Predicting strength distributions of MEMS structures using flaw size and spatial density.

Area of Science:

• Materials Science
• Mechanical Engineering
• Reliability Engineering

Background:

• Microelectromechanical systems (MEMS) are susceptible to flaws introduced during fabrication.
• Understanding flaw populations is critical for predicting MEMS device strength and reliability.
• Existing methods for flaw characterization in MEMS are limited.

Purpose of the Study:

• To determine and verify flaw populations in individual MEMS layers.
• To establish a methodology for strength prediction in MEMS devices.
• To investigate the relationship between flaw characteristics and layer processing.

Main Methods:

• Utilized specialized specimen geometry for flaw analysis.
• Applied probabilistic analysis to strength distributions of notched and tensile bar specimens.
• Employed scanning probe-based topographic measurements for verification.

Main Results:

• Determined average spatial density and flaw size distribution across MEMS layers.
• Verified flaw spacings using topographic measurements, identifying grain boundary grooves as failure controllers.
• Observed that strength-controlling features become less dense and smaller in higher layers.

Conclusions:

• The developed method accurately determines flaw populations in MEMS.
• Flaw characteristics evolve predictably through the MEMS layer stack.
• This approach is directly applicable to enhancing MEMS reliability and design predictions.