Structured and unstructured grid adaptation schemes for numerical modeling of field problems
Proceedings of the third ARO workshop on Adaptive methods for partial differential equations
SIAM Journal on Numerical Analysis
A novel parallel adaptive Monte Carlo method for nonlinear Poisson equation in semiconductor devices
Mathematics and Computers in Simulation - Special issue: 3rd IMACS seminar on Monte Carlo methods - MCM 2001
Device modeling and simulations toward sub-10 nm semiconductor devices
IEEE Transactions on Nanotechnology
Modeling of quantum effects for ultrathin oxide MOS structures with an effective potential
IEEE Transactions on Nanotechnology
A SPICE-compatible model for nanoscale MOSFET capacitor simulation under the inversion condition
IEEE Transactions on Nanotechnology
Electronic design automation using a unified optimization framework
Mathematics and Computers in Simulation
Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design
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We propose in this paper a quantum correction transport model for nanoscale double-gate metal-oxide-semiconductor field effect transistor (MOSFET) device simulation. Based on adaptive finite volume, parallel domain decomposition, monotone iterative, and a posteriori error estimation methods, the model is solved numerically on a PC-based Linux cluster with MPI libraries. Quantum mechanical effect plays an important role in semiconductor nanoscale device simulation. To model this effect, a physical-based quantum correction equation is derived and solved with the hydrodynamic transport model. Numerical calculation of the quantum correction transport model is implemented with the parallel adaptive finite volume method which has recently been proposed by us in deep-submicron semiconductor device simulation. A 20 nm double-gate MOSFET is simulated with the developed quantum transport model and computational technique. Compared with a classical transport model, it is found that this model can account for the quantum mechanical effects of the nanoscale double-gate MOSFET quantitatively. Various biasing conditions have been verified on the simulated device to demonstrate its accuracy. Furthermore, for the same tested problem, the parallel adaptive computation shows very good computational performance in terms of the mesh refinements, the parallel speedup, the load-balancing, and the efficiency.