Evidence map›Paper›PMID 36987315›Full record

ArticlePolymers2023

Fabrication of 3D Printed Polylactic Acid/Polycaprolactone Nanocomposites with Favorable Thermo-Responsive Cyclic Shape Memory Effects, and Crystallization and Mechanical Properties.

Hao Liu, Chengdi Li, Simin Chen, Ping Chen, Jinbo Li, Huihua Jian, Guoyi Guo, Xiao Chen, Xiaofeng Zhu, Jun Wu

Abstract read
In one paragraph

Article in Polymers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 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

10 authors.

Hao LiuXinyu Key Laboratory of Materials Technology and Application for Intelligent Manufacturing, School of Mechanical and Electrical Engineering, Xinyu University, Xinyu 338004, China.ORCID 0000-0003-0997-0209
Chengdi LiXinyu Key Laboratory of Materials Technology and Application for Intelligent Manufacturing, School of Mechanical and Electrical Engineering, Xinyu University, Xinyu 338004, China.ORCID 0000-0003-3116-625X
Simin ChenXinyu Key Laboratory of Materials Technology and Application for Intelligent Manufacturing, School of Mechanical and Electrical Engineering, Xinyu University, Xinyu 338004, China.
Ping ChenXinyu Key Laboratory of Materials Technology and Application for Intelligent Manufacturing, School of Mechanical and Electrical Engineering, Xinyu University, Xinyu 338004, China.
Jinbo LiXinyu Key Laboratory of Materials Technology and Application for Intelligent Manufacturing, School of Mechanical and Electrical Engineering, Xinyu University, Xinyu 338004, China.
Huihua JianXinyu Key Laboratory of Materials Technology and Application for Intelligent Manufacturing, School of Mechanical and Electrical Engineering, Xinyu University, Xinyu 338004, China.
Guoyi GuoXinyu Key Laboratory of Materials Technology and Application for Intelligent Manufacturing, School of Mechanical and Electrical Engineering, Xinyu University, Xinyu 338004, China.
Xiao ChenXinyu Key Laboratory of Materials Technology and Application for Intelligent Manufacturing, School of Mechanical and Electrical Engineering, Xinyu University, Xinyu 338004, China.ORCID 0000-0001-7469-3637
Xiaofeng ZhuXinyu Key Laboratory of Materials Technology and Application for Intelligent Manufacturing, School of Mechanical and Electrical Engineering, Xinyu University, Xinyu 338004, China.
Jun WuXinyu Key Laboratory of Materials Technology and Application for Intelligent Manufacturing, School of Mechanical and Electrical Engineering, Xinyu University, Xinyu 338004, China.

Funding

National Natural Science Foundation of China 52161018Natural Science Foundation of Jiangxi 20224BAB214041Science and Technology Project of Jiangxi Educational Bureau GJJ212304Science and Technology Project of Jiangxi Educational Bureau GJJ212307Science and Technology Project of Jiangxi Educational Bureau GJJ2202213Science Technology Project of Jiujiang City [2015] No.64
6 · The paper itself

Abstract

In this work, 3D printed polylactic acid (PLA)/polycaprolactone (PCL) nanocomposites with favorable thermo-responsive cyclic shape memory effects (SMEs) and crystallization and mechanical properties were fabricated using a two-step method. First, an isocyanate-terminated PCL diol (PCL-NCO) was synthesized through the reaction between isocyanate groups of hexamethylene diisocyanate and active hydroxyl groups of PCL diol, and its physicochemical properties were characterized. A PLA/PCL blend with a PCL content of 50 wt% was fabricated via fused filament fabrication (FFF) 3D printing, and the influence of the PCL-NCO on the SME of the PLA/PCL blend was studied. The results indicated that the PCL-NCO significantly improved the cyclic shape memory performance of 3D printed PLA/PCL blends and was proved to be an effective interface compatibilizer for the blend system. Subsequently, the structure and properties of 3D printed PLA/PCL nanocomposites were investigated in detail by adding cellulose nanocrystal-organic montmorillonite (CNC-OMMT) hybrid nanofillers with different contents. It was found that the hybrid nanofillers greatly enhanced crystallization and mechanical properties of the nanocomposites due to adequate dispersion. The modification of the PLA/PCL blend and the preparation of the 3D printed nanocomposite can not only prolong the service life of a shape memory polymer product, but also broaden its application scope in advanced fields.

Indexed as

fused filament fabricationhybrid nanofillersinterface compatibilizernanocompositesthermo-responsive shape memory effects

Identifiers

PMID36987315
PMCPMC10053012

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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.