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Reliability of Raman measurements of thermal conductivity of single-layer graphene due to selective electron-phonon coupling: A first-principles study
Abstract
Raman spectroscopy has been widely used to measure thermal conductivity ($\ensuremath{\kappa}$) of two-dimensional (2D) materials such as graphene. This method is based on a well-accepted assumption that different phonon polarizations are in near thermal equilibrium. However, in this paper, we show that, in laser-irradiated single-layer graphene, different phonon polarizations are in strong nonequilibrium, using predictive simulations based on first principles density functional perturbation theory and a multitemperature model. We first calculate the electron cooling rate due to phonon scattering as a function of the electron and phonon temperatures, and the results clearly illustrate that optical phonons dominate the hot electron relaxation process. We then use these results in conjunction with the phonon scattering rates computed using perturbation theory to develop a multitemperature model and resolve the spatial temperature distributions of the energy carriers in graphene under steady-state laser irradiation. Our results show that electrons, optical phonons, and acoustic phonons are in strong nonequilibrium, with the flexural acoustic (ZA) phonons showing the largest nonequilibrium to other phonon modes, mainly due to their weak coupling to other carriers in suspended graphene. Since ZA phonons are the main heat carriers in graphene, we estimate that neglecting this nonequilibrium leads to underestimation of thermal conductivity in experiments at room temperature by a factor of 1.35 to 2.6, depending on experimental conditions and assumptions used. Underestimation is also expected in Raman measurements of other 2D materials when the optical-acoustic phonon coupling is weak.
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“So far, the thermal conductivities of monolayer or few-layer 2D materials have been dominantly measured by micro-Raman spectroscopy and thermal bridge method”
From Tutorial: Time-domain thermoreflectance (TDTR) for thermal property characterization of bulk and thin film materials (2018) · cites this paper as [222]
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“both with their intrinsic limitations that impair the accuracy of their measurements. 221, 222”
From Tutorial: Time-domain thermoreflectance (TDTR) for thermal property characterization of bulk and thin film materials (2018) · cites this paper as [222]
Citations
Cites
Special points for Brillouin-zone integrations
Monkhorst, H. J., & Pack, J. D. (1976) · Physical Review B · doi:10.1103/physrevb.13.5188 · Cited by 71,721
QUANTUM ESPRESSO: a modular and open-source software project for quantum simulations of materials
Giannozzi, P., Baroni, S., Bonini, N., Calandra, M., Car, R., Cavazzoni, C., Ceresoli, D., Chiarotti, G., Cococcioni, M., Dabo, I., et al. (2009) · Journal of Physics Condensed Matter · doi:10.1088/0953-8984/21/39/395502 · Cited by 29,793
Superior Thermal Conductivity of Single-Layer Graphene
Balandin, A. A., Ghosh, S., Bao, W., Calizo, I., Teweldebrhan, D., Miao, F., & Lau, C. N. (2008) · Nano Letters · doi:10.1021/nl0731872 · Cited by 13,823
Ferrari, A. C. (2007) · Solid State Communications · doi:10.1016/j.ssc.2007.03.052 · Cited by 7,706
Raman spectroscopy in graphene
Malard, L. M., Pimenta, M. A., Dresselhaus, G., & Dresselhaus, M. S. (2009) · Physics Reports · doi:10.1016/j.physrep.2009.02.003 · Cited by 6,168
Introduction to infrared and Raman spectroscopy
Jayasooriya, U. A. (1991) · Spectrochimica Acta Part A Molecular Spectroscopy · doi:10.1016/0584-8539(91)80026-f · Cited by 2,989
Spatially Resolved Raman Spectroscopy of Single- and Few-Layer Graphene
Graf, D., Molitor, F., Ensslin, K., Stampfer, C., Jungen, A., Hierold, C., & Wirtz, L. (2007) · Nano Letters · doi:10.1021/nl061702a · Cited by 2,631
Ghosh, S., Calizo, I., Teweldebrhan, D., Pokatilov, E. P., Nika, D. L., Balandin, A. A., Bao, W., Miao, F., & Lau, C. N. (2008) · Applied Physics Letters · doi:10.1063/1.2907977 · Cited by 2,116
Two-Dimensional Phonon Transport in Supported Graphene
Seol, J. H., Jo, I., Moore, A. L., Lindsay, L., Aitken, Z. H., Pettes, M. T., Li, X., Yao, Z., Huang, R., Broido, D., et al. (2010) · Science · doi:10.1126/science.1184014 · Cited by 1,926
Lin, Z., Zhigilei, L. V., & Celli, V. (2008) · Physical Review B · doi:10.1103/physrevb.77.075133 · Cited by 1,444
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Research works printed but not linked: 2
- S. I. Anisimov, 1974, Zh. Eksp. Teor. Fiz., 66, 776
- S. I. Anisimov, 1974, Sov. Phys. JETP, 39, 375
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Rezgui, H., Zhang, C., & Torres, C. M. S. (2026) · Applied Physics Letters · doi:10.1063/5.0314469 · Cited by 2
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Zhang, C., & Wu, L. (2025) · Applied Physics Letters · doi:10.1063/5.0248153 · Cited by 1
Nonequilibrium thermal transport across metal-Si interfaces from Boltzmann transport theory
Han, J., & Lee, S. (2025) · Physical review. B./Physical review. B · doi:10.1103/fndt-fln1 · Cited by 1
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Coco, M. (2023) · Applications in Engineering Science · doi:10.1016/j.apples.2023.100135
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Yue, Y. (2026) · Springer eBooks · doi:10.1007/978-981-95-5985-5_8
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Li, J., Lian, M., Liu, M., Liang, H., Zhang, C., & Xu, J. (2026) · Journal of Computational and Applied Mathematics · doi:10.1016/j.cam.2026.118043
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Metadata
- Authors
- Vallabhaneni, A. K., Singh, D., Bao, H., Murthy, J., & Ruan, X.
- Affiliations
- Purdue University West Lafayette (US)
- Intel (United States) (US)
- Shanghai Jiao Tong University (CN)
- Corresponding author
- Ruan, Xiulin
- ORCID
- Venue
- Physical Review B
- Publisher
- American Physical Society (APS)
- Published
- 2016-03-28
- Volume
- 93
- Issue
- 12
- ISSN
- 2469-9950 (ISSN-L)
- 2469-9969
- OpenAlex
- W2324689618
- Cited by
- 134
- References
- 33
- Citations by year
- 2026: 9 · 2025: 13 · 2024: 7 · 2023: 11 · 2022: 17 · 2021: 22 · 2020: 17 · 2019: 10 · 2018: 12 · 2017: 12 · 2016: 4
- FWCI
- 5.64
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Physical review. B./Physical review. B (publishedVersion)
- Funders
- Purdue University
- Air Force Office of Scientific Research (FA9550-11-1-0057)
- National Natural Science Foundation of China (51306111)
- Natural Science Foundation of Shanghai (13ZR1456000)
- Topics
- Physical Sciences › Materials Science › Materials Chemistry › Thermal properties of materials
- Physical Sciences › Materials Science › Materials Chemistry › Graphene research and applications
- Physical Sciences › Materials Science › Materials Chemistry › 2D Materials and Applications
- Keywords
- monolayer graphene, thermal conductivity, Raman thermometry, electron-phonon coupling, nonequilibrium phonons, electron cooling, optical phonons, laser irradiation, suspended graphene, density functional perturbation theory, two-dimensional materials
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