Structure Property Correlation of Polymer Dielectrics Using Electrical Response Data

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Year : 2026 | Volume : 14 | 03 | Page :
    By

    B Ram Priya,

  • G Mohandass,

  • C Sridhathan,

  • R Arangasamy,

  • R Tharwin Kumar,

  • NMG Kumar,

  1. Professor, Department of Electrical and Electronics Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India
  2. Professor, Department of Biomedical Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India
  3. Professor, Department of Electronics and Communication Engineering, KCG College of Technology, Karapakkam, Chennai, Tamil Nadu, India
  4. Professor, Department of Biomedical Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India
  5. Professor, Department of Electrical and Electronics Engineering, Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College), Tirupati, Andhra Pradesh, India
  6. Professor, Department of Electrical and Electronics Engineering, Sri M. Visvesvaraya Institute of Technology, Bangalore, Karnataka, India

Abstract

Polymer dielectrics are foundational to insulation, capacitors, embedded passives, and flexible electronics, where performance is governed by the frequency-dependent electrical response rather than a single dielectric constant. This study presents a spectroscopy-aware structure–property correlation framework that transforms dielectric response data into physically interpretable spectral fingerprints and learns mappings from polymer descriptors to these fingerprints for prediction and interpretation. Broadband spectra are standardized on a log-frequency grid and parameterized using relaxation-informed fitting (Havriliak–Negami with a conduction term) to extract compact descriptors such as high-frequency permittivity, relaxation strength, characteristic relaxation time, dispersion exponents, and DC conductivity proxy. Multi-output regression models are trained using polymer structure and available morphology/processing metadata to predict these spectral parameters and reconstruct permittivity and loss behavior over frequency, with uncertainty and domain-validity checks to support robust screening. Example results show stable fingerprint extraction, accurate prediction of key descriptors, and preservation of anchor-frequency properties and relaxation peak locations, demonstrating an interpretable pathway from polymer structure to dielectric dispersion and loss trends.

Keywords: Polymer dielectrics; Dielectric spectroscopy; Structure–property correlation; Havriliak–Negami modeling; Polymer informatics

How to cite this article:
B Ram Priya, G Mohandass, C Sridhathan, R Arangasamy, R Tharwin Kumar, NMG Kumar. Structure Property Correlation of Polymer Dielectrics Using Electrical Response Data. Journal of Polymer & Composites. 2026; 14(03):-.
How to cite this URL:
B Ram Priya, G Mohandass, C Sridhathan, R Arangasamy, R Tharwin Kumar, NMG Kumar. Structure Property Correlation of Polymer Dielectrics Using Electrical Response Data. Journal of Polymer & Composites. 2026; 14(03):-. Available from: https://journals.stmjournals.com/jopc/article=2026/view=243970


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Ahead of Print Subscription Original Research
Volume 14
03
Received 28/02/2026
Accepted 14/05/2026
Published 15/05/2026
Publication Time 76 Days
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