Thermal Transport in Ag8TS6 (T= Si, Ge, Sn) Argyrodites: An Integrated Experimental, Quantum-Chemical, and Computational Modelling Study
Joana Bustamante, Anupama Ghata, Aakash A. Naik, Christina Ertural, Katharina Ueltzen, Wolfgang G. Zeier, Janine George

TL;DR
This study combines experimental, quantum-chemical, and computational methods to analyze thermal transport in Ag8TS6 argyrodites, revealing their low thermal conductivity and potential for thermoelectric applications.
Contribution
It introduces a two-channel lattice-dynamics model and machine-learned potentials for predicting thermal conductivity, validated against experimental data.
Findings
Low lattice thermal conductivity due to anharmonicity and bond heterogeneity.
Thermal and ionic conductivities are independent and tunable separately.
Models accurately predict thermal conductivity across temperature range.
Abstract
Argyrodite-type Ag-based sulfides combine exceptionally low lattice thermal and high ionic conductivity, making them promising candidates for thermoelectric and solid-state energy applications. In this work, we studied Ag8TS6 (T= Si, Ge, Sn) argyrodite family by combining chemical-bonding analysis, lattice vibrational properties simulation, and experimental measurements to investigate their structural and thermal transport properties. Furthermore, we propose a two-channel lattice-dynamics model based on Gr\"uneisen-derived phonon lifetimes and compare it to an approach using machine-learned interatomic potentials. Both approaches are able to predict thermal conductivity in agreement with experimental lattice thermal conductivities along the whole temperature range, highlighting their potential suitability for future high-throughput predictions. Our findings also reveal a relationship…
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