ACOUSTO-OPTO-MECHANICAL SYSTEMS in PIEZOELECTRIC ALUMINUM NITRIDE NANOFILMS FOR RADIO FREQUENCY PHOTONICS

Carnegie Mellon University, Pittsburgh PA

Investigators

Abstract

The objective of this research is to use on-chip acoustics and photonics to produce miniaturized components that offer a very competitive approach for the synthesis of low power radio receivers. The approach consists in developing devices made out of piezoelectric aluminum nitride (AlN) thin films, in which acousto-optic (modulation of optical signals via elastic waves) and opto-mechanical (modulation of mechanical vibrations via radiation pressure) effects are exploited in confined nanoscale resonant structures. The proposed radio frequency (RF)-photonic receiver relies on an AlN piezoelectric micromechanical filter to select the incoming RF signal (electromechanical effect) and modulate the photonic signal (acousto-optic effect). It also uses the intrinsic non-linearity of the self-sustained opto-mechanical oscillator (opto-mechanical effect) to down convert the signal to baseband. The intellectual merit of this proposal consists in addressing the engineering challenges that limit the realization of compact RF-photonics receivers based on exploiting electromechanical, acousto-optic and opto-mechanical effects in AlN films. Scientifically, elasto-optic effects in thin AlN films and noise mechanisms in nanoscale opto-mechanical devices will be understood. Beyond directly impacting wireless communications, the proposed acousto-opto-mechanical platform will benefit the broader field of photonics by enabling visible and deep ultraviolet components that could be employed for medical applications. Simultaneously, the high mechanical displacement sensitivity attained via acousto-optic modulators can be transferred to inertial and pressure sensors to enhance their resolution. More broadly, the knowledge generated by these research activities will set the pathway for the synthesis of low power distributed communication links and will enable new generations of sensor networks.