## 3 Pavement Self-Sensing Technology Based on Conductive Polymer Composite Materials
### Factors Affecting the Electrical Conductivity of Polymer Composites
#### 3.1.2 Conductive Fillers  
Commonly used conductive materials include metal and carbon, metal conductive materials mainly include gold, silver, nickel, copper, etc. Carbon conductive materials are widely used in the development of sensitive composite materials for better binding with polymer compounds, and the most commonly used ones are CNTs [100; 102], CB, carbon fiber [103], and the GNP [104] class. The physicochemical properties of various carbon materials vary greatly due to their structural and scale differences. During the development process of composites, single-carbon materials or compound-carbon materials can be flexibly selected according to the needs and can be combined with different polymer materials. Nanoscale conductive fillers, due to their special nanoscale size effect and large specific surface area, cause the polymer matrix and conductive fillers to have a large area of direct or indirect interaction between them, which in turn causes a series of interfacial interaction changes and novel mechanical and electrical phenomena. CNTs have been widely used in research on self-sensing composites as conductive materials and structural reinforcement components due to their excellent mechanical and electrical properties. Due to the structure of carbon nanotubes and the lamellar structure of graphite, their axial conductivity is extremely superior, and they have an ultra-high aspect ratio, which is a very ideal conductive filler. In general, theory predicts that its electrical conductivity depends on the helicity of the arrangement of its layers of carbon atoms, i.e., the pipe diameter and the helix angle of the pipe wall (n, m). On the one hand, when the integer multiple of n/m is 3, it is easy to show a metal-like conductivity; on the other hand, when the diameter of CNTs is n < 6 nm, CNTs can be regarded as a one-dimensional quantum wire with good conductivity performance, and when the diameter of CNTs is n > 6 nm, the conductivity gradually decreases. In addition, according to the number of structural layers, CNTs can be categorized into single-walled CNTs and multi-walled CNTs, and the performance of SWCNTs is generally better than that of MWCNTs, but they are very expensive due to their more complex preparation. However,both SWCNTs and MWCNTs have extremely high Young's modulus and tensile strength values, and when they are subjected to mechanical deformation by external forces, they produce corresponding changes in the corresponding electrical signals, which also provides good application prospects for their participation in the preparation of sensing components. Nanoscale fillers have high specific surface energies, resulting in a low dispersion of CNTs in polymer matrices and common solvents, which are prone to aggregation. The conjugated and hyperconjugated electronic systems and hollow structures in the internal structure of CNTs in turn provide a basis for their further expansion, i.e., surface functionalization, such as amination [105], carboxylation [106; 107], macromolecule functionalization [108], and the modification of silane coupling agents [109]. Surface-functionalized CNTs help to reduce the repulsive forces between carbon CNTs, thus facilitating dispersion. Carbon black (CB), as spherical particles with sizes at the millimeter, micrometer, and nanometer scale, depending on the preparation process [76], has good electrical conductivity and low cost and is also widely used in the preparation of composite materials. However, due to the limitation of its shape, generally, CB has a high conductive value over penetration. Graphene is a conductive filler with a lamellar structure, which is a newly emerging material in recent years. The planar structure and ultra-high specific surface area of graphene allow for better transfer of stress to the matrix during the loading process, resulting in higher mechanical properties in polymer composites [110].