TMF Otimization in VGF Crystal Growth of GaAs by Artificial Neural Networks and Gaussian Process Models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F17%3A00477799" target="_blank" >RIV/67985807:_____/17:00477799 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
TMF Otimization in VGF Crystal Growth of GaAs by Artificial Neural Networks and Gaussian Process Models
Original language description
In Vertical Gradient Freeze growth of GaAs, the solid-liquid interface shape and subsequently the crystal quality can be improved by forced convection via travelling magnetic fields (TMFs). At present, general methodology to identify the relation and optimize magnetic and crystal growth parameters doesn’t exist. In this study, artificial neural networks (ANN) and Gaussian process models (GP) were used to assess the complex nonlinear relationships among the parameters and to optimize TMF for the interface flattening. 2D CFD simulations provided data sets for ANN and GP. The first encouraging results were presented and the strengths and weaknesses of both mathematical methods discussed.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10302 - Condensed matter physics (including formerly solid state physics, supercond.)
Result continuities
Project
<a href="/en/project/GA17-01251S" target="_blank" >GA17-01251S: Metalearning for Extraction of Rules with Numerical Consequents</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Electrotechnologies for Material Processing
ISBN
978-3-80273-095-5
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
203-208
Publisher name
Vulkan
Place of publication
Hannover
Event location
Hannover
Event date
Jun 6, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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