Elucidating structure-property correlations in ferroelectric Hf0.5Zr0.5O2 films using variational autoencoders
Abstract
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.
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BibTeX
@article{alhadalahbabi2026elucidating,
title = {{Elucidating structure-property correlations in ferroelectric Hf0.5Zr0.5O2 films using variational autoencoders}},
author = {Kévin Alhada-Lahbabi and Brice Gautier and Damien Deleruyelle and Grégoire Magagnin},
journal = {Materials \& Design},
year = {2026},
month = oct,
doi = {10.1016/j.matdes.2025.114020},
url = {https://hal.science/hal-05773460v1},
note = {CC BY},
}
RIS
TY - JOUR
TI - Elucidating structure-property correlations in ferroelectric Hf0.5Zr0.5O2 films using variational autoencoders
AU - Kévin Alhada-Lahbabi
AU - Brice Gautier
AU - Damien Deleruyelle
AU - Grégoire Magagnin
PY - 2026
DA - 2026/10/01
JO - Materials & Design
DO - 10.1016/j.matdes.2025.114020
UR - https://hal.science/hal-05773460v1
AB - 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.
SN - 0261-3069
SN - 0264-1275
ER -