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

Cook, Robert F.; DelRio, Frank W.; Boyce, Brad L.

doi:10.1038/s41378-019-0093-y

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

Journal Article · Mon Nov 04 00:00:00 EST 2019 · Microsystems & Nanoengineering (Online)

DOI:https://doi.org/10.1038/s41378-019-0093-y· OSTI ID:1624021

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^[2]; Boyce, Brad L. ^[3]

National Inst. of Standards and Technology (NIST), Gaithersburg, MD (United States). Materials Measurement Science Division, Material Measurement Laboratory
National Inst. of Standards and Technology (NIST), Gaithersburg, MD (United States). Materials Measurement Science Division, Applied Chemicals and Materials Division
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Materials Science and Engineering Center

The populations of flaws in individual layers of microelectromechanical systems (MEMS) structures are determined and verified using a combination of specialized specimen geometry, recent probabilistic analysis, and topographic mapping. Strength distributions of notched and tensile bar specimens are analyzed assuming a single flaw population set by fabrication and common to both specimen geometries. Both the average spatial density of flaws and the flaw size distribution are determined and used to generate quantitative visualizations of specimens. Scanning probe-based topographic measurements are used to verify the flaw spacings determined from strength tests and support the idea that grain boundary grooves on sidewalls control MEMS failure. The findings here suggest that strength controlling features in MEMS devices increase in separation, i.e., become less spatially dense, and decrease in size, i.e., become less potent flaws, as processing proceeds up through the layer stack. The method demonstrated for flaw population determination is directly applicable to strength prediction for MEMS reliability and design.

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Research Organization:: Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Basic Energy Sciences (BES)

Grant/Contract Number:: NA0003525

OSTI ID:: 1624021

Alternate ID(s):: OSTI ID: 1870472

Report Number(s):: SAND2022-3867J; PII: 93

Journal Information:: Microsystems & Nanoengineering (Online), Vol. 5, Issue 1; ISSN 2055-7434

Publisher:: Springer NatureCopyright Statement

Country of Publication:: United States

Language:: English

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