editor's blog
Subscribe Now

Teasing Apart FBAR Loading and Temperature Effects

We hear stories of a not-so-distant future when we can wave our tricorder-like devices around and detect all kinds of substances that might be in the air. One of the ways sensors like this can work is by having a resonating body: when a substance adsorbs on the surface, it changes the mass, thereby changing the resonance frequency.

The problem is, however, that temperature also affects the frequency, and it’s actually pretty hard to calibrate that out of the system. Using a reference resonator or a complex software algorithm is possible, but, according to a team from Cambridge, Universities of Sheffield, Bolton, and Manchester in the UK, and Kyung Hee University in Korea, it makes things more complex and/or costly.

They’ve come up with a way of teasing the loading and temperature effects apart. It involves a two-layer structure: 2 µm of ZnO over 2 µm of SiO2. When they get this vibrating, they see two modes:

  • One with a fundamental frequency at 754 MHz and harmonics at 2.26 and 3.77 GHz
  • One with a fundamental frequency at 1.44 GHz, and the next harmonic at 4.34 GHz

The first mode comes from the resonance of the combined ZnO/SiO2 structure; its half-wavelength relates to the combined 4-µm thickness of the overall structure. The second mode results from the ZnO layer by itself, with a half-wavelength driven by the 2-µm thickness of this layer, although it’s also affected by the SiO2 load.

Both ZnO and SiO2 have positive coefficients of thermal expansion (CTE), so both layers get thicker as temperature goes up. But the longitudinal wave velocity goes up for SiO2 and down for ZnO. As a result, the frequencies move in opposite directions as temperature changes: roughly 79.5 ppm/K for SiO2 and -7 ppm/K for ZnO.

Given those as base numbers, it now becomes possible to deconvolve the temperature and loading effects of whatever it is you’re trying to sense.

This was, of course, a university project, although it looks like they will be open to commercializing it. You can get more details in the full paper, but it’s behind a paywall (actually, several; you can Google “Dual-mode thin film bulk acoustic wave resonators for parallel sensing of temperature and mass loading” and pick your favorite one).

Leave a Reply

featured blogs
Jan 22, 2025
Shouldn't Matter mean I can eliminate all my other smart home apps? Almost. When it comes to smart home apps, review what device types might need an app....
Feb 5, 2025
Return of Rock ranks Telegraph Road as 5th among Dire Straits' best songs, describing it as "A fourteen-minute masterpiece worth every second of its length'...

featured chalk talk

Machine Learning on the Edge
Sponsored by Mouser Electronics and Infineon
Edge machine learning is a great way to allow embedded devices to run applications that can collect sensor data and locally process that data. In this episode of Chalk Talk, Amelia Dalton and Clark Jarvis from Infineon explore how the IMAGIMOB Studio, ModusToolbox™ Software, and PSoC and AURIX™ microcontrollers can help you develop a custom machine learning on the edge application from scratch. They also investigate how the IMAGIMOB Studio can help you easily develop and deploy AI/ML models and the benefits that the PSoC™ 6 Artificial Intelligence Evaluation Kit will bring to your next machine learning on the edge application design process.
Aug 12, 2024
56,248 views