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Tarun Singhal,
Ishta Rani,
Vinay Bhatia,
Ankur Singhal,
Parveen Kumar,
- Associate Professor, Department of Electronics and Communication Engineering, Chandigarh Engineering College-CGC, Landran, Mohali, Punjab, India
- Assistant Professor, Department of computer science and Engineering, Chandigarh Universiy, Gharuan, Punjab, India
- Professor, Department of Electronics and Communication Engineering, Chandigarh Engineering College-CGC, Landran, Mohali, Punjab, India
- Professor, Department of Electronics and Communication Engineering, Chandigarh Engineering College-CGC, Landran, Mohali, Punjab, India
- Assistant Professor, Department of computer science and Engineering, Chandigarh Universiy, Gharuan, Punjab, India
Abstract
The increasing demand for intelligent biomedical monitoring systems has accelerated research into ultra-low-power sensing technologies capable of operating with high sensitivity and minimal energy consumption. Conductive polymers have attracted considerable attention for biomedical and nanoelectronic applications due to their tunable electrical properties, biocompatibility, and environmental stability. Among them, Polypyrrole (PPy) is a promising functional polymer that can enhance charge transport and electrostatic coupling in nanoscale devices. In this work, a Deep Neural Network (DNN)-assisted Polypyrrole-gated Single Electron Transistor (SET) architecture is proposed for biomedical energy harvesting and charge detection applications. A Python-based simulation framework was developed to investigate SET current-voltage characteristics, Coulomb blockade behavior, and biomedical charge sensing response, PPy conductivity enhancement, and energy harvesting performance. The simulation results demonstrate a charging energy of 1.05 × 10⁻²⁰ J and a Coulomb temperature of 761.99 K, indicating stable charge confinement and room-temperature-compatible operation. The conductivity of the PPy layer increased from approximately 59 S/m to 78 S/m during sensing operation, improving electrostatic coupling and charge transport. Furthermore, the proposed sensor achieved a charge detection limit of 4.50 × 10⁻¹⁶ C and harvested 2.23 × 10⁻⁶ J of energy, demonstrating its suitability for self-powered biomedical sensing applications. The DNN model exhibited low prediction error and successfully captured the nonlinear relationship between biomedical charge variations and device response. The obtained results highlight the potential of conductive polymer-gated SET devices for next-generation wearable healthcare systems, implantable biosensors, and intelligent biomedical monitoring platforms.
Keywords: Polypyrrole, Conductive Polymer, Single Electron Transistor, DNN, Coloumb Blockade
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Journal of Polymer & Composites
| Volume | 14 | |
| 04 | ||
| Received | 18/06/2026 | |
| Accepted | 02/07/2026 | |
| Published | 27/08/2026 | |
| Publication Time | 70 Days |