Time evolution of self-assembled GaAs quantum rings grown by droplet epitaxy

Tung, Kar Hoo Patrick; Gao, Hongyi; Xiang, N.

doi:10.1016/j.jcrysgro.2013.02.029

Cited by 5 publications

(1 citation statement)

References 16 publications

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“…This sample is unusual as NHs are formed generally above 500 ℃ and under arsenic pressure of 10 -7 Torr. In sample 23, the NH was formed at low substrate temperature T substrate =300 ℃ and at medium arsenic pressure P as = 10 -6 Torr, after 1 minute of annealing at T=300 ℃ [25].…”

Section: 𝑄𝐷(%) =mentioning

confidence: 99%

Application of Self-Organizing Maps for Technological Support of Droplet Epitaxy

Ürmös¹,

Farkas²,

Farkas³

et al. 2017

ACTA POLYTECH HUNG

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The subject of this paper is the self-organized grouping of droplet epitaxial III-Vbased nano-structures. For the nano-structure grouping, our developed algorithm -called Quantum Structure Analyzer 1.0 -is used. The operation of this software is based on the principles of the Kohonen Self-Organizing Network. Here, three possibilities for nanostructured groupings are shown. On one hand, we examine the classification of nanostructures with Kohonen Self-Organizing Maps, on the other hand, fuzzy inference systems are applied for the same goal. In the case of the fuzzy methods two approaches are examined in detail. According to the first fuzzy inference approach, the shape factor is calculated from the size of nanostructures. According to the second fuzzy inference approach, the shape factor calculation is based on the controllable parameters of the growth process (eg. pressure and the temperature of the substrate).

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Section: 𝑄𝐷(%) =mentioning

confidence: 99%