Evidence map›Paper›PMID 39274049›Full record

ArticlePolymers2024

Solid State Additive Manufacturing of Thermoset Composites.

Bo Hong, Kaifeng Wang, Yang Li, Shuhan Ren, Peihua Gu

Abstract read
In one paragraph

Article in Polymers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Bo HongKey Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin 300354, China.
Kaifeng WangKey Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin 300354, China.ORCID 0000-0001-6827-329X
Yang LiSchool of Materials Science and Engineering, Tianjin University, Tianjin 300354, China.ORCID 0000-0001-9424-8485
Shuhan RenInternational Institute for Innovative Design and Intelligent Manufacturing Tianjin University in Zhejiang, Shaoxing 312000, China.
Peihua GuKey Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin 300354, China.

Funding

National Natural Science Foundation of China 52075367
6 · The paper itself

Abstract

Softening and subsequent deformation are significant challenges in additive manufacturing of thermal-curable thermosets. This study proposes an approach to address these issues, involving the preparation of thermosetting composite powders with distinct curing temperatures, the utilization of cold spray additive manufacturing (CSAM) for sample fabrication, and the implementation of stepwise curing for each component. To validate the feasibility of this approach, two single-component thermosetting powders P1 and P2 and their composite powder C were subjected to CSAM and stepwise curing. From the sample morphology observation and deposition/curing mechanism investigation based on thermomechanical analysis and differential scanning calorimetry, it is found that severe plastic deformation occurs during the CSAM process, accompanied by heat generation, leading to local melting to promote a good bond at the contact surface of the particles and form small pores. During the progressive curing, the samples printed using C demonstrate superior deformation resistance compared with those using P1 and P2, and the curing time is reduced from 16.7 h to 1.5 h, due to the sequential curing reactions of P1 and P2 components in composite C, allowing the uncured P2 and cured P1 to alternately remain solid for providing structural support and minimizing deformation.

Indexed as

additive manufacturingcold spraythermosets

Identifiers

PMID39274049
PMCPMC11397270

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.