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

    Metadata Updated: September 30, 2023

    Digital light processing (DLP) vat photopolymerization (VP) additive manufacturing (AM) uses patterned UV light to selectively cure a liquid photopolymer into a solid layer. Subsequent layers are printed on to preceding layers to eventually form a desired 3 dimensional (3D) part. This data set characterizes the 3D geometry of a single layer of voxels (volume pixels) printed with photomasks assigned random intensity levels at every pixel. The masks are computer generated, then printed onto a glass cover slide. Geometry of the printed voxels is characterized by laser scanning confocal microscopy. The data were originally curated to train image-to-image U-net machine learning models to predict voxel scale geometry given arbitrary photomasks, as described in the publication "A Data-Driven Approach to Complex Voxel Predictions in Grayscale Digital Light Processing Additive Manufacturing Using U-nets and Generative Adversarial Networks". Data are provided in a raw (native microscope format and photomask image) and processed into aligned mask-print training pairs. A total of 1500 8 pixel × 8 pixel (i.e. 96 000 pixel interactions) training pairs are provided. Jupyter notebooks for various steps in process are also provided.

    Access & Use Information

    Public: This dataset is intended for public access and use. License: See this page for license information.

    Downloads & Resources

    References

    https://doi.org/10.1002/smll.202301987

    Dates

    Metadata Created Date September 30, 2023
    Metadata Updated Date September 30, 2023
    Data Update Frequency irregular

    Metadata Source

    Harvested from NIST

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date September 30, 2023
    Metadata Updated Date September 30, 2023
    Publisher National Institute of Standards and Technology
    Maintainer
    Identifier ark:/88434/mds2-2950
    Data First Published 2023-07-20
    Language en
    Data Last Modified 2023-03-07 00:00:00
    Category Mathematics and Statistics:Statistical analysis, Materials:Polymers, Manufacturing:Additive manufacturing
    Public Access Level public
    Data Update Frequency irregular
    Bureau Code 006:55
    Metadata Context https://project-open-data.cio.gov/v1.1/schema/data.json
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
    Harvest Object Id 258b3b96-ea8b-4afd-b91b-23336732c8e4
    Harvest Source Id 74e175d9-66b3-4323-ac98-e2a90eeb93c0
    Harvest Source Title NIST
    Homepage URL https://data.nist.gov/od/id/mds2-2950
    License https://www.nist.gov/open/license
    Program Code 006:045
    Related Documents https://doi.org/10.1002/smll.202301987
    Source Datajson Identifier True
    Source Hash ec306a1c57f4995372b26fd3d171828a788aabfb77ee3e65fab5efe5d07ac805
    Source Schema Version 1.1

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