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ACS Applied Energy Materials
Article . 2021 . Peer-reviewed
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Rational Design of High-Energy-Density Polymer Composites by Machine Learning Approach

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 22 Jan 2021 English Publisher:American Chemical Society (ACS)Journal:ACS Applied Energy Materials, volume 4, pages 1,449-1,458 (issn: 2574-0962, eissn: 2574-0962, Copyright policy )
Authors: Ming-Xiao Zhu; Qiu-Cheng Yu; Heng-Gao Song; Ting-Xin Chen; Ji-Ming Chen;

doi: 10.1021/acsaem.0c02647

Rational Design of High-Energy-Density Polymer Composites by Machine Learning Approach

Abstract

Rationally designing polymer composite structures, including physical parameters of nanofillers, nanofiller–matrix interface characteristics, and geometric distribution of nanofillers, is thought t...

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Keywords

High-Energy-Density Polymer Composites, Machine Learning Approach Rationally, Chemical Sciences not elsewhere classified, Gaussian process regression algorithm, Biophysics, permittivity, ML, ε r, dielectric properties, filler doping scheme, U e, nanofiller, E b, Physical Sciences not elsewhere classified, Biological Sciences not elsewhere classified, design polymer composites

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    popularity
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    		 Top 10%
    influence
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
33
Top 10%
Top 10%
Top 10%
Green