학술논문

Conductivity Analysis of Carbon Black and Graphite Composites based on Percolation Theory
Document Type
Conference
Source
2024 IEEE 3rd International Conference on Micro/Nano Sensors for AI, Healthcare, and Robotics (NSENS) Micro/Nano Sensors for AI, Healthcare, and Robotics (NSENS), 2024 IEEE 3rd International Conference on. :120-123 Mar, 2024
Subject
Bioengineering
Components, Circuits, Devices and Systems
Computing and Processing
General Topics for Engineers
Robotics and Control Systems
Signal Processing and Analysis
Mechanical sensors
Graphite
Medical services
Conductivity
Robot sensing systems
Stability analysis
Mechanical factors
carbon-based polymer composites
conductive analysis
percolation theory
Language
Abstract
Conductive polymers, particularly carbon-based ones like carbon black and graphite, have gained attention for their unique electrical and mechanical properties. Carbon black, with its high conductivity and excellent electron transport, is a cost-effective additive that improves the overall conductivity of composites. Graphite, known for its conductivity and mechanical stability, offers extended electron movement and durability. These advantages make carbon-based conductive polymers suitable for flexible sensors. In this study, we optimize the properties of carbon black and graphite using percolation theory by manipulating the concentration and arrangement of conductive fillers. Simulations indicate that incorporating graphite enhances the conductivity of carbon black, enabling the theoretical analysis of high-performance flexible sensors. This research paves a pathway for the manufacture of flexible carbon-based sensors with superior electronic properties.