Tailoring the properties of graphene nanosheets during electrochemical exfoliation

IF 3.1 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY
Markus Ostermann , Lukas Kalchgruber , Jürgen Schodl , Peter Lieberzeit , Pierluigi Bilotto , Markus Valtiner
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Abstract

The large-scale production of graphene remains a significant bottleneck in harnessing the potential of this material. Electrochemical exfoliation offers a green, sustainable production protocol that is suitable for industrial scale-up. However, the material produced often suffers from a low yield and limited functional groups, which restricts its use in advanced applications.
In this study, we introduce a mathematical model that elucidates the intricate influences of production parameters, such as temperature and potential, on the characteristics of the product. A comprehensive understanding of the exfoliation process is achieved through detailed insights provided by X-ray photoelectron spectroscopy, Raman spectroscopy, X-ray diffraction, and powder conductivity measurements. Design-of-Experiment and Pareto analysis are employed to determine the optimal production conditions. As a result, graphene nanosheets, tailored with specific physical and chemical properties (e.g., functional groups, conductivity), can be produced.
Furthermore, we describe the significant influence of the cation during sulfate-based anodic exfoliation, which allows for efficiency and cost optimization. In general, the tailoring aspect of this work paves the way towards the industrial production of graphene nanosheets, tailored to the intended application. Simultaneously, the experimental design lays the foundation for a data-driven machine learning method for the optimal synthesis of sustainable two-dimensional materials.

Abstract Image

电化学剥离过程中石墨烯纳米片的特性
石墨烯的大规模生产仍然是利用这种材料潜力的一个重大瓶颈。电化学剥离提供了一种绿色、可持续的生产方案,适用于工业规模扩大。然而,所生产的材料通常存在产率低和官能团有限的问题,这限制了其在高级应用中的使用。在这项研究中,我们引入了一个数学模型来说明生产参数,如温度和电势,对产品特性的复杂影响。通过x射线光电子能谱、拉曼光谱、x射线衍射和粉末电导率测量提供的详细见解,全面了解剥离过程。采用实验设计法和帕累托分析法确定了最优生产条件。因此,可以生产出具有特定物理和化学性质(例如,官能团,电导率)的石墨烯纳米片。此外,我们还描述了硫酸盐基阳极剥离过程中阳离子的重要影响,从而实现了效率和成本的优化。总的来说,这项工作的定制方面为石墨烯纳米片的工业生产铺平了道路,为预期的应用量身定制。同时,实验设计为数据驱动的机器学习方法为可持续二维材料的最佳合成奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Carbon Trends
Carbon Trends Materials Science-Materials Science (miscellaneous)
CiteScore
4.60
自引率
0.00%
发文量
88
审稿时长
77 days
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