Dynamics Simulations Of Thermal Conductivity Research Articles

Molecular Dynamics Simulation of Thermal Conductivity and Vibrational Density of States of Cadmium Telluride

This study aims to calculate the thermal conductivity and vibrational density of states of CdTe using MD simulation. The lengths of CdTe varied from 10 nm, 20 nm, 30 nm, 40 nm, and 50 nm, with fixed width and height of 10 nm at room temperature (300 K). The results show the decrease of thermal conductivity as a function of length due to phonon-phonon interaction. The width varied from 10 nm, 20 nm, 30 nm, 40 nm, and 50 nm at room temperature (300 K) with a fixed length and height of 10 nm. Similarly, the height varied from 10 nm, 20 nm, 30 nm, 40 nm, and 50 nm with fixed length and width at room temperature (300 K). It was found that the phonon spread less in the boundaries of the mean free path which follows the creation processes resulting to the decrease of thermal conductivity. The temperatures varied from 50 K, 75 K, 100 K, 300 K, 500 K, 700 K, 900 K, 1,000 K, and 1,365 K with fixed dimensions of 50 nm in length, 50 nm in width, and 50 nm in height. As observed, the thermal conductivity decreases with a further increase in temperature. There were four major peaks found in the vibrational density of states of cadmium telluride: ~1.3 THz and ~3.5 THz which corresponds to transverse and longitudinal acoustic modes, ~4.5 THz and ~5 THz which corresponds to transverse and longitudinal optical modes.

Molecular dynamics simulation of thermal conductivity of diamond/epoxy resin composites

Improving the thermal conductivity (TC) of epoxy resin thermal interface material is of great significance in tackling the heat dissipation problem of high heat flux in microelectronic chips such as 5G. Using non-equilibrium molecular dynamics (MD) method, the effects of two different filling styles of nano-diamond fillers on the TC of EP based composites are investigated. The results show that the TC of the composite increases with the diamond size when single-particle filling is used, and that a larger diamond size leads to a more significant reduction of the free volume fraction and thus an improvement of the TC. In the multi-particle packing, the composite TC first increases and then decreases with increasing particle number. Increasing the number of particles reduces the free volume fraction, but also results in a larger specific surface area and interfacial thermal resistance, which has a more significant weakening effect on the TC. Moreover, within the same mass fraction of nano-diamond filler, increasing the filler size has a more significant TC improvement on the composite than increasing the number of particles. This study is instructive for the design and preparation of high thermal conductivity nanodiamond/epoxy resin composites.

Molecular dynamics simulations of thermal conductivity between two nanoparticles in contact

The nanoscale properties of materials can have a great influence on their macroscopic behavior; for instance, the generation and accumulation of defects at the nanoscale, such as point defects, porosity, and interfaces, can change their thermal properties. In this work, we study the role of an interface in the thermal conductivity between two nanoparticles without any external load. We consider a system subjected to a temperature gradient perpendicular to the contact surface and study the thermal conductivity, thermal conductance, thermal resistance, and contact resistance vs nanoparticle size. The thermal resistance at the interface increases linearly with nanoparticles’ contact radius ac. A model based on the contact area between two nanoparticles allows us to reasonably explain the obtained numerical results for the thermal conductivity, leading to a net decrease in effective conductivity as the nanoparticle size increases, reasonably well described by a (ac/R) dependence. Simulated thermal conductance was found to be proportional to (ac/R).

Evolutionary multi-objective optimization and Pareto-frontal uncertainty quantification of interatomic forcefields for thermal conductivity simulations

Predictive Molecular Dynamics simulations of thermal transport require forcefields that can simultaneously reproduce several structural, thermodynamic and vibrational properties of materials like lattice constants, phonon density of states, and specific heat. This requires a multi-objective optimization approach for forcefield parameterization. Existing methodologies for forcefield parameterization use ad-hoc and empirical weighting schemes to convert this into a single-objective optimization problem. Here, we provide and describe software to perform multi-objective optimization of Stillinger–Weber forcefields (SWFF) for two-dimensional layered materials using the recently developed 3rd generation non-dominated sorting genetic algorithm (NSGA-III). NSGA-III converges to the set of optimal forcefields lying on the Pareto front in the multi-dimensional objective space. This set of forcefields is used for uncertainty quantification of computed thermal conductivity due to variability in the forcefield parameters. We demonstrate this new optimization scheme by constructing a SWFF for a representative two-dimensional material, 2H-MoSe2 and quantifying the uncertainty in their computed thermal conductivity. Program summaryProgram Title: MOGA-NSGA3Program Files doi: http://dx.doi.org/10.17632/pbc6nb7hp9.1Licensing Provisions: GNU General Public License 3Programming Language: C++Nature of problem: Interatomic forcefields used for molecular dynamics simulations of thermal conductivity must be parameterized to accurately capture structural and vibrational properties of the material system being modeled. Therefore, these forcefields must be simultaneously optimized against several (n≥ 5) material properties. However, such parameterization is difficult using existing forcefield parameterization schemes, which are limited to optimization of a single or few (n< 3) objectives.Solution method: We present software to perform evolutionary optimization of forcefields for thermal conductivity simulations using the recently developed 3rd generation non-dominated sorting genetic algorithm (NSGA-III). The algorithm’s unique reference-point-based niching and non-dominated sorting schemes enable efficient exploration of higher-dimensional objective spaces while preserving diversity among forcefield populations. The best set of forcefields on the Pareto front are used for estimating uncertainty in computed thermal conductivity due to forcefield parameterization.

Molecular dynamics simulation of thermal conductivity of silicone rubber**Project supported by the Science Fund for Creative Research Groups of the National Natural Science Foundation of China (Grant No. 51621062) and the National Natural Science Foundation of China (Grant No. 51802144).

Silicone rubber is widely used as a kind of thermal interface material (TIM) in electronic devices. However few studies have been carried out on the thermal conductivity mechanism of silicone rubber. This paper investigates the thermal conductivity mechanism by non-equilibrium molecular dynamics (NEMD) in three aspects: chain length, morphology, and temperature. It is found that the effect of chain length on thermal conductivity varies with morphologies. In crystalline state where the chains are aligned, the thermal conductivity increases apparently with the length of the silicone-oxygen chain, the thermal conductivity of 79 nm-long crystalline silicone rubber could reach 1.49 W/(m⋅K). The thermal conductivity of amorphous silicone rubber is less affected by the chain length. The temperature dependence of thermal conductivity of silicone rubbers with different morphologies is trivial. The phonon density of states (DOS) is calculated and analyzed. The results indicate that crystalline silicone rubber with aligned orientation has more low frequency phonons, longer phonon MFP, and shorter conducting path, which contribute to a larger thermal conductivity.

Molecular Dynamics Simulations of Thermal Conductivity of Germanene Nanoribbons (GeNR) with Armchair and Zigzag Chirality

Germanene, an allotrope of germanium which is a two dimensional material withsp2hybridization, has almost the same properties with graphene except for its buckled structure. In this study, germanium nanoribbon (GeNR) is use for it is still a new material for nanoscale level of research. In this paper, we investigate the effect of chirality on the thermal conductivity of zigzag GeNR (ZGeNR) and armchair GeNR (AGeNR) chiralities using equilibrium molecular dynamics with varied lengths at fixed temperature and varied temperatures at fixed length. The simulations were carried out in Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) using Tersoff potential for the Ge-Ge interactions. The thermal conductivity is calculated using Green-Kubo method. It is found that the chirality can affect the thermal conductivity of GeNR. Our results show that thermal conductivity of AGeNR is higher than ZGeNR in both increasing temperatures and lengths similar to the thermal conductivity behavior obtained in silicene nanoribbons [Int. J. Mech. Mater. Des. 9 (2013) 105].

Ensemble averaging vs. time averaging in molecular dynamics simulations of thermal conductivity

In this report, we compare time averaging and ensemble averaging as two different methods for phase space sampling in molecular dynamics (MD) calculations of thermal conductivity. For the comparison, we calculate thermal conductivities of solid argon and silicon structures, using equilibrium MD. We introduce two different schemes for the ensemble averaging approach and show that both can reduce the total simulation time as compared to time averaging. It is also found that velocity rescaling is an efficient mechanism for phase space exploration. Although our methodology is tested using classical MD, the approaches used for generating independent trajectories may find their greatest utility in computationally expensive simulations such as first principles MD. For such simulations, where each time step is costly, time averaging can require long simulation times because each time step must be evaluated sequentially and therefore phase space averaging is achieved through sequential operations. On the other hand, with ensemble averaging, phase space sampling can be achieved through parallel operations, since each trajectory is independent. For this reason, particularly when using massively parallel architectures, ensemble averaging can result in much shorter simulation times (∼100–200X), but exhibits similar overall computational effort.

Molecular dynamics simulations of thermal conductivity in 2D complex Yukawa liquids

The thermal conductivity in strongly coupled complex dusty plasma liquids (SCCDPLs) has been investigated through an improved homogenous nonequilibrium molecular simulation (HNEMS) method, for the first time. The HNEMS method has been employed for two-dimensional (2D) Yukawa systems in a canonical ensemble. The thermal conductivities with suitable normalizations (plasma and Einstein frequencies), in the value of low force field strength, have been computed for a wide range of plasma state points of Coulomb coupling (Γ) and screening strength (κ). The new simulation results are found to obey the simple analytical temperature scaling law. The present HNEMS results are in generally with parts of earlier HNEMS, equilibrium molecular dynamics (EMD) and experimental data in the literature for the 2D and there-dimensional (3D) SCCDPLs. It is shown that the HNEMS method can be used to estimate the thermal conductivity very effectively and to understand the fundamental behaviours in 2D Yukawa systems.

Molecular Dynamics Simulation of Thermal Conductivity of Primary Particle of Silica Aerogel

The amorphous Si O2 and primary particle unit(PPU) of Si O2 aerogel are generated using the melting-quenching process based on the molecular dynamics method. Their thermal conductivities(TC) are also calculated by the non-equilibrium molecular dynamics(NEMD). The size effect on the TC caused by the heat source and heat sink has been taken into account. The predicted TC of the bulk amorphous Si O2 material is in good agreement with the available results in literature. Calculated results also show that the particle diameter has made the TC of the PPU show scale effect in the range of 2-6 nm though the effect is relative small. The diameter of the interface between particles has significant effect on the TC of the PPU which increase 171.61% as the interface diameter increases from 0.89 nm to 2.49 nm when the particle diameter is 3 nm. A temperature drop at the interface showed that there is interfacial thermal resistance between the neighboring particles. It is also shown that, the smaller the interface size, the bigger the interface thermal resistance.

Molecular Dynamics Simulation of Thermal Conductivity of Aluminum

In this research, the thermal conductivity of aluminum (Al) in macro scale was investigated by the molecular dynamics simulation technique. We used FORTRAN programming in the simulations and used a fixed number of atoms, N, confined to a fixed pressure, P, and maintained at a constant preset temperature, T, i.e. the NPT ensemble. The Sutton-Chen many-body potential was used to calculate energy and force. The temperature and pressure of the system were controlled by Nosé-Hoover thermostat and Berendsen barostat respectively. We could solve the equations of motion using the Velocity Verlet algorithm. We calculated the thermal conductivity of Al in the macro scale using the Green-Kubo method. Moreover, we have studied the effect of increasing temperature on the value of the thermal conductivity of Al. The obtained results showed that the computed thermal conductivities are in good agreement with experimental data.

Molecular dynamics simulation of thermal conductivity of Cu–Ar nanofluid using EAM potential for Cu–Cu interactions

Mechanism of heat conduction in copper-argon nanofluids is studied by molecular dynamics simulation and the thermal conductivity was obtained using the Green–Kubo method. While the interatomic potential between argon atoms is described using the well-known Lennard–Jones (L–J) potential, a more accurate embedded atom method (EAM) potential is used in describing the interatomic interaction between copper atoms. It is found that the heat current autocorrelation function obtained using L–J potential to describe the copper-copper interatomic interaction fluctuates periodically due to periodic oscillation of the instantaneous microscopic heat fluxes. Thermal conductivities of nanofluids using EAM potentials were calculated with different volume fractions but the same nanoparticle size. The results show that thermal conductivity of nanofluids are almost a linear function of the volume fraction and slightly higher than the results predicted by the conventional effective media theory for a well-dispersed solution. A solid-like base fluid liquid layer with a thickness of 0.6 nm was found in the simulation and this layer is believed to account for the small discrepancy between the results of MD simulation and the conventional effective media theory.