Computational Design and Performance Prediction of Creep-Resistant Ferritic Superalloys Email Page
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Performer: The University of Tennessee
Courtesy of Center for Nano-phase<br/>Materials Sciences at ORNL (DOE) -<br/>G. Song, Z. Sun, P. K. Liaw, Unpublished, UTK
Courtesy of Center for Nano-phase
Materials Sciences at ORNL (DOE) -
G. Song, Z. Sun, P. K. Liaw, Unpublished, UTK
Website: University of Tennessee
Award Number: FE0024054
Project Duration: 10/01/2014 – 09/30/2017
Total Award Value: $626,681
DOE Share: $500,000
Performer Share: $126,681
Technology Area: Coal Utilization Science
Key Technology: High Performance Materials
Location: Knoxville, Tennessee

Project Description

The objectives of this research are to (1) develop and integrate modern computational tools and algorithms, i.e., predictive first-principles calculations, computational-thermodynamic modeling, and meso-scale dislocation-dynamics simulations, to design high-temperature alloys for applications in fossil energy power plants; and (2) understand the processing-microstructure-property-performance links underlying the creep behavior of novel ferritic alloys strengthened by hierarchical coherent B2/L21 precipitates.

Project Benefits

The proposed research will advance computational modeling used in the accelerated design of high-temperature alloys. The methods developed to compute thermodynamic and kinetic quantities from first-principles calculations will be applicable to other alloy systems. Quantitative creep modeling will lay a foundation for designing a wide range of advanced precipitation-strengthened alloys. It is also expected that the project will develop a novel creep-resistant hierarchical ferritic superalloy for applications in advanced steam-turbine systems. Also, Ph.D. students and research associates will be trained in the integration of state-of-the-art computational and experimental methods that will form the framework for modern alloy design.

Contact Information

Federal Project Manager Richard Dunst:
Technology Manager Briggs White:
Principal Investigator Peter Liaw:


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