Characterization of light element impurities in gallium-nitride-phosphide by SIMS analysis

Characterization of light element impurities in gallium-nitride-phosphide by SIMS analysis

Applied Surface Science 231–232 (2004) 808–812 Characterization of light element impurities in gallium-nitride-phosphide by SIMS analysis R.C. Reedy*...

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Applied Surface Science 231–232 (2004) 808–812

Characterization of light element impurities in gallium-nitride-phosphide by SIMS analysis R.C. Reedy*, J.F. Geisz, A.J. Ptak, B.M. Keyes, W.K. Metzger National Renewable Energy Laboratory, MS 3215, 1617 Cole Blvd., Golden, CO 80401, USA Available online 20 April 2004

Abstract GaNP thin films grown by epitaxial processes show little or no carbon or oxygen incorporation when measured by secondary ion mass spectrometry. Accurate determination of impurity concentration is important for understanding the optical and electrical properties of this material. A new method for background subtraction is proposed, with the main assumption that the background contribution is inversely proportional to the secondary ion matrix signal. The total impurity concentration, i.e. the sum of real and background, is given by the inverse function. Efforts are taken to reduce background limits before background subtraction is performed. As the matrix signal increases, the background contribution becomes insignificant as the total impurity level approaches the real level. Multiple data points are obtained from several sputter rates. The real impurity level is obtained from the least-squares fit of the total impurity concentration versus matrix signal. Background subtraction via inverse function is an intuitive method that can be effectively used to remove gas-phase contributions in measurements of light elements in the thin films grown by epitaxial processes. # 2004 Elsevier B.V. All rights reserved. Keywords: SIMS; Background; Raster; Light element; GaNP

1. Introduction GaNxP1x and related materials show potential in the development of III–V multijunction solar cells that are grown lattice-matched to silicon [1]. Solar cells consisting of III–V materials are commonly grown by metalorganic chemical-vapor deposition (MOCVD) and by molecular-beam epitaxy (MBE). GaNP layers grown by MOCVD have shown poor electrical quality [2]. MBE grown GaNP layers have photoluminescence (PL) decay lifetimes measured to be an order of *

Corresponding author. Tel.: þ1-303-384-6589; fax: þ1-303-384-6604. E-mail address: [email protected] (R.C. Reedy).

magnitude longer than in the best films grown by MOCVD. The PL decay lifetime in GaNP is correlated with the impurity concentration, which implies a deeplevel complex detrimental to the electrical quality. Secondary ion mass spectrometry (SIMS) is frequently used in the fine-tuning of MOCVD growth conditions to reduce incorporation of light element impurities (H, C and O). SIMS measurements of comparable MBE grown GaNP have shown little or no impurity incorporation. However, these materials frequently challenge the limits of the technique. Procedures to reduce the light element background limits were employed. Various methods of background subtraction were tested to determine a suitable method for these particular experiments.

0169-4332/$ – see front matter # 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.apsusc.2004.03.080

R.C. Reedy et al. / Applied Surface Science 231–232 (2004) 808–812

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Quantified depth profiles of these samples will show only background limits under various sputter rates.

2. Methods of background subtraction Before background subtraction is performed, steps should be taken to reduce the contribution from residual gas-phase species. These steps include allowing the samples and holder to outgas sufficiently in the sample chamber, maintaining the best vacuum possible, using a cryogenic shroud, and sputtering as fast as possible allowed by sample characteristics. Additional reductions can be achieved on some instruments by energy filtering of the secondary ions and/or by using smaller contrast apertures [3]. 2.1. Background subtraction with control sample The least complicated method for background subtraction uses a control sample known to contain undetectable quantities of the impurity of interest. Ideally, the control sample is loaded in the same sample holder and is profiled under the same analytical conditions as the other samples. The background concentration from the control is subtracted from the other depth profiles. Care must be taken because background levels may decrease over the course of the day.

2.3. Background subtraction by linear extrapolation This is a method presented by Gnaser [7] that uses the relationship between the light elements present in the gas-phase of the SIMS instrument. The sample must be known not to contain at least one of these elements, or it may exist at a level much less than its gas-phase contribution. Concentration levels of impurities known to be in the sample (Y) and not to be in the sample (X) from multiple erosion rates are fit to the linear formula. From the linear least-squares fit, b is the real value of the impurity known to be in the film, and m is the relationship between the light element impurities. An error is introduced in this method when the impurity X exists in the sample. Solving for the Y intercept: Yreal ¼ Y  mðX þ Xreal Þ

(2)

The real value calculated by this method will appear low by an amount equal to mXreal. 2.4. Background subtraction via inverse function

2.2. Background subtraction with change in sputter rate This method is a comparison of impurity and matrix signals from more than one sputter rate. Variations of this method appear in [4–6]. The total impurity signal consists of background and real components. In the case of two sputter rates (raster sizes), the background is subtracted from the total signal to give the real impurity level by Ci ¼ RSF

Ii2  Ii1 Im2  Im1

(1)

where Ii2 and Ii1 are the secondary ion intensities of the impurity signal under large and small raster sizes, respectively, Im2 and Im1 are the secondary ion intensities of the matrix signal and RSF represents the relative sensitivity factor. A difference in impurity signal must be observed when changing sputter rate, i.e. when the real level in the sample is contributing noticeably to the total signal. If a sample contains a real impurity concentration much less than background, then (by this method) Ii2 ¼ Ii1 and, therefore, Ci ¼ 0.

We propose a new method for background subtraction, one that may have greater accuracy than the first two described above. This method can be applied when the real value in a sample has some influence on the total secondary ion signal. The main assumption is that the background contribution is inversely proportional to the matrix signal. We could also assume that it is inversely proportional to the sputter rate or primary-beam density. However, fewer errors are introduced in matrix signal measurement. The total impurity concentration, i.e. the sum of real and background is given by the inverse function: Ci ¼

k þ CiðrealÞ Im

(3)

As the matrix signal (Im) increases, the background contribution becomes insignificant as the total impurity level approaches the real level. Multiple data points are obtained from several sputter rates during one or several profiles. The real impurity level is obtained from the least-squares fit of the total impurity concentration versus matrix signal.

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3. Experimental conditions

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60 70 80 90 110 125 150

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0.4 0.6 0.8 Depth [microns]

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Fig. 1. Ion intensity variations with change in primary-beam rastered area (60 mm ! 150 mm): (a) O in GaNP/GaP; (b) C in GaNP/GaP.

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150 125 110 90 80 70 60

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(a)

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Fig. 1(a) and (b) exhibits raw data from multiple profiles of oxygen and carbon. As raster size is decreased, the impurity signal increases. Note the large

Carbon Concentration [atoms/cm ]

Oxygen signal [counts/s]

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4. Results and discussion

Oxygen Concentration [atoms/cm ]

The samples that inspired the inverse function method consisted of an 800 nm GaNP epitaxial layer grown on a GaP substrate. N composition ranged from 1 to 2 at.%. The substrate of these samples contained more C and O than the epilayer, a unique feature that allowed for background subtraction in both layers. The thickness limitation did not allow for multiple sputter rates per profile, therefore multiple profiles were taken at several raster sizes ranging from 60 mm  60 mm to 150 mm  150 mm. The SIMS measurements were conducted using a Cameca IMS-5F instrument with a Csþ micro-beam source. The 14.5 keV, 100 nA primary-beam was focused into a spot about 50 mm in diameter. A cryoshroud at liquid-nitrogen temperature was used, the sample chamber pressure was 2:6  108 Pa. Samples

(and holder) were allowed to outgas in the sample chamber for 2 days prior to analysis. Negative secondary ions were collected one element per profile on the electron multiplier. A 150 mm field of view and a 750 mm field aperture resulted in a 60 mm diameter analysis area. The 31 P matrix current was measured at the end of each profile on the Faraday cup. Profiles of 31 P through the epilayer into the substrate showed less than a 1% variation in intensity. Therefore, very little improvement in accuracy would be gained by point-bypoint quantification.

1.0 2.0 Depth [microns]

3.0

Fig. 2. Quantified depth profiles with change in primary-beam rastered area (150 mm ! 60 mm): (a) O in GaNP/GaP; (b) C in GaNP/GaP.

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4 2 Cepi-layer = -6.38E15 ± 1.6E15

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Oepi-layer = 1.50E16 ± 1.46E15

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Csubstrate= 3.52E16 ± 1.38E15 0.0

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Oxygen concentration [x 10 cm ]

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1.0 2.0 8 -1 Matrix Current (x 10 s )

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Fig. 4. Matrix signal (31 P) vs. impurity concentration with change in primary-beam rastered area: (a) C in GaNP epilayer; (b) C in GaP substrate.

total C signal. Therefore, we can only report that the carbon in this epilayer is less than the lowest measured value, 8:95  1015 atoms cm3.

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5. Summary

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Osubstrate = 1.34E17 ± 1.67E15

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Carbon concentration [x 10 cm ]

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Oxygen concentration [x 10 cm ]

change in the substrate levels compared to the epilayer. Very little change in carbon in the epilayer is the first indication that the real level of carbon is much less than the background level. Loss of depth resolution is more evident in the carbon profiles due to a large amount of carbon contamination at the epilayer/substrate interface. Fig. 2(a) and (b) is quantified depth profiles that show a decrease in total oxygen and carbon levels with decrease in rastered area. Average concentration values of oxygen and carbon in the epilayer and substrate are obtained from regions where the quantified signal is stable. These values are input into a spreadsheet program, in addition to the matrix signal for each profile. Data are then fitted to the inverse function and are presented in Figs. 3 and 4. Note that the Y intercept in Fig. 4(a) is negative. For this layer, the real C value must be much less than the

Carbon concentration [x 10 cm ]

R.C. Reedy et al. / Applied Surface Science 231–232 (2004) 808–812

1.0 2.0 3.0 8 -1 Matrix Current (x 10 s )

Fig. 3. Matrix signal (31 P) vs. impurity concentration with change in primary-beam rastered area: (a) O in GaNP epilayer; (b) O in GaP substrate.

Background subtraction via inverse function is an intuitive method that can be effectively used to remove gas-phase contributions in depth profiles of light elements. Efforts must be taken to reduce background limits before background subtraction is performed, because it is necessary for the real impurity signal to have some effect on the total signal. This method is especially useful in measuring light element contamination in thin films grown by epitaxial processes.

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Acknowledgements This work was funded by the US Department of Energy under Contract No. DE-AC36-99GO10377. References [1] J.F. Geisz, D.J. Friedman, in: Proceedings of the 29th IEEE Photovoltaic Specialists Conference, New Orleans, 2002, p. 864. [2] J.F. Geisz, R.C. Reedy, B.M. Keyes, W.K. Metzger, Unintentional carbon and hydrogen incorporation in GaNP grown by

[3] [4]

[5]

[6] [7]

metal-organic chemical-vapor deposition, J. Cryst. Growth 259 (2003) 223–231. H. Yamazaki, J. Vac. Sci. Technol. A 15 (1997) 5. G.J. Scilla, in: Secondary ion mass spectrometry, A. Benninghoven, R.J. Colton, D.S. Simons, H.W. Werner (Eds.), Proceedings of the SIMS V, Springer, Berlin, 1986, p. 115. A. Ishitani, K. Okuno, A. Karen, S. Karen, F. Soeda, in: Proceedings of the International Conference on Materials and Process Characterization for VLSI, 1988, p. 124. N. Fujiyama, A. Karen, D.B. Sams, R.S. Hockett, K. Shingu, N. Inoue, Appl. Surf. Sci. 203/204 (2003) 457–460. H. Gnaser, Appl. Phys. Lett. 79 (2001) 4.