Unveiling structure-property correlations in ferroelectric $Hf_{0.5}Zr_{0.5}O_2$ films using variational autoencoders
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| Main Authors: | , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866929668275306496 |
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| author | Alhada-Lahbabi, Kévin Gautier, Brice Deleruyelle, Damien Magagnin, Grégoire |
| author_facet | Alhada-Lahbabi, Kévin Gautier, Brice Deleruyelle, Damien Magagnin, Grégoire |
| contents | While $Hf_{0.5}Zr_{0.5}O_2$ (HZO) thin films hold significant promise for modern nanoelectronic devices, a comprehensive understanding of the interplay between their polycrystalline structure and electrical properties remains elusive. Here, we present a novel framework combining phase-field (PF) modeling with Variational Autoencoders (VAEs) to uncover structure-property correlations in polycrystalline HZO. Leveraging PF simulations, we constructed a high-fidelity dataset of $P-V$ loops by systematically varying critical material parameters, including grain size, polar grain fraction, and crystalline orientation. The VAEs effectively encoded hysteresis loops into a low-dimensional latent space, capturing electrical properties while disentangling complex material parameters interdependencies. We further demonstrate a VAE-based inverse design approach to optimize $P-V$ loop features, enabling the tailored design of device-specific key performance indicators (KPIs), including coercive field, remanent polarization, and loop area. The proposed approach offers a pathway to systematically explore and optimize the material design space for ferroelectric nanoelectronics. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_05312 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Unveiling structure-property correlations in ferroelectric $Hf_{0.5}Zr_{0.5}O_2$ films using variational autoencoders Alhada-Lahbabi, Kévin Gautier, Brice Deleruyelle, Damien Magagnin, Grégoire Materials Science While $Hf_{0.5}Zr_{0.5}O_2$ (HZO) thin films hold significant promise for modern nanoelectronic devices, a comprehensive understanding of the interplay between their polycrystalline structure and electrical properties remains elusive. Here, we present a novel framework combining phase-field (PF) modeling with Variational Autoencoders (VAEs) to uncover structure-property correlations in polycrystalline HZO. Leveraging PF simulations, we constructed a high-fidelity dataset of $P-V$ loops by systematically varying critical material parameters, including grain size, polar grain fraction, and crystalline orientation. The VAEs effectively encoded hysteresis loops into a low-dimensional latent space, capturing electrical properties while disentangling complex material parameters interdependencies. We further demonstrate a VAE-based inverse design approach to optimize $P-V$ loop features, enabling the tailored design of device-specific key performance indicators (KPIs), including coercive field, remanent polarization, and loop area. The proposed approach offers a pathway to systematically explore and optimize the material design space for ferroelectric nanoelectronics. |
| title | Unveiling structure-property correlations in ferroelectric $Hf_{0.5}Zr_{0.5}O_2$ films using variational autoencoders |
| topic | Materials Science |
| url | https://arxiv.org/abs/2501.05312 |