Systematic optimization of triboelectric nanogenerator performance through surface micropatterning

Abstract

Abstract Since the first papers on triboelectric nanogenerators (TENG) were published in 2012, the performance and efficiency of these novel devices have continued to improve dramatically. Early on, it was found that adding nanostructures to the surfaces of the active materials improved the efficiency as it increased the surface area and thus the amount of charge transfer. While this method of optimization makes logical sense, there has been little systematic work to show exactly how the increased surface area improves TENG performance. Here we propose a simple geometric model showing how arrays of hemispheres can interlock with each other and increase the amount of surface contact based on the spacing between pattern features. We were able to correlate this with a polyamide and polyvinylidene fluoride (PVDF) model system TENG which were patterned using a method based on hot microcontact printing. By tuning the spacing between the pattern features, the output voltage and current can be improved by several times compared to a planar sample. By deepening our understanding of the surface interactions in TENG we can optimize TENG devices in smarter ways to reduce cost and improve performance.