Evidence map›Paper›PMID 35602181›Full record

ArticleAdditive manufacturing2022

Characterization of a 30 µm pixel size CLIP-based 3D printer and its enhancement through dynamic printing optimization.

Brian J Lee, Kaiwen Hsiao, Gabriel Lipkowitz, Tim Samuelsen, Lee Tate, Joseph M DeSimone

Abstract read
In one paragraph

Article in Additive manufacturing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Rising role of 3D-printing in delivery of therapeutics for infectious disease.Journal of controlled release : official journal of the Controlled Release Society · 2024
    Review
  14. Review
  15. Review
  16. Stretchable, recyclable thermosetsChemical science · 2023
    Article
  17. Review
  18. Article
  19. Review
  20. 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

6 authors.

Brian J LeeDepartment of Radiology, Stanford University, Stanford, CA, 94305.
Kaiwen HsiaoDepartment of Radiology, Stanford University, Stanford, CA, 94305.
Gabriel LipkowitzDepartment of Mechanical Engineering, Stanford University, Stanford, CA, 94305.
Tim SamuelsenDepartment of Mechanical Engineering, Stanford University, Stanford, CA, 94305.
Lee TateDigital Light Innovations, Austin, TX, 78728.
Joseph M DeSimoneDepartment of Radiology, Stanford University, Stanford, CA, 94305.

Funding

Stanford Molecular Imaging Scholars (SMIS) ProgramT32CA118681 · NCI · STANFORD UNIVERSITY · PI CRAIG S LEVIN · 2016 to 2026
$4.3M
RF-Transmissive PET insert for integrated PET/MRIF31EB020504 · NIBIB · STANFORD UNIVERSITY · PI LEE, BRIAN JUN · 2016 to 2017
$70k
NCI NIH HHS T32 CA118681NIBIB NIH HHS F31 EB020504Wellcome Trust
6 · The paper itself

Abstract

Resolving microscopic and complex 3D polymeric structures while maintaining high print speeds in additive manufacturing has been challenging. To achieve print precision at micrometer length scales for polymeric materials, most 3D printing technologies utilize the serial voxel printing approach that has a relatively slow print speed. Here, a 30-µm-resolution continuous liquid interface production (CLIP)-based 3D printing system for printing polymeric microstructures is described. This technology combines the high-resolution from projection microstereolithography and the fast print speed from CLIP, thereby achieving micrometer print resolution at x10

Indexed as

3D printingadditive manufacturingCLIP (continuous liquid interface production)high-resolutionoptimization

Identifiers

PMID35602181
PMCPMC9121862

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.