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Automated, physics-guided AI framework for asymmetry-aware ferroelectric compact models

Abstract Despite rapid progress in HfO₂-based ferroelectrics, asymmetry-aware characterization and its reflection in compact models remain insufficiently explored. Also, parameter extraction (PE) is still manual and inconsistent, particularly when asymmetric hysteresis and staged FeCAP (ferroelectri...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Joonhan Kim, Joonhyeok Lee, Juhwan Park, Minseop Kim, Huijun Kim, Jaeweon Kang, Hyunbo Cho, Hwan-wook Choi, Jongwook Jeon
Format: Artigo
Sprache:Inglês
Veröffentlicht: Nature Portfolio 2026-04-01
Schriftenreihe:Scientific Reports
Schlagworte:
Ferroelectric capacitor (FeCAP)
Ferroelectric field-effect transistor (FeFET)
Asymmetry-aware compact model
Neural network
Physics-guided learning
Parameter extraction (PE)
Online-Zugang:https://doi.org/10.1038/s41598-026-48536-w
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