Elucidating structure-property correlations in ferroelectric Hf0.5Zr0.5O2 films using variational autoencoders

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. • Explored Structure-Property Relationships with Variational Autoencoders. • Inverse Design of Hafnium Oxide for Tailored Electrical Properties. • Revealed the Impact of Polycrystalline Structure on HZO Electrical Performance.