MEMS High Aspect Ratio Trench Three-Dimensional Measurement Using Through-Focus Scanning Optical Microscopy and Deep Learning Method

High-aspect-ratio structures have become increasingly important in MEMS devices. In situ, real-time critical dimension and depth measurement for high-aspect-ratio structures is critical for optimizing the deep etching process. Through-focus scanning optical microscopy (TSOM) is a high-throughput and...

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Bibliographic Details
Published inApplied sciences Vol. 12; no. 17; p. 8396
Main Authors Li, Guannan, Shi, Junkai, Gao, Chao, Jiang, Xingjian, Huo, Shuchun, Cui, Chengjun, Chen, Xiaomei, Zhou, Weihu
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.09.2022
Subjects
Algorithms
convolutional neural network
Deep learning
Depth measurement
Dimensional analysis
Dimensional measurement
Etching
High aspect ratio
high-aspect-ratio structure
Light microscopy
Measurement methods
Methods
Microelectromechanical systems
Neural networks
Optical measurement
optical micro-nano metrology
Optical microscopy
Scanning electron microscopy
Silicon
Simulation
three-dimensional non-destructive measurement
through-focus scanning optical microscopy
Trenches
China
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Summary:High-aspect-ratio structures have become increasingly important in MEMS devices. In situ, real-time critical dimension and depth measurement for high-aspect-ratio structures is critical for optimizing the deep etching process. Through-focus scanning optical microscopy (TSOM) is a high-throughput and inexpensive optical measurement method for critical dimension and depth measurement. Thus far, TSOM has only been used to measure targets with dimension of 1 μm or less, which is far from sufficient for MEMS. Deep learning is a powerful tool that improves the TSOM performance by taking advantage of additional intensity information. In this work, we propose a convolutional neural network model-based TSOM method for measuring individual high-aspect-ratio trenches on silicon with width up to 30 μm and depth up to 440 μm. Experimental demonstrations are conducted and the results show that the proposed method is suitable for measuring the width and depth of high-aspect-ratio trenches with a standard deviation and error of approximately a hundred nanometers or less. The proposed method can be applied to the semiconductor field.
ISSN:2076-3417
2076-3417
DOI:10.3390/app12178396