Microstructure reconstruction and structural equation modeling for computational design of nanodielectrics

  • Yichi Zhang
  • He Zhao
  • Irene Hassinger
  • L. Catherine Brinson
  • Linda S. Schadler
  • Wei Chen
Part of the following topical collections:
  1. Multidisciplinary Design Optimization


Nanodielectric materials, consisting of nanoparticle-filled polymers, have the potential to become the dielectrics of the future. Although computational design approaches have been proposed for optimizing microstructure, they need to be tailored to suit the special features of nanodielectrics such as low volume fraction, local aggregation, and irregularly shaped large clusters. Furthermore, key independent structural features need to be identified as design variables. To represent the microstructure in a physically meaningful way, we implement a descriptor-based characterization and reconstruction algorithm and propose a new decomposition and reassembly strategy to improve the reconstruction accuracy for microstructures with low volume fraction and uneven distribution of aggregates. In addition, a touching cell splitting algorithm is employed to handle irregularly shaped clusters. To identify key nanodielectric material design variables, we propose a Structural Equation Modeling approach to identify significant microstructure descriptors with the least dependency. The method addresses descriptor redundancy in the existing approach and provides insight into the underlying latent factors for categorizing microstructure. Four descriptors, i.e., volume fraction, cluster size, nearest neighbor distance, and cluster roundness, are identified as important based on the microstructure correlation functions (CF) derived from images. The sufficiency of these four key descriptors is validated through confirmation of the reconstructed images and simulated material properties of the epoxy-nanosilica system. Among the four key descriptors, volume fraction and cluster size are dominant in determining the dielectric constant and dielectric loss.


Nanodielectric Material design Descriptor identification Microstructure characterization and reconstruction Structural Equation Modeling 



The support from NSF for this collaborative research: CMMI-1334929 (Northwestern University) and CMMI-1333977 (RPI), is greatly appreciated.


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Copyright information

© Zhang et al. 2015

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Yichi Zhang
    • 1
  • He Zhao
    • 1
  • Irene Hassinger
    • 2
  • L. Catherine Brinson
    • 1
  • Linda S. Schadler
    • 2
  • Wei Chen
    • 1
  1. 1.Northwestern UniversityEvanstonUSA
  2. 2.Rensselaer Polytechnic InstituteTroyUSA

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