000132444 001__ 132444
000132444 005__ 20240311111224.0
000132444 0247_ $$2doi$$a10.1103/PhysRevB.109.035417
000132444 0248_ $$2sideral$$a137574
000132444 037__ $$aART-2024-137574
000132444 041__ $$aeng
000132444 100__ $$aPan, Lijun
000132444 245__ $$aMachine learning boosted a b i n i t i o study of the thermal conductivity of Janus PtSTe van der Waals heterostructures
000132444 260__ $$c2024
000132444 5060_ $$aAccess copy available to the general public$$fUnrestricted
000132444 5203_ $$aCalculating 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 − PtTe 2 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.
000132444 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000132444 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000132444 700__ $$0(orcid)0000-0003-0971-1098$$aCarrete, Jesús
000132444 700__ $$aWang, Zhao
000132444 700__ $$aMadsen, Georg K. H.
000132444 773__ $$g109, 3 (2024)$$pPhys. Rev. B$$tPhysical Review B$$x2469-9950
000132444 787__ $$tCode and data for "Machine-learning-boosted ab-initio study of the thermal conductivity of Janus PtSTe van der Waals heterostructures"$$whttps://zenodo.org/records/10417653
000132444 8564_ $$s1756793$$uhttps://zaguan.unizar.es/record/132444/files/texto_completo.pdf$$yPostprint
000132444 8564_ $$s3214535$$uhttps://zaguan.unizar.es/record/132444/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000132444 909CO $$ooai:zaguan.unizar.es:132444$$particulos$$pdriver
000132444 951__ $$a2024-03-11-09:51:28
000132444 980__ $$aARTICLE