Evidence map›Paper›PMID 34297018›Full record

ArticleSoft matter2021

Simulated filament shapes in embedded 3D printing.

Leanne M Friedrich, Jonathan E Seppala

Abstract read
In one paragraph

Article in Soft matter, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. Computational approaches in bioprinting processes.Nature reviews bioengineering · 2026
    Article
  3. Article
  4. 3D Printing of Air.Research square · 2025
    Article
  5. Article
  6. Article
  7. Review
  8. High-Speed Embedded Ink Writing of Anatomic-Size Organ Constructs.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Leanne M FriedrichMaterials Science and Engineering Division, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA. jonathan.seppala@nist.gov.ORCID http://orcid.org/0000-0002-0382-3980
Jonathan E SeppalaMaterials Science and Engineering Division, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA. jonathan.seppala@nist.gov.ORCID http://orcid.org/0000-0002-5937-8716

Funding

Intramural NIST DOC 9999-NIST
6 · The paper itself

Abstract

Embedded 3D printing, wherein fluid inks are extruded into support baths, has enabled the manufacture of complex, custom structures ranging from cell-laden tissue analogues to soft robots. This method encompasses two techniques: embedded ink writing (EIW), where filaments are extruded, and embedded droplet printing (EDP), where droplets are suspended. Materials for embedded 3D printing can be Newtonian, but often both the ink and the support bath are yield stress fluids, following elastic behavior below the yield stress and shear-thinning, viscous behavior above the yield stress. The effect of surface tension on print quality has been debated, as inks have been printed into supports at high and low surface tensions. In order to guide material selection for embedded 3D printing and identify key scaling relationships that influence print quality, this study investigates the role of ink rheology, support rheology, and surface tension on the morphology of single filaments. Numerical simulations in OpenFOAM demonstrate that at low viscosities, surface tension controls the filament morphology. Where capillarity is suppressed, the ratio of the local ink and support viscosities and the shape of the yield surface in the support control the filament shape. Herschel-Bulkley support fluids (yield stress fluids) produce more stable, accurately positioned filaments than Newtonian supports. In the short term, non-zero surface tensions can suppress filament shape defects in EIW and are essential for producing droplets in EDP.

Identifiers

PMID34297018
PMCPMC9795507

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.