Evidence map›Paper›PMID 35169712›Full record

ArticleResearch (Washington, D.C.)2022

3D Printing of Nacre-Inspired Structures with Exceptional Mechanical and Flame-Retardant Properties.

Yang Yang, Ziyu Wang, Qingqing He, Xiangjia Li, Gengxi Lu, Laiming Jiang, Yushun Zeng, Brandon Bethers, Jie Jin, Shuang Lin and 6 more

Abstract read
In one paragraph

Article in Research (Washington, D.C.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
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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

16 authors.

Yang YangDepartment of Mechanical Engineering, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182, USA.ORCID https://orcid.org/0000-0002-4032-5446
Ziyu WangThe Institute of Technological Sciences, Wuhan University, Wuhan 430072, China.ORCID https://orcid.org/0000-0001-9718-1263
Qingqing HeDepartment of Mechanical Engineering, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182, USA.
Xiangjia LiSchool for Engineering of Matter, Transport and Energy, Arizona State University, 551 E Tyler Mall, Tempe, AZ 85281, USA.ORCID https://orcid.org/0000-0002-8549-4251
Gengxi LuDepartment of Biomedical Engineering, University of Southern California, 1042 Downey Way, Los Angeles, CA 90089, USA.ORCID https://orcid.org/0000-0001-7497-050X
Laiming JiangDepartment of Biomedical Engineering, University of Southern California, 1042 Downey Way, Los Angeles, CA 90089, USA.ORCID https://orcid.org/0000-0002-8658-3168
Yushun ZengDepartment of Biomedical Engineering, University of Southern California, 1042 Downey Way, Los Angeles, CA 90089, USA.ORCID https://orcid.org/0000-0001-5995-4085
Brandon BethersDepartment of Mechanical Engineering, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182, USA.
Jie JinEpstein Department of Industrial and Systems Engineering, University of Southern California, 3715 McClintock Ave, Los Angeles, CA 90089, USA.ORCID https://orcid.org/0000-0001-6170-3840
Shuang LinDepartment of Chemical Engineering and Materials Science, University of Southern California, 925 Bloom Walk, Los Angeles, California 90089, USA.
Siqi XiaoDepartment of Chemical Engineering and Materials Science, University of Southern California, 925 Bloom Walk, Los Angeles, California 90089, USA.
Yizhen ZhuSchool for Engineering of Matter, Transport and Energy, Arizona State University, 551 E Tyler Mall, Tempe, AZ 85281, USA.ORCID https://orcid.org/0000-0003-4077-8151
Xianke WuSchool of Physics and Technology, Wuhan University, Wuhan 430072, China.
Wenwu XuDepartment of Mechanical Engineering, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182, USA.
Qiming WangSonny Astani Department of Civil and Environmental Engineering, University of Southern California, Los Angeles, CA 90089, USA.ORCID https://orcid.org/0000-0003-1618-5065
Yong ChenEpstein Department of Industrial and Systems Engineering, University of Southern California, 3715 McClintock Ave, Los Angeles, CA 90089, USA.ORCID https://orcid.org/0000-0002-8377-5914

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Flame-retardant and thermal management structures have attracted great attention due to the requirement of high-temperature exposure in industrial, aerospace, and thermal power fields, but the development of protective fire-retardant structures with complex shapes to fit arbitrary surfaces is still challenging. Herein, we reported a rotation-blade casting-assisted 3D printing process to fabricate nacre-inspired structures with exceptional mechanical and flame-retardant properties, and the related fundamental mechanisms are studied. 3-(Trimethoxysilyl)propyl methacrylate (TMSPMA) modified boron nitride nanoplatelets (BNs) were aligned by rotation-blade casting during the 3D printing process to build the "brick and mortar" architecture. The 3D printed structures are more lightweight, while having higher fracture toughness than the natural nacre, which is attributed to the crack deflection, aligned BN (a-BNs) bridging, and pull-outs reinforced structures by the covalent bonding between TMSPMA grafted a-BNs and polymer matrix. Thermal conductivity is enhanced by 25.5 times compared with pure polymer and 5.8 times of anisotropy due to the interconnection of a-BNs. 3D printed heat-exchange structures with vertically aligned BNs in complex shapes were demonstrated for efficient thermal control of high-power light-emitting diodes. 3D printed helmet and armor with a-BNs show exceptional mechanical and fire-retardant properties, demonstrating integrated mechanical and thermal protection.

Identifiers

PMID35169712
PMCPMC8817185

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.