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Register a new userSimulating lattice thermal conductivity in semiconducting materials using high-dimensional neural network potential
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We demonstrate that a high-dimensional neural network potential (HDNNP) can predict the lattice thermal conductivity of semiconducting materials with an accuracy comparable to that of density functional theory (DFT) calculation. After a training procedure based on the force, the root mean square error between the forces predicted by the HDNNP and DFT is less than 40 meV/{AA}. As typical examples, we present the results for Si and GaN bulk crystals. The deviation from the thermal conductivity calculated using DFT is within 1% at 200 to 500 K for Si and within 5.4% at 200 to 1000 K for GaN.
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Semiconductors with very low lattice thermal conductivities are highly desired for applications relevant to thermal energy conversion and management, such as thermoelectrics and thermal barrier coatings. Although the crystal structure and chemical bonding are known to play vital roles in shaping heat transfer behavior, material design approaches of lowering lattice thermal conductivity using chemical bonding principles are uncommon. In this work, we present an effective strategy of weakening interatomic interactions and therefore suppressing lattice thermal conductivity based on chemical bonding principles and develop a high-efficiency approach of discovering low $kappa_{rm L}$ materials by screening the local coordination environments of crystalline compounds. The followed first-principles calculations uncover 30 hitherto unexplored compounds with (ultra)low lattice thermal conductivities from thirteen prototype crystal structures contained in the inorganic crystal structure database. Furthermore, we demonstrate an approach of rationally designing high-performance thermoelectrics by additionally incorporating cations with stereochemically active lone-pair electrons. Our results not only provide fundamental insights into the physical origin of the low lattice thermal conductivity in a large family of copper-based compounds but also offer an efficient approach to discovery and design materials with targeted thermal transport properties.
Thermal conductivities are routinely calculated in molecular dynamics simulations by keeping the boundaries at different temperatures and measuring the slope of the temperature profile in the bulk of the material, explicitly using Fouriers law of heat conduction. Substantiated by the observation of a distinct linear profile at the center of the material, this approach has also been frequently used in superdiffusive materials, such as nanotubes or polymer chains, which do not satisfy Fouriers law at the system sizes considered. It has been recently argued that this temperature gradient procedure yields worse results when compared with a method based on the temperature difference at the boundaries -- thus taking into account the regions near the boundaries where the temperature profile is not linear. We study a realistic example, nanocomposites formed by adding boron nitride nanotubes to a polymer matrix of amorphous polyethylene, to show that in superdiffusive materials, despite the appearance of a central region with a linear profile, the temperature gradient method is actually inconsistent with a conductivity that depends on the system size, and, thus, it should be only used in normal diffusive systems.
Engineering thermal transport in two dimensional materials, alloys and heterostructures is critical for the design of next-generation flexible optoelectronic and energy harvesting devices. Direct experimental characterization of lattice thermal conductivity in these ultra-thin systems is challenging and the impact of dopant atoms and hetero-phase interfaces, introduced unintentionally during synthesis or as part of deliberate material design, on thermal transport properties is not understood. Here, we use non-equilibrium molecular dynamics simulations to calculate lattice thermal conductivity of (Mo|W)Se$_2$ monolayer crystals including Mo$_{1-x}$W$_x$Se$_2$ alloys with substitutional point defects, periodic MoSe$_2$|WSe$_2$ heterostructures with characteristic length scales and scale-free fractal MoSe$_2$|WSe$_2$ heterostructures. Each of these features has a distinct effect on phonon propagation in the crystal, which can be used to design fractal and periodic alloy structures with highly tunable thermal conductivities. This control over lattice thermal conductivity will enable applications ranging from thermal barriers to thermoelectrics.
We study the size dependence of thermal conductivity in nanoscale semiconducting systems. An analytical formula including the surface scattering and the size confinement effects of phonon transport is derived. The theoretical formula gives good agreements with the existing experimental data for Si and GaAs nanowires and thin films.
Experimental realization of single-layer MoSi2N4 is among the latest groundbreaking advances in the field of two-dimensional (2D) materials. Inspired by this accomplishment, herein we conduct first-principles calculations to explore the stability of MC2N4 (M= Cr, Mo, W, V, Nb, Ta, Ti, Zr, Hf) monolayers. Acquired results confirm the desirable thermal, dynamical and mechanical stability of MC2N4 (M= Cr, Mo, W, V) nanosheets. Interestingly, CrC2N4, MoC2N4 and WC2N4 monolayers are found to be semiconductors with band gaps of 2.32, 2.76 and 2.86 eV, respectively, using the HSE06 functional, whereas VC2N4 lattice shows a metallic nature. The direct gap semiconducting nature of CrC2N4 monolayer results in excellent absorption of visible light. The elastic modulus and tensile strength of CrC2N4 nanosheet are predicted to be remarkably high, 676 and 54.8 GPa, respectively. On the basis of iterative solutions of the Boltzmann transport equation, the room temperature lattice thermal conductivity of CrC2N4 monolayer is predicted to be 350 W/mK, among the highest in 2D semiconductors. CrC2N4 and WC2N4 lattices are also found to exhibit outstandingly high piezoelectric coefficients. This study introduces CrC2N4 nanosheet as a novel 2D semiconductor with outstandingly high mechanical strength, thermal conductivity, carrier mobility and piezoelectric coefficient.
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