Evidence map›Paper›PMID 41374916›Full record

ArticlePolymers2025

Constructing Highly Ordered Continuous BNNS Networks in COP Film to Achieve Excellent Thermal Conduction and Dielectric Performance.

Jialong Jiang, Yi Zheng, Yuan Ji, Hong Wu, Shaoyun Guo

Abstract read
In one paragraph

Article in Polymers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Jialong JiangThe State Key Laboratory of Advanced Polymer Materials, Sichuan Provincial Engineering Research Center of Plastic/Rubber Complex Processing Technology, Polymer Research Institute of Sichuan University, Chengdu 610065, China.ORCID 0009-0007-2344-7285
Yi ZhengThe State Key Laboratory of Advanced Polymer Materials, Sichuan Provincial Engineering Research Center of Plastic/Rubber Complex Processing Technology, Polymer Research Institute of Sichuan University, Chengdu 610065, China.
Yuan JiThe State Key Laboratory of Advanced Polymer Materials, Sichuan Provincial Engineering Research Center of Plastic/Rubber Complex Processing Technology, Polymer Research Institute of Sichuan University, Chengdu 610065, China.
Hong WuThe State Key Laboratory of Advanced Polymer Materials, Sichuan Provincial Engineering Research Center of Plastic/Rubber Complex Processing Technology, Polymer Research Institute of Sichuan University, Chengdu 610065, China.ORCID 0000-0001-9972-0873
Shaoyun GuoThe State Key Laboratory of Advanced Polymer Materials, Sichuan Provincial Engineering Research Center of Plastic/Rubber Complex Processing Technology, Polymer Research Institute of Sichuan University, Chengdu 610065, China.

Funding

National Natural Science Foundation of China 52473043Natural Science Foundation of Sichuan Province 2025ZNSFSC0039State Key Laboratory of Advanced Polymer Materials sklapm2025-2-07
6 · The paper itself

Abstract

To meet the requirement of thermal management of modern electronic devices, polymer composites with high thermal conductivity (TC) and dielectric performance are nowadays in urgent demand. Herein, a highly ordered continuous network of boron nitride nano-sheet (BNNS) was constructed in cyclic olefin polymer (COP) films via the forced flow processing in the rubbery state (FFRS), melt-spinning, fiber-alignment, and hot-pressing procedures. The composites exhibited superior TC, low dielectric permittivity, and low dielectric loss simultaneously. The in-plane TC of the composites reached 3.92 W/(mK) when the content of BNNS was at 27 weight percentage (27 wt%), since the procedures improved the face-to-face contact between the BNNS (which was exfoliated, dispersed, and in-plane oriented during FFRS), enhancing the continuity of the BNNS thermally conductive network. Both the TC and the experimental results indicated the outstanding heat dissipation performance of the composites. Meanwhile, the dielectric permittivity and dielectric loss of the 27 wt% BNNS composites were 2.56 and 0.00085 at 10 GHz, respectively, lower than that of the COP-POE matrix. Moreover, the mechanical properties, water vapor permeability, and coefficient of thermal expansion of the composites were excellent. The composites with such highly ordered continuous networks are very promising in high-performance electronic devices.

Indexed as

boron nitridecontinuous networkdielectric lossdielectric permittivitythermal conductivity

Identifiers

PMID41374916
PMCPMC12694120

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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.