Suppr超能文献

Causes of ferroelectricity in HfO-based thin films: an ab initio perspective.

作者信息

Dogan Mehmet, Gong Nanbo, Ma Tso-Ping, Ismail-Beigi Sohrab

机构信息

Center for Research on Interface Structures and Phenomena, Yale University, New Haven, Connecticut 06520, USA and Department of Physics, Yale University, New Haven, Connecticut 06520, USA and Department of Physics, University of California, Berkeley, California 94720, USA.

Center for Research on Interface Structures and Phenomena, Yale University, New Haven, Connecticut 06520, USA and Department of Electrical Engineering, Yale University, New Haven, Connecticut 06520, USA.

出版信息

Phys Chem Chem Phys. 2019 Jun 21;21(23):12150-12162. doi: 10.1039/c9cp01880h. Epub 2019 May 30.

Abstract

We present a comprehensive first principles study of doped hafnia in order to understand the formation of ferroelectric orthorhombic[001] grains. Assuming that tetragonal grains are present during the early stages of growth, matching plane analysis shows that tetragonal[100] grains can transform into orthorhombic[001] during thermal annealing when they are laterally confined by other grains. We show that among 0%, 2% and 4% Si doping, 4% doping provides the best conditions for the tetragonal[100] → orthorhombic[001] transformation. This also holds for Al doping. We also show that for HfZrO, where x = 1.00, 0.75, 0.50, 0.25, and 0.00, the value x = 0.50 provides the most favorable conditions for the desired transformation. In order for this transformation to be preferred over the tetragonal[100] → monoclinic[100] transformation, out-of-plane confinement also needs to be present, as supplied by a top electrode. Our findings illuminate the mechanism that causes ferroelectricity in hafnia-based films and provide an explanation for common experimental observations for the optimal ranges of doping in Si:HfO, Al:HfO and HfZrO. We also present model thin film heterostructure computations of Ir/HfO/Ir stacks in order to isolate the interface effects, which we show to be significant.

摘要

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验