In this study, wearable triboelectric nanogenerators comprising bar-printed polyvinylidene fluoride (PVDF) films incorporated with cobalt-based metal–organic framework (Co-MOF) were developed. The enhanced output performance of the TENGs was attributed to the phase transition of PVDF from α-crystals to β-crystals, as facilitated by the incorporation of the MOF. The synthesis conditions, including metal ion, concentration, and particle size of the MOF, were optimized to increase open-circuit voltage (V_OC) and open-circuit current (I_SC) of PVDF-based TENGs. In addition to high operational stability, mechanical robustness, and long-term reliability, the developed TENG consisting of PVDF incorporated with Co-MOF (Co-MOF@PVDF) achieved a V_OC of 194 V and an I_SC of 18.8 μA. Furthermore, the feasibility of self-powered mobile electronics was demonstrated by integrating the developed wearable TENG with rectifier and control units to power a global positioning system (GPS) device. The local position of the user in real-time through GPS was displayed on a mobile interface, powered by the battery charged through friction-induced electricity generation.

Understanding charge transport mechanisms in thin-film transistors based on random networks of single-wall carbon nanotubes (SWCNT-TFTs) is essential for further advances to improve the potential for various nanoelectronic applications. Herein, a comprehensive investigation of the two-dimensional (2D) charge transport mechanism in SWCNT-TFTs is reported by analyzing the temperature-dependent electrical characteristics determined from the direct-current and non-quasi-static transient measurements at 80-300 K. To elucidate the time-domain charge transport characteristics of the random networks in the SWCNTs, an empirical equation was derived from a theoretical trapping model, and a carrier velocity distribution was determined from the differentiation of the transient response. Furthermore, charge trapping and de-trapping in shallow- and deep-traps in SWCNT-TFTs were analyzed by investigating charge transport based on their trapping/de-trapping rate. The comprehensive analysis of this study provides fundamental insights into the 2D charge transport mechanism in TFTs based on random networks of nanomaterial channels.