Effects of alloying on in-plane thermal conductivity and thermal boundary conductance in transition metal dichalcogenide monolayers

Foss, Cameron J.; Akšamija, Zlatan

doi:10.1103/physrevmaterials.4.124006

Cited by 5 publications

(5 citation statements)

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“…The internal scattering rate is comprised of these scattering mechanisms and is simply written as Γ int =Γ anh +Γ enc . We employ a commonly used empirical formalism for the anharmonic scattering rates [40], as described in our previous work [41], while Γ enc takes a similar form as the substrate scattering rate [39].…”

Section: Methodsmentioning

confidence: 99%

Thermal boundary conductance of monolayer beyond-graphene two-dimensional materials on SiO₂ and GaN

Foss

Akšamija

2021

Nanotechnology

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Two-dimensional (2D) materials have emerged as a platform for a broad array of future nanoelectronic devices. Here we use first-principles calculations and phonon interface transport modeling to calculate the temperature-dependent thermal boundary conductance (TBC) in single layers of beyond-graphene 2D materials silicene, hBN, boron arsenide (BAs), and blue and black phosphorene (BP) on amorphous SiO 2 and crystalline GaN substrates. Our results show that for 2D/3D systems, the room temperature TBC can span a wide range from 7 to 70 MW m −2 K −1 with the lowest being for BP and highest for hBN. We also show that 2D/3D TBC has a strong temperature dependence that can be alleviated by encapsulating the 2D/3D stack. Upon encapsulation with AlO x , the TBC of several beyond-graphene 2D materials can match or exceed reported values for graphene and numerous transition-metal dichalcogendies which are in the range of 15-40 MW m −2 K −1 . We also compute the room temperature TBC as a function of van der Waals spring coupling (K a ) where the TBC falls in the range of 50-150 MW m −2 K −1 at coupling strengths of K a =2-4 N m −1 for silicene, BAs, and blue phosphorene. We further identify group III-V materials with ultra-soft flexural branches as being promising 2D materials for thermal isolation and energy scavenging applications when matched with crystalline substrates.

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Section: Methodsmentioning

confidence: 99%

Thermal boundary conductance of monolayer beyond-graphene two-dimensional materials on SiO₂ and GaN

Foss

Akšamija

2021

Nanotechnology

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“…Foss and Aksajima calculated the in-plane thermal conductivities as a function of alloy concentration showing considerable decrease in the values compared to the pure materials (Figure 4f,g). 77 One particular strategy for lattice engineering is making so-called Janus TMDs, which are formed by replacing one of the chalcogenide layers in a TMD crystal with another chalcogenide layer, e.g., creating MoSSe and WSSe where the sulfur layer is below, the selenium layer is above the metal layer. A comprehensive first-principles investigation showed that both the in-plane and out-of-plane thermal conductivities of the asymmetrical structures are considerably lower than that of MoS 2 caused by the larger phonon−phonon scattering in Janus materials.…”

Section: Thermal Propertiesmentioning

confidence: 99%

“…Three intensively used experimental techniques are temperature-dependent luminescence and optothermal Raman ,, , as well as time-domain thermoreflectance (TDTR) . At the same time, non-experimental approaches, e.g., analytically solving the Boltzmann transport equation, using first-principles calculations using Vienna Ab initio Simulation Package (VASP), molecular dynamics (MD) simulations with a machine-learning-based interatomic potential or density-functional perturbation theory have also been used successfully to calculate band structure or directly thermal conductivity.…”

Section: Tmds and Their Property Modulationmentioning

confidence: 99%

“…One engineering tool for tailoring properties is alloying or inserting point defects; in this case, the properties can be fine-tuned by the concentrations; , for example, the thermal conductivities of MoS 2 , MoSe 2 , and MoS 1.34 Se 0.66 were 69(±2) W m –1 K –1 , 33(±2) W m –1 K –1 , and 17(±2) W m –1 K –1 . Foss and Aksajima calculated the in-plane thermal conductivities as a function of alloy concentration showing considerable decrease in the values compared to the pure materials (Figure f,g) . One particular strategy for lattice engineering is making so-called Janus TMDs, which are formed by replacing one of the chalcogenide layers in a TMD crystal with another chalcogenide layer, e.g., creating MoSSe and WSSe where the sulfur layer is below, the selenium layer is above the metal layer.…”

Section: Tmds and Their Property Modulationmentioning

confidence: 99%

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Engineered Two-Dimensional Transition Metal Dichalcogenides for Energy Conversion and Storage

Roy,

Joseph,

Zhang

et al. 2024

Chem. Rev.

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Designing efficient and cost-effective materials is pivotal to solving the key scientific and technological challenges at the interface of energy, environment, and sustainability for achieving NetZero. Two-dimensional transition metal dichalcogenides (2D TMDs) represent a unique class of materials that have catered to a myriad of energy conversion and storage (ECS) applications. Their uniqueness arises from their ultra-thin nature, high fractions of atoms residing on surfaces, rich chemical compositions featuring diverse metals and chalcogens, and remarkable tunability across multiple length scales. Specifically, the rich electronic/electrical, optical, and thermal properties of 2D TMDs have been widely exploited for electrochemical energy conversion (e.g., electrocatalytic water splitting), and storage (e.g., anodes in alkali ion batteries and supercapacitors), photocatalysis, photovoltaic devices, and thermoelectric applications. Furthermore, their properties and performances can be greatly boosted by judicious structural and chemical tuning through phase, size, composition, defect, dopant, topological, and heterostructure engineering. The challenge, however, is to design and control such engineering levers, optimally and specifically, to maximize performance outcomes for targeted applications. In this review we discuss, highlight, and provide insights on the significant advancements and ongoing research directions in the design and engineering approaches of 2D TMDs for improving their performance and potential in ECS applications.

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“…There have been several successful efforts to experimentally measure 2D/3D thermal boundary conductance (TBC) [10,11,[26][27][28][29] as well as to provide explanations of the underlying physical dynamics through theoretical modeling based on Green's functions [30][31][32][33], molecular dynamics (MD) [4,34], and the Boltzmann transport equation [35][36][37][38]. However, the vast majority of these studies focus on a few interface pairs involving graphene (Gr), hBN, and transition metal dichalcogenides (TMDs) on SiO 2 , while measurements of interfaces involving other substrates (AlO x , AlN, and diamond) [11] were primarily done with Gr as the 2D layer.…”

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confidence: 99%

Machine learning enables robust prediction of thermal boundary conductance of 2D substrate interfaces

Foss¹,

Akšamija²

2023

Preprint

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Two-dimensional van der Waals (vdW) materials exhibit a broad palette of unique and superlative properties, including high electrical and thermal conductivities, paired with the ability to exfoliate or grow and transfer single layers onto a variety of substrates thanks to the relatively weak vdW interlayer bonding. However, the same vdW bonds also lead to relatively low thermal boundary conductance (TBC) between the 2D layer and its 3D substrate, which is the main pathway for heat removal and thermal management in devices, leading to a potential thermal bottleneck and dissipation-driven performance degradation. Here we use first-principles phonon dispersion with our 2D-3D Boltzmann phonon transport model to compute the TBC of 156 unique 2D/3D interface pairs, many of which are not available in the literature. We then employ machine learning (ML) to develop streamlined predictive models, of which Neural Network and Gaussian process display the highest predictive accuracy (RMSE < 5 MW.m -2 .K -1 and R 2 >0.99) on the complete descriptor set. Then we perform sensitivity analysis to identify the most impactful descriptors, consisting of the vdW spring coupling constant, 2D thermal conductivity, ZA phonon bandwidth, the ZA phonon resonance gap, and the frequency of the first van Hove singularity or Boson peak. On that reduced set, we find that a decision-tree algorithm can make accurate predictions (RMSE < 20 MW.m -2 .K -1 and R 2 >0.9) on materials it has not been trained on by performing a transferability analysis. Our model allows optimal selection of 2D-substrate pairings to maximize heat transfer and will improve thermal management in future 2D nanoelectronics.

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Effects of alloying on in-plane thermal conductivity and thermal boundary conductance in transition metal dichalcogenide monolayers

Cited by 5 publications

References 86 publications

Thermal boundary conductance of monolayer beyond-graphene two-dimensional materials on SiO₂ and GaN

Thermal boundary conductance of monolayer beyond-graphene two-dimensional materials on SiO₂ and GaN

Engineered Two-Dimensional Transition Metal Dichalcogenides for Energy Conversion and Storage

Machine learning enables robust prediction of thermal boundary conductance of 2D substrate interfaces

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Effects of alloying on in-plane thermal conductivity and thermal boundary conductance in transition metal dichalcogenide monolayers

Cited by 5 publications

References 86 publications

Thermal boundary conductance of monolayer beyond-graphene two-dimensional materials on SiO2 and GaN

Thermal boundary conductance of monolayer beyond-graphene two-dimensional materials on SiO2 and GaN

Engineered Two-Dimensional Transition Metal Dichalcogenides for Energy Conversion and Storage

Machine learning enables robust prediction of thermal boundary conductance of 2D substrate interfaces

Contact Info

Product

Resources

About

Thermal boundary conductance of monolayer beyond-graphene two-dimensional materials on SiO₂ and GaN

Thermal boundary conductance of monolayer beyond-graphene two-dimensional materials on SiO₂ and GaN