Ultralow thermal conductivity and fast ionic diffusion endow superionic materials with excellent performance both as thermoelectric converters and as solid-state electrolytes. Yet the correlation and interdependence between these two features remain unclear owing to a limited understanding of their complex atomic dynamics. Here we investigate ionic diffusion and lattice dynamics in argyrodite Ag8SnSe6 using synchrotron X-ray and neutron scattering techniques along with machine-learned molecular dynamics. We identify a critical interplay of the vibrational dynamics of mobile Ag and a host framework that controls the overdamping of low-energy Ag-dominated phonons into a quasi-elastic response, enabling superionicity. Concomitantly, the persistence of long-wavelength transverse acoustic phonons across the superionic transition challenges a proposed ‘liquid-like thermal conduction’ picture. Rather, a striking thermal broadening of low-energy phonons, starting even below 50 K, reveals extreme phonon anharmonicity and weak bonding as underlying features of the potential energy surface responsible for the ultralow thermal conductivity (<0.5 W m−1 K−1) and fast diffusion. Our results provide fundamental insights into the complex atomic dynamics in superionic materials for energy conversion and storage.
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Data that support the plots within this paper and other findings of this study are available from the corresponding authors upon request. Source data are provided with this paper.
The input files including structure and neural network potential files used for calculating the thermal conductivity using LAMMPS are provided with this paper. The codes that support other findings of the study are available from the corresponding authors on request.
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J.M. thanks the National Science Foundation of China for the financial support (grant no. U1732154). Q.R. thanks the Guangdong Basic and Applied Basic Research Foundation (grant no. 2021B1515140014), the National Natural Science Foundation of China (grant no. 52101236), the Institute of High Energy Physics, Chinese Academy of Science (grant no. E15154U110) and the Open Project of Key Laboratory of Artificial Structures and Quantum Control (Ministry of Education; grant no. 2020-05). J.D. and O.D. were supported by the US National Science Foundation DMREF award (no. DMR-2119273). Y.P. thanks the National Science Foundation of China for support (no. T2125008). M.J. thanks the National Science Foundation of China for financial support (grant no. 52272006) and the ‘Shuguang Program’ from the Shanghai Education Development Foundation and Shanghai Municipal Education Commission. Z. Cheng thanks the Australia Research Council for support (no. DP210101436). X.T. acknowledges the financial support from the Guangdong Basic and Applied Basic Research Foundation (grant no. 2019B1515120079). Q.R. thanks Y. Guo and H. Su from ShanghaiTech University for the help on crystal alignment, and S. Danilkin, D. Yu and C.-W. Wang from the Australian Nuclear Science and Technology Organisation for the assistance with neutron data collection. We all acknowledge the beam time granted by Institut Laue-Langevin (proposal nos 5-14-263 and 5-14-268), Heinz Maier-Leibnitz (proposal no. 14754), J-PARC (proposal nos 2018B0262 and 2020A0228) and the Australian Nuclear Science and Technology Organisation (proposal no. P7875), and the technical support from Q. Gu during the experiments at the Australian Synchrotron.
The authors declare no competing interests.
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Supplementary Sections 1–6, Figs. 1–24, Tables 1 and 2 and refs. 1–7.
Supplementary Code 1
The initial structure file in LAMMPS format, neural network force-field file generated using DeePMD-kit code, LAMMPS input file, Fortran script and input file for lattice thermal conductivity calculations using time dependence heat flux.
Source Data Fig. 1
SXRD data plotted in Fig. 1a,b; and the lattice parameters as a function of temperature plotted in Fig. 1c.
Source Data Fig. 2
INS data plotted in Fig. 2a–c; INS data and QENS analysis plotted in Fig. 2d; and S(Q,E) data from MLMD simulations plotted in Fig. 2e.
Source Data Fig. 3
INS data plotted in Fig. 3a–d; partial phonon DOS from MLMD simulations plotted in Fig. 3e,f; and MSD values from MLMD simulations plotted in Fig. 3g,h.
Source Data Fig. 4
INS data plotted in Fig. 4a–c; Bose-factor-corrected dynamic structure factor plotted in Fig. 4d; and neutron-weighted DOS over energy transfer from MLMD simulations plotted in Fig. 4e.
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Ren, Q., Gupta, M.K., Jin, M. et al. Extreme phonon anharmonicity underpins superionic diffusion and ultralow thermal conductivity in argyrodite Ag8SnSe6. Nat. Mater. (2023). https://doi.org/10.1038/s41563-023-01560-x