Evidence map›Paper›PMID 42801578›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Sulfur-Oxygen Competitive Coordination Allosteric Hydrogel for Triboelectric Nanogenerator-Based Intelligent Tactile Recognition.

Shixia Lan, Lin Zhang, Yunyun Dong, Yongyun Mao, Wanbiao Hu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 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
–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

5 authors.

Shixia Lan *Yunnan Key Laboratory of Electromagnetic Materials and Devices, School of Materials and Energy, Yunnan University, Kunming, People's Republic of China.
Lin Zhang *School of Software and AI, Yunnan University, Kunming, People's Republic of China.
Yunyun DongSchool of Software and AI, Yunnan University, Kunming, People's Republic of China.ORCID https://orcid.org/0009-0004-5251-9928
Yongyun MaoYunnan Key Laboratory of Electromagnetic Materials and Devices, School of Materials and Energy, Yunnan University, Kunming, People's Republic of China.ORCID https://orcid.org/0000-0001-9538-5772
Wanbiao HuYunnan Key Laboratory of Electromagnetic Materials and Devices, School of Materials and Energy, Yunnan University, Kunming, People's Republic of China.ORCID https://orcid.org/0000-0003-0180-9648

Funding

Electron Microscope Center of Yunnan UniversityMajor Science and Technology Projects of Yunnan Province 202602AB080007National Natural Science Foundation of China 22269025
6 · The paper itself

Abstract

Flexible sensing technologies based on triboelectric nanogenerators (TENG) have shown promise for wearable electronics and human‑machine interaction. However, existing hydrogel‑based TENGs suffer from an inherent trade‑off between interfacial adhesion and electrical output, and their material recognition capability is compromised in real‑wearing environments due to signal variations. Here, the authors propose a smart glove system integrating a dynamic Ag

Indexed as

dynamic coordination hydrogelelectronic skin (e‑skin)material recognitionsmart glovetriboelectric nanogenerator (TENG)

Identifiers

PMID42801578
PMCPMC13616259

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.