Evidence map›Paper›PMID 42045166›Full record

ArticleMicrosystems & nanoengineering2026

Magnetic-induced deformation driving triboelectric sensor with dual-mode perception for magnetic field and contacting pressure.

Tingting Zhang, Shengxin Wang, Shuzhe Qin, Zhenqiu Gao, Weiwei Zhang, Tingyu Zeng, Azamat Yeshmukhametov, Gulnur Kalimuldina, Hao Lei, Zhen Wen

Abstract read
In one paragraph

Article in Microsystems & nanoengineering, 2026. 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
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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

10 authors.

Tingting ZhangDepartment of Chemistry and Chemical Engineering, Heze University, Heze, China.
Shengxin WangDepartment of Chemistry and Chemical Engineering, Heze University, Heze, China.
Shuzhe QinInstitute of Functional Nano and Soft Materials (FUNSOM), Joint International Research Laboratory of Carbon-Based Functional Materials and Devices, Soochow University, Suzhou, China.
Zhenqiu GaoInstitute of Functional Nano and Soft Materials (FUNSOM), Joint International Research Laboratory of Carbon-Based Functional Materials and Devices, Soochow University, Suzhou, China.
Weiwei ZhangDepartment of Chemistry and Chemical Engineering, Heze University, Heze, China.
Tingyu ZengDepartment of Communications and Networking, Xi'an Jiaotong-Liverpool University, Suzhou, China.
Azamat YeshmukhametovDepartment of Mechanical and Aerospace Engineering, Department of Robotics Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Astana, Kazakhstan.
Gulnur KalimuldinaDepartment of Mechanical and Aerospace Engineering, Department of Robotics Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Astana, Kazakhstan.
Hao LeiInstitute of Functional Nano and Soft Materials (FUNSOM), Joint International Research Laboratory of Carbon-Based Functional Materials and Devices, Soochow University, Suzhou, China. haolei@suda.edu.cn.
Zhen WenInstitute of Functional Nano and Soft Materials (FUNSOM), Joint International Research Laboratory of Carbon-Based Functional Materials and Devices, Soochow University, Suzhou, China. wenzhen2011@suda.edu.cn.ORCID http://orcid.org/0000-0001-9780-6876

Funding

National Natural Science Foundation of China (National Science Foundation of China) 62304184Natural Science Foundation of Jiangsu Province (Jiangsu Provincial Natural Science Foundation) BK20240152Natural Science Foundation of Shandong Province (Shandong Provincial Natural Science Foundation) ZR20220B132Natural Science Foundation of Shandong Province (Shandong Provincial Natural Science Foundation) ZR20230B107
6 · The paper itself

Abstract

Integrating magnetic field evasion and obstacle avoidance is crucial for the safe operation of intelligent robots, yet the limited sensitivity and discrete structure of magnetic field/pressure dual-mode sensors hinder their broader application. In this work, we present a dual-mode triboelectric sensor (DM-TS) that achieves noncontact magnetic field sensing and contact pressure sensing by incorporating ferrofluid as a triboelectric material. Under varying magnetic field intensities or directions, it redistributes along the magnetic field lines, modulating its contact area with spiked silicone rubber to generate distinct electrical signals for magnetic field sensing. The DM-TS exhibits a longitudinal magnetic field sensitivity of 11.35 V/T in the linear response region ranging from 63 ~ 277 mT, which is comparable to existing flexible magnetosensitive devices or commercial Hall effect sensors. For contact sensing, applied pressure deforms the silicone rubber with spike structures, altering the contact area between triboelectric layers and producing corresponding electrical outputs. The pressure sensitivity increases with the applied pressure range, reaching 370.56 mV/kPa within the 19.37-27.3 kPa range. As a proof-of-concept for intelligent robotic systems, the DM-TS has been integrated into an unmanned ground vehicle (UGV), successfully demonstrating simultaneous strong magnetic field evasion and obstacle avoidance.

Identifiers

PMID42045166
PMCPMC13121769

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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.