Article ID Journal Published Year Pages File Type
1524946 Materials Chemistry and Physics 2011 10 Pages PDF
Abstract

A back-propagation artificial neural network (ANN) was established to predict the formation enthalpies of Al2X-type intermetallics as a function of some physical parameters. These physical parameters include the electronegativity difference, the electron density difference, the atomic size difference, and the electron–atom ratio (e/a). The values calculated by the ANN method agree with experiments well to typically within 10%, indicating that the well-trained back-propagation (BP) neural network is feasible, and can precisely predict the formation enthalpies of Al2X-type intermetallics. The method comparison based on the predicted formation enthalpies suggests that our ANN method is superior to Miedema's model. Some trends of formation enthalpies for Al2X-type intermetallics were also observed from the ANN.

Research highlights▶ An ANN was built to predict the formation enthalpies of Al2X-type intermetallics. ▶ The values predicted by the ANN agree with experiments well to typically within 10%. ▶ The method comparison suggests that our ANN method is superior to Miedema's model. ▶ Some trends of formation enthalpies for Al2X-type intermetallics were observed.

Related Topics
Physical Sciences and Engineering Materials Science Electronic, Optical and Magnetic Materials
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