Evidence map›Paper›PMID 35699797›Full record

ReviewNano-micro letters2022

Efficient Preconstruction of Three-Dimensional Graphene Networks for Thermally Conductive Polymer Composites.

Hao-Yu Zhao, Ming-Yuan Yu, Ji Liu, Xiaofeng Li, Peng Min, Zhong-Zhen Yu

Open access · diamondAbstract readReview
In one paragraph

Review in Nano-micro letters, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
14.0field-weighted citation impact, top 1% of its field
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

15 citing papers in PubMed, 197 citations in OpenAlex.

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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

6 authors at 2 institutions in 2 countries.

Hao-Yu ZhaoBeijing Key Laboratory of Advanced Functional Polymer Composites, Beijing University of Chemical Technology, Beijing, 100029, People's Republic of China.
Ming-Yuan YuCollege of Materials Science and Engineering, Beijing University of Chemical Technology, Beijing, 100029, People's Republic of China.
Ji LiuSchool of Chemistry, CRANN and AMBER, Trinity College Dublin, Dublin, Ireland. ji.liu@tcd.ie.
Xiaofeng LiBeijing Key Laboratory of Advanced Functional Polymer Composites, Beijing University of Chemical Technology, Beijing, 100029, People's Republic of China. xfli@mail.buct.edu.cn.
Peng MinCollege of Materials Science and Engineering, Beijing University of Chemical Technology, Beijing, 100029, People's Republic of China.
Zhong-Zhen YuBeijing Key Laboratory of Advanced Functional Polymer Composites, Beijing University of Chemical Technology, Beijing, 100029, People's Republic of China. yuzz@mail.buct.edu.cn.
Beijing University of Chemical Technology · CNTrinity College Dublin · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electronic devices generate heat during operation and require efficient thermal management to extend the lifetime and prevent performance degradation. Featured by its exceptional thermal conductivity, graphene is an ideal functional filler for fabricating thermally conductive polymer composites to provide efficient thermal management. Extensive studies have been focusing on constructing graphene networks in polymer composites to achieve high thermal conductivities. Compared with conventional composite fabrications by directly mixing graphene with polymers, preconstruction of three-dimensional graphene networks followed by backfilling polymers represents a promising way to produce composites with higher performances, enabling high manufacturing flexibility and controllability. In this review, we first summarize the factors that affect thermal conductivity of graphene composites and strategies for fabricating highly thermally conductive graphene/polymer composites. Subsequently, we give the reasoning behind using preconstructed three-dimensional graphene networks for fabricating thermally conductive polymer composites and highlight their potential applications. Finally, our insight into the existing bottlenecks and opportunities is provided for developing preconstructed porous architectures of graphene and their thermally conductive composites.

Indexed as

Anisotropic aerogelsGraphene networksPhase change compositesThermal conductivityThermal interface materials

Identifiers

PMID35699797
PMCPMC9198159
OpenAlexW4282827125

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.