An experimental and computational analysis of a MOCVD process for the growth of Al films using DMEAA

An experimental and computational analysis of a MOCVD process for the growth of Al films using DMEAA

The analysis of a metal-organic chemical vapor deposition (MOCVD) process is performed by combining computational fluid dynamics (CFD) simulations and experimental measurements. The analysis is applied to a vertical, cold-wall reactor, where aluminum coatings are grown from dimethylethylamine alane...

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Bibliographic Details
Published in:Surface & coatings technology Vol. 201; no. 22; pp. 8868 - 8872
Main Authors: Xenidou, T.C., Boudouvis, A.G., Markatos, N.C., Samélor, D., Senocq, F., PrudHomme, N., Vahlas, C.
Format: Journal Article Conference Proceeding
Language:English
Published: Lausanne Elsevier B.V 25-09-2007
Elsevier
Subjects:
Aluminum
Chemical Sciences
Chemical vapor deposition (including plasma-enhanced cvd, mocvd, etc.)
Computational fluid dynamics
Cross-disciplinary physics: materials science; rheology
DMEAA
Exact sciences and technology
Material chemistry
Materials science
Methods of deposition of films and coatings; film growth and epitaxy
MOCVD process
Physics
Computational fluid dynamics
Aluminum
DMEAA
MOCVD process
CVD
Manufacturing processes
Fluid dynamics
Growth
Surface treatments
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Summary:The analysis of a metal-organic chemical vapor deposition (MOCVD) process is performed by combining computational fluid dynamics (CFD) simulations and experimental measurements. The analysis is applied to a vertical, cold-wall reactor, where aluminum coatings are grown from dimethylethylamine alane (DMEAA), under low-pressure conditions. A two-dimensional model, based on the finite-volume method, is developed to predict the thermal and hydrodynamic characteristics of the flow within the MOCVD reactor, and the simulation results are compared with experimental data. It is shown that the computational predictions of the growth rates are in fair agreement with the experimental measurements.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0257-8972
1879-3347
DOI:10.1016/j.surfcoat.2007.04.080