Fast access of the lattice thermal conductivity and phonon quasiparticle spectra of MoTiCT (T = -O and -F) and Janus MoTiCOF MXenes from machine learning potentials.

The presence of strong anharmonic effects in surface functionalized MXenes greatly challenges the use of harmonic lattice dynamics calculations to predict their phonon spectra and lattice thermal conductivity at finite temperatures. Herein, we demonstrate the workflow for training and validating machine learning potentials in terms of moment tensor potential (MTP) for MXenes including MoTiC, MoTiCO, MoTiCF and Janus-MoTiCOF monolayers. Then, the MTPs of MXenes are successfully combined with the harmonic lattice dynamics calculations to obtain the temperature renormalized phonon spectra, three-phonon scattering rates, phonon relaxation times and lattice thermal conductivity at finite temperatures.