Evidence map›Paper›PMID 39212480›Full record

ArticleAngewandte Chemie (International ed. in English)2025

Synthesis and Solvent Free DLP 3D Printing of Degradable Poly(Allyl Glycidyl Ether Succinate).

Maddison I Segal, Alexander J Bahnick, Nicola G Judge, Matthew L Becker

Abstract read
In one paragraph

Article in Angewandte Chemie (International ed. in English), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

4 authors.

Maddison I SegalThomas Lord Department of Mechanical Engineering & Material Science, Duke University, Durham, NC, USA.ORCID https://orcid.org/0009-0005-8404-7598
Alexander J BahnickDepartment of Chemistry, Duke University, Durham, NC, USA.ORCID https://orcid.org/0000-0002-8420-5024
Nicola G JudgeDepartment of Chemistry, Duke University, Durham, NC, USA.ORCID https://orcid.org/0000-0002-2948-514X
Matthew L BeckerThomas Lord Department of Mechanical Engineering & Material Science, Duke University, Durham, NC, USA.ORCID https://orcid.org/0000-0003-4089-6916

Funding

Computational model-driven design to mitigate vein graft failure after coronary artery bypassR01HL159954 · NHLBI · STANFORD UNIVERSITY · PI HUMPHREY, JAY D., MARSDEN, ALISON L · 2022 to 2025
$2.7M
NHLBI NIH HHS 1R01HL159954-01NHLBI NIH HHS R01 HL159954
6 · The paper itself

Abstract

Digital light processing (DLP) printing forms solid constructs from fluidic resins by photochemically crosslinking polymeric resins with reactive functional groups. DLP is used widely due to its efficient, high-resolution printing, but its use and translational potential has been limited in some applications as state-of-the-art resins experience unpredictable and anisotropic part shrinkage due to the use of solvent needed to reduce resin viscosity and layer dependent crosslinking. Herein, poly(allyl glycidyl ether succinate) (PAGES), a low viscosity, degradable polyester, was synthesized by ring opening copolymerization and used in combination with degradable thiol crosslinkers to afford a solvent free resin that can be utilized in DLP printing. Varying resin formulations of PAGES polymer are shown to decrease part shrinkage from 14 % to 0.3 %. Photochemically printed parts fabricated from PAGES possess tensile moduli between 0.43 and 6.18 MPa and degradation profiles are shown to vary between 12 and 40 days under accelerated conditions based on degree of polymerization and crosslink ratio.

Indexed as

3D printingdegradable polymerspolyestersolvent freethiol-ene crosslinking

Identifiers

PMID39212480
PMCPMC11959289

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.