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Analysis of Conduction Band Offset Variation on the Electrostatics of UTB Devices through the Modified Effective Mass Approximation (mEMA)
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  • Harshit Kansal ,
  • Nalin Vilochan Mishra ,
  • Ravi Solanki ,
  • Aditya S Medury
Harshit Kansal
Indian Institute of Science Education and Research Bhopal

Corresponding Author:[email protected]

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Nalin Vilochan Mishra
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Ravi Solanki
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Aditya S Medury
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Abstract

In Ultra-thin Body (UTB) devices, besides the Ultra-thin (UT) nature of the channel, which manifests in terms of Quantum Confinement Effects (QCEs), the Band-offsets between the oxide and channel materials at their interface, also tends to strongly impact the channel electrostatics. Despite being very accurate in calculating the band-structure and hence considering QCEs for a given channel material, the Tight-Binding (TB) method tends to be more complicated to use at the channel/oxide interface of MOS devices, while on the other hand the Effective Mass Approximation (EMA) in spite of being less accurate, is a simpler approach to consider the effects of band-offsets at the interface. Given its accuracy, we firstly use the $sp^3d^5s^*$ TB method to calculate the Band-structure and then by considering significant k-points, efficiently incorporate the QCE into the electrostatics of Double-Gate (DG) Silicon-on-Insulator (SOI) MOS devices. Considering these results as a reference, with the assumption of an infinite potential well, we propose a modified Effective Mass Approximation (mEMA) approach, whereby introducing energy correction parameters, along with the effective mass parameters, all of which are shown to be gate bias, channel and oxide thickness dependent, the results obtained from the proposed approach are shown to have good agreement with the results from TB method. In order to analyze the effect of Conduction-Band Offset variations on the channel electrostatics parameters, we consider an $SiO_2$ layer of thickness of $1$ $nm$ and show the effect of different Band-offsets on the integrated charge density and gate capacitance, using the mEMA approach.