Carbon nanotubes (CNTs) and graphene are thought to be building bricks for next-generation thermal management devices due to their ultra-high thermal conductivities. However, in practical applications they do not exhibit their full potentials due to issues from interfaces, dopants, and functional groups. Thus, deep understanding of these effects on the thermal conductivities is needed. Molecular dynamics (MD) simulation can provide such insights into these material systems. However, prediction capability is limited by a narrow choice of chemical elements in traditional equilibrium MD potentials. Herein, non-equilibrium MD (NEMD) simulations were implemented to study the thermal conductivities of CNTs and graphene by using ReaxFF potentials (Reax-03, Reax-12, and Reax-15), all of which enable a wider choice of the element category. In the simulations, CNT and graphene have maximum lengths of 400 nm. The length-dependent thermal conductivities were studied in those systems. The ReaxFF potentials predicted higher thermal conductivities and longer phonon mean free paths than the traditional AIREBO potential. The geometry and location of G-peaks shown in the phonon density of states calculated by the Reax-03 and Reax-12 potentials were similar to the results obtained from the AIREBO potential. In contrast, a wider G-peak was obtained from the Reax-15 potential. The phonon dispersion curves based on each potential showed that Reax-03 and Reax-12 can predict accurate out-of-plane modes when compared with experiments. The Grtineisen parameters of the ZA mode based on the Reax-03 and Reax-12 potentials are smaller than those based on the AIREBO potential, indicating a lower anharmonicity of lattice vibrations. Radical distribution functions from the Reax-03 and Reax-12 potentials showed a higher lattice stiffness and longer phonon mean free paths (MFPs) than those obtained from the AIREBO potential. These results illustrate the capability of ReaxFF in predicting thermal conductivities of low dimensional carbon allotropes and their derivatives for advanced heat management. (C) 2017 Elsevier Ltd. All rights reserved.