Strong Scattering from Low-Frequency Rattling Modes Results in Low Thermal Conductivity in Antimonide Clathrate Compounds

Kamil M. Ciesielski, Brenden R. Ortiz, Lidia C. Gomes, Vanessa Meschke, Jesse Adamczyk, Tara L. Braden, Dariusz Kaczorowski, Elif Ertekin, Eric S. Toberer

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Recent discoveries of materials with ultralow thermal conductivity open a pathway to significant developments in the field of thermoelectricity. Here, we conduct a comparative study of three chemically similar antimonides to establish the root causes of their extraordinarily low thermal conductivity (0.4-0.6 W m-1 K-1 at 525 K). The materials of interest are the unconventional type-XI clathrate K58Zn122Sb207, the tunnel compound K6.9Zn21Sb16, and the type-I clathrate K8Zn15.5Cu2.5Sb28 discovered herein. Calculations of the phonon dispersions show that the type-XI compound exhibits localized (i.e., rattling) phonon modes with unusually low frequencies that span the entire acoustic regime. In contrast, rattling in type I clathrate is observed only at higher frequencies, and no rattling modes are present in the tunnel structure. Modeling reveals that low-frequency rattling modes profoundly limit the acoustic scattering time; the scattering time of the type-XI clathrate is half that of the type-I clathrate and a quarter of that of the tunnel compound. For all three materials, the thermal conductivities are additionally suppressed by soft framework bonding that lowers the acoustic group velocities and structural complexity that leads to diffusonic character of the optical modes. Understanding the details of thermal transport in structurally complex materials will be crucial for developing the next generation of thermoelectrics.

Original languageEnglish
Pages (from-to)2918-2935
Number of pages18
JournalChemistry of Materials
Volume35
Issue number7
DOIs
StatePublished - Apr 11 2023
Externally publishedYes

Funding

This work was funded primarily with support from the National Science Foundation (NSF) via grant DMR 1555340 sponsoring work of E.S.T., V.M., B.R.O., T.L.B., J.A., and K.M.C. E.E. and L.C.G. acknowledge support from NSF grant DMR 1729149. This research is part of the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation (awards OCI-0725070 and ACI-1238993), the State of Illinois, and as of December, 2019, the National Geospatial-Intelligence Agency. Blue Waters is a joint effort of the University of Illinois at Urbana-Champaign and its National Center for Supercomputing Applications. This work also used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562.(101) This work was funded primarily with support from the National Science Foundation (NSF) via grant DMR 1555340 sponsoring work of E.S.T., V.M., B.R.O., T.L.B., J.A., and K.M.C. E.E. and L.C.G. acknowledge support from NSF grant DMR 1729149. This research is part of the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation (awards OCI-0725070 and ACI-1238993), the State of Illinois, and as of December, 2019, the National Geospatial-Intelligence Agency. Blue Waters is a joint effort of the University of Illinois at Urbana–Champaign and its National Center for Supercomputing Applications. This work also used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562.

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