Automated Raman, PL and SHG Imaging Workflow for 2D Materials Characterisation

Introduction: Automated workflow for correlative imaging of 2D materials

Characterising 2D materials like graphene, transition metal dichalcogenides (TMDs), and hexagonal boron nitride (hBN) typically requires combining multiple optical techniques because each method reveals different physical properties. Without an automated workflow, the user must manually switch between techniques and initiate each measurement.

This article presents a workflow that integrates Raman, photoluminescence (PL), and polarisation-resolved second harmonic generation (SHG) imaging into one automated measurement routine. As all measurements are performed at the same sample position, the resulting image set enables direct comparison of the complementary information provided by the three techniques:

• Raman spectroscopy and imaging reveals crystal structure, layer number, strain, and defects.
• Photoluminescence provides information on the electronic structure, bandgap, and electronic behaviour.
• Polarised Second Harmonic Generation is sensitive to symmetry, crystal orientation, and layer stacking.

The automated workflow is particularly relevant for high-throughput characterisation, core facilities, and industrial environments that require reproducible multimodal measurements.

Fig. 1: Representative image examples of WS₂ flakes obtained with the automated workflow. From left to right: Raman image, PL image, and SHG images recorded at 0°, 20°, and 50° polarisation angle of the incoming laser wave.

Benefits of an automated workflow for correlative optical characterisation

Compared to manual workflows, the automated approach reduces user intervention allowing for high throughput and reproducibility in routine measurements (Table 1). Automation enables:

• Reduced time for measurements
• Consistent alignment across techniques
• Sequential acquisition without user intervention
• High spatial resolution
• Automated switching of spectrograph settings such as grating and centre of grating
• Automated laser switching

Table 1: Comparison of manual and automated workflow.

Workflow implementation for automated Raman, PL and SHG imaging

The workflow consists of a one-time microscope setup (Fig. 2, bright blue steps) followed by a fully automated acquisition sequence (Fig. 2, dark blue steps). Instead of starting each scan manually, the user defines the scan area. Then the system executes all measurement modalities point by point and line by line and stores co-registered datasets for direct comparison.

Fig. 2: Workflow for correlative Raman, PL and SHG imaging of 2D materials. Bright blue steps: Setting up the witec360 microscope. Dark blue steps: Automated workflow.

Microscope configuration

The automated workflow and exemplary measurements presented in this article rely on a fully automated witec360 microscope with the following equipment configuration:

• HexaLight spectrograph with 150 g/mm and 1800 g/mm gratings
• Lasers:
  • 532 nm for Raman and PL measurements
  • 1064 nm pulsed laser for SHG measurements
• Objectives:
  • 20x air objective for overview white light imaging
  • 100x air objective for all other measurements
• Dual-pass polarisation configuration enabling continuous rotation of the incident laser polarisation from 0° to 360°, while maintaining a parallel orientation between the incident and detected polarisations
• Motorised sample stage

The acquisition sequence (dark blue steps of the workflow in Fig. 2) was automated using the Workflow Manager of the WITec Suite software.

Using the automated workflow for multimodal characterisation of WS₂ flakes

Tungsten disulfide (WS₂) is a typical 2D semiconductor material used in optoelectronics and valleytronics. WS₂ flakes on Si/SiO₂ substrates were characterised using the automated, multimodal microscopy workflow integrating Raman, PL and polarised SHG imaging.

Fig. 3 shows the bright-field image of the area of interest. A common scan area was defined for Raman, PL and SHG imaging, indicated by the red box in Fig. 3. All measurements were performed sequentially by the automated routine without user intervention. High-resolution maps were acquired by raster scanning the sample with a fixed step size to ensure dense spatial sampling. At each position, Raman spectra, PL emission, and SHG signals were recorded under their respective excitation conditions while maintaining consistent spatial alignment. SHG images were acquired at seven distinct incident-polarisation angles revealing the crystallographic orientation of the WS₂ crystals. The parameters for the automated scans are set in the Large Area Scan in the Control Window of the WITec Control software and listed in Table 2.

The resulting datasets are intrinsically co-registered in the WITec Suite software and analysed to correlate structural, optical, and symmetry-related properties across the sample.

Fig. 3: Bright-field image of WS₂ flakes, with the red box highlighting the area of interest for further investigation by Raman, PL and SHG.

Table 2: Imaging parameters common to all measurements performed with this workflow.

Correlative Raman, PL and SHG analysis of WS₂ flakes

Figure 4 shows the nine co-registered Raman, PL and SHG datasets acquired automatically from the same sample region.

Fig. 4: Raman, PL and SHG image set of WS₂ flakes acquired using the automated measurement workflow. (a) Raman image, (b) PL image, and SHG images recorded at incident laser polarisation angles of (c) 0°, (d) 10°, (e) 20°, (f) 30°, (g) 40°, (h) 50°, and (i) 60°. All images were generated using SUM filtering over the respective spectral peaks.

The complementary information from the three techniques enables comprehensive characterisation of the WS₂ sample.

Raman imaging: For 2D materials, Raman spectroscopy allows the identification of layer thickness (intensity of Raman bands), strain or doping variations (via characteristic peak shifts), and confirms material uniformity. In this case, the analysed WS₂ crystals consist of uniform monolayers, without overlap (Fig. 4a).

PL imaging: Monolayer regions show strong PL emission. PL highlights defects or quenching regions and can differentiate mono- and multilayer domains. In this case, the strong PL signal confirms the monolayer nature of the crystals and highlights defects (Fig. 4b).

SHG imaging: SHG is sensitive to non-centrosymmetric structures. It provides strong signal in odd-layer WS₂ and reveals crystal orientation and domain boundaries (Fig. 4 c-i). To highlight the sensitivity of SHG to crystal orientation, images were acquired at different polarisation directions of the incident laser light.

Benefits of correlative Raman, PL and SHG imaging of 2D materials

Correlative Raman, PL and polarisation-resolved SHG imaging helps researchers comprehensively characterise 2D material samples. By correlating the datasets:

• Layer identification becomes unambiguous
• Optical and structural properties can be cross-validated
• Defects or heterogeneities are better understood
• Complementary information on orientation and symmetry, layer thickness, strain, doping, and defects is revealed.

Typical applications of automated correlative workflows

The presented automated workflow for 2D materials characterisation is especially useful for academic and industrial users who need reproducible characterisation workflows for:

• High-throughput screening of 2D materials
• Device fabrication optimisation
• Studying spatial heterogeneity
• Research on new layered materials

Summary

The example demonstrates an efficient, automated multimodal imaging workflow for characterising 2D materials that:

• Eliminates repeated manual intervention
• Combines Raman, PL and polarised SHG into one routine
• Produces high-resolution, co-registered datasets
• Assures reproducibility and comparability
• Enables deeper insight into material properties