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We theoretically study the Casimir interaction between Weyl semimetals. When the distance a between semi-infinite Weyl semimetals is in the micrometer regime, the Casimir attraction can be enhanced by the chiral anomaly. The Casimir attraction depends sensitively on the relative orientations between the separations (b 1, b 2) of Weyl nodes in the Brillouin zone and show anisotropic behavior for the relative orientation of these separations (b 1, b 2) when they orient parallel to the interface. This anisotropy is quite larger than that in conventional birefringent materials. The Casimir force can be repulsive in the micrometer regime if the Weyl semimetal slabs are sufficiently thin and the direction of Weyl nodes separations (b 1, b 2) is perpendicular to the interface. The Casimir attraction between Weyl semimetal slabs decays slower than 1/a4 when the Weyl nodes separations b 1 and b 2 are both parallel to the interface. [ABSTRACT FROM AUTHOR]

• A thermal conductivity model for graphene nanofluids is proposed by anisotropic analysis. • The model is renovated by analyzing the area without graphene along the heat conduction path. • The effects of graphene's length and thickness, interface layer are included in the model. • The model gives better fitting results with experimental data for graphene nanofluids. Many studies have shown that low concentration of graphene can appreciably increase the thermal conductivity of nanofluids that is difficult to explain by conventional thermal conductivity model. In this paper, a new model considering the effects of graphene's length and thickness, interface layer and anisotropic characteristics is established. The model is further modified by considering the possibility of absence of graphene in the actual thermal conduction path, that is only bulk liquid along the heat conduction path in some cases. It is found that the thermal conductivity predicted by the present model is positively correlated with the temperature, concentration and length of nanoparticles, while is slightly negatively correlated with thickness. This model is applied to predict thermal conductivities of graphene nanofluids in different cases compared to other models. The results indicate that the present model has a strong ability to predict graphene nanofluids especially at relatively low concentrations (<0.1 vol%). [ABSTRACT FROM AUTHOR]