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Figure 2: Description of the five modules required to build a SSVT-SRAM architecture
Overcoming Design and Process Challenges in Next-Generation SRAM Cell Architectures
March 8, 2021
Figure 2. SEMulator3D meshes generated for the model shown in Fig. 1. Left: Delaunay; Center: standard; Right: simple. Cross sections are shown for the Delaunay and standard meshes but the full model is shown for the simple mesh because the volume mesh is not accessible and thus no cross-section view is possible.
Connecting SEMulator3D to Third-Party Design and Analysis Software Using Meshing
April 15, 2021

Improving Your Understanding of Advanced Inertial MEMS Design

Published by Chris Welham at March 24, 2021
Categories
  • Coventor Blog
Tags
  • MEMS
  • MEMS gyroscope
  • MEMS Inertial Sensors
  • MEMS+
MEMS Blog Figure 1 Reverse engineered gyroscope, with suspension spring displayed in the call-out circle

Figure 1: Reverse engineered gyroscope, with suspension spring displayed in the call-out circle

Micro-Electrical-Mechanical Systems (MEMS) based inertial sensors are used measure acceleration and rotation rate. These sensors are integrated into units to measure motion, direction, acceleration or position, and can be found in a wide range of applications including smart phones, consumer electronics, medical devices, transportation systems, oil/gas exploration, military, aeronautical and space sensor systems. These sensors are almost exclusively microfabricated using deep silicon trench etching. Performance is strongly dependent on the trench profile used to define the shape of all of the components that make up the sensor and can normally only be ascertained after fabrication via electrical testing. Here at Coventor, we’ve been working to further improve our solutions to predict inertial MEMS performance from simulation, with a particular focus on process dependency.

The solution employs our MEMS+ simulation platform and a process sensitive device model, which enables trench sidewall-angle and CD loss to be varied. Simulations are script-driven in a Design of Experiments (DOE) loop via our MATLAB interface and the output post-processed to directly compute quadrature error and sense frequency shift. You can see a reverse engineered gyroscope used as a test vehicle in Figure 1 below [1,2]. The colored structures, one of which is magnified, are comprised of 2um wide beams and suspend the central mass (colored green) to allow it to move and sense rotation. In this example, trench sidewall angle and CD are both defined as a function of die location on the wafer x-axis, which is varied in the DOE. Figure 2 shows predicted quadrature error and sense frequency shift due to representative shifts in trench angle of from 0 to 0.2° and CD loss of from 0 to 150nm.

MEMS Blog Figure 1 Reverse engineered gyroscope, with suspension spring displayed in the call-out circle

Figure 1: Reverse engineered gyroscope, with suspension spring displayed in the call-out circle

 

Figure 2  Predicted gyroscope performance, as a function of die location.

Figure 2: Predicted gyroscope performance, as a function of die location.

Predicting device performance from simulation offers huge value for a product lifecycle. Here, the impact of process changes (trench profile and CD loss) on sensor performance and yield can be investigated without expensive and time-consuming build and test iterations. This enables engineers to digitally explore design ideas, and together with process experts, gain insights into design and process sensitivities, yield and failures modes – all to meet highly defined customer needs. Work continues in this exciting area and we look forward to providing additional updates a in future blog!

References

[1] Yan Loke (STMicroelectronics), “The THELMA MEMS Process from ST and Availability from the CMP Platform”, SEMICON West 2013

[2] Chipworks blog, “Apple uses Nine Degrees-of-Freedom Sensing in iPhone 4”

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Chris Welham
Chris Welham
Chris Welham, Ph.D. is the Technical Director of MEMS Applications at Coventor, where he manages Worldwide Application Engineering for Coventor’s MEMS software group. Chris has a BEng in Electronic Engineering and a PhD in Engineering, both from Warwick University. His Ph.D. work was focused on resonant pressure sensors. After obtaining his Ph.D., Chris worked for Druck developing commercial resonant sensors and interface electronics. Chris is based in Coventor's Paris office.

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Figure 1:   3D Gyroscope Model example with simulated pressure contours (left), and ambient cavity pressure vs. Q-factor graph with simulated and measured results (right) (courtesy: Murata)

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