Evidence map›Paper›PMID 32782990›Full record

ArticleInternational journal of bioprinting2020

Effects of Topology Optimization in Multimaterial 3D Bioprinting of Soft Actuators.

Ali Zolfagharian, Martin Denk, Abbas Z Kouzani, Mahdi Bodaghi, Saeid Nahavandi, Akif Kaynak

Erratum issuedAbstract read
In one paragraph

Article in International journal of bioprinting, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Machine learning boosts three-dimensional bioprinting.International journal of bioprinting · 2023
    Review
  3. Article
  4. Article
  5. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Ali ZolfagharianSchool of Engineering, Deakin University, Geelong 3216, Australia.
Martin DenkInstitute for Material and Building Research, Munich University of Applied Sciences, Munich, 80335, Germany.
Abbas Z KouzaniSchool of Engineering, Deakin University, Geelong 3216, Australia.
Mahdi BodaghiDepartment of Engineering, School of Science and Technology, Nottingham Trent University, Nottingham, NG11 8NS, United Kingdom.
Saeid NahavandiInstitute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Geelong, 3216, Australia.
Akif KaynakInstitute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Geelong, 3216, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, there has been a proliferation of soft robots and actuators that exhibit improved capabilities and adaptability through three-dimensional (3D) bioprinting. Flexibility and shape recovery attributes of stimuli-responsive polymers as the main components in the production of these dynamic structures enable soft manipulations in fragile environments, with potential applications in biomedical and food sectors. Topology optimization (TO), when used in conjunction with 3D bioprinting with optimal design features, offers new capabilities for efficient performance in compliant mechanisms. In this paper, multimaterial TO analysis is used to improve and control the bending performance of a bioprinted soft actuator with electrolytic stimulation. The multimaterial actuator performance is evaluated by the amplitude and rate of bending motion and compared with the single material printed actuator. The results demonstrated the efficacy of multimaterial 3D bioprinting optimization for the rate of actuation and bending.

Indexed as

MultimaterialSoft actuatorSoft robotThree-dimensional bioprintingTopology optimization

Identifiers

PMID32782990
PMCPMC7415864

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.