Evidence map›Paper›PMID 40330049›Full record

ArticleNational science review2025

Accessing pluripotent drones through reprogramming of dynamic soft self-healing chemical growth.

Kecheng Qin, Wei Tang, Xinyu Guo, Huxiu Xu, Yiding Zhong, Yonghao Wang, Qincheng Sheng, Huayong Yang, Jun Zou

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in National science review, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Bioinspired Twisted Artificial Muscles with Enhanced Performance for Underwater Applications.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  2. Self-Healing and Reprocessable Soft Robots Using 3D Digital Light Printing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    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

9 authors.

Kecheng QinState Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310058, China.
Wei TangState Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310058, China.ORCID https://orcid.org/0000-0002-2018-5474
Xinyu GuoState Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310058, China.
Huxiu XuState Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310058, China.
Yiding ZhongState Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310058, China.
Yonghao WangState Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310058, China.
Qincheng ShengState Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310058, China.
Huayong YangState Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310058, China.
Jun ZouState Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310058, China.ORCID https://orcid.org/0000-0003-2443-3516

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The functions of drones that are implemented by existing design paradigms are usually fixed and do not have the possibility of further 'differentiation'. Inspired by the biological concept of pluripotency, here we report a pluripotent drone that can further 'differentiate' into a series of drones with different functions to perform a variety of challenging tasks. To realize this concept, we propose a method of reprogrammable dynamic soft self-healing chemical growth (R-growth), by which the pluripotent drone can grow specific 'organs' to achieve corresponding functions, and after completing the corresponding tasks, these 'organs' can be retracted. Furthermore, these 'organs' are able to respond to possible damage through rapid self-healing (∼3.2 s, >1000 times faster than the self-healing of existing similar membranes). R-growth is large-scale (>1.5 m), fast (0.15 m/s), lightweight (∼5 g, 1/20 the weight of traditional micro air pumps), self-contained and free-wheeling. This method can be applied to various existing drones to significantly extend their functions and to enable an unprecedented range of tasks. This work realizes the growth, retraction, and switching of drone 'organs' with any function, while such ability of macro robots or humans, to date, only exists in science fiction movies.

Indexed as

chemical growthdynamic reprogramming growthfluidic soft actuationpluripotent dronesself-healing

Identifiers

PMID40330049
PMCPMC12051850

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.