Artificial neural network modeling of reduced glass transition temperature of glass forming alloys

Abstract

A model based on radial base function artificial neural network (RBFANN) was designed for the simulation and prediction of reduced glass transition temperature Trg of glass forming alloys. Its performance is examined by the influences of different kinds of alloys and elements, large and minor change of element content on the Trg, and composition dependence of Trg for La–Al–Ni ternary alloy system. Moreover, a group of Zr–Al–Ni–Cu bulk metallic glasses is designed by RBFANN. The values of Trg predicted by RBFANN agree well with the experimental values, indicating that the model is reliable and adequate.

Optimization of composition of as-cast chromium white cast iron based on wear-resistant performance

“…It is well-known that artificial neural network (ANN) can extract usable information from large quantity of discrete data with noise and is usable for resolving the highly non-linear and uncertain problems [14][15][16][17][18][19]. In general, there are two kinds of ANN, i.e., back-propagation artificial neural network (BPANN) and radial basis function artificial neural network (RBFANN), for being used to establish the model of the prediction.…”

Modeling glass-forming ability of bulk metallic glasses using computational intelligent techniques

“…In the last two decades, different families of amorphous alloys with excellent glass forming ability have been presented in the literature. For example, La-, Zr-, Pd-, Mg-, Cu-, Fe-, Ti-, Pr-, Co-, Ca-, Y-, Au-, Hfand Gd-based metallic glasses have shown superb glass-forming ability [2]. However, there exist no scientific rules or justified theories to design bulk metallic alloys with excellent GFA.…”

“…They developed various GFA criteria using thermal parameters which highly effect the GFA of metallic glasses [2]. These criteria are mostly based on three thermal characteristics of glass forming alloys i.e., glass transition temperature T g , the onset crystallization temperature T x , and liquidus temperature T l .…”

Glass forming ability, non-isothermal crystallization kinetics, and mechanical property of Zr61.5Al10.7Cu13.65Ni14.15 metallic glass

“…Many studies on glass formation, structure, physical and mechanical properties, and glass transition and crystallization process of glassy alloys have been conducted extensively [1][2][3][4][5][6][7][8][9][10][11]. Zr-based bulk metallic glasses can be produced by conventional casting process, leading to their successful applications as sporting goods, surgical instruments and electronic devices.…”