The Division of Materials Research and the Office of Cyberinfrastructure contribute funding to this CAREER award. This award supports computational and theoretical research and education aimed at improving our ability to predict phase diagrams of solid state alloys, based upon first-principles quantum mechanical calculations, without relying on experimental input. This project provides a firm conceptual framework and associated algorithms to model phenomena that commonly occur in technologically-relevant alloys, but that the field of alloy theory is currently poorly equipped to handle. The research has two thrusts:
1) Lattice instabilities. The well-established CALPHAD and cluster expansion formalisms are fundamentally based on the assumption that a set of well-defined lattices (e.g. bcc, fcc, hcp) remain at least metastable at all compositions. However, in numerous alloy systems (e.g. Ti-Al, Cu-Fe, etc.), some lattices are not even mechanically stable, thus impeding any attempts at calculating a proper free energy. This project handles this fundamental conceptual issue by suitably constraining the domain of integration traditionally employed to calculate free energies based on rigorous geometrical partitioning techniques, but without necessitating a full anharmonic treatment.
2) Novel compound prediction. While powerful methods (e.g. the cluster expansion) exist to model alloy ordering phenomena on a common underlying lattice, this project devises complementary methods that are applicable when this assumption is violated (notably, in Lave phases, sigma phases, etc.). The idea is to decompose the energy of an alloy system as a sum of atom cluster contributions. The proposed algorithm then attempts to re-assemble the lowest energy clusters, using combinatorial techniques, in search of low-energy crystal structures.
The proposed methods will be implemented in the PI's Alloy Theoretic Automated Toolkit (ATAT), a software package that already has an established user base. The educational components of this research activity include augmenting ATAT by a companion educational web site, which will provide tutorials and social networking tools focusing on thermodynamics and phase diagrams, as well as using ATAT in undergraduate and graduate classes to give students hands-on experience with materials design tools of the future. To promote diversity, this project will build upon the efforts of the MRSEC at Caltech in recruiting minority undergraduates from California State University, Los Angeles.
NON-TECHNICAL SUMMARY
The Division of Materials Research and the Office of Cyberinfrastructure contribute funding to this CAREER award. This award supports computational and theoretical research aimed at improving our ability to predict "phase diagrams". Phase diagrams are often called the "road maps of materials science", as they indicate which compounds form as a function of temperature and pressure, when different chemical elements are alloyed, thus providing crucial guidance in material design. This project focuses on prediction methods based on quantum mechanical calculations, without necessitating experimental input, a capability that is essential to enable the discovery of truly novel materials. The project provides a firm conceptual framework and associated algorithms to model phenomena that commonly occur in technologically-relevant alloys, but that the field of alloy theory is currently poorly equipped to handle.
The proposed methods will be implemented in the PI's Alloy Theoretic Automated Toolkit (ATAT), a software package that already has an established user base. The educational components of this research activity include augmenting ATAT by a companion educational web site, which will provide tutorials and social networking tools focusing on thermodynamics and phase diagrams, as well as using ATAT in undergraduate and graduate classes to give students hands-on experience with materials design tools of the future. To promote diversity, this project will build upon the efforts of the Materials Research Science and Engineering Center at Caltech in recruiting minority undergraduates from California State University, Los Angeles.
