Evidence map›Paper›PMID 37242843›Full record

ArticlePolymers2023

Influence of 3D Microstructure Pattern and Infill Density on the Mechanical and Thermal Properties of PET-G Filaments.

Lucas Lopes, Daniel Reis, Adilson Paula Junior, Manuela Almeida

Abstract read
In one paragraph

Article in Polymers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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.

Lucas LopesDepartment of Civil Engineering, ISISE, ARISE, University of Minho, 4804-533 Guimaraes, Portugal.
Daniel ReisDepartment of Civil Engineering, ISISE, ARISE, University of Minho, 4804-533 Guimaraes, Portugal.
Adilson Paula JuniorDepartment of Civil Engineering, ISISE, ARISE, University of Minho, 4804-533 Guimaraes, Portugal.ORCID 0000-0002-1997-7087
Manuela AlmeidaDepartment of Civil Engineering, ISISE, ARISE, University of Minho, 4804-533 Guimaraes, Portugal.ORCID 0000-0003-2713-6322

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to evaluate the thermal and mechanical performances of PET-G thermoplastics with different 3D microstructure patterns and infill densities. The production costs were also estimated to identify the most cost-effective solution. A total of 12 infill patterns were analysed, including Gyroid, Grid, Hilbert curve, Line, Rectilinear, Stars, Triangles, 3D Honeycomb, Honeycomb, Concentric, Cubic, and Octagram spiral with a fixed infill density of 25%. Different infill densities ranging from 5% to 20% were also tested to determine the best geometries. Thermal tests were conducted in a hotbox test chamber and mechanical properties were evaluated using a series of three-point bending tests. The study used printing parameters to meet the construction sector's specific needs, including a larger nozzle diameter and printing speed. The internal microstructures led to variations of up to 70% in thermal performance and up to 300% in mechanical performance. For each geometry, the mechanical and thermal performance was highly correlated with the infill pattern, where higher infill improved thermal and mechanical performances. The economic performance showed that, in most cases, except for the Honeycomb and 3D Honeycomb, there were no significant cost differences between infill geometries. These findings can provide valuable insights for selecting the optimal 3D printing parameters in the construction industry.

Indexed as

additive manufacturingfusion deposition modellingPET-G filamentsthermomechanical testing

Identifiers

PMID37242843
PMCPMC10222068

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.