# Non-invasive Scanning Raman Spectroscopy and Tomography for Graphene Membrane Characterization

## TL;DR

This paper introduces a fast, non-invasive Raman spectroscopy method combined with tomography for large-scale, in-line characterization of graphene membranes, enabling detailed analysis of their structure and composition in NEMS devices.

## Contribution

It develops a novel Raman tomography technique for three-dimensional, non-invasive characterization of graphene membranes, enhancing quality control in NEMS fabrication.

## Key findings

- Effective differentiation between freestanding and supported graphene.
- Successful 3D Raman tomography of graphene membranes.
- Automated data analysis for in-line device monitoring.

## Abstract

Graphene has extraordinary mechanical and electronic properties, making it a promising material for membrane based nanoelectromechanical systems (NEMS). Here, chemical-vapor-deposited graphene is transferred onto target substrates to suspend it over cavities and trenches for pressure-sensor applications. The development of such devices requires suitable metrology methods, i.e., large-scale characterization techniques, to confirm and analyze successful graphene transfer with intact suspended graphene membranes. We propose fast and noninvasive Raman spectroscopy mapping to distinguish between freestanding and substrate-supported graphene, utilizing the different strain and doping levels. The technique is expanded to combine two-dimensional area scans with cross-sectional Raman spectroscopy, resulting in three-dimensional Raman tomography of membrane-based graphene NEMS. The potential of Raman tomography for in-line monitoring is further demonstrated with a methodology for automated data analysis to spatially resolve the material composition in micrometer-scale integrated devices, including free-standing and substrate-supported graphene. Raman tomography may be applied to devices composed of other two-dimensional materials as well as silicon micro- and nanoelectromechanical systems.

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Source: https://tomesphere.com/paper/1702.07534