METAGGA
METAGGA = SCAN  RTPSS  MBJ  LIBXC  ...
Default: The functional specified by LEXCH in the POTCAR if also GGA is not specified.
Description: selects a metaGGA functional.
Mind:

Available functionals
 METAGGA=LIBXC
 The LIBXC tag allows to use a metaGGA functional from the library of exchangecorrelation functionals Libxc^{[1]}^{[2]}^{[3]}. Along with METAGGA=LIBXC, it is also necessary to specify the tags LIBXC1 and LIBXC2 that specify the particular functional. Note that it is necessary to have Libxc >= 5.2.0 installed and VASP.6.3.0 or higher compiled with precompiler options.
 METAGGA=TPSS, RTPSS, or M06L
 The implementation of the TPSS and RTPSS (revTPSS) selfconsistent metageneralized gradient approximation within the projectoraugmentedwave method in VASP is discussed by Sun et al.^{[4]}. For details on the M06L functional, refer to the paper by Zhao and Truhlar^{[5]}.
 METAGGA=MS0, MS1, or MS2
 The MS (where MS stands for "made simple") functionals are presented in detail in references ^{[6]} and ^{[7]}. These functionals are believed to improve the description of noncovalent interactions over PBE, TPSS and revTPSS but not over M06L. The MS functionals are available as of VASP version ≥ 5.4.1.
 METAGGA=SCAN
 The SCAN (Strongly constrained and appropriately normed) ^{[8]} functional is a semilocal density functional that fulfills all known constraints that the exact density functional must fulfill. There are indications that this functional is superior to most gradient corrected functionals ^{[9]}. This functional is only available as of VASP version ≥ 5.4.3.
 METAGGA=RSCAN
 The rSCAN (regularized SCAN) functional ^{[10]}, introduces regularizations that improve the numerical sensitivity and convergence behavior. These regularizations break several of the exact constraints that the parent SCAN functional was designed to satisfy. However, testing has indicated that the accuracy of rSCAN can be inferior to SCAN in some cases ^{[11]}. This functional is available as of VASP version ≥ 6.2.0.
 METAGGA=R2SCAN
 The rSCAN (regularizedrestored SCAN) functional ^{[12]} modifies the regularizations introduced in rSCAN to enforce adherence to the exact constraints obeyed by SCAN. It fulfills all known constraints. However, it only recovers the slowly varying densitygradient expansion for exchange to second order, while SCAN recovers the expansion to 4th order. Testing indicates that rSCAN at least matches the accuracy of the parent SCAN functional but with significantly improved numerical efficiency and accuracy under lowcost computational settings. This functional is available as of VASP version ≥ 6.2.0, or in version 5.4.4 by patch 4.
 METAGGA=SCANL, RSCANL, or R2SCANL
 The functionals SCANL^{[13]}^{[14]}, rSCANL, and rSCANL^{[15]}^{[16]} are deorbitalized versions of SCAN, rSCAN, and rSCAN, respectively. They do not depend on the kineticenergy density , but on the Laplacian of the density , instead.
 METAGGA=OFR2
 The OFR2^{[16]} functional depends on the Laplacian of the density , but not on the kineticenergy density .
 METAGGA=MBJ
 The modified BeckeJohnson (MBJ) potential^{[17]}^{[18]} yields band gaps with an accuracy similar to hybrid functionals or GW methods, but is computationally less expensive. The exchange part of the MBJ potential (that is combined with the LDA correlation potential, ) consists of two terms whose relative weights are determined by a systemdependent constant :
 where is the BeckeRoussel (BR) potential that mimics the Coulomb potential created by the exchange hole^{[19]} and depends on , , and .
 The systemdependent is a function of the average of in the unit cell (of volume ):
 where , , and are free parameters that can be set by means of the CMBJA, CMBJB, and CMBJE tags, respectively. The default values are , bohr, and ^{[18]}. In Ref. ^{[20]}, the alternative values , bohr, and were proposed.
Mind:

 METAGGA=LMBJ
 The local MBJ (LMBJ) potential^{[21]}^{[22]} is a variant of the MBJ potential that was modified such that it does not suffer from the problems related to the presence of vacuum mentioned above for MBJ. The LMBJ potential has the same analytical form as the MBJ potential:
 with the difference that is now a positiondependent function:
 where
 with
 The default values of the parameters in LMBJ are (see erratum of Ref. ^{[22]}) , bohr, , ( bohr), and e/bohr. is the smearing parameter that determines the size of the region over which the average of is calculated, and is the threshold density, which corresponds to the Wigner–Seitz radius bohr. , , , , and can be set by means of the CMBJA, CMBJB, CMBJE, SMBJ, and RSMBJ tags, respectively.
 The first two points mentioned above for the MBJ potential also apply for the LMBJ potential.
POTCAR files: required information
MetaGGA calculations require POTCAR files that include information on the kinetic energy density of the coreelectrons. To check whether a particular POTCAR contains this information, type:
grep kinetic POTCAR
This should yield at least the following lines (for each element on the file):
kinetic energydensity mkinetic energydensity pseudized
and for PAW datasets with partial core corrections:
kinetic energy density (partial)
LASPH =.TRUE. should be selected if a metaGGA functional is selected. If LASPH =.FALSE., the onecenter contributions are only calculated for a spherically averaged density and kineticenergy density. This means that the onecenter contributions to the KohnSham potential are also spherical. Since the PAW method describes the entire space using plane waves, errors are often small even if the nonspherical contributions to the KohnSham potential are neglected inside the PAW spheres (additive augmentation, as opposed to the APW or FLAPW method where the plane wave contribution only describes the interstitial region between the atoms). Anyhow, if the density is strongly nonspherical around some atoms in your structure, LASPH =.TRUE. must be selected. Nonspherical terms are particularly encountered in d and felements, dimers, molecules, and solids with strong directional bonds.
Convergence issues
If convergence problems are encountered, it is recommended to preconverge the calculations using the PBE functional, and start the calculation from the WAVECAR file corresponding to the PBE ground state. Furthermore, ALGO = A (conjugate gradient algorithm for orbitals) is often more stable than charge density mixing, in particular, if the system contains vacuum regions.
Related tags and articles
LIBXC1, LIBXC2, GGA, CMBJ, CMBJA, CMBJB, CMBJE, SMBJ, RSMBJ, LASPH, LMAXTAU, LMIXTAU, LASPH, AMGGAX, AMGGAC, Bandstructure calculation using metaGGA functionals
References
 ↑ M. A. L. Marques, M. J. T. Oliveira, and T. Burnus, Comput. Phys. Commun., 183, 2272 (2012).
 ↑ S. Lehtola, C. Steigemann, M. J. T. Oliveira, and M. A. L. Marques, SoftwareX, 7, 1 (2018).
 ↑ https://www.tddft.org/programs/libxc/
 ↑ J. Sun, M. Marsman, G. Csonka, A. Ruzsinszky, P. Hao, Y.S. Kim, G. Kresse, and J. P. Perdew, Phys. Rev. B 84, 035117 (2011).
 ↑ Y. Zhao and D. G. Truhlar, J. Chem. Phys. 125, 194101 (2006).
 ↑ J. Sun, B. Xiao, and A. Ruzsinszky, J. Chem. Phys. 137, 051101 (2012).
 ↑ J. Sun, R. Haunschild, B. Xiao, I. W. Bulik, G. E. Scuseria, and J. P. Perdew, J. Chem. Phys. 138, 044113 (2013).
 ↑ J. Sun, A. Ruzsinszky, and J. P. Perdew, Phys. Rev. Lett. 115, 036402 (2015).
 ↑ J. Sun, R. C. Remsing, Y. Zhang, Z. Sun, A. Ruzsinszky, H. Peng, Z. Yang, A. Paul, U. Waghmare, X. Wu, M. L. Klein, and J. P. Perdew, Nat. Chem. 8, 831 (2016).
 ↑ A. P. Bartók and J. R. Yates, J. Chem. Phys. 150, 161101 (2019).
 ↑ D. MejíaRodríguez and S. B. Trickey, J. Chem. Phys. 151, 207101 (2019).
 ↑ J. W. Furness, A. D. Kaplan, J. Ning, J. P. Perdew, and J. Sun, J. Phys. Chem. Lett. 11, 8208 (2020).
 ↑ D. MejíaRodríguez and S. B. Trickey, Phys. Rev. A 91, 052512 (2017).
 ↑ D. MejiaRodriguez and S. B. Trickey, Phys. Rev. B 98, 115161 (2018).
 ↑ D. MejíaRodríguez and S. B. Trickey, Phys. Rev. B 102, 121109(R) (2020).
 ↑ ^{a} ^{b} A. D. Kaplan and J. P. Perdew, Phys. Rev. Mater. 6, 083803 (2022).
 ↑ A. D. Becke and E. R. Johnson, J. Chem. Phys. 124, 221101 (2006).
 ↑ ^{a} ^{b} F. Tran and P. Blaha, Phys. Rev. Lett. 102, 226401 (2009).
 ↑ A. D. Becke and M. R. Roussel, Phys. Rev. A 39, 3761 (1989).
 ↑ D. Koller, F. Tran, and P. Blaha, Phys. Rev. B 85, 155109 (2012).
 ↑ T. Rauch, M. A. L. Marques, and S. Botti, J. Chem. Theory Comput. 16, 2654 (2020).
 ↑ ^{a} ^{b} T. Rauch, M. A. L. Marques, and S. Botti, Phys. Rev. B 101, 245163 (2020).