Evolutionary search for new high-k dielectric materials: methodology and applications to hafnia-based oxides
Abstract
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.
Keywords
Cite
@article{arxiv.1307.6358,
title = {Evolutionary search for new high-k dielectric materials: methodology and applications to hafnia-based oxides},
author = {Qingfeng Zeng and Artem R. Oganov and Andriy O. Lyakhov and Congwei Xie and Xiaodong Zhang and Jin Zhang and Qiang Zhu and Bingqing Wei and Ilya Grigorenko},
journal= {arXiv preprint arXiv:1307.6358},
year = {2013}
}