Agilent Technologies Inc. (NYSE: A) today announced the latest release of its device modeling software platform, the Integrated Circuit Characterization and Analysis Program (IC-CAP).
, Agilent introduces major improvements to its flagship product for high-frequency device modeling. One key improvement is turnkey extraction of the
, the industry standard compact device model for GaN semiconductor devices.
GaN technology is becoming commonplace in today’s high-power RF communication circuits and automotive electronic components. Modeling these devices is challenging due to the impact of trapping and thermal effects on the device electrical characteristics. Existing GaAs models have been used as a first attempt to model GaN devices, but they are not accurate enough. The Angelov-GaN model, developed by Professor IItcho Angelov at Chalmers University of Technology, is quickly establishing itself as the industry’s solution to this dilemma.
Agilent’s W8533 Angelov-GaN extraction package, which is part of the IC-CAP platform, was developed in conjunction with industry partners and validated on real GaN processes. It provides a dedicated software environment that allows users to perform the necessary measurements and extraction of the Angelov-GaN model. Typical DC and network analyzers are supported for making DC and S-parameter measurements and de-embedding. A convenient interface lets users execute a step-by-step extraction flow to obtain the model parameters. A turnkey flow provides quick start modeling of GaN devices. The package also enables complete customization to optimize the flow to different technology flavors of GaN processes. Simulations are performed using Agilent’s
Advanced Design System
IC-CAP 2013.01 also features a new Python programming environment that is up to 100 times faster for typical tasks such as parameter extraction, data analysis, instrument control and interface responsiveness. It enables better code organization and provides an extensive set of libraries for math, instrument control and statistical analysis. With IC-CAP Python, users gain major efficiency when developing their programs. Python programs are interoperable with existing programs, ensuring compatibility with ongoing IC-CAP projects.