Annealing-Modulated Surface Reconstruction for Self-Assembly of High-Density Uniform InAs/GaAs Quantum Dots on Large Wafers Substrate

Nanomaterials (Basel). 2023 Jun 28;13(13):1959. doi: 10.3390/nano13131959.

Abstract

In this work, we developed pre-grown annealing to form β2 reconstruction sites among β or α (2 × 4) reconstruction phase to promote nucleation for high-density, size/wafer-uniform, photoluminescence (PL)-optimal InAs quantum dot (QD) growth on a large GaAs wafer. Using this, the QD density reached 580 (860) μm-2 at a room-temperature (T) spectral FWHM of 34 (41) meV at the wafer center (and surrounding) (high-rate low-T growth). The smallest FWHM reached 23.6 (24.9) meV at a density of 190 (260) μm-2 (low-rate high-T). The mediate rate formed uniform QDs in the traditional β phase, at a density of 320 (400) μm-2 and a spectral FWHM of 28 (34) meV, while size-diverse QDs formed in β2 at a spectral FWHM of 92 (68) meV and a density of 370 (440) μm-2. From atomic-force-microscope QD height distribution and T-dependent PL spectroscopy, it is found that compared to the dense QDs grown in β phase (mediate rate, 320 μm-2) with the most large dots (240 μm-2), the dense QDs grown in β2 phase (580 μm-2) show many small dots with inter-dot coupling in favor of unsaturated filling and high injection to large dots for PL. The controllable annealing (T, duration) forms β2 or β2-mixed α or β phase in favor of a wafer-uniform dot island and the faster T change enables optimal T for QD growth.

Keywords: T-dependent state population; arsenic influence; deposition; deposition amount; full width at half maximum; growth rate; growth temperature; in situ annealing; migration; nucleation; nucleation site; photoluminescence spectrum; quantum dot density; quantum dot size distribution; reconstruction phase; self-assembled quantum dots; surface arsenic.

Grants and funding

This research work was supported by the National Key Technologies R&D Program of China (grant No. 2018YFA0306101), the Science and Technology Program of Guangzhou (grant No. 202103030001), the Key-Area Research and Development Program of Guangdong Province (grant No. 2018B030329001), the National Natural Science Foundation of China (grant Nos. 62035017, 61505196), the Scientific Instrument Developing Project of Chinese Academy of Sciences (grant No. YJKYYQ20170032), and the Program of Beijing Academy of Quantum Information Sciences (grant No. Y18G01).