Journal
COMPUTATIONAL MATERIALS SCIENCE
Volume 46, Issue 1, Pages 124-127Publisher
ELSEVIER
DOI: 10.1016/j.commatsci.2009.02.013
Keywords
Artificial neural networks; Modeling; Electrical resistivity; Nanocrystalline semiconductors
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In this paper, a feed-forward multilayer perceptron artificial neural network model is used to simulate the electrical resistivity of nanocrystalline diluted magnetic semiconductors. Variations in the concentrations of Zn, Mn and temperature were used as the model inputs and the resulting electrical resistivity of the nanocrystalline semiconductors as the output of the model. Comparison between the model predictions and the experimental observations predicted a remarkable agreement between them. (C) 2009 Elsevier B.V. All rights reserved.
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