Computational Modeling of Magnetic Properties and Glass Forming Ability of Bulk Amorphous Materials

• Authors: M. Kabaer , H. Ovalioglu , I. Kucuk
• Languages of publication: EN

Abstracts

EN

A model based on artificial neural network was designed for the simulation and estimation of glass forming ability parameters and saturation magnetization and coercivity of bulk glassy alloys. Its performance is evaluated by the influences of different kinds of alloys and elements on the glass forming ability and magnetic properties. The values of glass forming ability parameters and saturation magnetization and coercivity values estimated by artificial neural network agree well with the experimental values, indicating that the model is reliable and adequate.

Keywords

EN

64.70.pe; 84.35.+i; 75.50.Vv; 75.50.Kj

Discipline

• 84.35.+i: Neural networks(for optical neural networks, see 42.79.Ta; see also 07.05.Mh Neural networks, fuzzy logic, artificial intelligence in computers in experimental physics; 87.18.Sn in biological complexity)
• 75.50.Vv: High coercivity materials
• 75.50.Kj: Amorphous and quasicrystalline magnetic materials
• 64.70.pe: Metallic glasses

• Journal: Acta Physica Polonica A
• Year: 2010
• Volume: 118
• Issue: 5
• Pages: 827-828

Dates

published

2010-11

Contributors

author

M. Kabaer

• Physics Department, Faculty of Arts and Sciences, Uludag University, Gorukle Campus 16059, Bursa, Turkey

author

H. Ovalioglu

• Physics Department, Faculty of Arts and Sciences, Uludag University, Gorukle Campus 16059, Bursa, Turkey

author

I. Kucuk

• Physics Department, Faculty of Arts and Sciences, Uludag University, Gorukle Campus 16059, Bursa, Turkey

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Identifiers

DOI

10.12693/APhysPolA.118.827