  High-k dielectric materials are important as gate oxides in microelectronics
and as potential dielectrics for capacitors. In order to enable computational
discovery of novel high-k dielectric materials, we propose a fitness model
(energy storage density) that includes the dielectric constant, bandgap, and
intrinsic breakdown field. This model, used as fitness function in conjunction
with first-principles calculations and global optimization evolutionary
algorithm USPEX, efficiently leads to practically important results. We found a
number of high-fitness structures of SiO2 and HfO2, some of which correspond to
known phases and some are new. The results allow us to propose characteristics
(genes) common to high-fitness structures - these are the coordination
polyhedra and their degree of distortion. Our variable-composition searches in
the HfO2-SiO2 system uncovered several high-fitness states. This hybrid
algorithm opens up a new avenue of discovering novel high-k dielectrics with
both fixed and variable compositions, and will speed up the process of
materials discovery.

Materials Science