Aluminum Scandium Nitride for mm-Wave Acoustic Filtering: Challenges and Outlook

In the recent years, microwave and millimeter wave frequencies have been untapped by acoustic devices for frontend filtering applications. Acoustic filtering promises low power consumption, linearity, small footprint and low insertion loss. Thus, many research and industry groups have been working on extending the frequencies of bulk acoustic wave (BAW) and surface acoustic wave (SAW) devices beyond 6 GHz, to accommodate the fast-growing cellphone and new radio wireless bands. Such frequency scaling is made possible thanks to the advances in the resonator material quality. Aluminum Scandium Nitride, amongst other piezoelectric materials, has been an attractive candidate for microwave acoustic filtering due to i) enhanced piezoelectricity at high Sc contents compared to pure AIN, and ii) thin film deposition/growth versatility and compatibility with CMOS or III-V fabrication processes.This work first reviews some of the recent advances in AlScN material growth, as well as resonator device innovations, that have led to the realization of high-performance filters with frequencies above 12 GHz and up to 50 GHz. The reported Al
1-x
Sc
x
N resonator figures of merit such as Q, $k_t^2$ and power handling are summarized, followed by a discussion of these metric vs Sc concentration. Finally, various types of phonon scattering mechanisms present in Al
1-x
Sc
x
N thin films will be discussed that give rise to a lower Q and lower thermal conductivity with increasing x (=Sc/(Al+Sc)). Specifically, phonon scattering from alloys and grain boundaries are shown to impact Al
1-x
Sc
x
N Q compared to AlN Q. Despite the great promise in achieving wide bandwidth filters, the lower Q and thermal conductivity in Al1-xScxN need to be considered and accounted for in the design of high-performance filters.Summary— This work summarizes the recent advances in AlScN acoustic resonators towards mm-wave acoustic filtering applications. The phonon scattering mechanisms and microstructure properties that give rise to filter metrics will be outlined.