Atomic-Scale Electronic Characterization of Defects in Silicon Carbide

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C: Physical Processes in Nanomaterials and Nanostructures

Atomic-Scale Electronic Characterization of Defects in Silicon Car-bide Nanowires by Electron Energy Loss Spectroscopy Lunet E. Luna, David Gardner, Velimir R. Radmilovic, Roya Maboudian, and Carlo Carraro J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.8b01661 • Publication Date (Web): 10 May 2018 Downloaded from http://pubs.acs.org on May 10, 2018

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The Journal of Physical Chemistry

Atomic-Scale Electronic Characterization of Defects in Silicon Carbide Nanowires by Electron Energy Loss Spectroscopy Lunet E. Luna‡†1, David Gardner‡1, Velimir Radmilovic2,3, Roya Maboudian1, Carlo Carraro*1 1

Department of Chemical and Biomolecular Engineering, University of California, Berkeley, California 94720, United States Serbian Academy of Sciences and Arts, Knez Mihailova 35, 11000 Belgrade, Serbia 3 National Center for Electron Microscopy, Lawrence Berkeley National Laboratory, University of California, Berkeley, CA 94720, USA 2

Supporting Information Placeholder in 4H-SiC for quantum computing. The large band gap of this material should facilitate the observation of optical transitions in defect centers without interference from the matrix. However, control of the local electronic structure of the material is hampered by the tendency of SiC to form a plethora of crystal structures, or polytypes, whose band gaps can vary by as much as 0.9 eV12. In the cubic, or 3C, polytype, the SiC bilayers alternate A-B-CA-B-C-…, and in the 100%-hexagonal 2H polytype, the layers alternate A-B-A-B-… Any other polytype can be classified according to its fraction of hexagonal sites, or hexagonality; for instance, in the 50%-hexagonal 4H polytype, the layers alternate A-B-C-BA-B-C-B-… The stacking orientations can be visualized in Figure 1, where different polytypes are observed in SiC nanowires using HAADF-STEM13. Alternatively, the difference can be visualized by the geometry. In the 3C polytype, the bonds are in a staggered orientation, whereas in the 2H polytype the bonds are eclipsed14.

ABSTRACT: The atomic-level resolution of scanning transmission electron microscopy (STEM) is used for structural characterization of nanomaterials, but the resolution afforded by TEM also enables electronic characterization of defects in these materials through electron energy loss spectroscopy (EELS). Here, the power of EELS is harnessed to characterize the local band gap of inclusion defects in hexagonal silicon carbide nanowires with a high density of stacking faults. The band gaps we extract from the EELS data align within 0.1 eV of expected values for hexagonal silicon carbide and stacking faults within hexagonal silicon carbide. These experiments show that individual cubic phase inclusions in hexagonal silicon carbide significantly alter the local electronic structure, in particular the band gap, in contrast to the polarizability tensor that retains the characteristic signature of the global hexagonal crystal structure.

Introduction: Silicon carbide (SiC) is the semiconductor of choice for applications involving many harsh conditions, because its physicochemical properties (such as melting point, breakdown voltage, chemical resistance, and thermal & mechanical characteristics) suit it for high power, high temperature, reactive, or biological environments1. A range of devices have been successfully demonstrated using single-crystalline SiC (such as commercial high-power and high temperature electronic devices1), and using polycrystalline SiC (such as corrosive gas microsensors2, emitters for thermionic energy conversion (T > 2000 K)3, and stress sensors for internal combustion engines4). More recently, SiC nanowires have received interest since they promise to combine the physicochemical properties of SiC with those associated with low dimensionality. Their usage has been reported in biological sensors5, field-emission cathodes6, nanoelectromechanical switches7, optical circuits8, and energy storage devices9. In addition, a recent surge of interest in the local electronic properties of defects in SiC crystals10 and nanostructures11 has been driven by the study of deep centers

Figure 1: Atomic-resolution electron micrographs of 3C, 4H, and 2H SiC polytypes taken with HAADF-STEM. Orange circles superimposed on the images denote hexagonal sites while blue circles denote cubic sites. The observed direction for each image, in hexagonal notation, is . Adapted from Luna et al. 13

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The aim of this paper is to show that the electronic structure of nanometer-sized stacking defects in SiC nanowires can be accurately resolved by means of electron energy loss spectroscopy (EELS). Each polytype has distinct electronic properties: for instance, the band gap can vary by as much as 0.9 eV between polytypes12. The proportion of polytypes in bulk SiC has been accurately predicted using an axial-next-nearest-neighbor-Ising (ANNNI) model by Cheng, et al.15 In addition, in single-crystalline samples, the electronic properties are well understood16–19. However, layers can spontaneously shift during high-temperature20–22 or high-voltage23 operation to create “stacking faults” that provide a potential well 0.2 to 1.0 eV below the conduction band minimum (CBM), effectively reducing the band gap in that region20–22,24 and degrading device performance23. Stacking faults can also arise during SiC synthesis25, and are prevalent in the bottom-up growth of SiC nanowires6. We have previously demonstrated the synthesis of vertically aligned arrays of hexagonal phase SiC nanowires grown directly on the 4H-SiC (0001) substrate using metal-catalyzed chemical vapor deposition (CVD)13. The transverse optical phonon peak observed by Raman spectroscopy at 780 cm-1 for all nanowires is consistent with a mostly hexagonal structure. High-resolution scanning transmission electron microscopy (HR-STEM) was employed to identify the stacking orientation of individual bilayers. Figure 2 shows a representative low-resolution STEM image of the nanowires on a TEM grid and a high-resolution HAADF-STEM image of the nanowire lattice planes. Using the images to assign each layer as hexagonal or cubic, the polytypic composition in the nanowires was found to be about 16% 3C, 39% 4H, and 47% 2H, and an ANNNI/nucleation theory model was used successfully to explain the observed polytypism in the nanowires13. Here, we exploit the ultrahigh spatial resolution of electron energy loss spectroscopy effected in a high-resolution transmission electron microscope to detect the differences in electronic structure between crystalline bilayers and stacking faults in SiC nanowires. The individual measurements are in agreement with calculations for single- or few-layer cubic inclusions in a hexagonal crystalline matrix24,26, while as a whole, the energy loss results are in good agreement with X-ray photoelectron spectroscopy (XPS) of an ensemble of nanowires. Experimental: As grown nanowire arrays were first characterized using XPS (Omicron Dar400 system with an achromatic Al Kα source) to examine the electronic structure of the ensemble (Figure 3a). We compare the spectra of a nanowire array to those of epitaxial films of degenerately n-doped 3C grown in an academic lab27 and n-doped 4H SiC grown commercially by CREE. All three samples were cleaned in hydrofluoric acid, rinsed in deionized water, and dried in N 2 . The high surface area of the nanowires warranted an additional exposure to oxygen plasma for 15 minutes to remove adventitious carbon. The valence band spectra of the three samples are shown in Figure 3b and the Si 2p region in Figure 3c, after subtraction of a constant and a Shirley background, respectively. The photoelectron spectrum of the nanowires in the

valence band region displays a noticeably slower rise with binding energy (BE) when compared to the 4H and 3C samples. This is due in part to a more substantial contribution of surface states28, particularly evident in the BE region below ~ 2 eV (note that in the crystalline samples photoelectrons are collected along the surface normal, whereas in the vertically aligned nanowires they are collected at grazing take-off angle, increasing surface sensitivity). Furthermore, the broadening of the spectrum by ~0.1 eV in the rising edge of the valence band is attributed to electric fields from potential wells filling with electrons29. The electric field strength depends on the number of nearby wells, and because of the stochastic distribution of faults, a distribution of electric field strength acting on photoelectrons naturally arises24,30. A smaller contribution to the broadening is the distribution of valence-band offsets (~0.05 eV) within the stacking faults22. A similar degree of broadening is observed in the Si 2p peak, for the same reasons31. With computational predictions upheld in the XPS spectra, we turn our attention to individual nanowires. The electronic structure of individual bilayers was studied using scanning transmission electron microscopy-based electron energy loss spectroscopy (STEM-EELS). STEM is a well-established technique for the characterization of the physical structure of nanomaterials. Recent advances in computation and instrumentation are enabling the use of STEM to characterize the electronic structure, such as the band-gap, of the specimen by collecting, measuring and analyzing the transmitted electrons’ kinetic energy.

Figure 2: Morphology and atomic stacking of SiC nanowires. (a) Low resolution STEM image of SiC nanowires on TEM grid. (b) Representative high-resolution HAADF-STEM image of SiC nanowire lattice planes. Orange circles superimposed on the images denote hexagonal sites while blue circles denote cubic sites. The observed direction, in hexagonal notation, is .

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The Journal of Physical Chemistry

Figure 3: XPS spectra for the nanowires, an epitaxial film of 3C SiC, and an epitaxial film of 4H SiC. (a) Cross-sectional SEM micrograph of nanowire ensemble. Scale bar is 2 μm. From Luna et al.13 (b) The valence band with a constant background subtracted, corresponding to the intensity at 0 eV BE. (c) The Si 2p region after Shirley background subtraction. and analyses were repeated on several nanowires, as provided in With low-loss EELS data, the first step is to remove the background Supplementary Information (Figure S1, S2 and Table S1). Altsignal from the zero-loss peak (ZLP) and radiative losses with a deconvolution routine. Next, the signal is fit to the form in Equation hough our measurements are not spatially resolved, we infer that smaller band gaps (2.5 – 2.6 eV) are associated with thicker cubic (1) derived and vindicated by Rafferty and Brown32: inclusions; larger band gaps (2.7 – 2.8 eV) are associated with thin𝑃𝑃 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 (𝐸𝐸) = 𝑦𝑦0 + 𝐴𝐴 ∗ (𝐸𝐸 − 𝐸𝐸g ) (1) ner cubic inclusions; and the largest gaps (3.3- 2.4 eV) are associated with hexagonal SiC24. It is to be noted that we do not observe where E is the energy loss of the electron, y 0 is the signal at E = any band gaps between 2.8 and 3.3 eV, as expected, since most E g , A is a fit scaling factor, Eg is the fit band gap, and P = 0.5 for types of stacking faults in hexagonal SiC are predicted to have a direct band gap transitions and 1.5 for indirect transitions, respecband gap between 2.4 and 2.8 eV24. To our knowledge, this is the tively. However, the application of this technique to semiconductor first time that STEM-EELS has been demonstrated to measure difnanomaterial characterization has been very limited33. Arenal, et ferences in band gap between pristine and defected regions of naal., compared the band gap in single-wall and multi-wall boron ninomaterials. tride nanotubes, and found no variation in band gap with wall thickThe fit band gap is sensitive to the method of ZLP removal. ness, as expected34. Wang, et al., were able to determine the band When the ZLP is removed by subtraction of a zero-loss peak recgap of their zinc oxide nanowires (20 – 100 nm) to be at the bulk orded in vacuum scaled to have the same intensity at loss = 0 eV, value35. Minella, et al., prepared 15-nm cubic silicon carbide nanthe fit band gap is 0.1 – 1.1 eV higher than the band gap obtained owires and fit the spectra to (1) with P = 0.5 for the direct transition, when the ZLP is removed by deconvolution. For instance, in nanfinding a direct band gap 0.9 eV greater than the bulk value. Given owire A, the band gap obtained when the ZLP is removed by subthat the direct band gap in 1-6 nm SiC nanodots was found to intraction is 3.8 eV, which is several tenths of an eV higher than any crease by only 0.5 eV from the bulk value using optical absorpSiC polytype. Unreasonable band gaps are obtained for several tion36, the large direct bandgap value reported for the nanowires37 other nanowires when subtraction is used (see Table S1). Minella may be an artifact of their background removal by subtraction30, or et al. also observed an abnormally high band gap in SiC using subthat indirect transitions were ignored, and the source was not montraction to remove the zero-loss peak from the EELS spectra37. ochromated35. Generally speaking, subtraction of a separately recorded peak in In our STEM-EELS experiments, we used a monochromated and vacuum should be avoided, because the shape of the low-loss reaberration-corrected transmission electron microscope on TEAM gion is not the same between spectra recorded in vacuum and spec0.5 at the National Center for Electron Microscopy (NCEM) with tra recorded from a sample because of the radiative losses that elec80 keV beam energy for EELS and 300 keV for imaging. The beam trons encounter when traveling through matter30. energy for the EELS experiments was chosen to reduce Cerenkov Conclusion: In summary, CVD-grown 4H SiC nanowires with losses. The resolution of the detector is 0.1 eV. The nanowires were a high density of stacking faults were characterized electronically prepared for analysis by sonicating in ethanol, drop casting on a as an ensemble by XPS and at the nanometer scale by STEMTEM grid, and gentle heating for 10 minutes. The zero-loss peak EELS. The XPS spectra are broadened because the stacking faults (ZLP) was removed using Thermo GRAMS Electronic Structure have a locally lower band gap, effectively forming a negativelyTools version G930. The signal was then fit to the functional form charged potential well that acts on emitted electrons. The band gap given by Rafferty and Brown32 in Equation 1. Determining the efdifference between hexagonal SiC regions and cubic stacking faults fective band gap by Equation (1) is preferred to using the onset of is clearly observed by electron energy loss spectroscopy in a scansignal as the band gap after deconvolution because the fit is less ning transmission electron microscope, which probes electronic sensitive to noise. A measurement was taken in an arbitrary spot structure with sub-nm resolution. The EELS results show that sevfor six nanowires, sampled from the same batch. eral-layer cubic phase inclusions in hexagonal silicon carbide loThe raw loss spectra, the spectra post-deconvolution, and the fit cally alter the electronic structure, in particular the band gap, comto Eq. (1) for two nanowires are shown in Figures 4a-b, and the pared to the inclusions’ effect on the polarizability tensor as measresiduals are shown below the respective figures in Figures 4c-d. ured by Raman spectroscopy13, which is only influenced by the loThe measurement on nanowire A yields Eg = 3.3 eV, identical to cal average ratio of cubic to hexagonal sites39. The outstanding the band gap of 4H-SiC within the resolution of the instrument. The agreement between the measured and predicted band gap values band gap of a hexagonal region is not affected by an adjacent stackdemonstrates the power of STEM-EELS to probe the electronic 24,38. A measurement on a separate but statistically identical ing fault structure of defects in other semiconductor nanomaterials. nanowire gives Eg = 2.5 eV, consistent with the band gap for a several-layer cubic inclusion in hexagonal SiC. The measurements



Figure 4: (a,b) Representative loss spectra for two of the nanowires studied in this work, the loss spectra post-deconvolution and the powerlaw fit (black line almost entirely covered by data) and (c,d) the respective residuals of the fit.

ASSOCIATED CONTENT Supporting Information The Supporting Information is available free of charge on the ACS Publications website. Raw data, signal after deconvolution, and fit for four other nanowires. Table including band gaps of nanowires by deconvolution and subtraction. (PDF)

AUTHOR INFORMATION Corresponding Author *[email protected]

Present Addresses †Lunet E. Luna currently resides at U.S. Naval Research Laboratory, Washington, DC 20375, United States of America

Author Contributions ‡These authors contributed equally.

Notes The authors declare no competing financial interests.

ACKNOWLEDGMENT The authors gratefully acknowledge the National Science Foundation Grant # 1207053 for support. L.E.L. thanks the University of California-Berkeley Chancellor’s Fellowship, NSF Graduate Research Fellowship, and the Gates Millennium Scholarship for additional support. V.R. acknowledges support from the Serbian Academy of Sciences and Art, under the project No. F141. The authors thank Professor Steven Saddow for the epitaxial 3C-SiC sample. Work at the Molecular Foundry was supported by the Office of Science, Office of Basic Energy Sciences, of the U. S. Department of Energy under Contract No. DE-AC02-05CH11231.

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