MOBO-Driven Advanced Sub-3-nm Device Optimization for Enhanced PDP Performance

Jeong, HyunJoon; Choi, JinYoung; Cho, HyungMin; Woo, SangMin; Kim, Yohan; Kong, Jeong-Taek; Kim, SoYoung

doi:10.1109/ted.2024.3378224

IEEE Trans. Electron Devices

2024

DOI: 10.1109/ted.2024.3378224

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MOBO-Driven Advanced Sub-3-nm Device Optimization for Enhanced PDP Performance

HyunJoon Jeong,

JinYoung Choi,

HyungMin Cho

et al.

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Cited by 2 publications

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Sequential Optimization Configuration Method for Power Quality Monitors Considering Photovoltaic Access

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Liang,

Zhong,

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Efficient Neural Network-Based Compact Modeling for Novel Device Structures Using a Multi-Fidelity Model and Active Learning

Jeong,

Choi,

Kim

et al. 2024

Electronics

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Neural network (NN)-based compact modeling methodologies are gaining attention due to the challenges of device complexity, narrow model coverage, and SPICE simulation speed in advanced semiconductor technology nodes. As device complexity increases, the number of process and structural variables also increases, which significantly increases the amount of technology computer-aided design (TCAD) simulation data required for NN-based compact modeling. This study proposes a multi-fidelity model and active learning approach to predict global and local variations of nanosheet FETs (NSFETs) with less than 1.5% error, significantly reducing the number of required TCAD simulations by more than half compared with conventional modeling techniques. In addition, the simplified NN model with a smaller training dataset significantly reduces the SPICE simulation time.

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MOBO-Driven Advanced Sub-3-nm Device Optimization for Enhanced PDP Performance

Cited by 2 publications

References 28 publications

Sequential Optimization Configuration Method for Power Quality Monitors Considering Photovoltaic Access

Sequential Optimization Configuration Method for Power Quality Monitors Considering Photovoltaic Access

Efficient Neural Network-Based Compact Modeling for Novel Device Structures Using a Multi-Fidelity Model and Active Learning

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