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Title: 3D Printing of Compositional Gradients Using the Microfluidic Circuit Analogy

Abstract

3D printing of structures with compositional gradients requires accurate dispensing control to achieve desired profiles. Here, empirical data are used with a model based on the microfluidic circuit analogy (MCA) to project dispense rate profiles that yield improved compositional accuracy in the printed part. Since minor variation in the experimental setup for each printing session can result in significant changes, a calibration procedure is developed to measure the system response. This calibration enables the extraction of the empirical MCA model parameters specific to each print session. Using the empirical parameters, the MCA model then can be used to predict appropriate dispense rates for the desired composition profile and toolpath of interest. Here, the MCA model is validated experimentally by direct ink write 3D printing of compositional gradients using viscoelastic polydimethylsiloxane inks and is shown to improve accuracy to desired profile by a factor of 2–5. This approach enables a new route to 3D print structures with arbitrarily complex compositional gradients.

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1];  [1];  [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1573945
Alternate Identifier(s):
OSTI ID: 1573287
Report Number(s):
LLNL-JRNL-783138
Journal ID: ISSN 2365-709X; 976792
Grant/Contract Number:  
AC52-07NA27344; AC52‐07NA27344; LLNL‐JRNL‐783138; 19‐ERD‐020
Resource Type:
Accepted Manuscript
Journal Name:
Advanced Materials Technologies
Additional Journal Information:
Journal Volume: 4; Journal Issue: 12; Journal ID: ISSN 2365-709X
Publisher:
Wiley
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; 3D printing; direct ink writing; multimaterial printing

Citation Formats

Nguyen, Du T., Yee, Timothy D., Dudukovic, Nikola A., Sasan, Koroush, Jaycox, Adam W., Golobic, Alexandra M., Duoss, Eric B., and Dylla‐Spears, Rebecca. 3D Printing of Compositional Gradients Using the Microfluidic Circuit Analogy. United States: N. p., 2019. Web. doi:10.1002/admt.201900784.
Nguyen, Du T., Yee, Timothy D., Dudukovic, Nikola A., Sasan, Koroush, Jaycox, Adam W., Golobic, Alexandra M., Duoss, Eric B., & Dylla‐Spears, Rebecca. 3D Printing of Compositional Gradients Using the Microfluidic Circuit Analogy. United States. https://doi.org/10.1002/admt.201900784
Nguyen, Du T., Yee, Timothy D., Dudukovic, Nikola A., Sasan, Koroush, Jaycox, Adam W., Golobic, Alexandra M., Duoss, Eric B., and Dylla‐Spears, Rebecca. Wed . "3D Printing of Compositional Gradients Using the Microfluidic Circuit Analogy". United States. https://doi.org/10.1002/admt.201900784. https://www.osti.gov/servlets/purl/1573945.
@article{osti_1573945,
title = {3D Printing of Compositional Gradients Using the Microfluidic Circuit Analogy},
author = {Nguyen, Du T. and Yee, Timothy D. and Dudukovic, Nikola A. and Sasan, Koroush and Jaycox, Adam W. and Golobic, Alexandra M. and Duoss, Eric B. and Dylla‐Spears, Rebecca},
abstractNote = {3D printing of structures with compositional gradients requires accurate dispensing control to achieve desired profiles. Here, empirical data are used with a model based on the microfluidic circuit analogy (MCA) to project dispense rate profiles that yield improved compositional accuracy in the printed part. Since minor variation in the experimental setup for each printing session can result in significant changes, a calibration procedure is developed to measure the system response. This calibration enables the extraction of the empirical MCA model parameters specific to each print session. Using the empirical parameters, the MCA model then can be used to predict appropriate dispense rates for the desired composition profile and toolpath of interest. Here, the MCA model is validated experimentally by direct ink write 3D printing of compositional gradients using viscoelastic polydimethylsiloxane inks and is shown to improve accuracy to desired profile by a factor of 2–5. This approach enables a new route to 3D print structures with arbitrarily complex compositional gradients.},
doi = {10.1002/admt.201900784},
journal = {Advanced Materials Technologies},
number = 12,
volume = 4,
place = {United States},
year = {Wed Nov 06 00:00:00 EST 2019},
month = {Wed Nov 06 00:00:00 EST 2019}
}

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