A computationally efficient model for inversion layer quantization effects in deep submicron N-channel MOSFETs

Successful scaling of MOS device feature size requires thinner gate oxides and higher levels of channel doping in order to simultaneously satisfy the need for high drive currents and minimal short-channel effects. However, in deep submicron (⩽0.25 μm gate length) technology, the combination of the extremely thin gate oxides (t _ox⩽10 nm) and high channel doping levels (⩾10¹⁷ cm^-3) results in transverse electric fields at the Si/SiO₂ interface that are sufficiently large, even near threshold, to quantize electron motion perpendicular to the interface. This phenomenon is well known and begins to have an observable impact on room temperature deep submicron MOS device performance when compared to the traditional classical predictions which do not take into account these quantum mechanical effects. Thus, for accurate and efficient device simulations, these effects must be properly accounted for in today´s widely used moment-based device simulators. This paper describes the development and implementation into PISCES of a new computationally efficient three-subband model that predicts both the quantum mechanical effects in electron inversion layers and the electron distribution within the inversion layer. In addition, a model recently proposed by van Dort et al. (1994) has been implemented in PISCES. By comparison with self-consistent calculations and previously published experimental data, these two different approaches for modeling the electron inversion layer quantization are shown to be adequate in order to both accurately and efficiently simulate many of the effects of quantization on the electrical characteristics of N-channel MOS transistors