Bandyopadhyay Disha, Sun Yiwei, Griffin Ross, Lee Lok Yi
Paragraf, 7-8 W Newlands, Somersham, Huntingdon PE28 3EB, United Kingdom.
Ecole Polytechnique Fédérale de Lausanne, Rue de la Maladière 71, Neuchâtel CH-2000, Switzerland.
ACS Omega. 2024 Oct 14;9(43):43447-43452. doi: 10.1021/acsomega.4c04675. eCollection 2024 Oct 29.
Application of revolve sphere levelling (RSL) as a practical and effective image processing tool for enhancing scanning tunnelling microscopy (STM) images of graphene atomic lattices is presented. Low-cost, ambient, and non-invasive STM methods overcome limitations of traditional imaging methods like scanning transmission electron microscopy (STEM) and transmission electron microscopy (TEM) that can introduce or alter defects in graphene. Utilizing high-quality graphene synthesized via Paragraf's patented Metal-Organic Chemical Vapor Deposition (MOCVD) method, RSL, which is easily implemented via the Gwyddion software package, effectively highlights the hexagonal lattice structure and specific defect structures. This provides clarity of the atomic structure that traditional methods struggle to achieve. This research emphasizes the utility of RSL in materials science for defect identification in graphene, and points to future research in optimizing RSL for a broader range of defects and applications in other 2D materials.
本文介绍了旋转球平整(RSL)作为一种实用且有效的图像处理工具在增强石墨烯原子晶格扫描隧道显微镜(STM)图像方面的应用。低成本、环境友好且非侵入性的STM方法克服了传统成像方法(如扫描透射电子显微镜(STEM)和透射电子显微镜(TEM))的局限性,这些传统方法可能会在石墨烯中引入或改变缺陷。利用通过Paragraf的专利金属有机化学气相沉积(MOCVD)方法合成的高质量石墨烯,通过Gwyddion软件包易于实现的RSL有效地突出了六边形晶格结构和特定的缺陷结构。这提供了传统方法难以实现的原子结构清晰度。本研究强调了RSL在材料科学中用于石墨烯缺陷识别的实用性,并指出了未来在优化RSL以用于更广泛的缺陷以及在其他二维材料中的应用方面的研究方向。