Coventor Blog

How To Build A Better MEMS Microphone

By: Chris Welham, Senior Manager, MEMS Applications Engineering

A Section of a MEMS Microphone Model


Here at Coventor, we are seeing a lot of interest in simulating noise, particularly for condenser microphones. With any transducer noise reduction is always a plus, and with microphones there are two specific applications that need low noise. One is where the microphone is positioned away from the sound source, such as in video calling or when using voice commands with tablet computers. The other is where multiple microphones are positioned in an array, to detect the direction of incoming sound or for noise canceling applications. read more…

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Comparing MEMS and the RMS Titanic: Some Thoughts from the IEEE MEMS 2018 Conference

By: Chris Welham, Sr. Manager, MEMS Applications Engineering

Conference dinner view of the life-size outlines of the Titanic and Olympic main deck’s, illuminated by blue light

How are MEMS and Large Ships Alike?

MEMS 2018 was held in Belfast, Northern Ireland this year, on the site where the RMS Titanic was built. On exhibit was the SS Nomadic, a tender used to transfer mail and passengers to the RMS Titanic and her sister ship RMS Olympic. Passing by the SS Nomadic on the way to the conference dinner, I noticed the riveted plates from which the tender was built. These riveted plates reminded me of the finite element plate models used in the MEMS+ module of CoventorMP, which can also be joined to other elements using “connectors” or “nodes” rather than rivets. read more…

Future Outlook: The Advantages of Fully Depleted Silicon on Insulator (FD-SOI) Technology

By: Michael Hargrove, SP&I Engineer

If my memory serves me well, it was at the 1989 Device Research Conference where the potential merits of SOI (Silicon on Insulator) technology were discussed in a heated evening panel discussion. At that panel discussion, there were many advocates for SOI, as well as many naysayers. I didn’t really think more about SOI technology until the mid-nineties, when I was sitting in a meeting where the first SOI device data was being presented in the hallowed halls of IBM. The data was incredibly scattered and my thinking was “this technology is going nowhere!” The purported performance advantage was stated to be ~35%, simply due to the capacitance reduction (no longer did the bottom junction capacitance play a role) and the speed advantages of stacked devices in a NAND circuit. It all sounded great, but in the mid-nineties, the data simply didn’t support it. Nonetheless, the SOI advocates pursued their beloved technology, and the rest is history. SOI technology has been part of IBM’s main stream high-performance technology base through the 14nm node, including FinFETs on SOI. read more…

What the Experts Think: Delivering the Next 5 Years of Semiconductor Technology

Coventor recently sponsored an expert panel discussion at IEDM 2017 to discuss how we might advance the semiconductor industry into the next generation of technology.  The panel discussed alternative methods to solve fundamental problems of technology scaling, using advances in semiconductor architectures, patterning, metrology, advanced process control, variation reduction, co-optimization and new integration schemes.  Our panel included Rick Gottscho, CTO of Lam Research; Mark Dougherty, vice president of advanced module engineering at GlobalFoundries; David Shortt, technical fellow at KLA-Tencor; Gary Zhang, vice president of computational lithography products at ASML; and Shay Wolfling, CTO of Nova Measuring Instruments.

The Next 5 Years of Semiconductor Technology

L-R: Ed Sperling (moderator), Shay Wolfling, Rick Gottscho, Mark Dougherty, Gary Zhang, David Shortt

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Delivering the Next 5 Years of Semiconductor Technology

New, advanced semiconductor processing and architectural technologies take years to perfect and put into production. In the meantime, semiconductor customers continue to demand faster, smaller and higher functioning devices. Semiconductor manufacturers need to decide whether (and when) to jump to the next generation of devices and production technologies, weighing the risk and benefit of bringing the next processing and architecture technologies to market. read more…

Reducing BEOL Parasitic Capacitance using Air Gaps

By: Michael Hargrove, SP&I Engineer

Reducing back-end-of-line (BEOL) interconnect parasitic capacitance remains a focus for advanced technology node development. Porous low-k dielectric materials have been used to achieve reduced capacitance, however, these materials remain fragile and prone to reliability concerns. More recently, air gap has been successfully incorporated into 14nm technology [1], and numerous schemes have been proposed to create the air gap [2-3].  There are many challenges to integrate air gap in BEOL such as process margin for un-landed vias and overall increased process complexity. In this paper, we introduce virtual fabrication (SEMulator3D®) as a means to study air gap process integration optimization and resulting interconnect capacitance reduction. Initial calibration to published air gap data is demonstrated. read more…

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Using Advanced Statistical Analysis to improve FinFET transistor performance

By: Jimmy Gu, SP&I Staff Engineer

Trial and error wafer fabrication is commonly used to study the effect of process changes in the development of FinFET and other advanced semiconductor technologies.  Due to the interaction of upstream unit process parameters (such as deposition conformality, etch anisotropy, selectivity) during actual fabrication, variations based upon process changes can be highly complex. Process simulators that mimic fab unit processes can now be used to model these complex interactions.  They can also help process engineers identify important process and/or design parameters that drive certain critical targets such as CDs, yield limiting spacing, 3D design rule violations, resistance/capacitance, and other process and design issues.   The number of possible parameters that affect device performance and yield can be quite large, so statistical analysis can provide useful insight and help identify critical performance parameters.  Coventor’s SEMulator3D virtual fabrication (or process simulation) platform contains an analytics module for conducting virtual design-of-experiments and statistical analysis. I would like to use an example of a 14nm FinFET process flow in SEMulator3D to identify important process parameters that drive fin top CD, which is a key metric for transistor performance.

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Silicon Photonics: Solving Process Variation and Manufacturing Challenges

By: Sandy Wen, Principal Engineer

As silicon photonics manufacturing gains momentum with additional foundry and 300mm offerings, process variation issues are coming to light. Variability in silicon processing affects the waveguide shape and can result in deviation in effective indices, propagation loss, and coupling efficiency from the intended design. In this article, we will highlight process variation issues that can occur in silicon photonics manufacturing and discuss techniques to mitigate these effects.

Figure 1. Example test photonic IC, with common elements such as waveguides, grating coupler, MZI, photodetector and fill pattern.

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