Journal
ACTA CRYSTALLOGRAPHICA SECTION C-STRUCTURAL CHEMISTRY
Volume 70, Issue -, Pages 76-84Publisher
INT UNION CRYSTALLOGRAPHY
DOI: 10.1107/S2053229613027861
Keywords
computational materials discovery; hafnia-based oxides; dielectric materials
Categories
Funding
- Research Fund of the State Key Laboratory of Solidification Processing of NWPU [65-TP-2011, 83-TZ-2013]
- Basic Research Foundation of NWPU [JCY20130114]
- Natural Science Foundation of China [51372203, 51332004]
- National Science Foundation [EAR-1114313, DMR-1231586]
- DARPA [W31P4Q1310005, W31P4Q1210008]
- Government of the Russian Federation [14.A12.31.0003]
- Foreign Talents Introduction and Academic Exchange Program [B08040]
- Division Of Materials Research
- Direct For Mathematical & Physical Scien [1231586] Funding Source: National Science Foundation
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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 a fitness function in conjunction with first-principles calculations and the 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 of which 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 for discovering novel high-k dielectrics with both fixed and variable compositions, and will speed up the process of materials discovery.
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