Estimating Verticality Parameters in Deep Reactive Ion Etching using MEMS Oscillators

In view of characterizing a vertical profile of deep reactive ion etching (DRIE) without making a cross section, we propose a method to estimate representative parameters, namely, the underetched cross-section area and the second moment of area. The test structure consists of a series of MEMS oscillators, the resonance frequency of which was plotted for varied spring stiffness and fitted to a physical model derived from geometry. The estimation from oscillation measurement was compared to the actual profile parameters obtained from visual observation, showing correlation R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>=0.556 and 0.913 for the underetch area and the second moment of area, respectively.

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Published
2025-03-24
DOI
https://doi.org/10.1109/icmts63811.2025.11068919
Primary Topic
Advanced Memory and Neural Computing
Type
article
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article

Estimating Verticality Parameters in Deep Reactive Ion Etching using MEMS Oscillators

Shun Yasunaga, Yoshio Mita
Advanced Memory and Neural Computing
article

Estimating Verticality Parameters in Deep Reactive Ion Etching using MEMS Oscillators

Shun Yasunaga, Yoshio Mita
article en

Abstract

In view of characterizing a vertical profile of deep reactive ion etching (DRIE) without making a cross section, we propose a method to estimate representative parameters, namely, the underetched cross-section area and the second moment of area. The test structure consists of a series of MEMS oscillators, the resonance frequency of which was plotted for varied spring stiffness and fitted to a physical model derived from geometry. The estimation from oscillation measurement was compared to the actual profile parameters obtained from visual observation, showing correlation R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>=0.556 and 0.913 for the underetch area and the second moment of area, respectively.

Tokyo University of Information Sciences (JP), The University of Tokyo (JP)
Openalex Percentile: Top 85%
Advanced Memory and Neural Computing
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Estimating Verticality Parameters in Deep Reactive Ion Etching using MEMS Oscillators — Shun Yasunaga, Yoshio Mita · (2025) | TGRS Research Map | TGRS