Evidence map›Paper›PMID 40877229›Full record

ArticleMicrosystems & nanoengineering2025

Fast and accurate measurement of high aspect ratio MEMS trench array with optical lattice illumination.

Xiangjie Li, Xinqi Sui, Dengfeng Kuang

Abstract read
In one paragraph

Article in Microsystems & nanoengineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Xiangjie Li
Xinqi SuiInstitute of Modern Optics, Nankai University, Tianjin Key Laboratory of Micro-scale Optical Information Science and Technology, Tianjin, China.
Dengfeng KuangInstitute of Modern Optics, Nankai University, Tianjin Key Laboratory of Micro-scale Optical Information Science and Technology, Tianjin, China. dfkuang@nankai.edu.cn.ORCID http://orcid.org/0000-0002-7055-061X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The high aspect ratio (HAR) micro-electro-mechanical system trench array is a key component for the miniaturization of micro sensors, actuators, and other advanced precision equipment, with broad application prospects in defense, security, aerospace, energy, and other fields. Therefore, accurate and efficient measurement of the aspect ratio of microstructures will become a crucial method for monitoring and ensuring the reliability and stability of the device fabrication process. This paper presents a novel method that combines the lattice light field generated by a micro-axicon array with microscopic imaging technology to accurately measure the width and depth of HAR micro-trench structures. We designed and constructed a dedicated experimental system, initially using monochromatic microscopic imaging and edge extraction algorithms to obtain the width information of the trenches. Subsequently, the trench depth was measured using the diffraction lattice light field generated by the micro-axicon array. Experimental results indicate that as the light field propagates from the top to the bottom of the trench, the light spots in the lattice light field shift in position due to the presence of diffraction angles, with the displacement being closely related to the trench depth. A mapping between the displacement and depth is established through geometric relationships, enabling the calculation of the trench depth. We tested nine trench samples with different aspect ratios, with the maximum aspect ratio reaching 58.12. The experimental results, compared with the scanning electron microscope measurement values, show that the measurement errors are all <9%.

Identifiers

PMID40877229
PMCPMC12394687

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.