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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.
In a latest experimental advance, graphene-like and insulating BeO monolayer was successfully grown over silver surface by molecular beam epitaxy (ACS Nano 15(2021), 2497). Inspired by this accomplishment, in this work we conduct first-principles bas
Chemical vapor deposition has been most recently employed to fabricate centimeter-scale high-quality single-layer MoSi2N4 (Science; 2020;369; 670). Motivated by this exciting experimental advance, herein we conduct extensive first-principles based si
The structure and mobility of dislocations in the layered semiconductor InSe is studied within a multiscale approach based on generalized Peierls--Nabarro model with material-specific parametrization derived from first principles. The plasticity of I
The discovery of graphene makes it highly desirable to seek new two-dimensional materials. Through first-principles investigation, we predict two-dimensional materials of ReN$_{2}$: honeycomb and tetragonal structures. The phonon spectra establish th
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 proc