Layered Metal–Polymer Hybrid Laminates with Embedded Impact Sensors for Connected Automotive Panels

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Year : 2026 | Volume : 14 | 05 | Page :
By

Anil S Pol,

Sivakumar Balu,

Gaurao S. Dharme,

S.K. Ashok,

C. Karthikeyan,

K. Anguraj,

P. Sukania,

Chitra Devi D,

K. Nithya,

  1. Assistant Professor, Department of Mechanical Engineering, Visvesvaraya Technological University, Belagavi, Karnataka, India
  2. Senior Engineer, IEEE Senior Member, San Jose, California, , United States
  3. Workshop Superintendent, Agnel Technical College (Polytechnic),Bandra West Mumbai, Maharashtra, India
  4. Associate Professor, Department of Automobile Engineering, Dr. Mahalingam College of Engineering and Technology, Pollachi, Tamil Nadu, India
  5. Associate Professor, Department of Mechanical Engineering, Mohamed Sathak A.J. College of Engineering, Chennai, Tamil Nadu, India
  6. Associate Professor, Department of Electronics and Communication Engineering, Sona College of Technology, Salem, Tamil Nadu, India
  7. Assistant Professor, Department of Mathematics, R.M.K. Engineering College, Chennai, Tamil Nadu, India
  8. Associate Professor, Department of Computer Science and Engineering, R.M.D Engineering College, Chennai, Tamil Nadu, India
  9. Assistant Professor, Department of Artificial Intelligence and Machine Learning, St. Joseph’s College of Engineering, Chennai, Tamil Nadu, India

Abstract

The increasing demand for lightweight, intelligent, and structurally reliable automotive components has accelerated the development of multifunctional hybrid materials capable of simultaneously providing superior mechanical performance and real-time structural health monitoring. In this study, a novel layered metal-polymer hybrid laminate incorporating an embedded flexible impact sensor was developed for connected automotive panel applications. The laminate was fabricated using AA6061-T6 aluminum alloy face sheets and a thermoplastic polyurethane interlayer through hot-press compression molding. A flexible graphene/CNT-based sensor was embedded at the neutral plane of the polymer core to monitor impact events without compromising structural integrity. Mechanical evaluation demonstrated that the TPU interlayer enhanced impact energy absorption, delayed crack propagation, and improved damage tolerance under low-velocity impact loading while maintaining high tensile and flexural performance. The sensor exhibited stable and repeatable voltage responses over impact energies ranging from 5 J to 30 J, showing excellent correlation between sensor output and impact severity. Furthermore, an ESP32-based wireless communication module established an Internet of Things enabled structural health monitoring framework capable of transmitting real-time impact data to cloud platforms for remote visualization and predictive maintenance. The proposed multifunctional hybrid laminate successfully combines lightweight structural reinforcement, impact sensing, and intelligent connectivity within a single integrated architecture, demonstrating strong potential for next-generation automotive body panels, enhanced passenger safety, and sustainable vehicle technologies for future connected mobility ecosystems and autonomous transportation worldwide.

Keywords: Thermoplastic polyurethane, graphene/carbon nano-tube, metal–polymer hybrid laminate, remote visualization, flexural performance.

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How to cite this article: Anil S Pol, Sivakumar Balu, Gaurao S. Dharme, S.K. Ashok, C. Karthikeyan, K. Anguraj, P. Sukania, Chitra Devi D, K. Nithya. Layered Metal–Polymer Hybrid Laminates with Embedded Impact Sensors for Connected Automotive Panels. Journal of Polymer & Composites. 2026; 14(05):-.
How to cite this URL: Anil S Pol, Sivakumar Balu, Gaurao S. Dharme, S.K. Ashok, C. Karthikeyan, K. Anguraj, P. Sukania, Chitra Devi D, K. Nithya. Layered Metal–Polymer Hybrid Laminates with Embedded Impact Sensors for Connected Automotive Panels. Journal of Polymer & Composites. 2026; 14(05):-. Available from: https://journals.stmjournals.com/jopc/article=2026/view=250971

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Ahead of Print Subscription Original Research
Volume 14
05
Received 15/07/2026
Accepted 22/07/2026
Published 29/07/2026
Publication Time 14 Days

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