Role of Domain Walls on Imprint and Fatigue in HfO2-Based Ferroelectrics
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866913448905932800 |
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| author | Xie, Muting Yu, Hongyu Zhang, Binhua Xu, Changsong Xiang, Hongjun |
| author_facet | Xie, Muting Yu, Hongyu Zhang, Binhua Xu, Changsong Xiang, Hongjun |
| contents | HfO2-based ferroelectric materials are promising for the next generation of memory devices, attracting significant attention. However, their potential applications are significantly limited by fatigue and imprint phenomena, which affect device lifetime and memory capabilities. Here, to accurately describe the dynamics and field effects of HfO2, we adopt our newly developed DREAM-Allegro network scheme and develop a comprehensive machine-learning model for HfO2. Such model can not only predict the interatomic potential, but also predict Born effective charges. Applying such model, we explore the role of domain dynamics in HfO2 and find that the fatigue and imprint phenomena are closely related to the so-called E-path and T-path switching pathways. Based on the different atomic motions in the two paths, we propose that an inclined electric field can sufficiently suppress fatigue and enhancing the performance of HfO2-based ferroelectric devices. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_19197 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Role of Domain Walls on Imprint and Fatigue in HfO2-Based Ferroelectrics Xie, Muting Yu, Hongyu Zhang, Binhua Xu, Changsong Xiang, Hongjun Materials Science HfO2-based ferroelectric materials are promising for the next generation of memory devices, attracting significant attention. However, their potential applications are significantly limited by fatigue and imprint phenomena, which affect device lifetime and memory capabilities. Here, to accurately describe the dynamics and field effects of HfO2, we adopt our newly developed DREAM-Allegro network scheme and develop a comprehensive machine-learning model for HfO2. Such model can not only predict the interatomic potential, but also predict Born effective charges. Applying such model, we explore the role of domain dynamics in HfO2 and find that the fatigue and imprint phenomena are closely related to the so-called E-path and T-path switching pathways. Based on the different atomic motions in the two paths, we propose that an inclined electric field can sufficiently suppress fatigue and enhancing the performance of HfO2-based ferroelectric devices. |
| title | Role of Domain Walls on Imprint and Fatigue in HfO2-Based Ferroelectrics |
| topic | Materials Science |
| url | https://arxiv.org/abs/2407.19197 |