Artículos de revistas
Application of an Artificial Intelligence Technique to Improve Purification in the Zone Refining Process
Registro en:
Journal Of Electronic Materials. Springer, v. 39, n. 1, n. 49, n. 55, 2010.
0361-5235
WOS:000273402700009
10.1007/s11664-009-0947-4
Autor
Cheung, T
Cheung, N
Garcia, A
Institución
Resumen
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) A combined theoretical and experimental approach was undertaken to quantitatively determine the influence of a variable solute distribution coefficient, k, on impurity distribution in multipass purification by zone refining. Axial impurity profiles have been experimentally determined for a number of zone passes. It has been shown that the adoption of a variable-k approach in the simulation of impurity profiles during different zone passes is generally much closer to the experimental profiles than the usual adoption of a constant k. An artificial intelligence technique interacts with the numerical model to determine the best molten zone size in each pass in order to provide maximum purification. 39 1 49 55 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) FAEPEX-UNICAMP Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)