scholarly journals Multiscale modelling of heat conduction in all-MoS2 single-layer heterostructures

RSC Advances ◽  
2017 ◽  
Vol 7 (18) ◽  
pp. 11135-11141 ◽  
Author(s):  
Bohayra Mortazavi ◽  
Timon Rabczuk
Keyword(s):  
Thermal Conductivity ◽  
Heat Conduction ◽  
Effective Thermal Conductivity ◽  
Multiscale Modeling ◽  
Single Layer ◽  
Multiscale Modelling

We developed a combined atomistic-continuum multiscale modeling to explore the effective thermal conductivity of all-MoS2 single-layer heterostructures.

Modeling Heat Conduction Across Thermal Interface Materials With Micro-Particles

2008 ◽  
Author(s):  
C. Channy Wong
Keyword(s):  
Thermal Conductivity ◽  
Heat Conduction ◽  
Composite Materials ◽  
Effective Thermal Conductivity ◽  
Thermal Interface Materials ◽  
Conduction Path ◽  
Micro Particles ◽  
Mechanical And Electrical Properties ◽  
Interface Materials ◽  
Composite Polymeric Material

Different types of fillers with high electrical and thermal conductivities, e.g. graphite and alumina, have been added to adhesive polymers to create composite materials with improved mechanical and electrical properties. Previous modeling efforts have found that it is relatively difficult to predict the effective thermal conductivity of a composite polymeric material when incorporated with large volume content of fillers. We have performed comprehensive computational analysis that models the thermal contacts between fillers. This unique setup can capture the critical heat conduction path to obtain the effective thermal conductivity of the composite materials. Results of these predictions and its comparison with experimental data will be presented in this paper.

Effect of radial heat conduction on effective thermal conductivity of carbon nanotube bundles

2018 ◽  
Vol 61 (12) ◽  
pp. 1959-1966 ◽  
Author(s):  
JianLi Wang ◽  
YaMei Song ◽  
YuFeng Zhang ◽  
YuHan Hu ◽  
Hang Yin ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Heat Conduction ◽  
Carbon Nanotube ◽  
Effective Thermal Conductivity ◽  
Nanotube Bundles ◽  
Radial Heat

scholarly journals Multiscale modeling of thermal conductivity of polycrystalline graphene sheets

Nanoscale ◽  
2014 ◽  
Vol 6 (6) ◽  
pp. 3344-3352 ◽  
Author(s):  
Bohayra Mortazavi ◽  
Markus Pötschke ◽  
Gianaurelio Cuniberti
Keyword(s):  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Multiscale Modeling ◽  
Graphene Sheets ◽  
Multiscale Approach

We developed a multiscale approach to explore the effective thermal conductivity of polycrystalline graphene sheets.

Nanofluids Suspensions: Possible Explanations for the Apparent Enhanced Effective Thermal Conductivity

2005 ◽  
Author(s):  
Peter Vadasz
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Heat Conduction ◽  
Effective Thermal Conductivity ◽  
Heterogeneous Medium ◽  
Alternative Possibilities ◽  
Dual Phase ◽  
Transfer Enhancement ◽  
Scale Level ◽  
Macro Scale

The spectacular heat transfer enhancement revealed experimentally in naofluids suspensions is being investigated theoretically at the macro-scale level aiming at explaining the possible mechanisms that lead to such impressive experimental results. In particular, the possibility that Dual-Phase-Lagging heat conduction in the heterogeneous medium (nanofluid suspension) could have been the source of the excessively improved effective thermal conductivity of the suspension is shown to provide a viable explanation. The investigation of alternative possibilities is needed however prior to reaching an ultimate conclusion.

scholarly journals Impact of water vapor diffusion and latent heat on the effective thermal conductivity of snow

2020 ◽  
Author(s):  
Kévin Fourteau ◽  
Florent Domine ◽  
Pascal Hagenmuller
Keyword(s):  
Thermal Conductivity ◽  
Diffusion Coefficient ◽  
Heat Conduction ◽  
Water Vapor ◽  
Effective Thermal Conductivity ◽  
Latent Heat ◽  
Effective Diffusion Coefficient ◽  
Effective Diffusion ◽  
Water Vapor Transport ◽  
Fast Kinetics

Abstract. Heat transport in snowpacks is generally thought to occur through two independent processes: heat conduction and latent heat transport carried by water vapor. This paper investigates the coupling between both these processes in snow, with an emphasis on the impacts of the kinetics of the sublimation and deposition of water vapor onto ice. In the case where kinetics is fast, latent heat exchanges at ice surfaces modify their temperature, and therefore the thermal gradient within ice crystals and the heat conduction through the entire microstructure. Furthermore, in this case, the effective thermal conductivity of snow can be expressed by a purely conductive term complemented by a term directly proportional to the effective diffusion coefficient of water vapor in snow, which illustrates the inextricable coupling between heat conduction and water vapor transport. Numerical simulations on measured three-dimensional snow microstructures reveal that the effective thermal conductivity of snow can be significantly larger, up to about 50 % for low-density snow, than if water vapor transport is neglected. Comparison of our numerical simulations with literature data suggests that the fast kinetics hypothesis could be a reasonable assumption to model snow physical properties. Lastly, we demonstrate that under the fast kinetics hypothesis the effective diffusion coefficient of water vapor is related to the effective thermal conductivity by a simple linear relationship. Under such condition, the effective diffusion coefficient of water vapor is expected to lie in the narrow 100 % to about 80 % range of the value of the diffusion coefficient of water vapor in air for most seasonal snows. This may greatly facilitate the parameterization of water vapor diffusion of snow in models.

MULTISCALE MODELING OF THE EFFECTIVE THERMAL CONDUCTIVITY OF 2D WOVEN COMPOSITES BY MECHANICS OF STRUCTURE GENOME AND NEURAL NETWORKS

2021 ◽  
Author(s):  
XIN LIU ◽  
BO PENG ◽  
WENBIN YU
Keyword(s):  
Neural Network ◽  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Multiscale Modeling ◽  
Network Models ◽  
Thermal Design ◽  
Data Driven ◽  
Woven Composites ◽  
Neural Network Models ◽  
The Neural Network

A data-driven multiscale modeling approach is developed to predict the effective thermal conductivity of two-dimensional (2D) woven composites. First, a two-step homogenization approach based on mechanics of structure genome (MSG) is developed to predict effective thermal conductivity. The accuracy and efficiency of the MSG model are compared with the representative volume element (RVE) model based on three-dimensional (3D) finite element analysis (FEA). Then, the simulation data is generated by the MSG model to train neural network models to predict the effective thermal conductivity of three 2D woven composites. The neural network models have mixed input features: continuous input (e.g., fiber volume fraction and yarn geometries) and discrete input (e.g., weave patterns). Moreover, the neural network models are trained with the normalized features to enable reusability. The results show that the developed data-driven models provide an ultra-efficient yet accurate approach for the thermal design and analysis of 2D woven composites.

Phonon Wave Heat Conduction in Thin Films and Superlattices

1999 ◽  
Vol 121 (4) ◽  
pp. 945-953 ◽  
Author(s):  
G. Chen
Keyword(s):  
Thin Film ◽  
Thin Films ◽  
Thermal Conductivity ◽  
Heat Conduction ◽  
Ray Tracing ◽  
Thermal Conductance ◽  
Single Layer ◽  
Ray Tracing Method ◽  
Conductivity Of Thin Films ◽  
Tracing Method

Heat conduction in thin films and superlattices is important for many engineering applications such as thin-film based microelectronic, photonic, thermoelectric, and thermionic devices. Past modeling efforts on the thermal conductivity of thin films were based on solving the Boltzmann transport equation that treats phonons as particles. The effects of phonon interference and tunneling on the heat conduction and the thermal conductivity of thin films and superlattices remain to be explored. In this work, the wave effects on the heat conduction in thin films and superlattices are studied based on the consideration of the acoustic wave propagation in thin film structures and neglecting the internal scattering. A transfer matrix method is used to calculate the phonon transmission and heat conduction through these structures. The effects considered in this work include the phonon interference, tunneling, and confinement. The phonon dispersion is considered by introducing frequency-dependent Lamb constants. A ray-tracing method that treats phonons as particles is also developed for comparison. Sample calculations are performed on double heterojunction structures resembling Ge/Si/Ge and n-period superlattices similar to Ge/Si/n(Si/Ge)/Ge, It is found that phonon confinements caused by the phonon spectra mismatch and by the total internal reflection create a dramatic decrease of the overall thermal conductance of thin films. The phonon interference in a single layer does not have a strong effect on its thermal conductance but for superlattice structures, the stop bands created by the interference effects can further reduce the thermal conductance. Tunneling of phonon waves occurs when the constituent layers are 1–3 monolayer thick and causes a slight recovery in the thermal conductance when compared to thicker layers. The thermal conductance obtained from the ray tracing and the wave methods approaches the same results for a single layer. For superlattices, however, the wave method leads to a finite thermal conductance even for infinitely thick superlattices while the ray tracing method gives a thermal conductance that decreases with increasing number of layers. Implications of these results on explaining the recent thermal conductivity data of superlattices are explored.

Theoretical and DSMC Studies on Heat Conduction of Gas Confined in a Cuboid Nanopore

2017 ◽  
Vol 139 (5) ◽  
Author(s):  
Chuan-Yong Zhu ◽  
Zeng-Yao Li ◽  
Wen-Quan Tao
Keyword(s):  
Thermal Conductivity ◽  
Heat Conduction ◽  
Effective Thermal Conductivity ◽  
Numerical Study ◽  
Direct Simulation Monte Carlo ◽  
Mean Free Path ◽  
Confined Space ◽  
Temperature Jumps ◽  
Side Walls ◽  
The Impact

This paper presents a theoretical and numerical study on the heat conduction of gas confined in a cuboid nanopore, in which there exists a temperature difference between the top and bottom walls and the side walls are adiabatic. A modified gas mean free path in confined space is proposed by considering the impact of collisions between molecules and solid surfaces, with which an effective thermal conductivity model of gas in the transition regime is derived. A direct simulation Monte Carlo (DSMC) study on the heat conduction of argon and helium in a cuboid nanopore is carried out to validate the present model. The influences of the Knudsen number and the treatments of boundary conditions on the heat conduction and effective thermal conductivity of gas in nanopores are studied. The temperature jumps and the reduction of heat flux near side walls are analyzed.

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