Evidence map›Paper›PMID 38714684›Full record

ArticleNature communications2024

3D printing with a 3D printed digital material filament for programming functional gradients.

Sang-Joon Ahn, Howon Lee, Kyu-Jin Cho

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. TranslatingFrontiers in bioengineering and biotechnology · 2026
    Article
  6. Material-Gradient Enabled Enhancement of Strength and Strain-Hardening of Lattice Structures.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  7. Review
  8. Article
  9. Review
  10. Review
  11. Article
  12. Review
  13. Continuous Multi-Material Additive Manufacturing.Research (Washington, D.C.) · 2025
    Article
  14. Review
  15. Review
  16. Article
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

3 authors.

Sang-Joon AhnSoft Robotics Research Center, Seoul National University, Seoul, Republic of Korea.
Howon LeeDepartment of Mechanical Engineering, Institute of Advanced Machines and Design, Seoul National University, Seoul, Republic of Korea. howon.lee@snu.ac.kr.ORCID http://orcid.org/0000-0001-5778-2398
Kyu-Jin ChoSoft Robotics Research Center, Seoul National University, Seoul, Republic of Korea. kjcho@snu.ac.kr.ORCID http://orcid.org/0000-0003-2555-5048

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Additive manufacturing, or 3D printing attracts growing attention as a promising method for creating functionally graded materials. Fused deposition modeling (FDM) is widely available, but due to its simple process, creating spatial gradation of diverse properties using FDM is challenging. Here, we present a 3D printed digital material filament that is structured towards 3D printing of functional gradients, utilizing only a readily available FDM printer and filaments. The DM filament consists of multiple base materials combined with specific concentrations and distributions, which are FDM printed. When the DM filament is supplied to the same printer, its constituent materials are homogeneously blended during extrusion, resulting in the desired properties in the final structure. This enables spatial programming of material properties in extreme variations, including mechanical strength, electrical conductivity, and color, which are otherwise impossible to achieve with traditional FDMs. Our approach can be readily adopted to any standard FDM printer, enabling low-cost production of functional gradients.

Identifiers

PMID38714684
PMCPMC11076495

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.