Quantitative identification of significant k-points enabling accurate & computationally efficient UTB MOS device simulation

Nalin Vilochan Mishra, A. Medury
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Abstract

Ahstract-A semi-empirical $\mathbf{sp}^{3}\mathbf{d}^{5}\mathbf{s}^{*}$ tight-binding model is used to simulate the full-band structure, which in turn is used to calculate the electrostatics of Ultra- Thin-Body (UTB) MOS devices through a self-consistent solution with the 1-D Poisson's equation. Through the identification of significant k-points from the full band structure and calculation of electrostatics of UTB MOS devices over those k-points a computationally efficient yet accurate approach valid over a wide range of channel thicknesses, gate voltages and device temperatures has been shown. In this work, we focus on the practical implementation of this approach, where we show that the choice of a semi-empirical parameter η, which is a weighting factor (multiplier) to the maximum Fermi-Dirac probability (corresponding to the conduction band minima), is critical in identifying the significant k-points. Through an algorithm to quantify η, which is then used to accurately and effectively calculate device electrostatics, we obtain the optimal value of η, showing that this value, for a particular device temperature, is channel thickness independent while varying with gate voltage.
定量识别重要的k点,实现精确和计算效率高的UTB MOS器件模拟
摘要:采用半经验的$\mathbf{sp}^{3}\mathbf{d}^{5}\mathbf{s}^{*}$紧密结合模型模拟了超薄体(UTB) MOS器件的全带结构,并通过一维泊松方程的自洽解计算了该模型的静电特性。通过从全带结构中识别重要的k点,并计算UTB MOS器件在这些k点上的静电,显示了在宽范围的通道厚度,栅极电压和器件温度下有效的计算高效而准确的方法。在这项工作中,我们将重点放在这种方法的实际实现上,在这里我们表明,选择半经验参数η,这是最大费米-狄拉克概率(对应于导带最小值)的加权因子(乘数),对于识别重要的k点至关重要。通过量化η的算法,可以准确有效地计算器件静电,得到了最优η值,表明在特定器件温度下,η值与通道厚度无关,但随栅极电压的变化而变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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