Evidence map›Paper›PMID 42411832›Full record

ArticleAdvanced materials (Deerfield Beach, Fla.)2026

Feed-Draw Printing Enables Monolithically Integrated Flexible Sensors With High Interfacial Toughness and Wide Linear Range.

Xingxiang Li, Ziqi Hua, Yuxuan Sun, Boxi Sun, Dongxiao Li, Jiyang Wu, Zhengchao Du, Mengting Wang, Hao Jing, Yi Liu and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Advanced materials (Deerfield Beach, Fla.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

15 authors.

Xingxiang LiInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, China.
Ziqi HuaInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, China.
Yuxuan SunInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, China.
Boxi SunInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, China.
Dongxiao LiInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, China.
Jiyang WuInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, China.
Zhengchao DuInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, China.
Mengting WangInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, China.
Hao JingInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, China.
Yi LiuInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, China.
Hongbin ZangSchool of Manufacturing Science and Engineering, Southwest University of Science and Technology, Mianyang, China.
Weihua LiSchool of Mechanical, Materials, Mechatronic and Biomedical Engineering, University of Wollongong, Wollongong, New South Wales, Australia.
Tingrui PanSuzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, China.
Shiwu ZhangInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, China.
Mujun LiInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, China.ORCID https://orcid.org/0000-0001-7488-5364

Funding

Fundamental Research Funds for the Central UniversitiesMajor Project of Anhui Province's Science and Technology Innovation 202423h08050003National Key Research and Development Program of China 2020YFA0710100University of Science and Technology of China-Southwest University of Science and Technology Counterpart Cooperation and Development KY2090002503USTC Research Funds of the Double First-Class Initiative YD2090003002
6 · The paper itself

Abstract

Flexible sensors are essential for wearable electronics and robotic perception, yet their practical deployment is fundamentally constrained by the compromise between sensing sensitivity and mechanical durability, as well as the deficiency in achieving robust integration with other functional components. Here, we report a monolithic microcone capacitive sensor (MMCS) fabricated via a feed-draw printing (FDP) strategy, which enables the direct fabrication of programmable microcone morphologies and in situ co-curing across dielectric and electrode layers. This strategy generates continuous, covalently interlinked interfaces with interfacial toughness of up to 1 547 J m

Indexed as

3D printingdirect ink writingflexible capacitive sensorflexible electronicswearable technology

Identifiers

PMID42411832
PMCPMC13486200

What OpenQuestion holds

Textmetadata
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.