Computational Screening of MXene Electrodes for Pseudocapacitive Energy Storage

MXenes (two-dimensional transition-metal carbides and nitrides) are promising materials for capacitive energy storage due to the large chemical space of existing and potential compositions, but only a few of them have been experimentally explored. In this work, we computationally screen a series of MXene electrodes (Mn+1XnTx: M = Sc, Ti, V, Zr, Nb, Mo; X = C, N; T = O, OH; n = 1–3) to simulate their pseudocapacitive performance in the aqueous H2SO4 electrolyte. We find that nitride MXenes exhibit better pseudocapacitive performance than carbide MXenes. Especially, Ti2NTx is predicted to have a high gravimetric capacitance over a wide voltage window, whereas Zrn+1NnTx MXenes are predicted to possess the best areal capacitive performance. Evaluating the descriptors for the capacitance trends, we find that more positive hydrogen adsorption free energy (weak binding to H) and smaller change of the potential at the point of zero charge after H binding lead to higher capacitance. Our work provides helpful guidance to selectively develop high-performance MXene pseudocapacitors and to further screen MXene electrodes.