Evidence map›Paper›PMID 38689905›Full record

Article3D printing and additive manufacturing2024

Impact of Beam Shape on Print Accuracy in Digital Light Processing Additive Manufacture.

Andrew Reid, James Windmill

Abstract read
In one paragraph

Article in 3D printing and additive manufacturing, 2024. 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
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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.

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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

2 authors.

Andrew ReidCenter for Ultrasonic Engineering, University of Strathclyde, Glasgow, United Kingdom.ORCID https://orcid.org/0000-0003-0511-4640
James WindmillCenter for Ultrasonic Engineering, University of Strathclyde, Glasgow, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Photopolymerization-based additive manufacturing requires selectively exposing a feedstock resin to ultraviolet (UV) light, which in digital light processing is achieved either using a digital micromirror device or a digital mask. The minimum tolerances and resolution for a multilayer process are separate for resolution through the Z-axis, looking through the thickness of a printed part, and resolution in the XY-axes, in the plane of the printed layer. The former depends wholly on the rate of attenuation of the incident UV light through the material relative to the mechanical motion of the build layer, while the latter is determined by a two-dimensional pattern of irradiance on the resin formed by the digital micromirror device or the digital mask. The size or the spacing of elements or pixels of this digital mask is frequently given by manufacturers as the "resolution" of the device, however, in practice the achievable resolution is first determined by the beam distribution from each pixel. The beam distribution is, as standard, modeled as a two-parameter Gaussian distribution but the key parameters of peak intensity and standard deviation of the beam are hidden to the user and difficult to measure directly. The ability of models based on the Gaussian distribution to correctly predict the polymerization of printed features in the microscale is also typically poor. In this study, we demonstrate an alternative model of beam distribution based on a heavy-tailed Lorentzian model, which is able to more accurately predict small build areas for both positive and negative features. We show a simple calibration method to derive the key space parameters of the beam distribution from measurements of a single-layer printed model. We propose that the standard Gaussian model is insufficient to accurately predict a print outcome as it neglects higher-order terms, such as beam skew and kurtosis, and in particular failing to account for the relatively heavy tails of the beam distribution. Our results demonstrate how the amendments to the beam distribution can avoid errors in microchannel formation, and better estimates of the true XY-axes resolution of the printer. The results can be used as the basis for voxel-based models of print solidification that allow software prediction of the photopolymerization process.

Indexed as

beam profilingdigital light processingpolymerization mechanics

Identifiers

PMID38689905
PMCPMC11057548

What OpenQuestion holds

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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.