Abstract
Floating-gate Metal-Oxide Semiconductor (MOS) has been investigated and applied in many applications such as artificial intelligence, analog mixed-signal, neural networks, and memory fields. This study aims to propose a methodology for extracting a DC model for a 65 nm floating-gate MOS transistor. The method in this work uses the combination architecture of MOS transistor, capacitance, and voltage-controlled voltage source which can archive a high accuracy result. Moreover, the advantage of the method is that the MOS transistor was a completed model which enhances the flexibility and accuracy between a fabricated device and modeled architecture. In our work, the industrial standard model Berkeley Short-channel IGFET Model (BSIM) 3v3.1, level 49 was deployed, and the DC simulation was obtained with the use of LTspice tool.
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Acknowledgment
We acknowledge the support of time and facilities from Ho Chi Minh City University of Technology (HCMUT), VNU-HCM for this study.
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Cong, T.D., Hoang, T. (2023). A Methodology of Extraction DC Model for a 65 nm Floating-Gate Transistor. In: Dao, NN., Thinh, T.N., Nguyen, N.T. (eds) Intelligence of Things: Technologies and Applications. ICIT 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 187. Springer, Cham. https://doi.org/10.1007/978-3-031-46573-4_19
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DOI: https://doi.org/10.1007/978-3-031-46573-4_19
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