Grayscale Digital Light Processing and Post‐Treatment for the Fabrication of 3D‐Printed Polymer Blends

Hergert, John; Uzcategui, Asais Camila; Muralidharan, Archish; Crespo-Cuevas, Victor; Ferguson, Virginia L.; McLeod, Robert R.

doi:10.1002/adem.202101543

Cited by 6 publications

(1 citation statement)

References 45 publications

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“…Grayscaling at the edge of local positive or negative features, referred to as pixel blending or antialiasing, can eliminate stairstep effects (i.e., pixelation artifacts) and enhance feature accuracy. [7,10,11] Further uses of grayscale seek to limit the degree of conversion of the photopolymerization reaction to introduce controlled mechanical heterogeneity in final parts [12,13] and can reduce stress concentration. [14] Such heterogeneity can be amplified by means of dual-cure resin systems, [15] wherein a secondary cure step can result in an elastic modulus range spanning orders of magnitude.…”

Section: Introductionmentioning

confidence: 99%

A Data‐Driven Approach to Complex Voxel Predictions in Grayscale Digital Light Processing Additive Manufacturing Using U‐Nets and Generative Adversarial Networks

Killgore

Kolibaba

Caplins

et al. 2023

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Data‐driven U‐net machine learning (ML) models, including the pix2pix conditional generative adversarial network (cGAN), are shown to predict 3D printed voxel geometry in digital light processing (DLP) additive manufacturing. A confocal microscopy‐based workflow allows for the high‐throughput acquisition of data on thousands of voxel interactions arising from randomly gray‐scaled digital photomasks. Validation between prints and predictions shows accurate predictions with sub‐pixel scale resolution. The trained cGAN performs virtual DLP experiments such as feature size‐dependent cure depth, anti‐aliasing, and sub‐pixel geometry control. The pix2pix model is also applicable to larger masks than it is trained on. To this end, the model can qualitatively inform layer‐scale and voxel‐scale print failures in real 3D‐printed parts. Overall, machine learning models and the data‐driven methodology, exemplified by U‐nets and cGANs, show considerable promise for predicting and correcting photomasks to achieve increased precision in DLP additive manufacturing.

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Section: Introductionmentioning

confidence: 99%

A Data‐Driven Approach to Complex Voxel Predictions in Grayscale Digital Light Processing Additive Manufacturing Using U‐Nets and Generative Adversarial Networks

Killgore

Kolibaba

Caplins

et al. 2023

Small

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Multi‐Jet Fusion 3D Voxel Printing of Conductive Elastomers

2022

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3D voxel printing enables the fabrication of parts with site‐specific materials and properties at voxel‐scale resolution, while the current research mainly focuses on the variations in mechanical properties and colors. In this work, the design and fabrication of voxelated conductive elastomers using Multi Jet Fusion 3D voxel printing actualized by a newly developed multifunctional agent (MA) are investigated. The MA, mainly consisting of carbon nanotubes and poly(3,4‐ethylenedioxythiophene) polystyrene sulfonate, serves as an infrared‐absorbing colorant, a reinforcement, and a conductive filler simultaneously. By controlling the drop‐on‐demand dispensing of the agents on thermoplastic polyurethane powder, the electrical conductivity across a single printed part can be tailored over a wide range from 10−10 to 10−1 S cm−1 at a voxel resolution of ≈100 µm. Assembly‐free strain sensors comprising conductive sensing layers and insulating frames are fabricated to demonstrate the capability of the technique in manufacturing all‐printed wearable devices.

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Design of grayscale digital light processing 3D printing block by machine learning and evolutionary algorithm

Zhao

Zhang²,

Dong³

et al. 2022

Composites Communications

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Grayscale Digital Light Processing and Post‐Treatment for the Fabrication of 3D‐Printed Polymer Blends

Abstract: The ORCID identification number(s) for the author(s) of this article can be found under https://doi.org/10.1002/adem.202101543.

Cited by 6 publications

References 45 publications

A Data‐Driven Approach to Complex Voxel Predictions in Grayscale Digital Light Processing Additive Manufacturing Using U‐Nets and Generative Adversarial Networks

A Data‐Driven Approach to Complex Voxel Predictions in Grayscale Digital Light Processing Additive Manufacturing Using U‐Nets and Generative Adversarial Networks

Multi‐Jet Fusion 3D Voxel Printing of Conductive Elastomers

Design of grayscale digital light processing 3D printing block by machine learning and evolutionary algorithm

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