Laser writing of metal-oxide doped graphene films for tunable sensor applications

Flexible and wearable devices play a pivotal role in the realm of smart portable electronics due to their diverse applications in healthcare monitoring, soft robotics, human-machine interfaces, and artificial intelligence. Nonetheless, the extensive integration of intelligent wearable sensors into mass production faces challenges within a resource-limited environment, necessitating low-cost manufacturing, high reliability, stability, and multi-functionality. In this study, a cost-effective fiber laser direct writing method (fLDW) was illustrated to create highly responsive and robust flexible sensors. These sensors integrate laser-induced graphene (LiG) with mixed metal oxides on a flexible polyimide film. fLDW simplifies the synthesis of graphene, functionalization of carbon structures into graphene oxides and reduced graphene oxides, and deposition of metal-oxide nanoparticles within a single experimental laser writing setup. The preparation and surface modification of dense oxygenated graphene networks and semiconducting metal oxide nanoparticles (CuO _<i>x</i> , ZnO _<i>x</i> , FeO _<i>x</i> ) enables rapid fabrication of LiG/MO _<i>x</i> composite sensors with the ability to detect and differentiate various stimuli, including visible light, UV light, temperature, humidity, and magnetic fluxes. Further, this <i>in situ</i> customizability of fLDW-produced sensors allows for tunable sensitivity, response time, recovery time, and selectivity. The normalized current gain of resistive LiG/MO _<i>x</i> sensors can be controlled between -2.7 to 3.5, with response times ranging from 0.02 to 15 s, and recovery times from 0.04 to 6 s. Furthermore, the programmable properties showed great endurance after 200 days in air and extended bend cycles. Collectively, these LiG/MO _<i>x</i> sensors stand as a testament to the effectiveness of fLDW in economically mass-producing flexible and wearable electronic devices to meet the explicit demands of the Internet of Things.