nnp:mosfet_in_2d
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nnp:mosfet_in_2d [2020/08/03 01:41] daryoush.nosraty-alamdary [Appendix: MOSFET] |
nnp:mosfet_in_2d [2020/08/03 14:41] daryoush.nosraty-alamdary [Appendix: MOSFET] |
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| <figure fig34> | <figure fig34> | ||
| - | {{ :nnp:modelocking.gif?550 |}} | + | {{ :nnp:mosfet_class_erd.png?550 |}}<caption> ** The classical energy resolved density in the $L_{\rm G} = 25 \ \rm nm$ MOSFET at three different energy levels. ** |
| - | <caption> ** The input characteristics of the N-Ch MOSFET calculated classically with the Masetti mobility, both in normal and logarithmic scales, without the effect of the shift of the ohmic drain contact. ** | + | </caption> |
| + | </figure> | ||
| + | Now let us look at the same energy resolved densities in the MOSFET source and drain region, obtained using the quantum mechanics alone: | ||
| + | <figure fig35> | ||
| + | {{ :nnp:mosfet_qm_erd_qm-confinement.png?580 |}} | ||
| + | <caption> ** The quantum mechanical energy resolved density in the MOSFET source and drain regions, showing spacial quantum confinement at discrete energy levels. ** | ||
| + | </caption> | ||
| + | </figure> | ||
| + | In the above figure we can clearly see that compared to the classical density, the quantum mechanical density indicate quantum confinement in the source drain doping regions. Furthermore, as we shall see in figure {{ref>fig36}}, also the density in the inversion layer shows quantum confinement for different discrete energy levels: | ||
| + | <figure fig36> | ||
| + | {{ :nnp:mosfet-lg25nm_qm-confinement-in-channel_2d.png?550 |}} | ||
| + | <caption> ** The quantum mechanical energy resolved density in the inversion layer of the MOSFET-channel, at two different energy levels, showing the standing wave pattern, which indicates quantum confinement. ** | ||
| </caption> | </caption> | ||
| </figure> | </figure> | ||
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| - | |||
| In the above input characteristics curve, however, the drift and diffusion parts are hard to distinguish from each other without the logarithmic scale. | In the above input characteristics curve, however, the drift and diffusion parts are hard to distinguish from each other without the logarithmic scale. | ||
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