Boltzmann-Statistics-Aware Non-Quasi-Static-Charge Model for IC Simulations

IF 2.9 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Transactions on Electron Devices Pub Date : 2024-12-13 DOI:10.1109/TED.2024.3513945
Chetan Kumar Dabhi;Girish Pahwa;Sayeef Salahuddin;Chenming Hu
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Abstract

In this article, Boltzmann statistics consideration is added to the charge-deficit large-signal non-quasi-static (NQS) model. The new model eliminates the nonphysical negative drain transport (as opposed to displacement) current at large drain voltage and under fast gate voltage ( $\text {V}_{\text {gs}}$ ) turn-on. The new model agrees well with the technology computer-aided design (TCAD) simulation data for turn-on and turnoff transients and for all the drain voltage ( $\text {V}_{\text {ds}}$ ) values, small or large. In addition, the model captures the temperature dependence of channel charge partition between source charge and drain charge in agreement with TCAD simulation results, thus reconfirming the importance of including Boltzmann statistics in NQS models. The new Boltzmann-aware NQS model is implemented in Verilog-A and tested using commercial circuit simulators. It is intended for the simulation of large-signal and small-signal NQS, and high-speed analog, logic and memory circuits.
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集成电路仿真的玻尔兹曼统计感知非准静态电荷模型
本文在电荷亏缺大信号非准静态(NQS)模型中加入了玻尔兹曼统计的考虑。新模型消除了在大漏极电压和快速栅极电压($\text {V}_{\text {gs}}$)导通下的非物理负漏极输运(而不是位移)电流。新模型与计算机辅助设计(TCAD)技术的通断瞬态仿真数据和所有漏极电压($\text {V}_{\text {ds}}$)值,无论大小,都符合得很好。此外,该模型捕获了通道电荷在源电荷和漏电荷之间分配的温度依赖性,与TCAD仿真结果一致,从而再次证实了在NQS模型中加入玻尔兹曼统计量的重要性。新的玻尔兹曼感知NQS模型在Verilog-A中实现,并使用商用电路模拟器进行了测试。它适用于大信号和小信号NQS、高速模拟、逻辑和存储电路的仿真。
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来源期刊
IEEE Transactions on Electron Devices
IEEE Transactions on Electron Devices 工程技术-工程:电子与电气
CiteScore
5.80
自引率
16.10%
发文量
937
审稿时长
3.8 months
期刊介绍: IEEE Transactions on Electron Devices publishes original and significant contributions relating to the theory, modeling, design, performance and reliability of electron and ion integrated circuit devices and interconnects, involving insulators, metals, organic materials, micro-plasmas, semiconductors, quantum-effect structures, vacuum devices, and emerging materials with applications in bioelectronics, biomedical electronics, computation, communications, displays, microelectromechanics, imaging, micro-actuators, nanoelectronics, optoelectronics, photovoltaics, power ICs and micro-sensors. Tutorial and review papers on these subjects are also published and occasional special issues appear to present a collection of papers which treat particular areas in more depth and breadth.
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