Evolutionary Optimization of Chemistry of Bulk Metallic Glasses

Abstract

Metallic glass is basically an alloy whose metallic species are “frozen” in amorphous glassy state rather than forming a standard crystalline structure. Metallic glasses have no grain boundaries and no dislocations and stacking faults. They are several times stronger than steel and considerably harder and more elastic. Formation of metallic glasses by extremely high cooling (~105 K/sec) of the melt was first accomplished in 1960s. The resulting metallic glass thickness was limited to extremely thin ribbons. In the 1990s, researchers formed new classes of metallic glasses in bulk. The bulk metallic glasses (BMGs) are composed of three or more metals in the alloy melt and a few diatomatous earth ingredients in order to lower the cooling rate. Cooling rates of the new alloys are from 100 K/s to 1 K/s. The possible thickness of these newer metallic glasses increased from micrometers to centimeters. One of the keys to lowering the cooling speed and creating larger specimens is that bulk metallic glasses should have ingredients with atomic species having large size and chemical differences. Thus, multiple thermo-mechanical properties and the cooling speed of bulk metallic glass alloys depend strongly on the concentrations of each of the chemical elements in a given alloy. The proposed methodology for accurately determining concentration of each of the important alloying elements is based on the use of a combination of a robust multiobjective optimization algorithm and on traditional experimentation. Specifically, the proposed alloy design method combines an advanced stochastic multi-objective evolutionary optimization algorithm based on self-adapting response surface methodology and a relatively very small data set of thermo-mechanical properties and the corresponding concentrations of alloying elements. During the iterative computational design procedure, new metallic glass alloys need to be manufactured and experimentally evaluated for their properties in order to continuously verify the accuracy of the entire design methodology. This metallic glass alloy design optimization method thus minimizes the need for costly and time-consuming experimental evaluations of new metallic glass alloys to fewer than 200 new alloys.