Novel Machine-Learning-Based Modeling of Ferroelectric Characteristics in Hafnium Zirconium Oxide-Based Devices Using P–E Curve Images via Dual Graph Attention Networks
- 1 November 2026
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Electron Devices
- Vol. 73 (11) , 6675-6680
Abstract
No abstract availableThis publication has 20 references indexed in Scilit:
- Using Raman spectroscopy and x-ray diffraction for phase determination in ferroelectric mixed Hf1−xZrxO2-based layersJournal of Applied Physics, 2022
- Ferroelectric Phase Content in 7 nm Hf(1−x)ZrxO2 Thin Films Determined by X‐Ray‐Based MethodsPhysica Status Solidi (a), 2021
- Next generation ferroelectric materials for semiconductor process integration and their applicationsJournal of Applied Physics, 2021
- Wake‐Up Effect in HfO2‐Based Ferroelectric FilmsAdvanced Electronic Materials, 2020
- Phase field modeling of domain dynamics and polarization accumulation in ferroelectric HZOApplied Physics Letters, 2019
- A comprehensive study on the structural evolution of HfO2thin films doped with various dopantsJournal of Materials Chemistry C, 2017
- Ferroelectricity in Simple Binary ZrO2 and HfO2Nano Letters, 2012
- Phase transitions in ferroelectric silicon doped hafnium oxideApplied Physics Letters, 2011
- Ferroelectricity in hafnium oxide thin filmsApplied Physics Letters, 2011
- An iterative procedure for the polygonal approximation of plane curvesComputer Graphics and Image Processing, 1972