Efficient sensitivity simulation of semiconductor devices

The shrinking volume of aggressively scaled semiconductor devices induces the emergence of novel stochastic phenomena collectively denoted as device variability. The random nature associated to technological parameters (e.g. atomistic doping, device and electrode size uncertainty, etc.) determine variations in the electrical features (e.g. threshold voltage, transconductance, etc.) since they are no longer mitigated by the device volume. These phenomena can be modelled exploiting the same techniques developed for physics-based noise analysis, traced back to the model Green's functions. Using such techniques, statistical analysis of the device subject to random variations can be addressed with high computational efficiency.  Similarly, the (deterministic) sensitivity to technological and physical parameters can be exploited for the optimisation of the device performance and the sensitivity analysis of the device embedded in realistic circuits. In particular, the research group has developed unique capabilities for variability and sensitivity analysis of AC (small-signal) and Large-Signal device parameters, exploiting the concept of the Conversion Green's Functions. In recent years, simulation capabilities have been demonstrated for the statistical analysis of nanometer scale devices (in particular FinFETs) and of microwave devices, also embedded in microwave circuits (power amplifiers) with concurrent variations of device and circuit parameters (external loads).

ERC Sector:

  • PE7_5 (Micro and nano) electronic, optoelectronic and photonic components

Keywords:

  • Semiconductor device modelling
  • Variability
  • Device optimisation

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