Abstract: Two-dimensional materials (2DMs) continue to attract a lot of attention, particularly for their extreme flexibility and superior thermal properties. Molecular dynamics simulations are among the most powerful methods for computing these properties, but their reliability depends on the accuracy of interatomic interactions. While first principles approaches provide the most accurate description of interatomic forces, they are computationally expensive. In contrast, classical force fields are computationally efficient, but have limited accuracy in interatomic force description. Machine learning interatomic potentials, such as Gaussian Approximation Potentials, trained on density functional theory (DFT) calculations offer a compromise by providing both accurate estimation and computational efficiency. In this work, we present a systematic procedure to develop Gaussian approximation potentials for selected 2DMs, graphene, buckled silicene, and h-XN (X = B, Al, and Ga, as binary compounds) structures. We validate our approach through calculations that require various levels of accuracy in interatomic interactions. The calculated phonon dispersion curves and lattice thermal conductivity, obtained through harmonic and anharmonic force constants (including fourth order) are in excellent agreement with DFT results. HIPHIVE calculations, in which the generated GAP potentials were used to compute higher-order force constants instead of DFT, demonstrated the first-principles level accuracy of the potentials for interatomic force description. Molecular dynamics simulations based on phonon density of states calculations, which agree closely with DFT-based calculations, also show the success of the generated potentials in high-temperature simulations.

Abstract: The newest members of a two-dimensional material family, involving transition metal carbides and nitrides (called MXenes), have garnered increasing attention due to their tunable electronic and thermal properties depending on the chemical composition and functionalization. This flexibility can be exploited to fabricate efficient electrochemical energy storage (batteries) and energy conversion (thermoelectric) devices. In this study, we calculated the Seebeck coefficients and lattice thermal conductivity values of oxygen terminated M2CO2 (where M = Ti, Zr, Hf, Sc) monolayer MXene crystals in two different functionalization configurations (model-II (MD-II) and model-III (MD-III)), using density functional theory and Boltzmann transport theory. We estimated the thermoelectric figure-of-merit, zT, of these materials by two different approaches, as well. First of all, we found that the structural model (i.e. adsorption site of oxygen atom on the surface of MXene) has a paramount impact on the electronic and thermoelectric properties of MXene crystals, which can be exploited to engineer the thermoelectric properties of these materials. The lattice thermal conductivity kappa(l), Seebeck coefficient and zT values may vary by 40% depending on the structural model. The MD-III configuration always has the larger band gap, Seebeck coefficient and zT, and smaller kappa(l) as compared to the MD-II structure due to a larger band gap, highly flat valence band and reduced crystal symmetry in the former. The MD-III configuration of Ti2CO2 and Zr2CO2 has the lowest kappa(l) as compared to the same configuration of Hf2CO2 and Sc2CO2. Among all the considered structures, the MD-II configuration of Hf2CO2 has the highest kappa(l), and Ti2CO2 and Zr2CO2 in the MD-III configuration have the lowest kappa(l). For instance, while the band gap of the MD-II configuration of Ti2CO2 is 0.26 eV, it becomes 0.69 eV in MD-III. The zT(max) value may reach up to 1.1 depending on the structural model of MXene.