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Machine learning boosted a b i n i t i o study of the thermal conductivity of Janus PtSTe van der Waals heterostructures

Authors: Pan, Lijun; Carrete, Jesús; Wang, Zhao; Madsen, Georg K. H.;

Machine learning boosted a b i n i t i o study of the thermal conductivity of Janus PtSTe van der Waals heterostructures

Abstract

Calculating the thermal conductivity of heterostructures with multiple layers presents a significant challenge for state-of-the-art ab initio methods. In this study we introduce an efficient neural-network force field (NNFF) to explore the thermal transport characteristics of van der Waals heterostructures based on PtSTe, using both the phonon Boltzmann transport equation and molecular dynamics (MD) simulations. Besides demonstrating a remarkable level of agreement with both theoretical and experimental data, our predictions reveal that heterogeneous combinations like PtSTe−PtTe2 display a notable reduction in thermal conductivity at room temperature, primarily due to broken out-of-plane symmetries and the presence of weak van der Waals interactions. Furthermore, our study highlights the superiority of MD simulations with NNFFs in capturing higher-order anharmonic phonon properties. This is demonstrated through the analysis of the temperature-dependent thermal conductivity curves of PtSTe-based van der Waals heterostructures and advances our understanding of phonon transport in those materials.

The authors acknowledge the support from the National Natural Science Foundation of China (Grant No. 11964002) and China Scholarship Council (CSC) Grant No. 202106660010.

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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