Two-dimensional chalcogenide-based materials of group 14 elements are predicted as potential thermoelectric (TE) materials, though the figure of merit (ZT) obtained requires improvement to be commercially accessible. Herein, we have computationally modeled synthesized γ-GeSe and reduced-dimension 2D layers (monolayer, bilayer, trilayer, and quad-layer) and subjected them to first-principles calculations to extract essential properties pertaining to TE. The ZT values obtained for the considered systems are found to be remarkably high (quad-layer: 2.8; trilayer: 3.1; bilayer: 3.8), even at a high temperature of 900 K. The dimensionality reduction (3D to 2D) as well as reducing layers (quad-layer to bilayer) improved the ZT considerably in comparison to that of bulk γ-GeSe (0.8 at 900 K). Even though the power factor decreases with decreasing layers, ultralow lattice thermal conductivities (k L) are responsible for the high ZT. Ultralow k L (>1 W m–1 K–1) was observed in 2D γ-GeSe at all temperature ranges, with the lowest k L observed in the bilayer (0.15 W m–1 K–1) and trilayer (0.17 W m–1 K–1) at 900 K. The low k L is also supported by the presence of high anharmonicity, high phonon scattering rates, low elastic constants, low group velocity, and low Debye temperature. We envisage that these findings will motivate investigations on similar low-dimensional materials for improved thermoelectric performance.

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The theoretical determination of thermoelectric (TE) properties of a material depends upon the considered order of phonon interactions within the system. While three-phonon interactions have been used widely, four-phonon interactions should be considered in cases where lattice thermal conductivity (κ L ) is overestimated by three-phonon-based calculations, leading to a lower figure of merit (ZT). Here, we have evaluated bulk and bilayer systems of orthorhombic and hexagonal GeS as potential TE materials. The o-GeS and h-GeS bulk systems show higher ZT values of 0.96 than their respective bilayer systems. The effect of four-phonon scattering has been calculated in the o-GeS and h-GeS bilayer systems, revealing that κ L is more dominant in the o-GeS bilayer. This disparity can be attributed to the presence of a larger phonon band gap in the o-GeS bilayer compared to the h-GeS bilayer. The percentage change in κ L upon considering a higher order four-phonon scattering also increases with temperature. The four-phonon interactions lead to lower κ L and higher ZT values of 0.508 for the o-GeS bilayer along the y-axis at 900 K. These findings show the vitality of considering higher order four-phonon interactions in calculating the lattice thermal conductivity and ZT values for such materials.

To achieve seamless heat dissipation, it is essential to use materials with high thermal conductivity to improve thermal management. In this study, we have utilized ab initio and machine learning techniques to systematically explore the lattice thermal conductivity of BN and other group 13 nitride based bulk and bilayer materials. By employing data-driven training of potentials of different atomic configurations at different time steps obtained from the AIMD data, we have demonstrated the comparability of the results obtained from the machine-learned potentials compared to the density functional theory (DFT) based calculations on thermal conductivity. Furthermore, we examined the significance of four phonon interactions in group 13 nitrides by comparing the calculated values with the available experimental values. Notably, bilayer AlN exhibits a high thermal conductivity (881 W m–1 K–1) due to its stronger covalent bonding, which contradicts the trend observed from B to In. Our study highlights that the machine learning potential-based approach can provide more accurate results than DFT, paving the way for future robust investigations of materials using high-throughput screening techniques.