Nanoscale thermal transport at PbTe grain boundaries: a neural-network-potential molecular dynamics study

Susumu Fujii; Tatsuya Yokoi; Katsuyuki Matsunaga

doi:10.1039/d5ta09725h

January 1, 2026Journal of Materials Chemistry AOpen Access

Nanoscale thermal transport at PbTe grain boundaries: a neural-network-potential molecular dynamics study

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Key Points

The research aims to understand how grain boundaries influence thermal conductivity in thermoelectric materials like PbTe.
Utilized molecular dynamics simulations to analyze thermal transport at grain boundaries.
Employed neural-network potentials to model interactions at the atomic level.
Investigated the effects of grain boundary characteristics on thermal conductivity.
Identified significant reductions in thermal conductivity at specific grain boundaries.
Revealed mechanisms by which grain boundaries enhance thermoelectric efficiency.
Found that tailored grain boundary structures can lead to improved energy conversion rates.

Implication

Molecular dynamics examines thermal transport at grain boundaries in thermoelectric materials, suggesting efficiency improvements.

Abstract

Grain boundaries (GBs) are nano- and mesoscale defects that play a key role in tailoring lattice thermal conductivity κ l and enhancing thermoelectric conversion efficiency. However, even in the prototypical thermoelectric...

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Cite This Study

Fujii et al. (2026) studied this question.

synapsesocial.com/papers/699e9143f5123be5ed04eb17 https://doi.org/10.1039/d5ta09725h

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Nanoscale thermal transport at PbTe grain boundaries: a neural-network-potential molecular dynamics study

Key Points

Implication

Abstract

Discussion

Cite This Study

Nanoscale thermal transport at PbTe grain boundaries: a neural-network-potential molecular dynamics study

Key Points

Implication

Abstract

Discussion

Cite This Study

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