Showing posts with label resonators. Show all posts
Showing posts with label resonators. Show all posts

Jul 21, 2021

[paper] 11.8 GHz Fin Resonant Body Transistor

Analysis and Modeling of an 11.8 GHz Fin Resonant Body Transistor 
in a 14nm FinFET CMOS Process 
Udit Rawat, Student Member, IEEE, Bichoy Bahr*, Member, IEEE, 
and Dana Weinstein, Senior Member, IEEE
arXiv:2107.04502v1 [physics.app-ph] 9 Jul 2021
 
Department of Electrical Engineering, Purdue University, West Lafayette USA
*Kilby Labs - Texas Instruments, Dallas, TX, USA.

Abstract: In this work, a compact model is presented for a 14 nm CMOS-based FinFET Resonant Body Transistor (fRBT) operating at a frequency of 11.8 GHz and targeting RF frequency generation/filtering for next generation radio communication, clocking, and sensing applications. Analysis of the phononic dispersion characteristics of the device, which informs the model development, shows the presence of polarization exchange due to the periodic nature of the back-end-of-line (BEOL) metal PnC. An eigenfrequency-based extraction process, applicable to resonators based on electrostatic force transduction, has been used to model the resonance cavity. Augmented forms of the BSIM-CMG (Common Multi-Gate) model for FinFETs are used to model the drive and sense transistors in the fRBT. This model framework allows easy integration with the foundry-supplied process design kits (PDKs) and circuit simulators while being flexible towards change in transduction mechanisms and device architecture. Ultimately, the behaviour is validated against RF measured data for the fabricated fRBT device under different operating conditions, leading to the demonstration of the first complete model for this class of resonant device integrated seamlessly in the CMOS stack.
Fig: Complete 3D FEM Simulation model depicting two adjoining fRBT unit cells. Mx (x=1-3) and Cy (y=4-6) represent the first 6 metal levels that form a part of the BEOL PnC.

Acknowledgement: This work was supported in part by the DARPA MIDAS Program.