[paper] DL Physics-Driven MOSFET Modeling

Ming-Yen Kao, H. Kam, and Chenming Hu, Life Fellow, IEEE

Deep-Learning-Assisted Physics-Driven MOSFET Current-Voltage Modeling

in IEEE Electron Device Letters

DOI: 10.1109/LED.2022.3168243

Abstract: In this work, we propose using deep learning to improve the accuracy of the partially-physics-based conventional MOSFET current-voltage model. The benefits of having some physics-driven features in the model are discussed. Using a portion of the Berkeley Short-channel IGFET Common-Multi-Gate (BSIM-CMG), the industry-standard FinFET and GAAFET compact model, as the physics model and a 3-layer neural network with 6 neurons per layer, the resultant model can well predict IV, output conductance, and transconductance of a TCAD-simulated gate-all-around transistor (GAAFET) with outstanding 3-sigma errors of 1.3%, 4.1%, and 2.9%, respectively. Implications for circuit simulation are also discussed.

Fig: (a) Model implementation for circuit simulations, without the relative gm and gds errors terms in the cost function, Model shows larger prediction error in (b) gm and (c) gds.

Acknowledgements: This work was supported by the Berkeley Device Modeling Center, 

UCB, CA (USA)

[paper] Cryogenic Temperature Effects in 10-nm Bulk CMOS FinFETs

Sujit K. Singh, Sumreti Gupta, Reinaldo A. Vega* and Abhisek Dixit

Accurate Modeling of Cryogenic Temperature Effects in 10-nm Bulk CMOS FinFETs Using the BSIM-CMG Model

in IEEE Electron Device Letters

DOI: 10.1109/LED.2022.3158495.

  

 Indian Institute of Technology, New Delhi (IN)

*IBM Research, Albany, NY (USA)

Abstract: In this letter, we have proposed modifications to the existing BSIM-CMG compact model to enhance its ability to model the behavior of short channel bulk FinFETs (both n and p-type) from room temperature down to cryogenic temperatures (10K). The proposed model is highly accurate in capturing the subthreshold swing, threshold voltage, and effective mobility trends observed in FinFET cryogenic operation. For efficient optimization of the proposed model parameters, we have proposed an adequate modeling strategy. We have compared convergence time between the existing BSIM-CMG model and the proposed model by simulating a reasonably large circuit using pseudo-inverters.

Fig (a) TEM image of the fin cross-section (b) Measured device layout-related parameters 

[BOOK] FinFET Modeling for IC Simulation and Design Using the BSIM-CMG Standard

 FinFET Modeling for IC Simulation and Design Using the BSIM-CMG Standard
 Yogesh Singh Chauhan, Darsen Lu, Sriramkumar Venugopalan, Sourabh Khandelwal, Juan Pablo Duarte, Navid Paydavosi, Ai Niknejad, Chenming Hu

DESCRIPTIONThis book is the first to explain FinFET modeling for IC simulation and the industry standard – BSIM-CMG - describing the rush in demand for advancing the technology from planar to 3D architecture, as now enabled by the approved industry standard. The book gives a strong foundation on the physics and operation of FinFET, details aspects of the BSIM-CMG model such as surface potential, charge and current calculations, and includes a dedicated chapter on parameter extraction procedures, providing a step-by-step approach for the efficient extraction of model parameters.

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With this book you will learn:

• Why you should use FinFET
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