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Artificial neural network modeling of reduced glass transition temperature of glass forming alloys
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10.1063/1.2899633
/content/aip/journal/apl/92/11/10.1063/1.2899633
http://aip.metastore.ingenta.com/content/aip/journal/apl/92/11/10.1063/1.2899633

Figures

Image of FIG. 1.
FIG. 1.

DSC curves of Zr-based BMGs developed by us at the heating rate of . (a) , (b) , (c) , (d) , and (e) .

Image of FIG. 2.
FIG. 2.

Simulated and experimental results for the influences of large and minor change of element’s content on reduced glass transition temperature, (a) to in , (b) Ti to in , (c) Cu to in , (d) Nb to in , (e) Mo to in , (f) Ta to in , and (g) Ag to in , respectively.

Image of FIG. 3.
FIG. 3.

Simulated and experimental results of the influences of different elements on reduced glass transition temperature.

Image of FIG. 4.
FIG. 4.

Composition dependence of reduced glass transition temperature simulated by RBFANN for La–Al–Ni ternary alloy system.

Tables

Generic image for table
Table I.

The glass transition temperature , onset melting temperature , predicted and experimental reduced glass transition temperature for Zr–Al–Ni–Cu BMGs developed by us.

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/content/aip/journal/apl/92/11/10.1063/1.2899633
2008-03-19
2014-04-24
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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Artificial neural network modeling of reduced glass transition temperature of glass forming alloys
http://aip.metastore.ingenta.com/content/aip/journal/apl/92/11/10.1063/1.2899633
10.1063/1.2899633
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