In suspended graphene under substantial tensile strain, classical molecular dynamics shows a thermal conductivity that grows without apparent bound with system size and simulation time, a signature of anomalous (non-Fourier) heat transport expected for two-dimensional momentum-conserving systems. Zhou et al. (2025) demonstrated, in million-atom simulations with a near-first-principles neuroevolution potential (NEP, a machine-learned interatomic potential trained on first-principles data), that introducing grain boundaries into graphene restores a finite thermal conductivity even under the same strong tensile strain, but left the microscopic mechanism unexplained and left the asymptotic divergence of strained pristine graphene unconfirmed. The open problem is to identify the dominant scattering processes, length and time scales, and the interplay with asymmetric interatomic interactions and near-integrable dynamics by which grain boundaries suppress the divergence and restore Fourier-like heat conduction in strained two-dimensional momentum-conserving systems, and to definitively establish whether the thermal conductivity of strained pristine graphene diverges in the infinite-size, infinite-time limit.

Background

Whether Fourier's empirical law of heat conduction holds in low-dimensional systems with momentum-conserving dynamics is a long-standing open problem of nonequilibrium statistical physics (A. Dhar, Adv. Phys. 57, 457 (2008); G. Benenti, D. Donadio, S. Lepri, R. Livi, Riv. Nuovo Cimento 46, 105 (2023)). In equilibrium molecular dynamics (MD), thermal conductivity κ\kappa is computed from the Green-Kubo formula, which integrates the equilibrium heat-current autocorrelation function C(t)C(t); the 'running' conductivity κ(t)\kappa(t) is the integral up to correlation time tt. In one- and two-dimensional systems whose microscopic dynamics conserve total momentum, hydrodynamic arguments (reasoning from the long-wavelength, fluid-like collective modes) predict a long-time tail C(t)∼t−d/2C(t)\sim t^{-d/2} in dd dimensions, so in 2D the integral grows logarithmically and κ\kappa is expected to diverge with system size unless some scattering mechanism cuts off the tail. Consistent with this, classical MD of suspended graphene found a finite, size-convergent κ\kappa without strain but a logarithmically divergent κ\kappa when uniaxial tensile strain exceeds about 2% (L. F. C. Pereira and D. Donadio, Phys. Rev. B 87, 125424 (2013)); the physical picture is that tensile strain suppresses the out-of-plane flexural (ZA) phonons — the bending modes whose acoustic dispersion is quadratic in unstrained membranes — and thereby weakens the scattering that would otherwise regularize transport. Related first-principles work is contested: M. Xu (Phys. Scr. 98, 115951 (2023)) argued that an anomalous size effect of κ\kappa is generic in two-dimensional dielectrics, while Z. Han and X. Ruan (Phys. Rev. B 108, L121412 (2023)) found from an exact solution of the phonon Boltzmann transport equation (BTE, the kinetic equation for phonon populations) including four-phonon (higher-order anharmonic) scattering that the room-temperature κ\kappa of unstrained monolayer graphene converges to about 1300 W/(m K). In one-dimensional momentum-conserving lattices it is known that asymmetric interatomic interactions (potentials that are not even functions of the relative displacement of neighboring atoms) can restore normal heat conduction (Y. Zhong, Y. Zhang, J. Wang, H. Zhao, Phys. Rev. E 85, 060102 (2012)), and nearly integrable dynamics (dynamics close to an integrable one, in which so many quantities are exactly conserved that heat transport cannot fully relax) is also implicated in anomalous crossovers, so both symmetry breaking of the interactions and proximity to integrability are recognized ingredients controlling Fourier behavior. Polycrystalline graphene, as grown by chemical vapor deposition, contains grain boundaries — interfaces between crystalline domains of different lattice orientation — which act as scattering planes for phonons and reduce κ\kappa in a grain-size-dependent way (Z. Fan et al., Nano Lett. 17, 5919 (2017); the in-plane versus flexural decomposition of κ\kappa is given in Z. Fan et al., Phys. Rev. B 95, 144309 (2017)). Zhou et al. (J. Appl. Phys. 137, 014305 (2025)) used the neuroevolution potential (NEP, a machine-learned interatomic potential trained on first-principles forces and energies) as implemented in the open-source GPUMD package (a molecular-dynamics code running on graphics processing units) to simulate over 1.4 million atoms. They found that at 300 K under 40 GPa biaxial tensile stress (about 5% strain) the running κ\kappa of pristine graphene shows no sign of convergence up to a correlation time of 5 ns, consistent with divergence, whereas polycrystalline graphene with a grain size of about 14 nm under the same conditions has a finite, convergent κ\kappa. They state explicitly that these results do not definitely confirm divergence at infinite correlation time, and that further investigations are required to understand the role of grain boundaries and the underlying mechanisms that could lead to Fourier's heat conduction law in low-dimensional momentum-conserving systems.

Problem Statement

Elucidate the microscopic mechanism by which grain boundaries suppress the divergence of the thermal conductivity and restore Fourier-like finite heat conduction in strained, momentum-conserving two-dimensional systems, using polycrystalline graphene under strong tensile strain as the demonstrated instance and stating explicitly whether the mechanism identified for graphene is expected to hold for other strained two-dimensional momentum-conserving systems. The joint target is to identify the dominant scattering processes and the relevant length and time scales through which grain boundaries cut off the long-time hydrodynamic tail of the heat-current autocorrelation; to establish how this suppression interplays with asymmetric interatomic interactions and the near-integrable dynamics of the strained membrane; and, as the complementary half of the same question, to definitively establish the asymptotic (infinite-size, infinite-time) behavior of the thermal conductivity of strained pristine graphene — divergent (with growth law) or convergent — resolving the extrapolation-limited ambiguity left by existing molecular-dynamics data.

References

  1. Xiaoye Zhou, Yuqi Liu, Benrui Tang, Junyuan Wang, Haikuan Dong, Xiaoming Xiu, Shunda Chen, Zheyong Fan, 'Million-atom heat transport simulations of polycrystalline graphene approaching first-principles accuracy enabled by neuroevolution potential on desktop GPUs', Journal of Applied Physics 137, 014305 (2025), DOI 10.1063/5.0244987 (arXiv:2410.13535), https://doi.org/10.1063/5.0244987
  2. Luiz Felipe C. Pereira, Davide Donadio, 'Divergence of the thermal conductivity in uniaxially strained graphene', Physical Review B 87, 125424 (2013), DOI 10.1103/PhysRevB.87.125424 (arXiv:1303.1569), https://arxiv.org/abs/1303.1569
  3. Zherui Han, Xiulin Ruan, 'Thermal conductivity of monolayer graphene: Convergent and lower than diamond', Physical Review B 108, L121412 (2023), DOI 10.1103/PhysRevB.108.L121412 (arXiv:2302.12216), https://arxiv.org/abs/2302.12216
  4. Mingtian Xu, 'Anomalous size effect of thermal conductivity of two-dimensional dielectric materials', Physica Scripta 98, 115951 (2023), DOI 10.1088/1402-4896/ad0086, https://doi.org/10.1088/1402-4896/ad0086
  5. Zheyong Fan, Petri Hirvonen, Luiz Felipe C. Pereira, Mikko M. Ervasti, Ken R. Elder, Davide Donadio, Ari Harju, Tapio Ala-Nissila, 'Bimodal grain-size scaling of thermal transport in polycrystalline graphene from large-scale molecular dynamics simulations', Nano Letters 17, 5919-5924 (2017), DOI 10.1021/acs.nanolett.7b01742, https://doi.org/10.1021/acs.nanolett.7b01742
  6. Zheyong Fan, Luiz Felipe C. Pereira, Petri Hirvonen, Mikko M. Ervasti, Ken R. Elder, Davide Donadio, Tapio Ala-Nissila, Ari Harju, 'Thermal conductivity decomposition in two-dimensional materials: Application to graphene', Physical Review B 95, 144309 (2017), DOI 10.1103/PhysRevB.95.144309, https://doi.org/10.1103/PhysRevB.95.144309
  7. Yi Zhong, Yong Zhang, Jiao Wang, Hong Zhao, 'Normal heat conduction in one-dimensional momentum conserving lattices with asymmetric interactions', Physical Review E 85, 060102 (2012), DOI 10.1103/PhysRevE.85.060102, https://doi.org/10.1103/PhysRevE.85.060102
  8. Abhishek Dhar, 'Heat transport in low-dimensional systems', Advances in Physics 57, 457-537 (2008), DOI 10.1080/00018730802538522, https://doi.org/10.1080/00018730802538522
  9. Giuliano Benenti, Davide Donadio, Stefano Lepri, Roberto Livi, 'Non-Fourier heat transport in nanosystems', La Rivista del Nuovo Cimento 46, 105-161 (2023), DOI 10.1007/s40766-023-00041-w, https://doi.org/10.1007/s40766-023-00041-w
  10. Xiguang Wu, Wenjiang Zhou, Haikuan Dong, Penghua Ying, Yanzhou Wang, Bai Song, Zheyong Fan, Shiyun Xiong, 'Correcting force error-induced underestimation of lattice thermal conductivity in machine learning molecular dynamics', The Journal of Chemical Physics 161, 014103 (2024), DOI 10.1063/5.0213811, https://doi.org/10.1063/5.0213811
  11. Abhishek Kumar, Kunwar Abhikeern, Amit Singh, 'Decoupling ripple and tensile strain effects and understanding curvature effects on thermal conductivity of polycrystalline graphene', Journal of Applied Physics 137 (2025), DOI 10.1063/5.0255653 (arXiv:2501.01730), https://doi.org/10.1063/5.0255653
  12. Kunwar Abhikeern, Amit Singh, 'Lattice thermal conductivity and phonon properties of polycrystalline graphene', Nanoscale Advances 7, 1125-1133 (2025), DOI 10.1039/d4na00772g (arXiv:2409.04503), https://doi.org/10.1039/d4na00772g
  13. Rongxiang Luo, Jiaqi Wen, Juncheng Guo, 'Heat Conduction in Momentum-Conserving Fluids: From quasi-2D to 3D systems', arXiv:2604.10536 (2026), https://arxiv.org/abs/2604.10536
  14. Ke Xu, Hekai Bu, Shuning Pan, Eric Lindgren, Yongchao Wu, Yong Wang, Jiahui Liu, Keke Song, Bin Xu, Yifan Li, Tobias Hainer, Lucas Svensson, Julia Wiktor, Rui Zhao, Hongfu Huang, Cheng Qian, Shuo Zhang, Zezhu Zeng, Bohan Zhang, Benrui Tang, Yang Xiao, Zihan Yan, Jiuyang Shi, Zhixin Liang, Junjie Wang, Ting Liang, Shuo Cao, Yanzhou Wang, Penghua Ying, Nan Xu, Chengbing Chen, Yuwen Zhang, Zherui Chen, Xin Wu, Wenwu Jiang, Esme Berger, Yanlong Li, Shunda Chen, Alexander J. Gabourie, Haikuan Dong, Shiyun Xiong, Ning Wei, Yue Chen, Jianbin Xu, Feng Ding, Zhimei Sun, Tapio Ala-Nissila, Ari Harju, Jincheng Zheng, Pengfei Guan, Paul Erhart, Jian Sun, Wengen Ouyang, Yanjing Su, Zheyong Fan, 'GPUMD 4.0: A high-performance molecular dynamics package for versatile materials simulations with machine-learned potentials', Materials Genome Engineering Advances 3, e70028 (2025), DOI 10.1002/mgea.70028, https://doi.org/10.1002/mgea.70028