Journal of Materials Science

, Volume 47, Issue 21, pp 7703–7715 | Cite as

MQSPR modeling in materials informatics: a way to shorten design cycles?

  • N. Sukumar
  • Michael Krein
  • Qiong Luo
  • Curt Breneman
First Principles Computations

Abstract

We demonstrate applications of quantitative structure–property relationship (QSPR) modeling to supplement first-principles computations in materials design. We have here focused on the design of polymers with specific electronic properties. We first show that common materials properties such as the glass transition temperature (Tg) can be effectively modeled by QSPR to generate highly predictive models that relate polymer repeat unit structure to Tg. Next, QSPR modeling is shown to supplement and guide first-principles density functional theory (DFT) computations in the design of polymers with specific dielectric properties, thereby leveraging the power of first-principles computations by providing high-throughput capability. Our approach consists of multiple rounds of validated MQSPR modeling and DFT computations to optimize the polymer skeleton as well as functional group substitutions thereof. Rigorous model validation protocols insure that the statistical models are able to make valid predictions on molecules outside the training set. Future work with inverse QSPRs has the potential to further reduce the time to optimize materials properties.

Supplementary material

10853_2012_6639_MOESM1_ESM.doc (334 kb)
Supplementary material 1 (DOC 335 kb)

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • N. Sukumar
    • 1
    • 2
  • Michael Krein
    • 2
  • Qiong Luo
    • 2
  • Curt Breneman
    • 2
  1. 1.Department of ChemistryShiv Nadar UniversityDadriIndia
  2. 2.Rensselaer Exploratory Center for Cheminformatics Research and Department of Chemistry and Chemical BiologyRensselaer Polytechnic InstituteTroyUSA

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