Dynamic analysis of rapid-melting growth using SiGe on insulator

Thin Solid Films 557 (2014) 125–128

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Dynamic analysis of rapid-melting growth using SiGe on insulator Ryo Matsumura a,⁎, Yuki Tojo a, Masashi Kurosawa a,b,1, Taizoh Sadoh a, Masanobu Miyao a a b

Department of Electronics, Kyushu University, 744 Motooka, Fukuoka 819-0395, Japan JSPS Research Fellow, 5-3-1 Kojimachi, Chiyoda-ku, Tokyo 102-0083, Japan

a r t i c l e

i n f o

Available online 12 September 2013 Keywords: SiGe-on-insulator Rapid-melting growth Lateral epitaxy Si segregation

a b s t r a c t Dynamics in rapid-melting growth are analyzed by using Si-segregation phenomena in SiGe-on-insulator (SGOI). To clarify growth-stream and growth-velocity, SiGe profiles in SGOI network and stripe structures are investigated. Based on 2-dimensional Si-concentration mapping for SGOI network, visualization of routes of growth fronts becomes possible. In addition, analysis of Si concentration profiles in SGOI stripes enables evaluation of growth velocity. It is clarified that growth velocity increases by 15 times with increasing growth distance for SGOI stripe with 500 μm length. These techniques are useful to understand detailed kinetics in rapid-melting growth. © 2013 Elsevier B.V. All rights reserved.

1. Introduction In order to break through the scaling limit of Si metal-oxidesemiconductor field-effect transistor performance, various functional devices enabling ultrahigh speed operation, ultralow power dissipation, and optical-, and spintronic-functionalities should be integrated on Si-platform [1–5]. SiGe-on-insulator (SGOI) structures are big candidates for this purpose, because they enable formation of high-carriermobility channel for advanced transistors [1–3]. In addition, SGOI structures provide buffer layers for epitaxial growth of optical- and spintronic-materials [4,5]. We previously developed SiGe-mixing-triggered rapid-melting growth, which achieved defect-free single-crystal Ge-on-insulator (GOI) stripes [6–9]. Namely, our intensive efforts in this field significantly improved this technique [10–15], which achieved high-quality giant GOI stripes (~1 cm) [14]. Moreover, we realized GOI network structures by using this technique [12,13]. In such complex network structures, routes of growth stream initiated from seeding regions have not been clarified. In addition, growth velocity during the melt-back process has not been revealed. Clarification of such information is essential to comprehensive understanding of rapid-melting growth. Recently, we applied this rapid-melting growth to crystallization of a-SiGe stripes on insulator [16–18]. This achieved SGOI stripes having laterally graded Si concentration profiles, generated by Si segregation during the melt-back growth [16–18]. Growth experiments under a wide range of stripe lengths (10–500 μm) revealed that the shapes of the Si concentration profiles were classified into two groups, depending on the stripe length [17]. Namely, universal laterally-graded SiGe-

⁎ Corresponding author: Tel.: +81 92 802 3737; fax: +81 92 802 3724. E-mail address: [email protected] (R. Matsumura). 1 Present address: Graduate School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan. 0040-6090/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.tsf.2013.08.129

profiles obeying Scheil equation are obtained for all samples with short stripe length (≤200 μm) (group I). For samples with long stripe lengths (≥300 μm), anomalous two-step-falling profiles are obtained (group II). Here, these SiGe profiles depended on the cooling rate, and an important role of growth velocity in segregation dynamics was indicated [17]. Such results trigger an idea to clarify the growth stream and growth velocity during the melt-back process by analyzing SiGe profiles in groups I and II, respectively. In the present study, we examine Si concentration profiles in SGOI network structures and long SGOI stripes. Visualization of growth front routes becomes possible by tracing the Si concentration profiles. In addition, growth velocity is quantitatively evaluated as a function of the growth distance through analysis of the anomalous two-step-falling Si-concentration profiles. 2. Experimental procedure In the experiment, Si (100) substrates (600 μm thickness) covered with Si3N4 films (100 nm thickness) were used. These films were patterned using dry etching to form seeding areas (20 × 25 μm2). Subsequently, a-Si0.15Ge0.85 layers (100 nm thickness) were deposited by the molecular-beam deposition system at a base pressure of 7 × 10−8 Pa. They were patterned into narrow stripes (3 μm width) and mesh shape. The sample structures are schematically shown in Fig. 1(a) and (b). The stripes with 100 μm length have double Si-seeds [Fig. 1(a)], while the mesh-structures and the stripes with 300–500 μm length have a single Si-seed [Fig. 1(b)]. Then, capping films of SiO2 (800 nm thickness) were deposited by RF magnetron sputtering at room temperature to suppress the agglomeration of SiGe during the melt-back process. Finally, the samples were heat-treated at 1200 °C (1 s) in N2 ambient using rapid-thermal annealing (RTA), where the cooling-rate after annealing was 17 °C/s. The sample temperatures during annealing were monitored by a thermo-couple contacted to the back-side of the samples.

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a)

the SiGe profiles in stripe structures without coalescence of growth fronts [17], those with coalescence have not been clarified. Thus, effects of coalescence on SiGe segregation should be examined. For this purpose, we employ the stripes having double Si-seeds, as shown in Fig. 1(a). A Nomarski micrograph of a sample after RTA is shown in Fig. 2(a). The sample surface is very smooth, and we cannot recognize a coalescence region of two growth fronts initiated from both-side Si-seeds. To reveal the lateral distributions of Si atoms along the growth direction, we performed micro-probe Raman spectroscopy measurements. Typical Raman spectra were obtained at two different positions (i) and (ii) are shown in Fig. 2(b). Raman peaks due to Ge\Ge, Si\Ge, and Si\Si bonding in c-SiGe are clearly observed in spectra (i) obtained near the seed. On the other hand, the Si\Ge and Si\Si peaks are not observed in spectra (ii) obtained in the meddle region of the stripe. From the intensities of such Ge\Ge and Si\Ge peaks, the Si concentration was evaluated using the equation proposed by Mooney et al. [19] The Si concentration profile in the double-seed SGOI is shown by circles in Fig. 2(c). Si concentrations are ~45% near the both seeding areas and decrease with increasing distance from seed, reaching ~0% at the middle of the stripe. When the molten Si0.15Ge0.85 layer cools down, it reaches to liquidus-curve at 1100 °C by judging from Si\Ge phase-diagram [20]. Consequently, solid Si0.45Ge0.55 is produced in the molten region. With

<110> Si0.15Ge0.85 Si3N4 Si(100)-sub. 100 µm 3 µm

b)

<110> Si0.15Ge0.85 Si3N4 Si(100)-sub.

10 10µµmm

SiGe SiGe 3 µm

300 - 500 µm

Fig. 1. Schematic sample structures having double Si-seeds (a) and single Si-seed (b).

To evaluate Si concentration in grown layers, micro-probe Raman spectroscopy measurements (spot diameter: 1 μm, excitation laser wavelength: 532 nm) were performed using a monochromator (HR 640, HORIBA).

a)

Route 1 3. Results and discussion 3.1. Visualization of growth-stream

Route 2

In rapid-melting growth of complex network structures, coalescence of two growth fronts inevitably occurs. Although we previously clarified

(i)

10 µm

(ii)

c)

Si Concentration (%)

Si

SiGe

Ge-Ge

Si-sub.

Si-Ge Si-Si

((i)) (ii) 300

400

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30 20

Si-sub. seed

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0

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single-seed 50 µm [15]

20

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Raman shift (cm-1)

double-seed 100 µm

40

b) Si Concentration (%)

b)

Intensity (arb. units)

Si

Growth Collision

Si Concentration (%)

a)

A

20

40

60

Position (µm)

A

Route 2

40

Collision

30

Growth

20

Growth

10 0

0 0

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100

Position (µm) Fig. 2. Nomarski image (a), Raman spectra (b), and Si concentration profile (c) in grown SGOI stripe (100 μm length) having double Si seeds. The data for single-seed stripe (50 μm length) are also shown in (c).

0

5

10

Position (µm) Fig. 3. Nomarski image (a), and Si concentration profiles [(b),(c)] of SGOI network structure. Si concentration profiles along Routes 1 and 2, indicated in (a), are shown in (b) and (c), respectively.

R. Matsumura et al. / Thin Solid Films 557 (2014) 125–128

Si Concentration (%) 0

10

20

30

40

Si-sub. seed

10 µm

Fig. 4. Si concentration mapping for SGOI network structure.

cooling, the solidification continues along the solidus-curve of the phase-diagram. This well explains the profiles of decreasing curves from the peak concentration of 45%. These results indicate that the solidification of molten SiGe goes through along the thermal-equilibrium process. Since Si concentration decreases with increasing growth distance by segregation, the minimum Si concentration at ~50 μm suggests that coalescence of two growth fronts occurred there. The Si concentration profile for a single-seed stripe (50 μm length) is also shown by triangles in Fig. 2(c), which is replotted from our previous report [17]. Interestingly, the profile shape for the single-seed stripe (50 μm length) well agrees with that for the half of the double-seed stripe (100 μm length). This suggests that the SiGe profiles in doubleseed stripes can be expressed by Scheil equation of the conventional segregation theory [21].  xk−1 ; C S ðxÞ ¼ k  C 0 1− L

ð1Þ

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depend on the composition in mixed materials [22], k is treated as a fitting parameter in our calculation considering the Si concentration dependence [17]. The obtained values of k agreed with the theoretical ones calculated from the phase diagram [17]. The calculated profile obtained by fitting is shown by the solid curve in Fig. 2(c), which shows a good agreement with the experimental data. Consequently, it is found that SiGe profiles expressed by Scheil equation are obtained even for the stripes having the coalescence region of two growth fronts. This is an important finding to analyze the routes of growth fronts in complex network structures, where growth-front coalescence inevitably occurs. We investigate routes of growth fronts in SGOI network structures obtained by RTA of a-SiGe layers, as shown in Fig. 1(b). A typical Nomarski micrograph of a grown layer is shown in Fig. 3(a), where no agglomeration or breaking is observed. The Si concentration profiles were evaluated by micro-probe Raman spectroscopy. The results obtained along arrows indicated in Fig. 3(a) are shown in Fig. 3(b) and (c). For Route 1, the Si concentration decreases monotonically, which indicates that the growth front moved from the Si seed along Route 1 without any collisions. On the other hand, for Route 2, the Si concentrations show a minimum at ~6 μm in Fig. 3(c). This indicates that two growth fronts initiated from the Si seed coalesced around the middle of Route 2. Here, it is noted that the Si concentration profile shape in the network structure shown in Fig. 3(c) is different from that in the stripe shown in Fig. 2(c). This difference should be generated by the different changing features of the volume of the melting SiGe. Namely, for stripe structure, the volume of the melting SiGe linearly decreases with the distance from the seed. On the other hand, for network structures, the decrease rate of the volume of the melting SiGe increases with increasing distance from the seed, because the large areal SiGe network structure starts from a single seed and expands toward the edge. In order to visualize the routes of the growth stream in the network structures, 2-dimensional mapping of Si concentrations was carried out. The result is shown in Fig. 4. We can see the growth stream visually by tracing the color mapping of the Si concentrations. This visualization technique is very useful to analyze the routes of growth stream during the melt-back process. 3.2. Quantitative analysis of growth velocity

where C0 and CS are the Si concentrations before and after rapid-melting growth, respectively, k is the segregation coefficient of Si at solid/liquid interface, x is the distance from the seed, and L is a half the stripe length for double-seed stripes. Since the segregation coefficients are known to

The Si concentration profiles after growth of stripes (stripe length L: 300–500 μm) are shown in Fig. 5(a). Anomalous two-step falling features are observed, as we previously reported [17]. To reveal the

a)

b) Seed

10 1

0 0

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0.5 x2 / L

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Si Conc.

Solid (i)

L = 500 µm L = 300 µm 0 0

200

d

Liquid

Solid (ii)

Si Conc.

Si Concentration (%)

20 Si Conc. (%)

L = 400 µm 40

Liquid

400

Distance from Seed, x (µm) Fig. 5. Si profiles in SGOI stripes (L: 300–500 μm) as a function of distance from seed (x), fitted curve calculated using ke, (solid line) and k (dotted lines) (a), and expected behaviors of segregated Si atoms (b). Si profiles in the second falling regions as a function of x2/ΔL and fitted curves (dotted lines) calculated using k are shown in the inset of (a).

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15

function of x2/ΔL. The calculated profiles using Eq. (1) are also shown by the dotted lines in the figure. They agree well with the experiments. This analysis clarifies the physical meaning of ΔL. It is the critical length of molten-regions, where the segregated atoms can diffuse completely into the stripe-edge forming uniform distribution, as shown as (ii) in Fig. 5(a). In order to evaluate the growth velocity, we analyze the effective segregation coefficient ke. The values of ke obtained for all samples are summarized as a function of distance from seed x in Fig. 6. From these ke values, we evaluated the growth velocity R, based on Eq. (2). Here, the values of R were normalized with that nearest to the seed. The results are shown in Fig. 6. Interestingly, the growth velocity increases with increasing growth distance and becomes 15 times as large as that nearest to the Si seed. This technique is very useful to analyze the growth velocity during the melt-back process.

300 µm 400 µm 500 µm

2

10

1

5

Growth Velocity (arb. units)

Effective Segregation Coeff., ke

L

0

0 200

0

400

4. Summary

Distance from Seed, x (µm) Fig. 6. Effective segregation coefficient ke and growth velocity as a function of distance from seed.

phenomena, let us discuss Si segregation phenomena during the rapidmelting growth. In the derivation of Scheil equation, i.e, Eq. (1), it is assumed that segregated Ge atoms completely diffuse into the whole molten regions, and the Si concentrations in the molten regions are uniform [21]. These conditions can be satisfied for short stripe length (≤200 μm) [17]. On the other hand, when the stripe length becomes long, Si atoms cannot distribute uniformly. Expected behaviors of Si atoms in this situation are schematically shown in Fig. 5(b). Long molten regions due to long stripe lengths (L) do not allow the complete diffusion of segregated Ge atoms into the stripe edge. Thus, the Si atoms distribute nonuniformly in the molten SiGe regions neighboring the solid/liquid interfaces. Such situations are illustrated as (i) in Fig. 5(b). Consequently, the effective segregation coefficient (ke) expressed by the following equation [23] should be used in Eq. (1) instead of the segregation coefficient k, ke ¼

k ; k þ ð1−kÞexpð−Rd=DÞ

ð2Þ

where R is the growth velocity, D is the diffusion constant, and d is the length of the boundary region with non-uniform distribution. The d value is analogous to the diffusion length of the segregated atoms in the molten region. The solid curve in Fig. 5(a) was obtained by fitting of the modified Scheil equation using the effective segregation coefficient ke [Eq. (2)] to the experimental data in the first falling regions. It is found that fitting is very good. On the other hand, when the melt-back growth approaches to the stripe-edge, segregated Ge atoms at the solid/liquid interface diffuse into the stripe edge completely. This is because the molten region becomes short enough to enable uniform distribution of segregated Ge atoms. This results in the uniform distribution of Si atoms, which is illustrated as (ii) in Fig. 5(b). In these situations, the Si concentration profiles should be expressed by the conventional Scheil equation as shown in Eq. (1). Here, we define ΔL as the lengths of secondary falling-regions, i.e., distance between the point where the Si concentration begins to show second-decrease and the stripe edge, and x2 as the distance measured from the beginning point of the secondary falling-curve (L − ΔL). Consequently, x2 can be expressed as [x − (L − ΔL)]. Si profiles in the secondary falling-regions are re-plotted in the inset of Fig. 5(a) as a

Dynamics of rapid-melting growth have been analyzed by using the Si segregation phenomena of SiGe mixed crystal. Visualization of routes of growth stream becomes possible by tracing the Si concentration profiles. Moreover, increase of growth velocity by 15 times during the meltback process has been revealed. This technique is very useful to understand detailed kinetics in rapid-melting growth. Acknowledgments The authors wish to thank Dr. I. Mizushima of Toshiba Corporation for stimulating discussions during the course of this study. M. K. wishes to thank JSPS research program for young scientists. A part of this work was supported by a Grant-in-Aid for Scientific Research from the Ministry of Education, Culture, Sport, Science, and Technology in Japan. References [1] M. Miyao, E. Murakami, H. Etoh, K. Nakagawa, A. Nishida, J. Cryst. Growth 111 (1991) 912. [2] K. Morii, T. Iwasaki, R. Nakane, M. Takenaka, S. Takagi, IEEE Electron Device Lett. 31 (2010) 1092. [3] T. Nishimura, C.H. Lee, T. Tabata, S.K. Wang, K. Nagashio, K. Kita, A. Toriumi, Appl. Phys. Express 4 (2011) 064201. [4] J. Liu, R. Camacho-Aguilera, J.T. Bessette, X. Sun, X. Wang, Y. Cai, L.C. Kimerling, J. Michel, Thin Solid Films 520 (2012) 3354. [5] K. Hamaya, Y. Ando, T. Sadoh, M. Miyao, Jpn. J. Appl. Phys. 50 (2011) 010101. [6] Y. Liu, M.D. Deal, D. Plummer, Appl. Phys. Lett. 84 (2004) 2563. [7] D.J. Tweet, J.J. Lee, J.S. Maa, S.T. Hsu, Appl. Phys. Lett. 87 (2005) 141908. [8] J. Feng, Y. Liu, P.B. Griffin, J.D. Plummer, IEEE Electron Device Lett. 27 (2006) 911. [9] T. Hashimoto, C. Yoshimoto, T. Hosoi, T. Shimura, H. Watanabe, Appl. Phys. Express 2 (2009) 066502. [10] M. Miyao, T. Tanaka, K. Toko, M. Tanaka, Appl. Phys. Express 2 (2009) 045503. [11] M. Miyao, K. Toko, T. Tanaka, T. Sadoh, Appl. Phys. Lett. 92 (2009) 022115. [12] K. Toko, Y. Ohta, T. Sakane, T. Sadoh, I. Mizushima, M. Miyao, Appl. Phys. Lett. 98 (2011) 042101. [13] I. Mizushima, K. Toko, Y. Ohta, T. Sakane, T. Sadoh, M. Miyao, Appl. Phys. Lett. 98 (2011) 182107. [14] K. Toko, Y. Ohta, T. Tanaka, T. Sadoh, M. Miyao, Appl. Phys. Lett. 99 (2011) 032103. [15] M. Kurosawa, N. Kawabata, T. Sadoh, M. Miyao, Appl. Phys. Lett. 100 (2012) 172107. [16] T. Tanaka, K. Toko, T. Sadoh, M. Miyao, Appl. Phys. Express 3 (2010) 031301. [17] R. Matsumura, Y. Tojo, M. Kurosawa, T. Sadoh, I. Mizushima, M. Miyao, Appl. Phys. Lett. 101 (2012) 241904. [18] Y. Tojo, R. Matsumura, H. Yokoyama, M. Kurosawa, K. Toko, T. Sadoh, M. Miyao, Appl. Phys. Lett. 102 (2013) 092102. [19] P.M. Mooney, F.H. Dacol, J.C. Tsang, J.O. Chu, Appl. Phys. Lett. 75 (1993) 2069. [20] T.B. Massalski, Binary Alloy Phase Diagrams, American Society for Metals, Ohio, 1986. [21] E. Scheil, Z. Metallkd. 34 (1942) 70. [22] J. Woodacre, D. Labrie, M. Saghir, J. Cryst. Growth 327 (2011) 35. [23] C.W. Pearce, in: S.M. Sze (Ed.), VLSI Technology, McGraw-Hill, New York, 1988, p. 20.