Laser induced graphene on polymer substrate for flexible sensing applications in healthcare

  • Wen Liu

Student thesis: Phd

Abstract

Graphene, known as a novel 2D material, has drawn extensive attention due to remarkable electrical properties such as electrical conductivity, chemical stability and mechanical properties. Conventional methods to prepare graphene commonly involve complex and time-consuming processes, harsh conditions and costly precursors, hindering the scale-up and commercialization of graphene for numerous applications. The emergence of the laser-induced graphene (LIG) method has demonstrated exceptional potential for generating 3D graphene networks, delivering notable cost-effectiveness and a simplified and rapid fabrication process. Nevertheless, current LIG is limited to substrates, laser types, and nanoparticle integration process. These constraints impede the development of flexible sensors with high sensitivity, stability and excellent compatibility with the human body. Accordingly, having LIG developed and optimized is essential for improving the properties of flexible sensors in healthcare monitoring. In this thesis work, three novel LIG technologies have been developed, including (1) laser directly writing the LIG on the fabric substrates for wearable strain sensors, (2) Utilizing a one-step laser process to simultaneously generate platinum (Pt) nanoparticles embedded in LIG flakes for precise human motion detection and (3) developing a LIG/Au composite on the flexible substrate for glucose detection. For the generation of LIG on the fabric substrate, a UV laser (355nm in wavelength) direct writing technique is developed to produce a porous graphene network on polyimide fabrics for the application of flexible strain sensors. It was found that the quality of graphene induced by ultraviolet laser is heavily relevant to the laser energy input. With optimised laser fluence of 20.5 mJ/cm2, a porous graphene foam with a low sheet resistance of 20 Ω/sq can be obtained and exhibits excellent electrical properties. In addition, the assembly strain sensor using the polyimide fabrics as the substrate shows a high sensitivity (Maximum GF of 27), a small strain threshold value of 0.08%, and high mechanical stability in long-term testing (4% increase of resistance after 1000 cycles). With the significant sensing performance, multiple human motion activities can be detected and recorded in the form of resistance change including finger bending, wrist bending and muscle movement, indicating promising potential in the field of healthcare monitor. Secondly, a one-step laser synthesis to simultaneously generate Pt nanoparticles embedded in the porous LIG network was developed to enhance the sensing performance for precise human motion detection. The laser process involved irradiating a polymer film formed with a mixture of polybenzimidazole (PBI) and Pt(acac)2 solution at the laser fluence of 25.2 mJ/cm2. The results reveal a crack-based sensing mechanism resulting from the specific microstructure of LIG flakes loaded with Pt nanoparticles, which leads to a high sensitivity (a gauge factor, GFmax = 489.3), a small hysteresis, and an excellent working stability for more than 5000 cycles. In addition, this Pt/LIG strain sensor is able to capture multiscale human motion signals from subtle physical activities such as pulse beating, chewing and swallowing to large-scale limb movements including knee bending, which benefits the practical sensing abilities in healthcare. Apart from developing high-performance flexible strain sensors, a further study on flexible glucose biosensor was carried out. Inspired from the one-step laser synthesis of LIG/Pt active materials, a facial method was developed to deposit ultra-thin gold layer on the surface of porous LIG flakes on a flexible polyimide substrate. By controlling the amount of gold used for thermal evaporation, a gold layer with optimized morphology can be efficiently fabricated, showing excellent electrical conductivity and electrochemical activity. Benefiting from the optimized Au morphology, the as-prepar
Date of Award31 Dec 2023
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorAndrew Thomas (Supervisor)

Keywords

  • electrochemical activity
  • glucose biosensors
  • flexible strain sensors
  • Laser-induced graphene
  • human motion detection

Cite this

'