Enhancing triboelectrification via multiscale roughness dependent thermal dissipation

Abstract

Polymer-based triboelectric nanogenerators (TENGs) have held promise due to their excellent interfacial conformity and ease of fabrication. However, the role of surface roughness in triboelectricity requires further study. In this study, we have manipulated the nano-/micro-scale roughness configuration in polydimethylsiloxane (PDMS) over a wide range of extents using various sandpaper-based templates. According to the power spectral density analysis, the spatial frequency of template-free PDMS exhibits several distinct bandwidth regions each with different fractal dimensions significantly higher than 2, despite having the lowest roughness value. In contrast, most template-based PDMS shows an entire spatial frequency region that scales nearly with a single power factor corresponding to a fractal dimension as low as 2, despite slight increases in roughness values. Consequently, the surface temperature gradient and output performance of TENG increased, following the trend of fractal dimension and roughness, but the surface potentials have remained almost invariant. However, excessive increases in the surface roughness cause the spatial frequency to be divided once again into several different bandwidth regions with different cutoffs and higher fractal dimensions. These results suggest that the performance of TENG can be controlled by tuning both surface roughness and self-affine properties over multiple scales. Specifically, adhesive interaction becomes dominant on surfaces with lower fractality, enhancing TENG performance due to the expanded contact area. This study sheds light on the relationship among triboelectricity, thermal dissipation, and topography.