arXiv subjects

Hua Bao

Publications and source records attributed to Hua Bao.

27 records · Page 2Linked to original sources

arXiv2019

Influence of Boundaries and Thermostatting on Nonequilibrium Molecular Dynamics Simulations of Heat Conduction in Solids

Nonequilibrium molecular dynamics (NEMD) has been extensively used to study thermal transport at various length scales in many materials. In this method, two local thermostats at different temperatures are used to generate a nonequilibrium steady state with a constant heat flux. Conventionally, the thermal conductivity of a finite system is calculated as the ratio between the heat flux and the temperature gradient extracted from the linear part of the temperature profile away from the local thermostats. Here we show that, with a proper choice of the thermostat, the nonlinear part of the temperature profile should actually not be excluded in thermal transport calculations. We compare NEMD results against those from the atomistic Green's function method in the ballistic regime, and those from the homogeneous nonequilibrium molecular dynamics method in the ballistic-to-diffusive regime. These comparisons suggest that in all the transport regimes, one should directly calculate the thermal conductance from the temperature difference between the heat source and sink and, if needed, convert it to the thermal conductivity by multiplying it with the system length. Furthermore, we find that the Langevin thermostat outperforms the Nosé-Hoover (chain) thermostat in NEMD simulations because of its stochastic and local nature. We show that this is particularly important for studying asymmetric carbon-based nanostructures, for which the Nosé-Hoover thermostat can produce artifacts leading to unphysical thermal rectification. Our findings are important to obtain correct results from molecular dynamics simulations of nanoscale heat transport as the accuracy of the interatomic potentials is rapidly improving.

cond-mat.mes-hall↗

arXiv2019

A revisit to phonon-phonon scattering in single-layer graphene

Understanding the mechanisms of thermal conduction in graphene is a long-lasting research topic, due to its high thermal conductivity. Peierls-Boltzmann transport equation (PBTE) based studies have revealed many unique phonon transport properties in graphene, but most previous works only considered three-phonon scatterings and relied on interatomic force constants (IFCs) extracted at 0 K. In this paper, we explore the roles of four-phonon scatterings and the temperature dependent IFCs on phonon transport in graphene through our PBTE calculations. We demonstrate that the strength of four-phonon scatterings would be severely overestimated by using the IFCs extracted at 0 K compared with those corresponding to a finite temperature, and four-phonon scatterings are found to significantly reduce the thermal conductivity of graphene even at room temperature. In order to reproduce the prediction from molecular dynamics simulations, phonon frequency broadening has to be taken into account when determining the phonon scattering rates. Our study elucidates the phonon transport properties of graphene at finite temperatures, and could be extended to other crystalline materials.

cond-mat.mtrl-sci↗

arXiv2019

Deep learning methods based on cross-section images for predicting effective thermal conductivity of composites

Effective thermal conductivity is an important property of composites for different thermal management applications. Although physics-based methods, such as effective medium theory and solving partial differential equation, dominate the relevant research, there is significant interest to establish the structure-property linkage through the machine learning method. The performance of general machine learning methods is highly dependent on features selected to represent the microstructures. 3D convolutional neural networks (CNNs) can directly extract geometric features of composites, which have been demonstrated to establish structure-property linkages with high accuracy. However, to obtain the 3D microstructure in composite is generally challenging in reality. In this work, we attempt to use 2D cross-section images which can be easier to obtain in real applications as input of 2D CNNs to predict effective thermal conductivity of 3D composites. The results show that by using multiple cross-section images along or perpendicular to the preferred directionality of the fillers, the prediction accuracy of 2D CNNs can be as good as 3D CNNs. Such a result is demonstrated with the particle filled composite and a stochastic complex composite. The prediction accuracy is dependent on the representativeness of cross-section images used. Multiple cross-section images can fully determine the shape and distribution of fillers. The average over multiple images and the use of large-size images can reduce the uncertainty and increase the prediction accuracy. Besides, since cross-section images along the heat flow direction can distinguish between serial structures and parallel structures, they are more representative than cross-section images perpendicular to the heat flow direction.

physics.comp-ph↗

arXiv2019

The lattice and electronic thermal conductivity of doped SnSe: a first-principles study

Recently, it has been found that crystalline tin selenide (SnSe) holds great potential as a thermoelectric material due to its ultralow thermal conductivity and moderate electronic transport performance. As thermoelectric application usually requires doped material, charge carriers can play a role in the thermal transport in doped SnSe, but such an effect has not been clearly elucidated in previous theoretical and experimental studies. Here we performed a fully first-principles study on the effects of electrons to the thermal transport in doped SnSe. The electron-phonon coupling (EPC) effects on both phonons and charge carriers were considered using the mode specific calculation in our work. It is found that for phonons, EPC are weak compared to the intrinsic phonon-phonon scattering even at high carrier concentrations and thus have negligible effects on the lattice thermal conductivity. The electronic thermal conductivity is not negligible when the carrier concentration is higher than $10^{19} cm^{-3}$ and the values can be as high as 1.55, 1.45 and 1.77 $Wm^{-1}K^{-1}$ on a, b and c axes, respectively, for $10^{20} cm^{-3}$ electron concentration at 300K. The Lorenz number of SnSe is also calculated and it is dependent on crystal orientations, carrier concentrations, and carrier types. The simple estimation of electronic thermal conductivity using Wiedemann-Franz law can cause large uncertainties for doped SnSe.

physics.app-ph↗

arXiv2018

A relaxation time model for efficient and accurate prediction of lattice thermal conductivity

Prediction of lattice thermal conductivity is important to many applications and technologies, especially for high-throughput materials screening. However, the state-of-the-art method based on three-phonon scattering process is bound with high computational cost while semi-empirical models such as the Slack equation are less accurate. In this work, we examined the theoretical background of the commonly-used computational models for high-throughput thermal conductivity prediction and proposed an efficient and accurate method based on an approximation for three-phonon scattering strength. This quasi-harmonic approximation has comparable computational cost with many widely-used thermal conductivity models but had the best performance in regard to quantitative accuracy. As compared to many models that can only predict lattice thermal conductivity values, this model also allows to include Normal processes and obtain the phonon relaxation time.

physics.comp-ph↗

arXiv2018

High thermal conductivity of bulk epoxy resin by bottom-up parallel-linking and strain: a molecular dynamics study

The ultra-low thermal conductivity (~0.3 Wm-1K-1) of amorphous epoxy resins significantly limits their applications in electronics. Conventional top-down methods e.g. electrospinning usually result in aligned structure for linear polymers thus satisfactory enhancement on thermal conductivity, but they are deficient for epoxy resin polymerized by monomers and curing agent due to completely different cross-linked network structure. Here, we proposed a bottom-up strategy, namely parallel-linking method, to increase the intrinsic thermal conductivity of bulk epoxy resin. Through equilibrium molecular dynamics simulations, we reported on a high thermal conductivity value of parallel-linked epoxy resin (PLER) as 0.80 Wm-1K-1, more than twofold higher than that of amorphous structure. Furthermore, by applying uniaxial tensile strains along the intra-chain direction, a further enhancement in thermal conductivity was obtained, reaching 6.45 Wm-1K-1. Interestingly, we also observed that the inter-chain thermal conductivities decrease with increasing strain. The single chain of epoxy resin was also investigated and, surprisingly, its thermal conductivity was boosted by 30 times through tensile strain, as high as 33.8 Wm-1K-1. Our study may provide a new insight on the design and fabrication of epoxy resins with high thermal conductivity.

cond-mat.mtrl-sci↗

arXiv2017

Probing the phonon surface interaction by wave packet simulation: effect of roughness and morphology

One way to reduce the lattice thermal conductivity of solids is to induce additional phonon surface scattering through nanostructures. However, how phonons interact with boundaries, especially at the atomic level, is not well understood. In this work, we performed two-dimensional atomistic wave packet simulations to investigate the phonon surface interaction. Emphasis has been given to the angular-resolved phonon reflection at smooth, periodically rough, and amorphous surfaces. We found that the acoustic phonon reflection at a smooth surface is not simply specular. Mode conversion can occur after reflection, and the detailed energy distribution after reflection will dependent on surface condition and polarization of incident phonon. At periodically rough surfaces, the reflected wave packet distribution does not follow the well-known Ziman's model, but shows a nonmonotonic dependence on the depth of surface roughness. When an amorphous layer is attached to the surface, the incident wave packet will be absorbed by the amorphous region, and results in quite diffusive reflection. Our results clearly show that the commonly used specular-diffusive model is not enough to describe the phonon reflection at a periodically rough surface, while an amorphous layer can induce strong diffusive reflection. This work provides a careful analysis of phonon reflection at a surface with different morphology, which is important to a better understanding of thermal transport in various nanostructures.

cond-mat.mes-hall↗

arXiv2015

Unexpectedly Large Tunability of Lattice Thermal Conductivity of Monolayer Silicene via Mechanical Strain

Strain engineering is one of the most promising and effective routes toward continuously tuning the electronic and optic properties of materials, while thermal properties are generally believed to be insensitive to mechanical strain. In this paper, the strain-dependent thermal conductivity of monolayer silicene under uniform bi-axial tension is computed by solving the phonon Boltzmann transport equation with force constants extracted from first-principles calculations. Unlike the commonly believed understanding that thermal conductivity only slightly decreases with increased tensile strain for bulk materials, it is found that the thermal conductivity of silicene first increases dramatically with strain and then slightly decreases when the applied strain increases further. At a tensile strain of 4%, the highest thermal conductivity is found to be about 7.5 times that of unstrained one. Such an unusual strain dependence is mainly attributed to the dramatic enhancement in the acoustic phonon lifetime. Such enhancement plausibly originates from the flattening of the buckling of the silicene structure upon stretching, which is unique for silicene as compared with other common two-dimensional materials. Our findings offer perspectives of modulating the thermal properties of low-dimensional structures for applications such as thermoelectrics, thermal circuits, and nanoelectronics.

cond-mat.mes-hall↗

arXiv2013

Light Trapping in Thin Film Disordered Nanohole Patterns: Effects of Oblique Incidence and Intrinsic Absorption

Finite-difference time-domain method is employed to investigate the optical properties of semiconductor thin films patterned with circular holes. The presence of holes enhances the coupling of the incident plane wave with the thin film and greatly enhances the absorption performance. For a typical 100 nm thin film, the optimal hole pattern is achieved when the hole radius is 180 nm and volume fraction is about $30\%$. Disorderness can alter the absorption spectra and has an impact on the broadband absorption performance. The non-uniform radius of holes can slightly broaden the absorption peaks and enhance the integrated absorption. Random hole position can completely change the shape of the absorption spectra and the averaged integrated absorption efficiency is slightly smaller than the optimized ordered nanohole pattern. Compared to random positioned nanoholes or ordered nanohole, amorphous arrangement of nanoholes will result in a much better absorption performance. However, it is also found that the absorption enhancement of amorphous pattern over an ordered pattern is weak when the incident angle departures from normal or when the intrinsic material absorption is strong.

cond-mat.mes-hall↗