Data provided by National Institute of Standards and Technology
This Photopolymer AM-Bench 2022 Challenge is to accurately model the relationship between photopatterned print fidelity and cure depth to exposure time with four resins, which serve to orthogonally probe the relationship between resin reactivity and viscosity. The data sets included here are broken down into three categories and are as follows: (1) resin characterization: Fourier transform infrared spectroscopy and rheometry, (2) light engine characterization: photomask dimensions, beam profilometry and radiometry, and (3) cure depth and profile: laser scanning confocal microscopy.
About this Dataset
Updated: 2024-02-22
Metadata Last Updated:
2022-05-01 00:00:00
Date Created:
N/A
Data Provided by:
Dataset Owner:
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| Title | AM Bench 2022 Vat Photopolymerization Challenge Data: Resin properties, light engine calibration, and calibration print dimensions (AMB2022-07) |
|---|---|
| Description | This Photopolymer AM-Bench 2022 Challenge is to accurately model the relationship between photopatterned print fidelity and cure depth to exposure time with four resins, which serve to orthogonally probe the relationship between resin reactivity and viscosity. The data sets included here are broken down into three categories and are as follows: (1) resin characterization: Fourier transform infrared spectroscopy and rheometry, (2) light engine characterization: photomask dimensions, beam profilometry and radiometry, and (3) cure depth and profile: laser scanning confocal microscopy. |
| Modified | 2022-05-01 00:00:00 |
| Publisher Name | National Institute of Standards and Technology |
| Contact | mailto:[email protected] |
| Keywords | vat photopolymerization , additive manufacturing , photopolymer , cure depth , AFM , laser scanning confocal microscopy , FTIR , rheology , radiometry |
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