# Reading a graphene Raman spectrum

> A one-page guide to the Raman spectrum of graphene: how the 2D band changes from one layer to graphite, the NPL monolayer criteria, what the 2D width says about the substrate, the defect distance from I(D)/I(G), the defect type from I(D)/I(D′), and the strain–doping map that separates the two.

- Page: https://www.labcanvas.com/templates/graphene-research/reading-graphene-raman-spectrum
- Open in the LabCanvas editor (LabCanvas account): https://www.labcanvas.com/editor.html?template=graphene-raman-guide
- Updated: 2026-10-14
- Category: Graphene research
- Method: Raman guide
- Starting materials: Graphene on SiO₂/Si, hBN or as a CVD film; spectra at 532 nm unless stated
- Product: Number of layers, monolayer check, defect distance and type, strain and doping
- Key result: Spectra, maps and lines computed by LabCanvas from the cited measurements; the layer-dependent 2D line shapes are schematic and carry no numbers on the shift axis; the strain–doping points are generated around set means
- Figure: 1920 × 1080 px, 45 editable layers (6 generated objects with settings)

## Steps

1. **2D band and layers**: One Lorentzian for a monolayer, four components for an AB bilayer (Mafra et al. 2012) and six for ABA and ABC trilayers (Park & Ryu 2015); graphite shows 2D₁ and 2D₂ near 2680 and 2720 cm⁻¹ and I(G)/I(2D) grows with the number of layers, past 1.4 in multilayers (Qiu et al. 2016); the 2D band is stronger than G below five layers (Gupta et al. 2006)
2. **Monolayer check**: The NPL criteria at 532 nm: FWHM(2D) ≤ 35 cm⁻¹ and I(2D)/I(G) ≥ 2 (Muñoz-Vargas et al. 2025); a monolayer spectrum has its single 2D band at 2675 cm⁻¹, about 28 cm⁻¹ wide (Qiu et al. 2016)
3. **What the 2D width tells you**: 12.1 and 17.9 cm⁻¹ computed for a perfect lattice, 17–20 cm⁻¹ for graphene in hBN and above 22 cm⁻¹ on SiO₂ (Neumann et al. 2015); a CVD film measured 26.2 ± 1.7 cm⁻¹ (Muñoz-Vargas et al. 2025)
4. **How many defects**: I(D)/I(G) against the mean distance between defects, L_D, rises to a maximum near 3 nm and depends on the laser; for L_D ≥ 10 nm, L_D² ≈ 4.3 × 10³ / (E_L⁴ · I(D)/I(G)), L_D in nm, E_L in eV (Cançado et al. 2011)
5. **Which defects**: I(D)/I(D′) is about 13 for sp³ defects, about 7 for vacancy-like defects and about 3.5 for boundaries (Eckmann et al. 2012)
6. **Strain or doping**: In the (ω_G, ω_2D) plane strain moves points along a line of slope 2.45 (57 cm⁻¹ of G shift per % of biaxial strain) and hole doping along one of slope 0.7, both through the undoped, unstrained point (1582, 2670) cm⁻¹ at 532 nm (Lee et al. 2012); the 2D position moves 88 cm⁻¹ per eV of laser energy (Yang et al. 2019; Valeš et al. 2020)

## Strengths

- Raman counts layers without damage and at high throughput (Ferrari et al. 2006)
- One spectrum gives layers, defects, strain and doping
- The NPL criteria give a pass/fail monolayer test (Muñoz-Vargas et al. 2025)

## Limitations

- A turbostratic multilayer can pass the monolayer criteria (Muñoz-Vargas et al. 2025)
- I(D)/I(G) has two defect distances for one value and depends on the laser (Cançado et al. 2011)
- The substrate changes the 2D width (Neumann et al. 2015)

## Uses

- Quality control of exfoliated and CVD graphene
- Checking defects after processing
- Mapping strain and doping across devices

## References

1. Ferrari et al., “Raman spectrum of graphene and graphene layers”, Phys. Rev. Lett. 2006. https://doi.org/10.1103/PhysRevLett.97.187401 (primary)
2. Muñoz-Vargas et al., “Simple graphene film production by chemical vapour deposition and the use of AI for quality analysis”, Nanoscale Adv. 2025. https://doi.org/10.1039/d5na00668f (primary)
3. Cançado et al., “Quantifying defects in graphene via Raman spectroscopy at different excitation energies”, Nano Lett. 2011. https://doi.org/10.1021/nl201432g (primary)
4. Eckmann et al., “Probing the nature of defects in graphene by Raman spectroscopy”, Nano Lett. 2012. https://doi.org/10.1021/nl300901a (primary)
5. Lee et al., “Optical separation of mechanical strain from charge doping in graphene”, Nat. Commun. 2012. https://doi.org/10.1038/ncomms2022 (primary)
6. Qiu et al., “Raman and conductivity analysis of graphene for biomedical applications”, Materials 2016. https://doi.org/10.3390/ma9110897 (further reading)
7. Mafra et al., “Using the G′ Raman cross-section to understand the phonon dynamics in bilayer graphene systems”, Nano Lett. 2012. https://doi.org/10.1021/nl300477n (further reading)
8. Park & Ryu, “Direction-controlled chemical doping for reversible G-phonon mixing in ABC trilayer graphene”, Sci. Rep. 2015. https://doi.org/10.1038/srep08707 (further reading)
9. Gupta et al., “Raman scattering from high-frequency phonons in supported n-graphene layer films”, Nano Lett. 2006. https://doi.org/10.1021/nl061420a (further reading)
10. Neumann et al., “Raman spectroscopy as probe of nanometre-scale strain variations in graphene”, Nat. Commun. 2015. https://doi.org/10.1038/ncomms9429 (further reading)
11. Yang et al., “Annealing effect on UV-illuminated recovery in gas response of graphene-based NO₂ sensors”, RSC Adv. 2019. https://doi.org/10.1039/c9ra01295h (further reading)
12. Valeš et al., “Graphene-enhanced Raman scattering on single layer and bilayers of pristine and hydrogenated graphene”, Sci. Rep. 2020. https://doi.org/10.1038/s41598-020-60857-y (further reading)

Credit: Computed by LabCanvas after Ferrari et al., PRL 2006 (doi:10.1103/PhysRevLett.97.187401), Muñoz-Vargas et al., Nanoscale Adv. 2025, Neumann et al., Nat. Commun. 2015, Cançado et al., Nano Lett. 2011, Eckmann et al., Nano Lett. 2012, Lee et al., Nat. Commun. 2012, and the papers in the details.

## Questions

**What does the “Reading a graphene Raman spectrum” template show?** A one-page guide to the Raman spectrum of graphene: how the 2D band changes from one layer to graphite, the NPL monolayer criteria, what the 2D width says about the substrate, the defect distance from I(D)/I(G), the defect type from I(D)/I(D′), and the strain–doping map that separates the two.

**What are the steps shown in “Reading a graphene Raman spectrum”?** 1. 2D band and layers: One Lorentzian for a monolayer, four components for an AB bilayer (Mafra et al. 2012) and six for ABA and ABC trilayers (Park & Ryu 2015); graphite shows 2D₁ and 2D₂ near 2680 and 2720 cm⁻¹ and I(G)/I(2D) grows with the number of layers, past 1.4 in multilayers (Qiu et al. 2016); the 2D band is stronger than G below five layers (Gupta et al. 2006). 2. Monolayer check: The NPL criteria at 532 nm: FWHM(2D) ≤ 35 cm⁻¹ and I(2D)/I(G) ≥ 2 (Muñoz-Vargas et al. 2025); a monolayer spectrum has its single 2D band at 2675 cm⁻¹, about 28 cm⁻¹ wide (Qiu et al. 2016). 3. What the 2D width tells you: 12.1 and 17.9 cm⁻¹ computed for a perfect lattice, 17–20 cm⁻¹ for graphene in hBN and above 22 cm⁻¹ on SiO₂ (Neumann et al. 2015); a CVD film measured 26.2 ± 1.7 cm⁻¹ (Muñoz-Vargas et al. 2025). 4. How many defects: I(D)/I(G) against the mean distance between defects, L_D, rises to a maximum near 3 nm and depends on the laser; for L_D ≥ 10 nm, L_D² ≈ 4.3 × 10³ / (E_L⁴ · I(D)/I(G)), L_D in nm, E_L in eV (Cançado et al. 2011). 5. Which defects: I(D)/I(D′) is about 13 for sp³ defects, about 7 for vacancy-like defects and about 3.5 for boundaries (Eckmann et al. 2012). 6. Strain or doping: In the (ω_G, ω_2D) plane strain moves points along a line of slope 2.45 (57 cm⁻¹ of G shift per % of biaxial strain) and hole doping along one of slope 0.7, both through the undoped, unstrained point (1582, 2670) cm⁻¹ at 532 nm (Lee et al. 2012); the 2D position moves 88 cm⁻¹ per eV of laser energy (Yang et al. 2019; Valeš et al. 2020).

**What are the starting materials and the product?** Starting materials: Graphene on SiO₂/Si, hBN or as a CVD film; spectra at 532 nm unless stated. Product: Number of layers, monolayer check, defect distance and type, strain and doping.

**Which papers is “Reading a graphene Raman spectrum” based on?** Ferrari et al., “Raman spectrum of graphene and graphene layers”, Phys. Rev. Lett. 2006 (doi:10.1103/PhysRevLett.97.187401); Muñoz-Vargas et al., “Simple graphene film production by chemical vapour deposition and the use of AI for quality analysis”, Nanoscale Adv. 2025 (doi:10.1039/d5na00668f); Cançado et al., “Quantifying defects in graphene via Raman spectroscopy at different excitation energies”, Nano Lett. 2011 (doi:10.1021/nl201432g); Eckmann et al., “Probing the nature of defects in graphene by Raman spectroscopy”, Nano Lett. 2012 (doi:10.1021/nl300901a); Lee et al., “Optical separation of mechanical strain from charge doping in graphene”, Nat. Commun. 2012 (doi:10.1038/ncomms2022); Qiu et al., “Raman and conductivity analysis of graphene for biomedical applications”, Materials 2016 (doi:10.3390/ma9110897); Mafra et al., “Using the G′ Raman cross-section to understand the phonon dynamics in bilayer graphene systems”, Nano Lett. 2012 (doi:10.1021/nl300477n); Park & Ryu, “Direction-controlled chemical doping for reversible G-phonon mixing in ABC trilayer graphene”, Sci. Rep. 2015 (doi:10.1038/srep08707); Gupta et al., “Raman scattering from high-frequency phonons in supported n-graphene layer films”, Nano Lett. 2006 (doi:10.1021/nl061420a); Neumann et al., “Raman spectroscopy as probe of nanometre-scale strain variations in graphene”, Nat. Commun. 2015 (doi:10.1038/ncomms9429); Yang et al., “Annealing effect on UV-illuminated recovery in gas response of graphene-based NO₂ sensors”, RSC Adv. 2019 (doi:10.1039/c9ra01295h); Valeš et al., “Graphene-enhanced Raman scattering on single layer and bilayers of pristine and hydrogenated graphene”, Sci. Rep. 2020 (doi:10.1038/s41598-020-60857-y).

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