Evidence map›Paper›PMID 40050263›Full record

ArticleNature communications2025

Addressable and perceptible dynamic reprogram of ferromagnetic soft machines.

Yuxuan Sun, Boxi Sun, Xiang Cui, Weihua Li, Yue Zhang, Li He, Shutong Nong, Zhengqing Zhu, Jiyang Wu, Dongxiao Li and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 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. Article
  2. Magneto-X Effects in Magnetic Soft Materials and Their Applications.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
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

14 authors.

Yuxuan Sun *Institute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, 230026, Hefei, China.
Boxi Sun *Institute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, 230026, Hefei, China.ORCID http://orcid.org/0000-0002-1244-8019
Xiang Cui *School of Computer Science and Technology, University of Science and Technology of China, 230026, Hefei, China.
Weihua LiSchool of Mechanical, Materials, Mechatronic and Biomedical Engineering, University of Wollongong, Wollongong, NSW 2522, Australia.
Yue ZhangThe First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, 230000, Hefei, Anhui, China.
Li HeThe First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, 230000, Hefei, Anhui, China.ORCID http://orcid.org/0000-0003-2155-606X
Shutong NongInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, 230026, Hefei, China.
Zhengqing ZhuInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, 230026, Hefei, China.
Jiyang WuInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, 230026, Hefei, China.
Dongxiao LiInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, 230026, Hefei, China.
Xingxiang LiInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, 230026, Hefei, China.
Shiwu ZhangInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, 230026, Hefei, China. swzhang@ustc.edu.cn.ORCID http://orcid.org/0000-0001-7118-7704
Xiangyang LiSchool of Computer Science and Technology, University of Science and Technology of China, 230026, Hefei, China. xiangyangli@ustc.edu.cn.
Mujun LiInstitute of Humanoid Robots, Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, 230026, Hefei, China. lmn@ustc.edu.cn.ORCID http://orcid.org/0000-0001-7488-5364

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Soft machines actuated by external magnetic fields have gained significant attention for their potential to interact with living organisms and complex environments. However, their adaptability and functionality are often limited by rigid magnetization during operation. In this work, we introduce dynamically reprogrammable magnetic soft machines with in situ reconfigurable magnetization profiles during operations, achieved through the synergy of various magnetic fields. A flexible resonant circuit is integrated into the machine body, enabling addressable and perceptible heating of specific regions via high-frequency fields of varying frequencies. The machine body is composed of microbeads made from a low-melting-point alloy and NdFeB microparticles. When heated, the alloy liquefies, allowing the rotation of NdFeB microparticles under a 40 mT pulsed programming field. Upon cooling, the new configuration is locked in place. This reprogramming process is equally effective for single or multiple machines, enabling versatile multi-pattern deformation of individual machines and cooperation of multiple ones. Furthermore, by incorporating addressable thermal actuation, we demonstrate in situ assembly of multiple robots. This work may enable a broad spectrum of magnetic soft machines with enhanced functionalities.

Identifiers

PMID40050263
PMCPMC11885537

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.