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We present a density functional theory study of stacked MXenes with the aim of assessing the accuracy of the most widely used exchange–correlation (xc) functionals for calculating properties relevant for battery electrode materials, namely, mechanical stability, open-circuit voltages, and lithium diffusion barriers. The open-circuit voltage results are nearly independent of the choice of xc-functional, while the lithium diffusion barriers are shown to be heavily dependent on the selected xc-functional, with diffusivities spanning 5 orders of magnitude. This is shown to be due to differences in the computed interlayer distances between the MXene monolayers, which are found to be linearly related to the diffusion barriers. This underlines the importance of starting from reliable crystal structures when modeling MXenes as battery electrode materials. Using an experimental reference materials database, we show a general trend in lattice parameter accuracy for 2D stacked materials with the chosen xc-functionals. Our results reveal that the optB88-vdW functional provides the best average accuracy for predicting the out-of-plane lattice parameter and hence also the best estimate for the transition-state barriers, while PBE with D3 damping performs only slightly worse on average.

In his comment Maździarz 2019 (2D Mater. 6 048001) raises doubts concerning the reliability of our test for dynamical (in particular elastic) stability of monolayer materials, which neglects the shear components of the stiffness tensor and only considers the sign of the planar stiffness coefficients. We agree that our analysis has not been complete, but find that it suffices in practice except for very few cases (less than 1% of the materials). Nevertheless, for completeness we are currently calculating the shear components of the elastic tensor for all the materials in the C2DB.

Localized electronic states formed inside the band gap of a semiconductor due to crystal defects can be detrimental to the material's optoelectronic properties. Semiconductors with a lower tendency to form defect induced deep gap states are termed defect-tolerant. Here we provide a systematic first-principles investigation of defect tolerance in 29 monolayer transition metal dichalcogenides (TMDs) of interest for nanoscale optoelectronics. We find that the TMDs based on group VI and X metals form deep gap states upon creation of a chalcogen (S, Se, Te) vacancy, while the TMDs based on group IV metals form only shallow defect levels and are thus predicted to be defect-tolerant. Interestingly, all the defect sensitive TMDs have valence and conduction bands with a very similar orbital composition. This indicates a bonding/antibonding nature of the gap, which in turn suggests that dangling bonds will fall inside the gap. These ideas are made quantitative by introducing a descriptor that measures the degree of similarity of the conduction and valence band manifolds. Finally, the study is generalized to nonpolar nanoribbons of the TMDs where we find that only the defect sensitive materials form edge states within the band gap.

The need for prediction of accurate electronic binding energies has led to the development of different schemes for combining density functional calculations, typically at the level of the generalized gradient approximation (GGA), with experimental information. We analyze one such scheme by Stevanovic´ et al. [Phys. Rev. B85, 115104 (2012)PRBMDO1098-012110.1103/PhysRevB.85.115104] for predictions of compound enthalpies of formation using fitted elemental-phase reference energies. We show that different versions of GGA with or without +U and a meta-GGA (TPSS) lead to comparable accuracy after fitting the reference energies. Our results also show that the recently developed mBEEF, a Bayesian error estimation functional, gives comparable accuracy with the other functionals even without the fitting. The mBEEF functional furthermore supplies an ensemble estimate of the prediction errors in reasonable agreement with the actual errors. We also show that using the fitting scheme on the mBEEF ensemble leads to improved accuracy including realistic error estimation.

We introduce the Computational 2D Materials Database (C2DB), which organises a variety of structural, thermodynamic, elastic, electronic, magnetic, and optical properties of around 1500 two-dimensional materials distributed over more than 30 different crystal structures. Material properties are systematically calculated by state-of-the art density functional theory and many-body perturbation theory (G$_0\!$W$\!_0$ and the Bethe-Salpeter Equation for $\sim$200 materials) following a semi-automated workflow for maximal consistency and transparency. The C2DB is fully open and can be browsed online or downloaded in its entirety. In this paper, we describe the workflow behind the database, present an overview of the properties and materials currently available, and explore trends and correlations in the data. Moreover, we identify a large number of new potentially synthesisable 2D materials with interesting properties targeting applications within spintronics, (opto-)electronics, and plasmonics. The C2DB offers a comprehensive and easily accessible overview of the rapidly expanding family of 2D materials and forms an ideal platform for computational modeling and design of new 2D materials and van der Waals heterostructures., Comment: Add journal reference and DOI; Minor updates to figures and wording