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Title: Mining Materials Design Rules from Data: The Example of Polymer Dielectrics

Abstract

Mining of currently available and evolving materials databases to discover structure–chemistry–property relationships is critical to developing an accelerated materials design framework. The design of new and advanced polymeric dielectrics for capacitive energy storage has been hampered by the lack of sufficient data encompassing wide enough chemical spaces. Here, data mining and analysis techniques are applied on a recently presented computational data set of around 1100 organic polymers, organometallic polymers, and related molecular crystals, in order to obtain qualitative understanding of the origins of dielectric and electronic properties. By probing the relationships between crucial chemical and structural features of materials and their dielectric constant and band gap, design rules are devised for optimizing either property. Learning from this data set provides guidance to experiments and to future computations, as well as a way of expanding the pool of promising polymer candidates for dielectric applications.

Authors:
ORCiD logo [1];  [1];  [1]
  1. Univ. of Connecticut, Storrs, CT (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1479688
Resource Type:
Accepted Manuscript
Journal Name:
Chemistry of Materials
Additional Journal Information:
Journal Volume: 29; Journal Issue: 21; Journal ID: ISSN 0897-4756
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; Insulators; Metals; Organic polymers; Electrical properties; Polymers

Citation Formats

Mannodi-Kanakkithodi, Arun, Huan, Tran Doan, and Ramprasad, Rampi. Mining Materials Design Rules from Data: The Example of Polymer Dielectrics. United States: N. p., 2017. Web. doi:10.1021/acs.chemmater.7b02027.
Mannodi-Kanakkithodi, Arun, Huan, Tran Doan, & Ramprasad, Rampi. Mining Materials Design Rules from Data: The Example of Polymer Dielectrics. United States. doi:https://doi.org/10.1021/acs.chemmater.7b02027
Mannodi-Kanakkithodi, Arun, Huan, Tran Doan, and Ramprasad, Rampi. Tue . "Mining Materials Design Rules from Data: The Example of Polymer Dielectrics". United States. doi:https://doi.org/10.1021/acs.chemmater.7b02027. https://www.osti.gov/servlets/purl/1479688.
@article{osti_1479688,
title = {Mining Materials Design Rules from Data: The Example of Polymer Dielectrics},
author = {Mannodi-Kanakkithodi, Arun and Huan, Tran Doan and Ramprasad, Rampi},
abstractNote = {Mining of currently available and evolving materials databases to discover structure–chemistry–property relationships is critical to developing an accelerated materials design framework. The design of new and advanced polymeric dielectrics for capacitive energy storage has been hampered by the lack of sufficient data encompassing wide enough chemical spaces. Here, data mining and analysis techniques are applied on a recently presented computational data set of around 1100 organic polymers, organometallic polymers, and related molecular crystals, in order to obtain qualitative understanding of the origins of dielectric and electronic properties. By probing the relationships between crucial chemical and structural features of materials and their dielectric constant and band gap, design rules are devised for optimizing either property. Learning from this data set provides guidance to experiments and to future computations, as well as a way of expanding the pool of promising polymer candidates for dielectric applications.},
doi = {10.1021/acs.chemmater.7b02027},
journal = {Chemistry of Materials},
number = 21,
volume = 29,
place = {United States},
year = {2017},
month = {10}
}

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