材料科学
遗传算法
锆
领域(数学)
相(物质)
微晶
铪
算法
计算机科学
化学
机器学习
数学
纯数学
有机化学
冶金
作者
Sandeep Sugathan,Krishnamohan Thekkepat,Soumya Bandyopadhyay,Jiyoung Kim,Pil‐Ryung Cha
出处
期刊:Nanoscale
[The Royal Society of Chemistry]
日期:2022-01-01
卷期号:14 (40): 14997-15009
被引量:7
摘要
Ferroelectric hafnium zirconium oxide (HZO) thin films show significant promise for applications in ferroelectric random-access memory devices, ferroelectric field-effect transistors, and ferroelectric tunneling junctions. However, there are shortcomings in understanding ferroelectric switching, which is crucial in the operation of these devices. Here a computational model based on the phase field method is developed to simulate the switching behavior of polycrystalline HZO thin films. Furthermore, we introduce a novel approach to optimize the effective Landau coefficients describing the free energy of HZO by combining the phase field model with a genetic algorithm. We validate the model by accurately simulating switching curves for HZO thin films with different ferroelectric phase fractions. The simulated domain dynamics during switching also shows amazing similarity to the available experimental observations. The present work also provides fundamental insights into enhancing the ferroelectricity in HZO thin films by controlling the grain morphology and crystalline texture. It can potentially be extended to improve the ferroelectric properties of other hafnia based thin films.
科研通智能强力驱动
Strongly Powered by AbleSci AI