Search research articles

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Weld Formation Between Polymer Films Prepared at Different Temperatures: Insights from Molecular Dynamics Simulations.

Macromolecules·2026

Same author

Tuning High-Density Polyethylene Microstructure and Properties from Known Distributions of Dynamic Bonds.

Journal of the American Chemical Society·2025

Same author

Ascorbic Acid Modulates Collagen Properties in Glucocorticoid-Induced Osteoporotic Bone: Insights into Chemical, Mechanical, and Biological Regulation.

Advanced healthcare materials·2025

Same author

Quantifying residual orientation and thermal stress contributions to birefringence in the material extrusion of polylactide.

Additive manufacturing·2025

Same author

Online Measurement for Parameter Discovery in Fused Filament Fabrication.

Integrating materials and manufacturing innovation·2024

Same author

Simulated inter-filament fusion in embedded 3D printing.

Biofabrication·2024

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: Sep 5, 2025

Author Spotlight: Modular Neuronal Networks for Analyzing Brain Functions

Author Spotlight: Modular Neuronal Networks for Analyzing Brain Functions

Published on: June 7, 2024

Suppression of Filament Defects in Embedded 3D Printing.

Leanne M Friedrich¹, Ross T Gunther², Jonathan E Seppala¹

¹Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, Maryland 20899, United States.

ACS Applied Materials & Interfaces

|July 5, 2022

Summary

Embedded 3D printing creates intricate soft structures. Optimizing ink and support fluid properties, like viscosity and interfacial tension, improves filament shape and print fidelity.

Keywords:

3D printing Herschel−Bulkley extrusion rheology support bath surface tension

More Related Videos

Author Spotlight: Real-Time Imaging of Bonding in 3D-Printed Layers

Author Spotlight: Real-Time Imaging of Bonding in 3D-Printed Layers

Published on: September 1, 2023

3D Printing and In Situ Surface Modification via Type I Photoinitiated Reversible Addition-Fragmentation Chain Transfer Polymerization

3D Printing and In Situ Surface Modification via Type I Photoinitiated Reversible Addition-Fragmentation Chain Transfer Polymerization

Published on: February 18, 2022

Related Experiment Videos

Last Updated: Sep 5, 2025

Author Spotlight: Modular Neuronal Networks for Analyzing Brain Functions

Author Spotlight: Modular Neuronal Networks for Analyzing Brain Functions

Published on: June 7, 2024

Author Spotlight: Real-Time Imaging of Bonding in 3D-Printed Layers

Author Spotlight: Real-Time Imaging of Bonding in 3D-Printed Layers

Published on: September 1, 2023

3D Printing and In Situ Surface Modification via Type I Photoinitiated Reversible Addition-Fragmentation Chain Transfer Polymerization

3D Printing and In Situ Surface Modification via Type I Photoinitiated Reversible Addition-Fragmentation Chain Transfer Polymerization

Published on: February 18, 2022

Area of Science:

Materials Science
Fluid Dynamics
Additive Manufacturing

Background:

Embedded 3D printing allows fabrication of complex soft materials using low-viscosity fluids.
Challenges include filament defects like non-ideal cross-sections, surface roughness, rupture, and contraction, impacting print fidelity.

Purpose of the Study:

To investigate the effects of rheology, print speed, and interfacial tension on filament defects in embedded 3D printing.
To identify key parameters controlling filament shape and stability for improved print quality.

Main Methods:

Digital image analysis of in situ printing videos and post-print filament images.
Utilizing model water-based and oil-based ink systems with a viscoelastic support bath.
Systematic variation of ink/support rheology, print speeds, and interfacial tension.

Main Results:

For water-based systems, the local viscosity ratio near the nozzle dictates filament shape; a slightly higher ink viscosity yields round, smooth filaments.
For oil-based inks in water-based supports, the capillary number governs filament shape, with higher values suppressing rupture/contraction but increasing roughness.
Nonzero interfacial tension is advantageous, producing rounder, smoother filaments than zero interfacial tension inks at equivalent viscosity ratios.

Conclusions:

Filament shape and fidelity in embedded 3D printing are controllable by tuning fluid properties and printing parameters.
Understanding rheological and capillary effects is crucial for optimizing the embedded 3D printing process for intricate soft structures.