Evidence map›Paper›PMID 41156426›Full record

ArticleMicromachines2025

Automated Shear Strength Characterization at Micro Scales Based on a Microrobotic System.

Panbing Wang, Xintao Li, Xinyu Liu

Abstract read
In one paragraph

Article in Micromachines, 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

3 authors.

Panbing WangSchool of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.ORCID 0000-0003-1152-2456
Xintao LiSchool of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.
Xinyu LiuSchool of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.

Funding

Key Laboratory of Equipment Data Security and Guarantee Technology, Ministry of Education No.GDZB2024030100National Natural Science Foundation of China 62403127Natural Science Foundation of Jiangsu Province BK20220813
6 · The paper itself

Abstract

Mechanical properties are critical for characterizing and fabricating advanced materials. While current characterization methods are well-established for the nanoscale and larger millimeter-scale, a significant gap exists in automated testing at the microscale. To address this, we propose an automated, rapid characterization method based on a microrobotic system. We first develop a 6-degree-of-freedom (DOF) microrobotic system for sample alignment and testing. An image processing method is then designed for real-time sample recognition, supplying essential feedback for both alignment and testing procedures. Furthermore, a soft force sensor is fabricated and calibrated to ensure precise force measurement. Experiments on copper wires and graphite films demonstrate the method's high precision and reliability. This work provides a robust solution for microscale mechanical property characterization, offering significant potential for advanced material development.

Indexed as

mechanical propertymicromanipulationmicrorobotshear strength characterizationsoft sensors

Identifiers

PMID41156426
PMCPMC12566290

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.