Computational materials science experts at the Ames Laboratory of the U.S. Department of Energy and their collaborators have determined the source of a material called high-entropy alloys and a method for adjusting strength and ductility. This discovery may help the power generation and aviation industries to develop more efficient engines, reducing fuel consumption and carbon emissions.
High-entropy alloys are composed of four or more different elements and usually have many desirable characteristics-they are light weight, high strength, strong ductility, and corrosion resistance. They are ideal for energy power generation applications in extreme environments such as aviation. However, since the elements constituting the alloy and their relative proportions may vary, it is difficult and time-consuming to test the absolute number of possible combinations and their characteristics through experiments.
The team led by Ames Lab used quantum mechanics modeling methods to computationally discover and predict the atomic structure of the particularly promising HEA system FexMn80−xCo10Cr10, and how the transformations and defects in this structure lead to stronger and more ductile structures s material.
"When we can determine these transformations and their effects on material properties, we can predict its strength, and we can consciously design the strength and ductility for these very complex alloys," said Du, a scientist in the Ames Laboratory. Ann Johnson said. These predictions were then confirmed through experiments, using advanced electron microscopy to study single crystal samples, including selective areas and electron backscatter diffraction. It is worth noting that this method is applicable to any multi-element composite alloy.
Johnson said that theory-oriented computational design has great prospects in optimizing the properties of these materials, making them stronger, more malleable, and in many cases cheaper. These performance improvements can have a significant impact on applications in extreme environments, such as turbine engines used in power generation or aviation, which work more efficiently at higher temperatures.
"Using this predictive method, we have been able to speed up our alloy development schedule by more than 50% and have demonstrated a 10-20% increase in operating temperature," Johnson said. He said that as far as aviation is concerned, this can translate into cost savings of hundreds of millions of dollars and significantly reduce greenhouse gas emissions.
-This press release was originally published on the Ames Laboratory website
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