 do show the measured peak energy in area 10 being higher than for area 7. This is likely due to its proximity to the domain boundary and image drift such that area 10 may be partially straddling the domain boundary. In the remaining surveys, wholly in un-poled regions, no notable distinction is seen. Thus, Fig. 6 provides additional data supporting the conclusion that a relative shift in the O KLL transition energy peak can be used to differentiate polarization domains in MgLN.
Over time, as more surveys are performed the mean energy of individual surveys can drift farther than the relative shift in peak energies from opposite domains in a single survey. This necessitates a relative measurement in order to characterize domain polarization and has so far been one notable limitations of using AES for characterizing MgLN domains.
Because the drift of mean energy after a number of surveys can be larger than the peak separation on an individual survey, experiments have so far been limited to selecting a cluster of survey areas rather than employing mapping across the whole SEM image. Another challenge to mapping the whole FOV is that the MgLN sample is highly tilted in the AES instrument in order to mitigate charging. Thus the top (bottom) of the image is farther away from (closer to) the Auger electron analyzer, which alters the detected Auger electron energy. The mean survey energy generally drifts faster at smaller FOV, which is at least partially caused by the higher incident charge density at smaller FOVs. As noted, survey areas closer to the domain boundary have smaller deviations from the mean peak energy and this can be seen more broadly by tracking the positions of areas 9 and 10 (cyan and light orange) across surveys 1-40 in Fig. 6.
Due to the drift of the mean peak energy between individual surveys, Fig. 7 shows the peak energy of all 10 survey areas for the surveys shown in Fig. 6, with each individual survey’s mean peak energy subtracted (deviation from the mean). The reliable separation of peak energies from poled (blue colors) and un-poled areas (red/orange colors) is more clear with each survey’s mean energy subtracted.
Fig. 7. Peak energies’ deviation from the mean of each individual survey’s peaks for the surveys shown in Fig. 6. Changing FOV shows the relative peak shift between domains is consistent but decreases with FOV. At 100 $\mathrm{\mu}$m FOV the deviation from the mean decreases with more surveys indicating an effect from cumulative current density incident on a survey area. Survey areas 9 and 10 are nearest to the domain boundary and consistently have less relative peak shift due to this proximity. FOVs are in microns.
In order to quantify the peak energy separation from opposite polarization domains, it is useful to look at the average difference of the +Z and -Z domains’ deviations from the mean, in particular when looking at the decreasing relative shift between polarization domains with decreasing FOV. For survey numbers 1-40 at FOVs of 500 $\mathrm{\mu}$m, 200 $\mathrm{\mu}$m, and 100 $\mathrm{\mu}$m shown in Fig. 6 the average difference of the poled and un-poled areas’ mean deviations is 6.6 eV (surveys numbers 1-10, 31-40), 4.5 eV (surveys numbers 11-20), and 1.3 eV (surveys numbers 21-30), respectively. The average difference of the deviation from the mean for the control group surveys (areas only in the unmodified +Z region, surveys 41-70) for FOVs of 500 $\mathrm{\mu}$m, 200 $\mathrm{\mu}$m, and 100 $\mathrm{\mu}$m are -0.07 eV (surveys 41-50), 0.01 eV (surveys 51-60), and 0.05 eV (surveys 61-70), respectively, with their mean standard deviation being 0.15 eV. The average difference of the deviation from the mean for the surveys with both +Z and -Z domains are all significantly larger than both those of the control group and the control group’s standard deviation, though there are still not well understood positional and charge dependent effects.
A second data set is shown in Fig. 8, taken from the same MgLN sample and in the same region as Fig. 6, but on a different day. Surveys #1-53 have odd-numbered areas located within the poled −Z domain, and even-numbered areas located in the un-poled original +Z domain, while surveys #54-82 have all 10 survey areas located in the original un-poled +Z domain. In surveys #1-53 blue colors (corresponding to poled −Z domain) have consistently higher peak energies than red/orange colors (corresponding to un-poled −Z domain). The data in Fig. 8 is also given in Fig. 9 but shown as the deviation from the mean. The peak separation between poled and un-poled survey areas is quite clear across a number of surveys and FOVs. As stated previously, survey areas closest to the domain boundary (areas 9 and 10 corresponding to cyan and light orange) have consistently smaller peak separation. When comparing the 200 $\mathrm{\mu}$m FOV surveys in the two data sets of Figs. 6 or 8, we see that the survey-to-survey change in mean energy is positive or negative, respectively. Even though the survey-to-survey average peak energy drift is somewhat unpredictable, Figs. 7 and 9 show that the AES domain characterization experiments using relative peak shifts are repeatable. This also again emphasizes the requirement of a relative measurement of peak position rather than an absolute peak energy measurement: the energy of the O KLL transition from MgLN samples is modified by multiple factors, which may include MgLN’s insulating, pyroelectric, and ferroelectric properties.
Fig. 8. Peak energies across numerous surveys and FOVs; similar to Fig. 6 except taken on a different day and AES session. Peak energies from areas located in the poled -Z domain [1,3,5,7,9] in surveys 1-53 have consistently higher energy than those in the un-poled +Z domain [2,4,6,8,10]. This indicates characterization experiments are repeatable. The initial surveys in the un-poled region (#54 and #55) have an uncharacteristic shift of the survey areas on the right hand side of the image [10,8,6,4,2], which quickly fades after a few surveys or cumulative dwell time under the SEM beam. This is likely due to initial charge relaxation effects of the area when initially exposed to the e-beam. Surveys 42 and 53 were taken with 100 ms/step, all other surveys used a faster 2 ms/step.
Fig. 9. Peak energy deviation from the mean energy of individual survey for a large number of surveys, similar to Fig. 7 but data was taken on a different day (raw data already given in Fig. 8). Once the survey areas were moved to the unmodified region of the sample there is an initial uncharacteristic shift in approximately surveys #54-59. The relative peak separation between odd and even survey areas is initially opposite to that seen when odd survey areas are in the poled −Z domain. We attribute this to charging effects due to the new survey area being in close proximity to the previous area that has accumulated substantial charge. The dissipation of the relative shift after about 5 surveys at the larger 500 $\mathrm{\mu}$m FOV supports this notion.
The limits of the AES system’s (Physical Electronics 710) spatial resolution is reported to be 8 nm (20 kV, 1 nA primary beam) [71], although we expect that this resolution likely cannot be achieved with insulating ferroelectric samples due to charging effects. The results with 100 $\mathrm{\mu}$m FOV presented in Fig. 7 (surveys 31-40) and in Fig. 9 (surveys 32-42) have survey areas in -Z and +Z domains, which are separated by 9 $\mathrm{\mu}$m, center-to-center. For this set of measurements, most but not all are separable, suggesting that 9 um is close to the resolution limit for this experimental configuration (5 kV, 10 nA primary beam). Preliminary results testing lower current (1 nA) at a FOV of 10 $\mathrm{\mu}$m have shown reduced peak energy drift and promising improvements in spatial resolution, with 0.9 $\mathrm{\mu}$m spatial resolution between survey areas potentially achievable, however with reduced signal-to-noise ratio. Ongoing investigations are exploring methods for reducing sample charging to achieve higher spatial resolution while maintaining sufficient signal-to-noise ratio.
The shift in the Auger O KLL transition energy peak between the +Z and -Z domains of LN surfaces could stem from a difference in electron affinity between the two domains. Other research has seen a difference in the electron affinity between domains of opposite polarization in LN using UV-photoelectron emission microscopy (PEEM) with -Z domains having a lower electron affinity [23]. The difference between domains of 1.6eV in the electron photo-threshold was attributed to differential adsorption on the domain surfaces with exposure to atmosphere [23]. In AES, the kinetic energy of the Auger electrons is decreased by the electron affinity [72]. Thus, the lower electron affinity of -Z domains would be expected to result in a shift to higher energy Auger peaks for -Z domains compared to +Z domains, consistent with the results presented in this paper. Similar differential effects between different domains were observed in the selective deposition of charged polystyrene microspheres on domain-patterned LN [73]. Electrostatic force microscopy and scanning surface potential microscopy studies of ferroelectric barium titanate measured a potential difference between domains of opposite polarity and concluded that surface adsorbates played a role in the shift [39]. However, the electron affinity can also be affected by surface reconstructions and atomic steps [21]. Density functional theory calculations of the ionization energy differences between domains suggest the differences exist in clean surfaces, and originate largely from different surface terminations [21]. Regardless of the sources of the differences in electron affinity between domains, AES can play a role in its detection and mapping domain structures. Furthermore, studying the origin of the relative peak shift between domains may lead to a method to enhance the dipole field and further improve spatial resolution.
There are two main advantages to AES for studying the contribution of adsorbates to the observed shift between the +Z and -Z domains. First, AES is operated in UHV such that once a surface is clean, atmospheric contamination can be negated. Second, the AES instrument contains an in situ Ar-ion etching capability that can be used to clean the surface and perform depth profiling. Initial tests utilizing the Ar-ion gun showed the relative peak shift between domains vanished after light Ar-ion etching. This suggests that the detected peak energy shifts between domains may be related to chemical adsorbates on the sample surface, however the shift may also be affected by differential surface charging. Further investigation into the origin of the ionization energy gap between different polarization domains is ongoing.
4. Summary
This work has demonstrated a new method of characterization for polarization domains in MgLN. Auger electron spectroscopy was used to differentiate polar +/- Z domains in MgLN by observing a relative shift in the energy of the O KLL transition energy peak between the two domains. Auger electrons emitted from the −Z domain had a consistently higher energy; the magnitude of the peak separation was found to be partially dependent on the proximity to the domain boundary and the amount of accumulated incident charge at smaller FOVs. Currently, domain differentiation is determined relatively, because the survey-to-survey mean peak energy drift can be greater than the per-survey peak energy separation. Spatial resolution down to approximately 9 $\mathrm{\mu}$m has been demonstrated alongside mm-scale characterization, a wide range of scales when compared with other non-destructive methods of characterization. Recent preliminary results exploring lower incident currents have shown some promise of improved spatial domain resolution (to below 1 $\mathrm{\mu}$m) and reduced peak energy drift (potentially negating the need for a relative measurement). Additionally, incorporating AES’s in situ Ar-ion sputtering will allow us to investigate the origin of the peak shift on various ferroelectric surfaces cleaned of contamination.
Funding
National Science Foundation (1710128).
Acknowledgments
The authors gratefully acknowledge Nathaniel Rieders for technical assistance and useful discussion. This work was performed in part at the Montana Nanotechnology Facility (MONT), a member of the National Nanotechnology Coordinated Infrastructure (NNCI), which is supported by the National Science Foundation under grant number ECCS-1542210. This material is based upon work supported by the National Science Foundation under Grant No. 1710128.
Disclosures
The authors declare no conflicts of interest.
References
1. L.-H. Peng, Y.-C. Fang, and Y.-C. Lin, “Polarization switching of lithium niobate with giant internal field,” Appl. Phys. Lett. 74(14), 2070–2072 (1999). [CrossRef]
2. D. N. Nikogosyan, Nonlinear Optical Crystals: A Complete Survey (Springer-Verlag, 2005).
3. M. Bashkansky, M. W. Pruessner, I. Vurgaftman, M. Kim, and J. Reintjes, “Higher-order spontaneous parametric down-conversion with back-propagating idler using a submicron poled KTP waveguide,” in Quantum Information and Computation IX, vol. 9873 (International Society for Optics and Photonics, 2016), p. 987303.
4. A. Zukauskas, G. Strmqvist, V. Pasiskevicius, F. Laurell, M. Fokine, and C. Canalias, “Fabrication of submicrometer quasi-phase-matched devices in KTP and RKTP [Invited],” Opt. Mater. Express 1(7), 1319–1325 (2011). [CrossRef]
5. J. Hellstrm, V. Pasiskevicius, H. Karlsson, and F. Laurell, “High-power optical parametric oscillation in large-aperture periodically poled KTiOPO4,” Opt. Lett. 25(3), 174–176 (2000). [CrossRef]
6. H. Karlsson, F. Laurell, and L. K. Cheng, “Periodic poling of RbTiOPO4 for quasi-phase matched blue light generation,” Appl. Phys. Lett. 74(11), 1519–1521 (1999). [CrossRef]
7. C. Canalias, V. Pasiskevicius, M. Fokine, and F. Laurell, “Backward quasi-phase-matched second-harmonic generation in submicrometer periodically poled flux-grown KTiOPO4,” Appl. Phys. Lett. 86(18), 181105 (2005). [CrossRef]
8. R. G. Batchko, V. Y. Shur, M. M. Fejer, and R. L. Byer, “Backswitch poling in lithium niobate for high-fidelity domain patterning and efficient blue light generation,” Appl. Phys. Lett. 75(12), 1673–1675 (1999). [CrossRef]
9. M. Neradovskiy, E. Neradovskaia, D. Chezganov, E. Vlasov, V. Y. Shur, H. Tronche, F. Doutre, G. Ayenew, P. Baldi, M. D. Micheli, and C. Montes, “Second harmonic generation in periodically poled lithium niobate waveguides with stitching errors,” J. Opt. Soc. Am. B 35(2), 331–336 (2018). [CrossRef]
10. G. A. Magel, M. M. Fejer, and R. L. Byer, “Quasi-phase matched second-harmonic generation of blue light in periodically poled LiNbO3,” Appl. Phys. Lett. 56(2), 108–110 (1990). [CrossRef]
11. V. Bermdez, J. Capmany, J. Garc, and E. Diguez, “Growth and second harmonic generation characterization of Er3+ doped bulk periodically poled LiNbO3,” Appl. Phys. Lett. 73(5), 593–595 (1998). [CrossRef]
12. L. E. Myers, R. C. Eckardt, M. M. Fejer, R. L. Byer, W. R. Bosenberg, and J. W. Pierce, “Quasi-phase-matched optical parametric oscillators in bulk periodically poled LiNbO3,” J. Opt. Soc. Am. B 12(11), 2102–2116 (1995). [CrossRef]
13. M. Yamada, N. Nada, M. Saitoh, and K. Watanabe, “First-order quasi-phase matched LiNbO3 waveguide periodically poled by applying an external field for efficient blue second-harmonic generation,” Appl. Phys. Lett. 62(5), 435–436 (1993). [CrossRef]
14. D. Feng, N. Ming, J. Hong, Y. Yang, J. Zhu, Z. Yang, and Y. Wang, “Enhancement of second-harmonic generation in LiNbO3 crystals with periodic laminar ferroelectric domains,” Appl. Phys. Lett. 37(7), 607–609 (1980). [CrossRef]
15. D. H. Jundt, G. A. Magel, M. M. Fejer, and R. L. Byer, “Periodically poled LiNbO3 for high-efficiency second-harmonic generation,” Appl. Phys. Lett. 59(21), 2657–2659 (1991). [CrossRef]
16. J. Webjorn, F. Laurell, and G. Arvidsson, “Fabrication of periodically domain-inverted channel waveguides in lithium niobate for second harmonic generation,” J. Lightwave Technol. 7(10), 1597–1600 (1989). [CrossRef]
17. J. Webjorn, F. Laurell, and G. Arvidsson, “Blue light generated by frequency doubling of laser diode light in a lithium niobate channel waveguide,” IEEE Photonics Technol. Lett. 1(10), 316–318 (1989). [CrossRef]
18. H. Ishizuki, I. Shoji, and T. Taira, “Periodical poling characteristics of congruent MgO:LiNbO3 crystals at elevated temperature,” Appl. Phys. Lett. 82(23), 4062–4064 (2003). [CrossRef]
19. P. K. Sen, N. Sisodia, R. Choubey, S. Kar, and K. Bartwal, “Effect of MgO doping on coercive field in LiNbO3 crystals,” J. Nonlinear Opt. Phys. Mater. 17(02), 175–183 (2008). [CrossRef]
20. K. Nakamura, J. Kurz, K. Parameswaran, and M. M. Fejer, “Periodic poling of magnesium-oxide-doped lithium niobate,” J. Appl. Phys. 91(7), 4528–4534 (2002). [CrossRef]
21. S. Sanna and W. G. Schmidt, “LiNbO3 surfaces from a microscopic perspective,” J. Phys.: Condens. Matter 29(41), 413001 (2017). [CrossRef]
22. V. Y. Shur, “Kinetics of ferroelectric domains: Application of general approach to LiNbO3 and LiTaO3,” in Frontiers of Ferroelectricity: A Special Issue of the Journal of Materials ScienceS. B. Lang and H. L. W. Chan, eds. (Springer, 2007), pp. 199–210.
23. W. Yang, B. Rodriguez, A. Gruverman, and R. Nemanich, “Polarization-dependent electron affinity of LiNbO3 surfaces,” Appl. Phys. Lett. 85(12), 2316–2318 (2004). [CrossRef]
24. Y. Yun and E. I. Altman, “Using ferroelectric poling to change adsorption on oxide surfaces,” J. Am. Chem. Soc. 129(50), 15684–15689 (2007). [CrossRef]
25. C. Canalias, S. Wang, V. Pasiskevicius, and F. Laurell, “Nucleation and growth of periodic domains during electric field poling in flux-grown KTiOPO4 observed by atomic force microscopy,” Appl. Phys. Lett. 88(3), 032905 (2006). [CrossRef]
26. V. Ivanov, V. Ganshin, and Y. Korkishko, “Analysis of ion exchanged Me : LiNbO3 and Cu: LiTaO3 waveguides by AES, SAM, EPR and optical methods,” Vacuum 43(4), 317–324 (1992). [CrossRef]
27. W. L. Holstein, “Etching study of ferroelectric microdomains in LiNbO3 and MgO:LiNbO3,” J. Cryst. Growth 171(3-4), 477–484 (1997). [CrossRef]
28. C. L. Sones, S. Mailis, W. S. Brocklesby, R. W. Eason, and J. R. Owen, “Differential etch rates in z-cut LiNbO3 for variable HF/HNO3 concentrations,” J. Mater. Chem. 12(2), 295–298 (2002). [CrossRef]
29. P. R. Potnis, N.-T. Tsou, and J. E. Huber, “A review of domain modelling and domain imaging techniques in ferroelectric crystals,” Materials 4(2), 417–447 (2011). [CrossRef]
30. S. Mailis, C. L. Sones, J. G. Scott, and R. W. Eason, “UV laser-induced ordered surface nanostructures in congruent lithium niobate single crystals,” Appl. Surf. Sci. 247(1-4), 497–503 (2005). [CrossRef]
31. V. Bermadez, F. Caccavale, C. Sada, F. Segato, and E. Diguez, “Etching effect on periodic domain structures of lithium niobate crystals,” J. Cryst. Growth 191(3), 589–593 (1998). [CrossRef]
32. C. Y. J. Ying, C. L. Sones, A. C. Peacock, F. Johann, E. Soergel, R. W. Eason, M. N. Zervas, and S. Mailis, “Ultra-smooth lithium niobate photonic micro-structures by surface tension reshaping,” Opt. Express 18(11), 11508–11513 (2010). [CrossRef]
33. K. Nassau, H. J. Levinstein, and G. M. Loiacono, “The domain structure and etching of ferroelectric lithium niobate,” Appl. Phys. Lett. 6(11), 228–229 (1965). [CrossRef]
34. F. Laurell, J. Webjorn, G. Arvidsson, and J. Holmberg, “Wet etching of proton-exchanged lithium niobate-a novel processing technique,” J. Lightwave Technol. 10(11), 1606–1609 (1992). [CrossRef]
35. V. Y. Shur, A. I. Lobov, A. G. Shur, S. Kurimura, Y. Nomura, K. Terabe, X. Y. Liu, and K. Kitamura, “Rearrangement of ferroelectric domain structure induced by chemical etching,” Appl. Phys. Lett. 87(2), 022905 (2005). [CrossRef]
36. V. Bermadez, A. Gil, L. Arizmendi, J. Colchero, A. M. Bara, and E. Diguez, “Techniques of observation and characterization of the domain structure in periodically poled lithium niobate,” J. Mater. Res. 15(12), 2814–2821 (2000). [CrossRef]
37. E. Soergel, “Piezoresponse force microscopy (PFM),” J. Phys. D: Appl. Phys. 44(46), 464003 (2011). [CrossRef]
38. A. Gruverman and S. V. Kalinin, “Piezoresponse force microscopy and recent advances in nanoscale studies of ferroelectrics,” J. Mater. Sci. 41(1), 107–116 (2006). [CrossRef]
39. S. V. Kalinin and D. A. Bonnell, “Local potential and polarization screening on ferroelectric surfaces,” Phys. Rev. B 63(12), 125411 (2001). [CrossRef]
40. S. V. Kalinin and D. A. Bonnell, “Imaging mechanism of piezoresponse force microscopy of ferroelectric surfaces,” Phys. Rev. B 65(12), 125408 (2002). [CrossRef]
41. R. L. Bihan, “Study of ferroelectric and ferroelastic domain structures by scanning electron microscopy,” Ferroelectrics 97(1), 19–46 (1989). [CrossRef]
42. V. Aristov, L. Kokhanchik, K.-P. Meyer, and H. Blumtritt, “Scanning electron microscopic investigations of peculiarities of the BaTiO3 ferroelectric domain contrast,” Phys. Stat. Sol. (a) 78(1), 229–236 (1983). [CrossRef]
43. L. S. Kokhanchik, “The use of surface charging in the SEM for lithium niobate domain structure investigation,” Micron 40(1), 41–45 (2009). [CrossRef]
44. Y. Zhou, D. S. Fox, P. Maguire, R. O’Connell, R. Masters, C. Rodenburg, H. Wu, M. Dapor, Y. Chen, and H. Zhang, “Quantitative secondary electron imaging for work function extraction at atomic level and layer identification of graphene,” Sci. Rep. 6(1), 21045 (2016). [CrossRef]
45. G. Rosenman, A. Skliar, I. Lareah, N. Angert, M. Tseitlin, and M. Roth, “Observation of ferroelectric domain structures by secondary-electron microscopy in as-grown KTiOPO4 crystals,” Phys. Rev. B 54(9), 6222–6226 (1996). [CrossRef]
46. P. S. Zelenovskiy, M. D. Fontana, V. Y. Shur, P. Bourson, and D. K. Kuznetsov, “Raman visualization of micro- and nanoscale domain structures in lithium niobate,” Appl. Phys. A 99(4), 741–744 (2010). [CrossRef]
47. R. Hammoum, M. Fontana, P. Bourson, and V. Shur, “Characterization of PPLN-microstructures by means of Raman spectroscopy,” Appl. Phys. A 91(1), 65–67 (2008). [CrossRef]
48. M. D. Fontana and P. Bourson, “Microstructure and defects probed by Raman spectroscopy in lithium niobate crystals and devices,” Appl. Phys. Rev. 2(4), 040602 (2015). [CrossRef]
49. G. Nataf, M. Guennou, A. Hauamann, N. Barrett, and J. Kreisel, “Evolution of defect signatures at ferroelectric domain walls in Mg-doped LiNbO3,” Phys. Status Solidi RRL 10(3), 222–226 (2016). [CrossRef]
50. P. Capek, G. Stone, V. Dierolf, C. Althouse, and V. Gopolan, “Raman studies of ferroelectric domain walls in lithium tantalate and niobate,” Phys. Status Solidi C 4(3), 830–833 (2007). [CrossRef]
51. G. Stone, B. Knorr, V. Gopalan, and V. Dierolf, “Frequency shift of Raman modes due to an applied electric field and domain inversion in LiNbO3,” Phys. Rev. B 84(13), 134303 (2011). [CrossRef]
52. D. Tuschel, “Three-dimensional raman imaging of ion-exchanged waveguides,” Spectroscopy 29, 14 (2014).
53. G. Stone and V. Dierolf, “Influence of ferroelectric domain walls on the Raman scattering process in lithium tantalate and niobate,” Opt. Lett. 37(6), 1032–1042 (2012). [CrossRef]
54. J. Scott, S. Mailis, C. Sones, and R. Eason, “A Raman study of single-crystal congruent lithium niobate following electric-field repoling,” Appl. Phys. A 79(3), 691–696 (2004). [CrossRef]
55. P. S. Bullen, H. C. Huang, H. Yang, J. I. Dadap, I. Kymissis, and R. M. Osgood, “Microscopy and microRaman study of periodically poled domains in deeply thinned lithium niobate wafers,” Opt. Mater. 57, 243–248 (2016). [CrossRef]
56. B. Liu, Y. Zheng, X. Zhao, H. Liu, and X. Chen, “Probe of symmetry reduction at domain walls by nonlinear Cherenkov measurement,” Opt. Express 24(26), 29459–29464 (2016). [CrossRef]
57. T. Kampfe, P. Reichenbach, A. Hauamann, T. Woike, E. Soergel, and L. M. Eng, “Real-time three-dimensional profiling of ferroelectric domain walls,” Appl. Phys. Lett. 107(15), 152905 (2015). [CrossRef]
58. Y. Sheng, V. Roppo, M. Ren, K. Kalinowski, C. Cojocaru, J. Trull, Z. Li, K. Koynov, and W. Krolikowski, “Multi-directional Aerenkov second harmonic generation in two-dimensional nonlinear photonic crystal,” Opt. Express 20(4), 3948–3953 (2012). [CrossRef]
59. Y. Sheng, A. Best, H.-J. Butt, W. Krolikowski, A. Arie, and K. Koynov, “Three-dimensional ferroelectric domain visualization by Aerenkov-type second harmonic generation,” Opt. Express 18(16), 16539–16545 (2010). [CrossRef]
60. T. Kampfe, P. Reichenbach, M. Schrader, A. Hauamann, L. Eng, T. Woike, and E. Soergel, “Optical three-dimensional profiling of charged domain walls in ferroelectrics by Cherenkov second-harmonic generation,” Phys. Rev. B 89(3), 035314 (2014). [CrossRef]
61. M. Ayoub, H. Futterlieb, J. Imbrock, and C. Denz, “3D imaging of ferroelectric kinetics during electrically driven switching,” Adv. Mater. 29(5), 1603325 (2017). [CrossRef]
62. X. Deng, H. Ren, H. Lao, and X. Chen, “Research on Cherenkov second-harmonic generation in periodically poled lithium niobate by femtosecond pulses,” J. Opt. Soc. Am. B 27(7), 1475–1480 (2010). [CrossRef]
63. H. Marcus, “Auger electron spectroscopy,” Encyclopedia of Materials: Science and Technology (Elsevier, 2001), pp. 393–398
64. J. Garra, J. M. Vohs, and D. A. Bonnell, “The effect of ferroelectric polarization on the interaction of water and methanol with the surface of LiNbO3(0001),” Surf. Sci. 603(8), 1106–1114 (2009). [CrossRef]
65. M. Zhao, D. Bonnell, and J. Vohs, “Influence of ferroelectric polarization on the energetics of the reaction of 2-fluoroethanol on BaTiO3,” Surf. Sci. 603(2), 284–290 (2009). [CrossRef]
66. A. Kuroda, S. Kurimura, and Y. Uesu, “Domain inversion in ferroelectric MgO:LiNbO3 by applying electric fields,” Appl. Phys. Lett. 69(11), 1565–1567 (1996). [CrossRef]
67. J.-P. Meyn, C. Laue, R. Knappe, R. Wallenstein, and M. Fejer, “Fabrication of periodically poled lithium tantalate for UV generation with diode lasers:,” Appl. Phys. B: Lasers Opt. 73(2), 111–114 (2001). [CrossRef]
68. T. Hatanaka, K. Nakamura, T. Taniuchi, H. Ito, Y. Furukawa, and K. Kitamura, “Quasi-phase-matched optical parametric oscillation with periodically poled stoichiometric LiTaO3,” Opt. Lett. 25(9), 651–653 (2000). [CrossRef]
69. R. S. Weis and T. K. Gaylord, “Lithium niobate: Summary of physical properties and crystal structure,” Appl. Phys. A 37(4), 191–203 (1985). [CrossRef]
70. D. R. Baer, A. S. Lea, J. D. Geller, J. S. Hammond, L. Kover, C. J. Powell, M. P. Seah, M. Suzuki, J. F. Watts, and J. Wolstenholme, “Approaches to analyzing insulators with Auger electron spectroscopy: Update and overview,” J. Electron Spectrosc. Relat. Phenom. 176(1-3), 80–94 (2010). [CrossRef]
71. PHI 710 l ULVAC-PHI, Inc. https://www.ulvac-phi.com/en/products/aes/phi-710/.
72. J. Lee, “Kinetic energy distribution of auger electrons of MgO, CaO, SrO and BaO induced by auger neutralization of He Ions,” Sae Mulli 67(10), 1168–1173 (2017). [CrossRef]
73. S. Habicht, R. Nemanich, and A. Gruverman, “Physical adsorption on ferroelectric surfaces: Photoinduced and thermal effects,” Nanotechnology 19(49), 495303 (2008). [CrossRef]
