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Accurate theoretical prediction of the band offsets at interfaces ofsemiconductor heterostructures can often be quite challenging. Although densityfunctional theory has been reasonably successful to carry out such calculationsand efficient and accurate semilocal functionals are desirable to reduce thecomputational cost. In general, the semilocal functionals based on thegeneralized gradient approximation (GGA) significantly underestimate the bulkband gaps. This, in turn, results in inaccurate estimates of the band offsetsat the heterointerfaces. In this paper, we investigate the performance ofseveral advanced meta-GGA functionals in the computational prediction of bandoffsets at semiconductor heterojunctions. In particular, we investigate theperformance of r2SCAN (revised strongly-constrained and appropriately-normedfunctional), rMGGAC (revised semilocal functional based on cuspless hydrogenmodel and Pauli kinetic energy density functional), mTASK (modified Aschebrockand K\"ummel meta-GGA functional), and LMBJ (local modified Becke-Johnson)exchange-correlation functionals. Our results strongly suggest that thesemeta-GGA functionals for supercell calculations perform quite well, especially,when compared to computationally more demanding GW calculations. We alsopresent band offsets calculated using ionization potentials and electronaffinities, as well as band alignment via the branch point energies. Overall,our study shows that the aforementioned meta-GGA functionals can be used withinthe DFT framework to estimate the band offsets in semiconductorheterostructures with predictive accuracy.

Efficient and improved prediction of the band offsets at semiconductor heterojunctions from meta-GGA density functionals