Predictive worst case statistical modeling of 0.8-μm BICMOS bipolar transistors: a methodology based on process and mixed device/circuit level simulators

The authors discuss the use of mixed-level physics-based device/circuit simulation software and semiconductor process simulator in the construction of predictive worst case process conditions for bipolar transistors currently being manufactured in AT&T 0.8-μm BICMOS technology. Process fluctuations are introduced into the process simulator using the Latin hypercube (Monte Carlo) sampling method. The method is different from those in previous similar studies in that the compact device model parameter extraction step for each sample process is bypassed and active devices in the circuit are described by the physical device simulator rather than a compact model representation. This eliminates deficiencies associated with compact semiconductor device models. Furthermore, inaccuracies and difficulties introduced by compact model parameter extractions (especially for bipolar transistors) are also eliminated. The method is very useful in identifying critical process steps which determine the electrical performance of the devices and circuits