Statistical Analysis of Surface Reconstruction Domains on InAs Wetting Layer Preceding Quantum Dot Formation
© The Author(s) 2010
Received: 25 June 2010
Accepted: 10 August 2010
Published: 24 August 2010
Surface of an InAs wetting layer on GaAs(001) preceding InAs quantum dot (QD) formation was observed at 300°C with in situ scanning tunneling microscopy (STM). Domains of (1 × 3)/(2 × 3) and (2 × 4) surface reconstructions were located in the STM image. The density of each surface reconstruction domain was comparable to that of subsequently nucleated QD precursors. The distribution of the domains was statistically investigated in terms of spatial point patterns. It was found that the domains were distributed in an ordered pattern rather than a random pattern. It implied the possibility that QD nucleation sites are related to the surface reconstruction domains.
KeywordsInAs Wetting layer Quantum dot Surface reconstruction Spatial point pattern
Quantum dots (QDs) are potentially used for high-efficiency laser devices . It is crucial to control QD formation to arrange QDs with high uniformity and high density. Little is known, however, of the growth mechanism of QDs, in particular the surface reconstruction of a wetting layer (WL) and QD nucleation sites in Stranski-Krastanow (S-K) mode. Because the surface reconstruction changes microscopically and dynamically in the course of WL growth, an in situ scanning tunneling microscopy (STM) technique such as STMBE  is essential. Atomic-scale in situ observation of an InAs WL on a GaAs(001) substrate has revealed that the surface reconstruction of the InAs WL changes from c(4 × 4) to the mixture of (1 × 3)/(2 × 3) and (2 × 4) prior to QD formation . It is considered that such surface reconstructions form domains on InAs WL, and investigating their distribution will give a clue to understand a QD nucleation mechanism.
The distribution of reconstruction domains is characterized by spatial point patterns: a regular (ordered) pattern, a Poisson (random) pattern, and a clustered (aggregated) pattern . In a regular pattern, points are distributed uniformly. Voronoi tessellation, that is a polygonal decomposition of a space by perpendicular bisector lines among neighboring points, is often used in spatial point analysis. The standard deviation of Voronoi cell areas represents well the point patterns. For more precise analysis, the distance to the nearest neighbor point from an arbitrary position, r 1, is helpful [5–7]. Let p(t) denote the probability that r 1 occurs less than t. The nearest neighbor distance function p(t) is identical to the probability of plotting a random point within the union area of circles whose radii are t and centers are the points. Trend of p(t) represents the characteristics of spatial point patterns.
In this paper, we investigate the surface reconstruction domains on InAs WL preceding QD formation by using in situ STM observation and discuss their distribution using spatial point analysis.
A piece (11 × 13 × 0.6 mm3) of GaAs(001) crystal was used as a substrate. First, the surface was thermally cleaned to remove the oxide layer under 1 × 10−4 Pa of an arsenic atmosphere in an MBE growth chamber. Next, a GaAs buffer layer was grown on the surface by using MBE until atomically smooth surface was obtained. The substrate was annealed at 430°C for 0.5 h to confirm the formation of c(4 × 4) reconstruction with reflection high-energy electron diffraction (RHEED). An STM unit was transferred to the sample holder in the growth chamber. A flux of In was irradiated to the sample during STM observation. After 1.5 monolayer (ML) of InAs WL growth, the substrate temperature was decreased to 300°C, and the As4 flux was shut off.
Density, d, and standard deviation of Voronoi cell area, σVc of surface reconstruction domains
(1 × 3)/(2 × 3) Domains
1.6 × 1012
(2 × 4) Domains
2.5 × 1012
The standard deviation of Voronoi cells for each surface reconstruction domain is also listed in Table 1. The total area of the Voronoi cells that are not touching the edge of the view field was normalized to 1.0 for the calculation. A typical value of a Poisson pattern by scattering 50 random points was ∼0.4, whereas that of the surface reconstruction domains was ∼0.3.
In conclusion, (1 × 3)/(2 × 3) and (2 × 4) domains were located in the in situ STM image of 1.5 ML of InAs WL preceding QD nucleation. The densities of the reconstruction domains were similar to that of QD precursors just after nucleation. Spatial point analysis of the surface reconstruction domains revealed that the domains were distributed in an ordered pattern rather than a typical random pattern.
Authors are grateful to Mr. Minoru Yamamoto, Ms. Sayo Yamamoto, and Mr. Hisanori Iwata.
This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
- Arakawa Y, Sakaki H: Appl. Phys. Lett. 1982, 40: 939. COI number [1:CAS:528:DyaL38XkvVansrg%3D]; Bibcode number [1982ApPhL..40..939A] COI number [1:CAS:528:DyaL38XkvVansrg%3D]; Bibcode number [1982ApPhL..40..939A] 10.1063/1.92959View ArticleGoogle Scholar
- Tsukamoto S, Koguchi N: J. Cryst. Growth. 1999,201(202):118. Bibcode number [1999JCrGr.201..118T] Bibcode number [1999JCrGr.201..118T] 10.1016/S0022-0248(98)01304-9View ArticleGoogle Scholar
- Tsukamoto S, Honma T, Bell GR, Ishii A, Arakawa Y: Small. 2006, 2: 386. COI number [1:CAS:528:DC%2BD28Xhs1aqsLs%3D] COI number [1:CAS:528:DC%2BD28Xhs1aqsLs%3D] 10.1002/smll.200500339View ArticleGoogle Scholar
- Diggle PJ: Statistical Analysis of Spatial Point Patterns. Oxford University Press Inc., New York; 2003.Google Scholar
- Tanemura M, Ogata Y: Suuri Kagaku (Math. Sci.). 1981, 213: 11. in Japanese in JapaneseGoogle Scholar
- Ogata Y, Tanemura M: Ann. Inst. Stat. Math.. 1981, 33: 315. 10.1007/BF02480944View ArticleGoogle Scholar
- Baddeley A, Gill RG: Ann. Stat.. 1997,25(1):263. 10.1214/aos/1034276629View ArticleGoogle Scholar
- Rasband WJ, :ImageJ. US National Institutes of Health, Bethesda, MD; 1997–2009. [http://rsb.info.nih.gov/ij/]Google Scholar
- Abramoff MD, Magelhaes PJ, Ram SJ: Biophotonics Int. 2004,11(7):36.Google Scholar