Multi-device Optimization for Scalable DC HEMT Model with Self-Heating Effect

摘要

This paper presents a new approach for extracting a scalable DC HEMT model. Scaling rules with unknown coefficients are assumed for each size dependent parameter, and the model parameter of different devices is thus correlated. A scalable model can then be extracted by multi-device optimization. The optimization is carried out on five devices with different gate width. In this way, accurate scaling rules for each parameter and very good I-V fittings for each device have been achieved simultaneously.