editor's blog
Subscribe Now

Comparing Oscillator Temp Compensation

MEMS oscillators are making a serious challenge to quartz these days. We looked at Sand 9’s approach recently, but as I thumbed back through other recent announcements, I came back across one that, in retrospect, had some relevant bits to discuss.

Silicon Labs’ earlier announcement focused on the CMOS+MEMS aspect of their work. At the time, I didn’t see anything I could add to the discussion, so I let the announcement stand on its own. But in light of some of the issues I covered in Sand 9’s release, I thought there were some things to come back to on the Silicon Labs story – some of which weren’t immediately apparent in their release.

This relates to temperature compensation, which seems to be the number one concern with these devices. Yes, everyone tries to compensate with circuitry, but if you can minimize the raw temperature effects, then the compensation is easier.

We looked at the stack that Sand 9 built to do this – silicon and oxide having opposing temperature coefficients and therefore physically compensating for each other. Well, Silicon Labs does something similar but not identical.

They use SiGe as the active material for the resonator, but they back it with SiO2, which again opposes the temperature characteristics of the SiGe.

The other subtlety here relates to the CMOS processing aspect, although again, it seems to be two different ways of accomplishing the same thing. Sand 9 discussed how having the compensation ASIC in the same package was important so that the ASIC was experiencing the same temperature as the sensor it was compensating.

With the Silicon Labs approach, this happens as a direct result of combining MEMS and CMOS on the same die: The compensation circuitry isn’t just next to the sensor; it’s on the same die as the sensor. So again, it experiences the same temperatures as the sensor. It’s probably even closer, although at some point, if you start arguing about hot spots on the actual die, you could question whether mere monolithic integration guarantees better compensation. It depends on where things are on the die and how “hot” the circuits are. So it remains to be proven whether monolithic compensation is practically any more effective than a well-engineered die-by-die solution.

You can find more on Silicon Labs’ process here.

Leave a Reply

featured blogs
Jan 20, 2021
As Jonathan Anthony Burkett famously said: '€œI look at this life as a puzzle without all the pieces in the box.'€...
Jan 20, 2021
Explore how EDA tools & proven IP accelerate the automotive design process and ensure compliance with Automotive Safety Integrity Levels & ISO requirements. The post How EDA Tools and IP Support Automotive Functional Safety Compliance appeared first on From Silicon...
Jan 20, 2021
OrbitIO System Planner is a multi-fabric interconnect planning and optimization solution. It provides a single-canvas environment where you can derive and evaluate connectivity between the dies and... [[ Click on the title to access the full blog on the Cadence Community sit...
Jan 19, 2021
I'€™ve been reading year-end and upcoming year lists about the future trends affecting technology and electronics. Topics run the gamut from expanding technologies like 5G, AI, electric vehicles, and various realities (XR, VR, MR), to external pressures like increased gover...

featured paper

Common Design Pitfalls When Designing With Hall 2D Sensors And How To Avoid Them

Sponsored by Texas Instruments

This article discusses three widespread application issues in industrial and automotive end equipment – rotary encoding, in-plane magnetic sensing, and safety-critical – that can be solved more efficiently using devices with new features and higher performance. We will discuss in which end products these applications can be found and also provide a comparison with our traditional digital Hall-effect sensors showing how the new releases complement our existing portfolio.

Click here to download the whitepaper

Featured Chalk Talk

Introducing Google Coral

Sponsored by Mouser Electronics and Google

AI inference at the edge is exploding right now. Numerous designs that can’t use cloud processing for AI tasks need high-performance, low-power AI acceleration right in their embedded designs. Wouldn’t it be cool if those designs could have their own little Google TPU? In this episode of Chalk Talk, Amelia Dalton chats with James McKurkin of Google about the Google Coral edge TPU.

More information about Coral System on Module