Evidence map›Paper›PMID 42797132›Full record

ArticlePolymers2026

FDM 3D Printing of Flame-Retardant Polylactic-Acid-Based Composites with Electromagnetic Interference Shielding Performance.

Jun Li, Zijie Xu, Qinniu Lv, Xin Wang, Yinghong Chen

Abstract read
In one paragraph

Article in Polymers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Jun LiState Key Laboratory of Advanced Polymer Materials, Polymer Research Institute of Sichuan University, Chengdu 610065, China.
Zijie XuState Key Laboratory of Advanced Polymer Materials, Polymer Research Institute of Sichuan University, Chengdu 610065, China.
Qinniu LvState Key Laboratory of Advanced Polymer Materials, Polymer Research Institute of Sichuan University, Chengdu 610065, China.
Xin WangResearch Center for Composite Materials, State Key Laboratory of Advanced Refractories, Shanghai University, Shanghai 200444, China.
Yinghong ChenState Key Laboratory of Advanced Polymer Materials, Polymer Research Institute of Sichuan University, Chengdu 610065, China.ORCID 0000-0003-2169-4673

Funding

International Science & Technology Cooperation Project of Chengdu 2021-GH03-00009-HZProgram for Featured Directions of Engineering Multi-disciplines of Si-chuan University 2020SCUNG203
6 · The paper itself

Abstract

In this work, flame-retardant (FR) PLA-based composites exhibiting both good flame retardancy and electromagnetic interference (EMI) shielding were fabricated through combining melt blending with fused deposition modeling (FDM) 3D printing. Intumescent flame-retardant (IFR) fillers and graphene nanoplatelets (GNPs) were incorporated to construct a synergistic system, and the resulting structure-property relationships were systematically investigated. The optimal performance was achieved with 15 wt% IFR fillers and 3 wt% GNPs. The prepared composite exhibited a residual char yield of 14.3% at 700 °C, significantly higher than that of neat PLA. Regarding flame retardancy, the limiting oxygen index (LOI) increased to 32.5%, and the vertical burning level achieved a UL-94 V-0 rating. In the cone calorimetry test, both the peak heat release rate and total heat release were markedly reduced, attributed to the formation of a dense and stable char layer. For EMI shielding, the FR composite achieved a total shielding effectiveness (SE

Indexed as

3D printingelectromagnetic interference (EMI) shieldingflame retardancyfused deposition modeling (FDM)polylactic acid (PLA)

Identifiers

PMID42797132
PMCPMC13611730

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.