Evidence map›Paper›PMID 32719508›Full record

ArticleNature materials2020

Biosynthetic self-healing materials for soft machines.

Abdon Pena-Francesch, Huihun Jung, Melik C Demirel, Metin Sitti

Abstract read
In one paragraph

Article in Nature materials, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.

0numbers the graph read from it
0cells of the map it votes in
67citing 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

67 citing papers in PubMed.

  1. Review
  2. Ecosystem-Centered Robot Design: Toward Ecoresorbable Sustainability Robots (ESRs).Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  3. Article
  4. Article
  5. Article
  6. Autonomous Polymer Frameworks for Sustainable Tissue-Interfaced Plastic Bioelectronics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  7. Review
  8. Impact of biomanufacturing protein fibers on achieving sustainable development.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Toward Autonomous Self-Healing in Soft Robotics: A Review and Perspective for Future Research.Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) · 2025
    Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

7 more citing papers are in PubMed but not listed here.

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

4 authors.

Abdon Pena-FranceschPhysical Intelligence Department, Max Planck Institute for Intelligent Systems, Stuttgart, Germany.ORCID http://orcid.org/0000-0002-7779-1651
Huihun JungCenter for Research on Advanced Fiber Technologies (CRAFT), Materials Research Institute, Huck Institutes of the Life Sciences, and Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA, USA.
Melik C DemirelCenter for Research on Advanced Fiber Technologies (CRAFT), Materials Research Institute, Huck Institutes of the Life Sciences, and Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA, USA. melik@psu.edu.ORCID http://orcid.org/0000-0003-0466-7649
Metin SittiPhysical Intelligence Department, Max Planck Institute for Intelligent Systems, Stuttgart, Germany. sitti@is.mpg.de.ORCID http://orcid.org/0000-0001-8249-3854

Funding

European Research Council 834531
6 · The paper itself

Abstract

Self-healing materials are indispensable for soft actuators and robots that operate in dynamic and real-world environments, as these machines are vulnerable to mechanical damage. However, current self-healing materials have shortcomings that limit their practical application, such as low healing strength (below a megapascal) and long healing times (hours). Here, we introduce high-strength synthetic proteins that self-heal micro- and macro-scale mechanical damage within a second by local heating. These materials are optimized systematically to improve their hydrogen-bonded nanostructure and network morphology, with programmable healing properties (2-23 MPa strength after 1 s of healing) that surpass by several orders of magnitude those of other natural and synthetic soft materials. Such healing performance creates new opportunities for bioinspired materials design, and addresses current limitations in self-healing materials for soft robotics and personal protective equipment.

Indexed as

Mechanical PhenomenaBiocompatible MaterialsEquipment DesignKineticsRoboticsTemperatureBiocompatible Materials

Identifiers

PMID32719508
PMCPMC7610468

What OpenQuestion holds

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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.