Alejandro Díaz Ortiz –
Optimal Inversion and Materials Informatics

Rational design of molecular systems and solid-state materials relies on the knowledge of the effective potentials or interactions to tailor motifs with favorable properties. In a combinatorial high-throughput approach the task is, in principle, simple: To solve the Schrödinger equation for all viable conformations and combinations of a list of candidate components. In practice, however, this is unfeasible due the astronomical size of the chemical space (i.e., the set of all spatial and chemical conformations available to the system) that must be scanned to optimize a target property.

Constructing maps that relate structure to physical properties is at the core of rational design strategies. The cluster expansion is the method of choice to map the configurational dependence of many physical properties in crystalline systems, including formation enthalpies, Curie temperatures, and magnetic moments. Cluster expansions of first-principles density-functional databases in multicomponent systems are now used as a routine tool for the prediction of zero- and finite-temperature physical properties. The ability of producing large databases of various degrees of accuracy, i.e., high-throughput calculations, makes pertinent the analysis of error propagation during the inversion process. This is a very demanding task as both data and numerical noise have to be treated on equal footing.

We are addressing this information-theory problem by using an analysis that combines the variational and evolutionary approaches to cluster expansions together with high-throughput first-principles calculations of bulk and low-dimensional alloy systems (read our recent paper).


External collaborators:
Juan M. Sanchez, The University of Texas at Austin, USA
Gus L.W. Hart, Brigham Young University, USA
Stefano Curtarolo, Duke University, USA
Bjoern Arnold, Ulm University, Germany
Martin Friak, MPI für Eisenforschung, Düsseldorf, Germany