Multi‐objective Design of Nanoscale Double Gate MOSFET Devices Using Surrogate Modeling and Global Optimization

Bentrcia, Toufik; Djeffal, F.; Chebaki, Elasaad

doi:10.1002/9781119242628.ch12

Cited by 1 publication

(2 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is worthy to mention that our hybrid framework based on the integration of metamodelling techniques and multi objective optimisation algorithms is a generic approach. Consequently, it has been applied successfully to other important parameters namely gain Av, transconductance generation factor TGF, threshold voltage Vth, swing factor S and OFF-current IOFF [35,36]. Our approach can be also applied to digital performance by including phenomena and mechanisms dominant at subthreshold regime of the device during the simulation phase and performing again the hyperparameters adjustment.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Approach for designing and modelling of nanoscale DG MOSFET devices using Kriging metamodelling technique

Bentrcia

Djeffal

Chebaki

2017

IET Circuits, Devices & Syst

Self Cite

View full text Add to dashboard Cite

In this study, the authors focus mainly on the investigation of Kriging interpolation method to elaborate surrogate models of the nanoscale double-gate metal oxide silicon field effect transistors (DG MOSFET) analogue/RF performance under critical operational conditions. The elaboration of such models is made possible through the generation of computer experiments using ATLAS-2D simulator, where the numerical simulations or experimental measurements, account for the accurate behaviour of the device including the ageing phenomena, short channel and quantum confinement effects. The validity of the obtained Kriging models is tested by comparing the predicted responses of the device with their numerical counterpart in terms of some statistical criteria namely the sum of relative errors, the mean percentage of absolute errors and the correlation coefficient. It is also shown that the obtained Kriging interpolation models are precise enough to be used as objective functions in the context of a genetic algorithm optimisation with the aim of improving the device analogue/RF performance in terms of transconductance and cutoff frequency parameters. Therefore, this study may provide more insights regarding the investigation of surrogate modelling tools in the field of deep nanoscale devices especially with the intractable mission of developing physical based models at this scale for nanoelectronic simulators.

show abstract

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…Moreover, the intensive applied voltages allow carriers to be accumulated in the oxide near the drain side. This ageing phenomenon known as the hot carrier effect contributes to the degradation of the overall performance of the device [4].…”

Section: Introductionmentioning

confidence: 99%