Evidence map›Paper›PMID 33911075›Full record

ArticleNature communications2021

3D-printed self-healing hydrogels via Digital Light Processing.

Matteo Caprioli, Ignazio Roppolo, Annalisa Chiappone, Liraz Larush, Candido Fabrizio Pirri, Shlomo Magdassi

Abstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.

0numbers the graph read from it
0cells of the map it votes in
72citing 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

72 citing papers in PubMed.

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  10. Mechanomedicine.Nature reviews bioengineering · 2026
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12 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

6 authors.

Matteo CaprioliDepartment of Applied Science and Technology, Politecnico di Torino, Turin, Italy.
Ignazio RoppoloDepartment of Applied Science and Technology, Politecnico di Torino, Turin, Italy. ignazio.roppolo@polito.it.ORCID 0000-0001-7602-4015
Annalisa ChiapponeDepartment of Applied Science and Technology, Politecnico di Torino, Turin, Italy.
Liraz LarushCasali Center for Applied Chemistry, Institute of Chemistry, The Hebrew University of Jerusalem, Edmond J. Safra Campus - Givat Ram, Jerusalem, Israel.
Candido Fabrizio PirriDepartment of Applied Science and Technology, Politecnico di Torino, Turin, Italy.ORCID 0000-0003-4991-9459
Shlomo MagdassiCasali Center for Applied Chemistry, Institute of Chemistry, The Hebrew University of Jerusalem, Edmond J. Safra Campus - Givat Ram, Jerusalem, Israel. magdassi@mail.huji.ac.il.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Self-healing hydrogels may mimic the behavior of living tissues, which can autonomously repair minor damages, and therefore have a high potential for application in biomedicine. So far, such hydrogels have been processed only via extrusion-based additive manufacturing technology, limited in freedom of design and resolution. Herein, we present 3D-printed hydrogel with self-healing ability, fabricated using only commercially available materials and a commercial Digital Light Processing printer. These hydrogels are based on a semi-interpenetrated polymeric network, enabling self-repair of the printed objects. The autonomous restoration occurs rapidly, at room temperature, and without any external trigger. After rejoining, the samples can withstand deformation and recovered 72% of their initial strength after 12 hours. The proposed approach enables 3D printing of self-healing hydrogels objects with complex architecture, paving the way for future applications in diverse fields, ranging from soft robotics to energy storage.

Indexed as

Printing, Three-DimensionalGuided Tissue RegenerationHumansHydrogelsPolymersHydrogelsPolymers

Identifiers

PMID33911075
PMCPMC8080574

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.