Abstract
The existence of point defects, holes, and corrugations (macroscopic defects) induces high catalytic potential in graphene and its derivatives. We report a systematic approach for microscopic and macroscopic defect density optimization in excimer laser-induced reduced graphene oxide by varying the laser energy density and pulse number to achieve a record detection limit of 7.15 nM for peroxide sensing. A quantitative estimation of point defect densities was obtained using Raman spectroscopy and confirmed with electrochemical sensing measurements. Laser annealing (LA) at 0.6 J cm-2 led to the formation of highly reduced graphene oxide (GO) by liquid-phase regrowth of molten carbon with the presence of dangling bonds, making it catalytically active. Hall-effect measurements yielded a mobility of ∼200 cm2 V-1 s-1. An additional increase in the number of pulses at 0.6 J cm-2 resulted in deoxygenation through the solid-state route, leading to the formation of holey graphene structure. The average hole size showed a hierarchical increase, with the number of pulses characterized with multiple microscopy techniques, including scanning electron microscopy, atomic force microscopy, and transmission electron microscopy. The exposure of edge sites due to high hole density after 10 pulses supported the formation of proximal diffusion layers, which led to facile mass transfer and improvement in the detection limit from 25.4 mM to 7.15 nM for peroxide sensing. However, LA at 1 J cm-2 with 1 pulse resulted in a high melt lifetime of molten carbon and the formation of GO characterized by a high resistivity of 3 × 10-2 Ω-cm, which was not ideal for sensing applications. The rapid thermal annealing technique using a batch furnace to generate holey graphene results in structure with uneven hole sizes. However, holey graphene formation using the LA technique is scalable with better control over hole size and density. This study will pave the path for cost-efficient and high-performance holey graphene sensors for advanced sensing applications.
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