Open-Source Tool for Engineering New Substances Developed by PSC Scientist and Colleagues

MuST, a new, open-source supercomputing code, radically reduces the complexity of simulating complex materials, promising predictions of the properties of samples large enough to be relevant to the real world more quickly, according to Yang Wang, senior computational scientist at PSC, in his presentation at the February 2021 XSEDE ECSS Symposium. MuST—named for the multiple scattering theory on which it’s based—uses density function theory (DFT) for ab initio investigation of disordered materials. In other words, predicting materials’ properties from first principles.

MuST takes advantage of locally self-consistent multiple scattering theory (LSMS) to simplify the problem of calculating the environment of a given atom surrounded by a complex and often disordered mixture of other atoms. Using a combination of the Korringa-Kohn-Rostoker and coherent potential approximation methods, MuST reduces this complexity. Instead of scaling to the third power, which is typical of DFT methods, it scales to the number of atoms. This makes MuST unique among such methods.

Using the KKR-CPA method, the MuST software converts the complex surroundings of an atom in a random alloy (brass, an alloy of copper (red) and zinc (blue), in this case) to an “effective medium” that averages the properties of the surrounding atoms (orange).

Initial work with the software has produced results as good as those of gold-standard methods that require much more computing power. MuST also goes beyond the reach of those methods when large numbers of atoms (thousands or more) are involved. Two goals for the future are incorporating the LSMS method with typical medium embedding to allow for capturing the metal-insulator transition phenomena driven by disorder in quantum materials, and integrating the Kubo-Greenwood formula into the package. This will enable the investigation of electronic transport in disordered structures—the sequential movement of electrons through a material. This phenomenon affects its properties and underlies important chemical processes like photosynthesis. You can watch Wang’s ECSS Symposium here. Scientists can download the program—and join the team to develop MuST—here.

The product of an international collaboration of PSC with the Oak Ridge National Laboratory, Universität Augsburg University, University of Chinese Academy of Sciences, Louisiana State University and Middle Tennessee State University, MuST was funded by the NSF’s Cyberinfrastructure for Sustained Scientific Innovation program and developed with the help of the Extended Collaborative Support Service (ECSS) of the NSF’s XSEDE cyberecosystem of supercomputing resources, in which PSC is a leading member.