Estimation of parameters of the dual-phase-lag model for heat conduction in metal-oxide-semiconductor field-effect transistors

This communication deals with the solution of an inverse parameter estimation problem with the dual-phase-lag heat conduction model. The case considered involves the heating of a metal-oxide-semiconductor field-effect transistor, for time and spatial scales where the validity of the classical heat conduction model based on Fourier's Law, which considers an infinite speed of propagation of thermal waves, has been questioned. The Markov chain Monte Carlo method is applied for the estimation of the parameters within the Bayesian framework of statistics, by using simulated transient temperature measurements.