Numerical simulation of InGaSb crystals growth under microgravity onboard the international space station

Jin, Xin; Mirsandi, H.; Yamamoto, Takuya; Takagi, Yasunari; Okano, Yasunori; Inatomi, Yuko; Hayakawa, Y.; Dost, S.

doi:10.7567/jjapcp.4.011107

Proc. 14th Int. Conf. On Global Research and Education, Inter-Academia 2015 2016

DOI: 10.7567/jjapcp.4.011107

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Numerical simulation of InGaSb crystals growth under microgravity onboard the international space station

Xin Jin¹,

H. Mirsandi²,

Takuya Yamamoto³

et al.

Abstract: In x Ga 1-x Sb bulk crystal was grown using a GaSb(seed)/InSb/GaSb(feed) sandwich-structured system onboard the International Space Station (ISS). In order to investigate the transport phenomena especially in terms of interface shapes and dissolution heights, the dissolution process was simulated under a micro-gravity level of the ISS. Simulation results showed that the seed/melt interface was concave towards the seed due to the temperature distribution of the system. This prediction is in good agreement with … Show more

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2022

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Control of growth interface shape during InGaSb growth by vertical gradient freezing under microgravity, and optimization using machine learning

Ghritli¹,

Okano²,

Inatomi³

et al. 2022

Jpn. J. Appl. Phys.

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Growth of high quality InGaSb crystals by Vertical Gradient Freezing (VGF) under microgravity was numerically simulated. Machine learning tools were used to optimize the growth conditions. The study focuses on controlling the growth interface shape which directly affects the quality and homogeneity of the grown crystals. Initially, Bayesian optimization was utilized to search for the most favorable growth conditions that promote a desirable flatter growth interface shape. Afterwards, a reinforcement learning model was developed. The system was subjected to a lower temperature gradient near the feed crystal and to crucible rotation with a rate ranging according to the obtained optimal strategy. Results showed that the interface deformation is considerably reduced, and a flatter growth interface could be maintained. The growth rate and solute concentration uniformity were also improved. This adaptive control recipe proves to hold a great potential in the continuous and rapid optimization of other crystal growth processes.

show abstract

Control of growth interface shape during InGaSb growth by vertical gradient freezing under microgravity, and optimization using machine learning

Ghritli¹,

Okano²,

Inatomi³

et al. 2022

Jpn. J. Appl. Phys.

Self Cite

View full text Add to dashboard Cite

show abstract

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Numerical simulation of InGaSb crystals growth under microgravity onboard the international space station

Cited by 1 publication

References 12 publications

Control of growth interface shape during InGaSb growth by vertical gradient freezing under microgravity, and optimization using machine learning

Control of growth interface shape during InGaSb growth by vertical gradient freezing under microgravity, and optimization using machine learning

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