We present a novel deuterium (D2) plasma treatment process for interface passivation that leads to reliability improvement under a low thermal budget. Specifically, physics-based simulations revealed a marked enhancement of key reliability phenomena such as leakage current, Negative Bias Temperature Instability (NBTI) and Voltage-Dependent Dielectric Breakdown (VDDB), also confirmed by experiments. Furthermore, the plasma treatment process optimization is accelerated through a physical model based on the Ginestra ™ simulation platform, which connects the process conditions to the defect passivation and the best device reliability.
A Novel D2 Plasma Treatment for Defect Passivation: From Modeling to Process Optimization / Vecchi, Sara; Bhosle, Vikram; Palmieri, Andrea; Cornigli, Davide; Buscemi, Fabrizio; Padovani, Andrea; Raj, Deven; Cockburn, Andrew; Date, Lucien; Thareja, Gaurav; Nardi, Federico; Larcher, Luca. - (2025), pp. 1-5. (Intervento presentato al convegno 2025 IEEE International Reliability Physics Symposium (IRPS) tenutosi a Monterey, CA, USA nel 30 marzo 2025 - 3 aprile 2025) [10.1109/irps48204.2025.10983832].
A Novel D2 Plasma Treatment for Defect Passivation: From Modeling to Process Optimization
Vecchi, Sara;Buscemi, Fabrizio;Padovani, Andrea;Larcher, Luca
2025
Abstract
We present a novel deuterium (D2) plasma treatment process for interface passivation that leads to reliability improvement under a low thermal budget. Specifically, physics-based simulations revealed a marked enhancement of key reliability phenomena such as leakage current, Negative Bias Temperature Instability (NBTI) and Voltage-Dependent Dielectric Breakdown (VDDB), also confirmed by experiments. Furthermore, the plasma treatment process optimization is accelerated through a physical model based on the Ginestra ™ simulation platform, which connects the process conditions to the defect passivation and the best device reliability.File | Dimensione | Formato | |
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(S. Vecchi - IRPS 2025) A Novel D2 Plasma Treatment for Defect Passivation - From Modeling to Process Optimization.pdf
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