Evidence map›Paper›PMID 38116226›Full record

Article3D printing and additive manufacturing2023

One-Shot 3D Printed Soft Device Actuated Using Metal-Filled Channels and Sensed with Embedded Strain Gauge.

Antonio Pavone, Gianni Stano, Gianluca Percoco

Abstract read
In one paragraph

Article in 3D printing and additive manufacturing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

3 authors.

Antonio PavoneDepartment of Mechanics, Mathematics and Management, Polytechnic of Bari, Bari, Italy.ORCID https://orcid.org/0000-0003-3089-5848
Gianni StanoDepartment of Mechanics, Mathematics and Management, Polytechnic of Bari, Bari, Italy.ORCID https://orcid.org/0000-0002-6676-8472
Gianluca PercocoDepartment of Mechanics, Mathematics and Management, Polytechnic of Bari, Bari, Italy.ORCID https://orcid.org/0000-0002-4438-0450

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this article, the multimaterial extrusion (M-MEX) technology is used to fabricate, in a single step, a three-dimensional printed soft electromagnetic (EM) actuator, based on internal channels, filled with soft liquid metal (Galinstan) and equipped with an embedded strain gauge, for the first time. At the state of the art, M-MEX techniques result underexploited for the manufacture of soft EM actuators: only traditional manufacturing approaches are used, resulting in many assembly steps. The main features of this work are as follows: (1) one shot fabrication, (2) smart structure equipped with sensor unit, and (3) scalability. The actuator was tested in conjunction with a commercial magnet, showing a bending angle of 22.4° (when activated at 4A), a relative error of 0.7%, and a very high sensor sensitivity of 49.7 Two more examples, showing all the potentialities of the proposed approach, are presented: a jumping frog-inspired soft robot and a dual independent two-finger actuator. This article aims to push the role of extrusion-based additive manufacturing for the fabrication of EM soft robots: several advantages such as portability, no cooling systems, fast responses, and noise reduction can be achieved by exploiting the proposed actuation system compared to the traditional and widespread actuation mechanisms (shape memory polymers, shape memory alloys, pneumatic actuation, and cable-driven actuation).

Indexed as

additive manufacturingelectromagnetic soft actuatorembedded sensorGalinstanmaterial extrusionsoft actuator

Identifiers

PMID38116226
PMCPMC10726192

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.