Evidence map›Paper›PMID 36080632›Full record

ArticlePolymers2022

Mechanical Response of Carbon Composite Octet Truss Structures Produced via Axial Lattice Extrusion.

Pritam Poddar, Mark Olles, Denis Cormier

Abstract read
In one paragraph

Article in Polymers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Fully bio-based composite and modular metastructures.Advanced composites and hybrid materials · 2025
    Article
  5. Review
  6. 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.

Pritam PoddarIndustrial and Systems Engineering, Rochester Institute of Technology, Rochester, NY 14623, USA.
Mark OllesIndustrial and Systems Engineering, Rochester Institute of Technology, Rochester, NY 14623, USA.
Denis CormierIndustrial and Systems Engineering, Rochester Institute of Technology, Rochester, NY 14623, USA.ORCID 0000-0003-4534-5961

Funding

Empire State Development Corporation 005134-008
6 · The paper itself

Abstract

Engineered lattice structures fabricated via additive manufacturing (AM) technologies are of great interest for many applications that require high strength and/or stiffness with minimum mass. This paper studies a novel axial lattice extrusion (ALE) AM technique that greatly enhances mechanical properties of polymeric lattice structures. When the novel ALE process was used to produce 84 mm × 84 mm × 84 mm octet truss lattice samples using fiber reinforced ABS, a total of 219,520 polymer interfaces in the lattice beams were eliminated relative to the conventional 3D printing alternative. Microscopic examination revealed near perfect alignment of the chopped carbon fibers with axes of the cylindrical beams that make up the lattice structure. The greatly enhanced beam quality with fiber reinforcement resulted in excellent mechanical properties. Compression testing yielded an average relative compressive strength of 17.4 MPa and an average modulus of 162.8 MPa. These properties rate very strongly relative to other published work, and indicate that the ALE process shows great potential for fabrication of high-strength, lightweight, large-scale, carbon-fiber composite components. The paper also contributes a modeling approach to finite element analysis (FEA) that captures the highly orthotropic properties of carbon fiber lattice beams. The diagonal shear failure mode predicted via the FEA model was in good agreement with experimentally observed results.

Indexed as

engineered cellular materialsfused filament fabricationlattice structuresoctet truss

Identifiers

PMID36080632
PMCPMC9459732

What OpenQuestion holds

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Registered trials

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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.