Evidence map›Paper›PMID 40676116›Full record

ArticleScientific reports2025

Dynamic 3D profiling of microscale surface using a MEMS mirror laser differential confocal microscope.

Qingjiu Chen, Donghai Yang, Feifei Wang, Wen Jung Li

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Qingjiu Chen *Department of Mechanical Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong.
Donghai Yang *Department of Mechanical Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong.
Feifei WangDepartment of Electrical and Electronic Engineering, The University of Hong Kong, Pok Fu Lam, Hong Kong. ffwang@eee.edu.hk.
Wen Jung LiDepartment of Mechanical Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong. wenjli@cityu.edu.hk.

Funding

Hong Kong Research Grants Council, General Research Fund 11216120
6 · The paper itself

Abstract

Several advanced techniques have been used for 3D micro-surface profiling, such as white light interferometry, confocal microscopy, and atomic force microscopy. However, a major technological limitation shared among these methods is the difficulty of imaging dynamic samples in real-time at high resolution. Specifically, profiling rapidly changing or moving surfaces at nanoscale 3D spatial resolution remains a challenging task. We demonstrate here a high-speed MEMS mirror-based laser differential confocal microscope for dynamic 3D micro-surface profiling. The MEMS mirror enables 2D scanning of 1200 × 650 pixels with a 140 × 90 μm field of view at 80 frames per second. Using laser differential confocal detection, the system achieves 25 nm axial resolution. The objective-space telecentric laser projection results in uniform axial response across the field of view, simplifying data acquisition and processing. These capabilities enable real-time 3D micro/nano scale profiling of dynamically changing surfaces at 80 frames per second without requiring motion stages. The system's substantial increase in imaging throughput enables, for the first time, real-time 3D profiling of dynamic microscale surface topographies at nanometer-level axial resolutions. The high-speed 3D profiling enabled by this system provides new insights for process development and quality control in precision micro/nano fabrication.

Indexed as

Confocal microscopyDynamic 3D surface profilingOptical 3D sensingScanning MEMS mirror

Identifiers

PMID40676116
PMCPMC12271404

What OpenQuestion holds

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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.