A parallel adaptive finite volume method for nanoscale double-gate MOSFETs simulation
Journal of Computational and Applied Mathematics - Special issue: Selected papers of the international conference on computational methods in sciences and engineering (ICCMSE-2003)
Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design
Analysis and modeling of CD variation for statistical static timing
Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design
Electrical characteristic fluctuations in 16 nm bulk-FinFET devices
Microelectronic Engineering
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Reliability of NAND-2 CMOS gates from threshold voltage variations
IIT'09 Proceedings of the 6th international conference on Innovations in information technology
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Modeling of device variability is crucial for the accuracy of timing in circuits and systems, and the stability of high-frequency application. Unfortunately, due to the randomness of dopant position in device, the fluctuation of device gate capacitance is nonlinear and hard to be modeled in current compact models. Therefore, a large-scale statistically sound "atomistic" device/circuit coupled simulation approach is proposed to characterize the random-dopant-induced characteristic fluctuations in 16-nm-gate CMOS integrated circuits concurrently capturing the discrete-dopant-number- and discrete-dopant-position-induced fluctuations. The variations of transition time of digital circuit (inverter, NAND, and NOR gates) and high-frequency characteristic of common-source amplifier are estimated. For the digital circuits, the function-dependent and circuit-topology-dependent characteristic fluctuations resulted from random nature of discrete dopants is for the first time discussed. This study provides an insight into random-dopant- induced intrinsic timing and high-frequency characteristic fluctuations. The accuracy of the simulation technique is confirmed by the use of experimentally calibrated transistor physical model.