Evidence map›Paper›PMID 33918461›Full record

ArticlePolymers2021

Experimental Characterization Framework for SLA Additive Manufacturing Materials.

Jordi Martín-Montal, Jesus Pernas-Sánchez, David Varas

Abstract read
In one paragraph

Article in Polymers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

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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

3 authors.

Jordi Martín-MontalDepartment of Continuum Mechanics and Structural Analysis, University Carlos III of Madrid, Leganés, 28911 Madrid, Spain.ORCID 0000-0002-8841-1423
Jesus Pernas-SánchezDepartment of Continuum Mechanics and Structural Analysis, University Carlos III of Madrid, Leganés, 28911 Madrid, Spain.ORCID 0000-0003-0263-8983
David VarasDepartment of Continuum Mechanics and Structural Analysis, University Carlos III of Madrid, Leganés, 28911 Madrid, Spain.ORCID 0000-0003-1607-4517

Funding

Ministerio de Ciencia, Innovación y Universidades DPI2017-85073-RUniversidad Carlos III de Madrid 2013/00413/003Universidad Carlos III de Madrid 2014/00006/003
6 · The paper itself

Abstract

Additive manufacturing (AM) is driving a change in the industry not only regarding prototyping but due to the ease of including printed parts in final designs. Engineers and designers can go deeper into optimization and improvements of their designs without drawbacks of long manufacturing times. However, some drawbacks such as the limited available materials or uncertainty about mechanical properties and anisotropic behavior of 3D printed parts prevent use in large-scale production. To gain knowledge and confidence about printed materials it is necessary to know how they behave under different stress states and strain-rate regimes, and how some of the printing parameters may affect them. The present work proposes an experimental methodology framework to study and characterize materials printed by stereolithography (SLA) to clarify certain aspects that must be taken into account to broaden the use of this kind of material. To this end, tensile and compression tests at different strain rates were carried out. To study the influence of certain printing parameters on the printed material behavior, samples with different printing angles (θ = [0-90]) and different printing resolution (layer height of 50 and 100 µm) were tested. In addition, the effects of curing time and temperature were also studied. The testing specimens were manufactured in the non-professional SLA machine

Indexed as

3D printingadditive manufacturingdynamic regimemechanical behavior and characterizationpolymers (durable resin)printing parametersstereolithography manufacturing

Identifiers

PMID33918461
PMCPMC8038279

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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.