ArticleMicromachines2023
Liquid Phase Graphene Exfoliation with a Vibration-Based Acoustofluidic Effector.
Article in Micromachines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Abstract
Liquid phase exfoliation (LPE) has emerged as a promising method for the industrial-scale production of graphene. However, one of its critical steps, namely sonication, has faced challenges due to high power consumption and low efficiency, leading to limited applicability in industrial settings. This study introduces a novel, cost-effective microfluidic sonication device designed to significantly reduce power consumption while efficiently assisting the LPE process for graphene production. By coupling a capillary with a buzzer and applying an appropriate electric signal, simulation and particle tracing experiments reveal the generation of robust shear forces resulting from acoustic streaming and cavitation when the capillary end is immersed in the liquid. For the first time, the capillary-based sonication device was effectively utilized for graphene exfoliation in a DMF (N,N-Dimethylformamide) + NaOH liquid phase system. The SEM (Scanning Electron Microscope) and Raman characterization results corroborate the successful exfoliation of 100 nm with thicknesses below 10 nm graphene sheets from graphite flakes using this pioneering device. The values of I2D/IG increase after processing, which suggests the exfoliation of graphite flakes into thinner graphene sheets. The vibration-based acoustofluidic effector represents a versatile and scalable miniature device, capable of being employed individually for small-batch production, thereby optimizing the utilization of raw 2D materials, particularly in experimental scenarios. Alternatively, it holds the potential for large-scale manufacturing through extensive parallelization, offering distinct advantages in terms of cost-efficiency and minimal power consumption.
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