Physics-informed AI Accelerated Retention Analysis of Ferroelectric Vertical NAND: From Day-Scale TCAD to Second-Scale Surrogate Model
Rattachement africain : us, kr. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
Ferroelectric field-effect transistors (FeFET)-based vertical NAND (Fe-VNAND) has emerged as a promising candidate to overcome z-scaling limitations with lower programming voltages. However, the data retention of 3D Fe-VNAND is hindered by the complex interaction between charge detrapping and ferroelectric depolarization. Developing optimized device designs requires exploring an extensive parameter space, but the high computational cost of conventional Technology Computer-Aided Design (TCAD) tools makes such wide-scale optimization impractical. To overcome these simulation barriers, we present a Physics-Informed Neural Operator (PINO)-based AI surrogate model designed for high-efficiency prediction of threshold voltage (Vth) shifts and retention behavior. By embedding fundamental physical principles into the learning architecture, our PINO framework achieves a speedup exceeding 10000x compared to TCAD while maintaining physical accuracy. The resulting surrogate provides a physics-consistent data engine for compact model parameter extraction and look-up-table (LUT) generation, directly supporting reliability-aware SPICE simulation of Fe-VNAND. This study demonstrates the model's effectiveness on a single FeFET configuration, serving as a pathway toward modeling the retention loss mechanisms.
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Georgia Institute of Technology pays non établi dans la noticeUniversité ou école supérieure
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Samsung (South Korea) pays non établi dans la noticeEntreprise
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Samsung Electronics (South Korea) pays non établi dans la noticeEntreprise
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Nvidia (United States) pays non établi dans la noticeEntreprise
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School of Electrical and Computer Engineering pays non établi dans la noticeUniversité ou école supérieure
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Ltd Samsung Electronics Co. pays non établi dans la noticeEntreprise
Georgia Institute of Technology, Samsung (South Korea) et Samsung Electronics (South Korea), avec 3 autres affiliations.
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