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The field of topological mechanics has recently emerged due to the interest in robustly transporting various types of energy in a flaw and defect-insensitive fashion. While there have been a significant number of studies based on discovering and proposing topological materials and structures, very few have focused on tuning the resulting topological bandgaps, which is critical because the bandgap frequency is fixed once the structure has been fabricated. Here, we perform both lattice dynamical calculations and molecular dynamical simulations to investigate strain effects on the phononic topological bandgaps in two-dimensional monolayer hexagonal boron nitride. Our studies demonstrate that while the topologically protected phononic bandgaps are not closed even for severely deformed hexagonal boron nitride and are relatively insensitive to uniaxial tension and shear strains, the position of the frequency gap can be efficiently tuned in a wide range through the application of biaxial strains. Overall, this work thus demonstrates that topological phonons are robust against the effects of mechanical strain engineering and shed light on the tunability of the topological bandgaps in nanomaterials. [ABSTRACT FROM AUTHOR]

We apply united-atom (UA) nonequilibrium molecular dynamics simulations to predict the thermal conductivity for amorphous polyethylene at room temperature with chain length (CL) increasing from 4 to 1260. The thermal conductivity is determined by the competition of the two mechanisms: (1) The collision among the UA beads and (2) the phonon vibration. The collision mechanism mainly dominates CL≤7, while the phonon vibration mechanism mainly determines CL ≥ 140. The competition between the two mechanisms determines 12 ≤ CL ≤ 140. In particular, the thermal conductivity for 8 ≤ CL ≤ 11 cannot be obtained accurately due to the aggregation of the beads. [ABSTRACT FROM AUTHOR]

The thermal conductivity of two-dimensional materials like graphene can efficiently be tuned by introducing holes, in which the density and distribution of the holes are the key parameters. Furthermore, the distribution of holes can induce a variation as high as 74% in the thermal conductivity for porous graphene with a given density of holes. Therefore, an existing challenge is to find the optimal distribution of holes that can minimize or maximize the thermal conductivity of porous graphene as the design space expands dramatically with increasing hole density. We therefore apply an inverse design methodology based on machine learning to reveal the relationship between hole distribution and thermal conductivity reduction in monolayer graphene. The methodology reveals that holes that are randomly distributed transverse to the direction of heat flow, but that exhibit some periodicity along the direction of heat flow, represent the optimal distribution to minimizing the thermal conductivity for porous graphene. Lattice dynamics calculations and wave packet simulations reveal that this spatial distribution effectively causes localization of the phonon modes in porous graphene, which reduces the thermal conductivity. Overall, this work demonstrates the power of machine learning-based design approaches to efficiently obtain new physical insights for scientific problems of interest. Image 1 [ABSTRACT FROM AUTHOR]

Thermal conductivity of graphene nanoribbons (GNR) with length 106 Å and width 4.92 Å after isotopic doping is investigated by molecular dynamics with quantum correction. Two interesting phenomena are found, (1) isotopic doping reduces thermal conductivity effectively in low doping region, and the reduction slows down in high doping region, (2) thermal conductivity increases with increasing temperature in both pure and doped GNR, but the increasing behavior is much more slow in the doped GNR than that in pure ones. Further studies reveal that the physics of these two phenomena is related to the localized phonon modes, whose number increases quickly (slowly) with increasing isotopic doping in low (high) isotopic doping region. [ABSTRACT FROM AUTHOR]

The extreme reduction of the thermal conductivity by defects and folds in carbon nanocoils (CNCs) are first demonstrated using nonequilibrium molecular dynamics simulations. The thermal conductivity for two different defect types with five different folds in the CNCs is extensively studied and the maximum reduction can be up to 70% at both room temperature and 600 K by comparison of the corresponding straight single-walled carbon nanotubes. We reveal that the phonon scattering by coupled defects and folds can govern the reduction of the thermal conductivity by calculating phonon polarization vectors. [ABSTRACT FROM AUTHOR]

Weperform molecular dynamics simulations to investigate the reductionof the thermal conductivity by kinks in silicon nanowires. The reductionpercentage can be as high as 70% at room temperature. The temperaturedependence of the reduction is also calculated. By calculating phononpolarization vectors, two mechanisms are found to be responsible forthe reduced thermal conductivity: (1) the interchanging effect betweenthe longitudinal and transverse phonon modes and (2) the pinchingeffect, that is, a new type of localization, for the twisting andtransverse phonon modes in the kinked silicon nanowires. Our workdemonstrates that the phonon interchanging and pinching effects, inducedby kinking, are brand-new and effective ways in modulating heat transferin nanowires, which enables the kinked silicon nanowires to be a promisingcandidate for thermoelectric materials. [ABSTRACT FROM AUTHOR]

We study thermal transport in folded graphene nanoribbons using molecular dynamics simulations and the non-equilibrium Green's function method. It is found that the thermal conductivity of flat graphene nanoribbons can be modulated by folding and changing interlayer couplings. The analysis of transmission reveals that the reduction of thermal conductivity is due to scattering of low frequency phonons by the folds. Our results suggest that folding can be utilized in the modulation of thermal transport properties in graphene and other two dimensional materials. [ABSTRACT FROM AUTHOR]

The lattice dynamics properties are investigated for twisting bilayer graphene. There are big jumps for the inter-layer potential at twisting angle θ=0° and 60°, implying the stability of Bernal-stacking and the instability of AA-stacking structures, while a long platform in [8,55]° indicates the ease of twisting bilayer graphene in this wide angle range. Significant frequency shifts are observed for the z breathing mode around θ=0° and 60°, while the frequency is a constant in a wide range [8,55]°. Using the z breathing mode, a mechanical nanoresonator is proposed to operate on a robust resonant frequency in terahertz range. [ABSTRACT FROM AUTHOR]