Transport and Helfand moments in the Lennard-Jones fluid. II. Thermal Conductivity

The thermal conductivity is calculated with the Helfand-moment method in the Lennard-Jones fluid near the triple point. The Helfand moment of thermal conductivity is here derived for molecular dynamics with periodic boundary conditions. Thermal conductivity is given by a generalized Einstein relation with this Helfand moment. We compute thermal conductivity by this new method and compare it with our own values obtained by the standard Green-Kubo method. The agreement is excellent.Comment: Submitted to the Journal of Chemical Physic

Manipulating thermal conductivity through substrate coupling

We report a new approach to the thermal conductivity manipulation -- substrate coupling. Generally, the phonon scattering with substrates can decrease the thermal conductivity, as observed in recent experiments. However, we find that at certain regions, the coupling to substrates can increase the thermal conductivity due to a reduction of anharmonic phonon scattering induced by shift of the phonon band to the low wave vector. In this way, the thermal conductivity can be efficiently manipulated via coupling to different substrates, without changing or destroying the material structures. This idea is demonstrated by calculating the thermal conductivity of modified double-walled carbon nanotubes and also by the ice nanotubes coupled within carbon nanotubes.Comment: 5 figure

Prediction of Thermo-Physical Properties of TiO2-Al2O3/Water Nanoparticles by Using Artificial Neural Network

In this paper, an artificial neural network is implemented for the sake of predicting the thermal conductivity ratio of TiO2-Al2O3/water nanofluid. TiO2-Al2O3/water in the role of an innovative type of nanofluid was synthesized by the sol–gel method. The results indicated that 1.5 vol.% of nanofluids enhanced the thermal conductivity by up to 25%. It was shown that the heat transfer coefficient was linearly augmented with increasing nanoparticle concentration, but its variation with temperature was nonlinear. It should be noted that the increase in concentration may cause the particles to agglomerate, and then the thermal conductivity is reduced. The increase in temperature also increases the thermal conductivity, due to an increase in the Brownian motion and collision of particles. In this research, for the sake of predicting the thermal conductivity of TiO2-Al2O3/water nanofluid based on volumetric concentration and temperature functions, an artificial neural network is implemented. In this way, for predicting thermal conductivity, SOM (self-organizing map) and BP-LM (Back Propagation-Levenberq-Marquardt) algorithms were used. Based on the results obtained, these algorithms can be considered as an exceptional tool for predicting thermal conductivity. Additionally, the correlation coefficient values were equal to 0.938 and 0.98 when implementing the SOM and BP-LM algorithms, respectively, which is highly acceptable. View Full-Tex

Experimental Determination of the Lorenz Number in Cu0.01Bi2Te2.7Se0.3 and Bi0.88Sb0.12

Nanostructuring has been shown to be an effective approach to reduce the lattice thermal conductivity and improve the thermoelectric figure of merit. Because the experimentally measured thermal conductivity includes contributions from both carriers and phonons, separating out the phonon contribution has been difficult and is mostly based on estimating the electronic contributions using the Wiedemann-Franz law. In this paper, an experimental method to directly measure electronic contributions to the thermal conductivity is presented and applied to Cu0.01Bi2Te2.7Se0.3, [Cu0.01Bi2Te2.7Se0.3]0.98Ni0.02, and Bi0.88Sb0.12. By measuring the thermal conductivity under magnetic field, electronic contributions to thermal conductivity can be extracted, leading to knowledge of the Lorenz number in thermoelectric materials

Chirality- and thickness-dependent thermal conductivity of few-layer graphene: a molecular dynamics study

The thermal conductivity of graphene nanoribbons (layer from 1 to 8 atomic planes) is investigated by using the nonequilibrium molecular dynamics method. We present that the room-temperature thermal conductivity decays monotonically with the number of the layers in few-layer graphene. The superiority of zigzag graphene in thermal conductivity is only available in high temperature region and disappears in multi-layer case. It is explained that the phonon spectral shrink in high frequency induces the change of thermal conductivity. It is also reported that single-layer graphene has better ballistic transport property than the multi-layer graphene.Comment: 3 figure