Evidence map›Paper›PMID 36080594›Full record

ArticlePolymers2022

A Comparative Study on the Self-Healing Characterizations and Formulation Optimization of Polyurea Coating.

Xinrui Shen, Zhenyuan Dong, Celine Sim, Yuanzhe Li

Open access · goldAbstract read
In one paragraph

Article in Polymers, 2022. 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
1.2field-weighted citation impact, top 25% of its field
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, 14 citations in OpenAlex.

  1. Review
  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

4 authors at 1 institution in 2 countries.

Xinrui ShenDepartment of Natural Sciences, University of Manchester, Manchester M13 9PL, UK.
Zhenyuan DongSchool of Materials Science & Engineering, Nanyang Technological University, Singapore 639798, Singapore.
Celine SimSchool of Materials Science & Engineering, Nanyang Technological University, Singapore 639798, Singapore.
Yuanzhe LiSchool of Materials Science & Engineering, Nanyang Technological University, Singapore 639798, Singapore.ORCID 0000-0001-7530-8286
Nanyang Technological University · SG

Funding

Ministry of Education Grant Call (Call 1/2018) _MSE (EP Code EP5P, Project ID 122018-T1-001-077)
6 · The paper itself

Abstract

Self-healing materials, especially self-healing polyurea/polyurethane, to replace traditional coating has been of increasing interest in the past decade. The frequency of regular maintenance work can also be reduced as the coating is capable of forming bonds at ruptured sites. This reduces the cost of maintenance and the risk involved in workers engaging in maintenance work. The extremely short curing time of polyurea coating could potentially outweigh the cost due to its short down time. With a high self-healing efficiency, self-healing polyurea could be the ultimate choice of protective coating. This report aims to find the optimum formulation for fabrication of polyurea with a high self-healing efficiency. This is conducted by changing the composition of the components chosen for formulation of polyurea. The choice of isocyanate and amine is varied to explore its impact on chain mobility and microphase separation, which are important factors affecting self-healing efficiency. A series of characterizations, including ATR-FTIR, DSC, optical microscope and mechanical tester, is used to analyze the factors affecting the self-healing efficiency of fabricated polyurea and to eventually determine the best formulation. The ideal formulation of toluene 2,4 diisocyanate-amine (TDI-P1000) polyurea managed to achieve a self-healing of 42%. Further studies could be done to include multiple healing mechanisms after different area of polyurea to boost its self-healing efficiency after repeated healing.

Indexed as

formulation optimizationpolyurea coatingself-healingself-healing mechanism

Identifiers

PMID36080594
PMCPMC9460880
OpenAlexW4293770067

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.