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nnp:mosfet_in_2d [2020/08/03 14:53]
daryoush.nosraty-alamdary [Comparison of Different Mobility Models]
nnp:mosfet_in_2d [2024/01/03 16:01]
stefan.birner removed
Line 634: Line 634:
 </​caption>​ </​caption>​
 </​figure>​ </​figure>​
 +As we can see there is clearly two different quantum confined modes in the inversion layer of the channel for this MOSFET.
  
-In the above input characteristics curve, however, the drift and diffusion parts are hard to distinguish from each other without the logarithmic scale. 
-This could be enhanced using a ''​shift''​ parameter in the ohmic contact of the drain: 
-<​code>​ 
- ​ohmic{ 
-      name = Drain_Contact 
-      shift = 0.40  # [eV] used to increase (or decrease) 
-                    #      the resistivity of the ohmic contact 
-      bias = $SourceDrainVoltage 
-   } 
-</​code>​ 
  
-Basically the shift of the band structure using the shift parameter in the ohmic contact leads to the change of the resistivity of the ohmic contact (see  [[https://​www.nextnano.de/​nextnanoplus/​software_documentation/​input_file/​contacts.htm|contacts{}]]). +With regards to the issue of convergence for the output characteristics, ​the convergence parameters become very relevant, since for the wrong set of parameters, the simulations may very well never converge and if so might take a significant amount of time. The key parameter to keep in mind is the ''​alpha_fermi''​ parameter in [[https://​www.nextnano.com/​nextnanoplus/​software_documentation/​input_file/​run.htm | current-poisson{}]] calculations,​ which would decide the fate of the calculations. ​This parameter needs to be chosen corrently, and also since it will be dynamically reduced, the //​alpha_scale//​ parameter also need to be set appropriately,​ with a relatively small //​alpha_iterations//​ (default is 1000, which is very high!!!), so that a quick adjustment can be achieved if the parameter is too large. ​One also needs to significantly increase the number of iterations from the default 100, to a few thousand. This so called under-relaxation parameter for the quasi-Fermi level is important due to the fact that it decides the volume of the search for the solutions.
-This has the advantage of bringing the I-V curve into a better form, distinguishing the drift and diffusion even without the logarithmic scale, and therefore consequently,​ making the determination of the threshold voltage $V_{\rm Th}$ easier. +
-However the price to pay is that the output current will be significantly less in terms of [A/cm] (in our case close to 1 order of magnitude less). +
-Without the shift in the drain contact the input I-V characteristics look somewhat differently,​ as shown in figure {{ref>​fig7}}:​ +
- +
-<figure fig7> +
-{{ :​nnp:​modelocking.gif?​550 |}} +
-<​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>​ +
- +
-With regards to the issue of convergence for the output characteristics,​ relevant, since for the wrong set of parameters, the simulations may very well never converge and if so might take a significant amount of time. +
-The key parameter to keep in mind is the ''​alpha_fermi''​ parameter in [[https://​www.nextnano.com/​nextnanoplus/​software_documentation/​input_file/​run.htm | current-poisson{}]] calculations,​ which would decide the fate of the calculations. +
-One also needs to significantly increase the number of iterations from the default 100, to a few thousand. +
-This so called under-relaxation parameter for the quasi-Fermi level is important due to the fact that it decides the volume of the search for the solutions.+
 If the solution somehow is located outside of this volume If the solution somehow is located outside of this volume
  
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---------(In development)------