METAGGA: Difference between revisions
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Revision as of 12:22, 16 October 2024
METAGGA = SCAN | RTPSS | MBJ | LIBXC | ...
Default: The functional specified by LEXCH in the POTCAR if also GGA is not specified.
Description: Selects a meta-GGA functional.
Mind:
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Available functionals
- METAGGA=LIBXC
- The LIBXC tag allows to use a meta-GGA functional from the library of exchange-correlation 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[4] and RTPSS (revTPSS[5]) self-consistent meta-generalized gradient approximation within the projector-augmented-wave method in VASP is discussed by Sun et al.[6]. For details on the M06-L functional, refer to the paper by Zhao and Truhlar[7].
- METAGGA=TPSS_X, RTPSS_X, or M06L_X
- The exchange component of TPSS, RTPSS, or M06L. Available since VASP.6.4.3.
- METAGGA=TPSS_C, RTPSS_C, or M06L_C
- The correlation component of TPSS, RTPSS, or M06L. Available since VASP.6.4.3.
- METAGGA=MS0, MS1, or MS2
- The MS (where MS stands for "made simple") functionals are presented in detail in references [8] and [9]. 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=MS0_X, MS1_X, or MS2_X
- The exchange component of MS0, MS1, or MS2. Available since VASP.6.4.3.
- METAGGA=MS0_C, MS1_C, or MS2_C
- The correlation component of MS0, MS1, or MS2. Available since VASP.6.4.3.
- METAGGA=SCAN
- The SCAN (Strongly constrained and appropriately normed) [10] 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 [11]. This functional is only available as of VASP version ≥ 5.4.3.
- METAGGA=RSCAN
- The rSCAN (regularized SCAN) functional [12], 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 [13]. This functional is available as of VASP version ≥ 6.2.0.
- METAGGA=R2SCAN
- The rSCAN (regularized-restored SCAN) functional [14] 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 density-gradient 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 low-cost computational settings. This functional is available as of VASP version ≥ 6.2.0, or in version 5.4.4 by patch 4.
- METAGGA=SCAN_X, RSCAN_X, or R2SCAN_X
- The exchange component of SCAN, RSCAN, or R2SCAN. Available since VASP.6.4.3.
- METAGGA=SCAN_C, RSCAN_C, or R2SCAN_C
- The correlation component of SCAN, RSCAN, or R2SCAN. Available since VASP.6.4.3.
- METAGGA=SREGTM1, SREGTM2, or SREGTM3
- The functionals v1-sregTM, v2-sregTM, and v3-sregTM from Francisco et al.[15]
- METAGGA=SCANL, RSCANL, or R2SCANL
- The functionals SCAN-L[16][17], rSCAN-L, and rSCAN-L[18][19] are deorbitalized versions of SCAN, rSCAN, and rSCAN, respectively. They do not depend on the kinetic-energy density , but on the Laplacian of the density , instead.
- METAGGA=OFR2
- The OFR2[19] functional depends on the Laplacian of the density , but not on the kinetic-energy density .
- METAGGA=SREGTM2L
- The functional v2-sregTM-L from Francisco et al.[20], which depends on the Laplacian of the density , but not on the kinetic-energy density .
- METAGGA=MBJ
- The modified Becke-Johnson (MBJ) potential[21][22] 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 system-dependent constant :
- where is the Becke-Roussel (BR) potential that mimics the Coulomb potential created by the exchange hole[23] and depends on , , and .
- The system-dependent 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 [22]. In Ref. [24], the alternative values , bohr, and were proposed.
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- METAGGA=LMBJ
- The local MBJ (LMBJ) potential[25][26] 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 or an interface mentioned above for MBJ. The LMBJ potential has the same analytical form as the MBJ potential:
- with the difference that is now a position-dependent function:
- where
- with
- The default values of the parameters in LMBJ are (see erratum of Ref. [26]) , 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
Calculations with a meta-GGA that depends on the kinetic-energy density require POTCAR files that include information on the kinetic-energy density of the core electrons. Almost all recent POTCAR files do fulfill this requirement, but there are some notable exceptions like O_GW. 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 energy-density mkinetic energy-density pseudized
and for PAW datasets with partial core corrections:
kinetic energy density (partial)
Mind: For POTCAR files without core electrons (H, He, Li_sv, Be_sv, and _GW variants thereof) the grep command given above will not return the line about pseudized kinetic energy-density, since all electrons are considered as valence. These potentials can nevertheless be used for all meta-GGA functionals.
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LASPH =.TRUE. should be selected if a meta-GGA functional is selected. If LASPH =.FALSE., the one-center contributions are only calculated for a spherically averaged density and kinetic-energy density. This means that the one-center contributions to the Kohn-Sham potential are also spherical. Since the PAW method describes the entire space using plane waves, errors are often small even if the non-spherical contributions to the Kohn-Sham 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 non-spherical around some atoms in your structure, LASPH =.TRUE. must be selected. Non-spherical terms are particularly encountered in d- and f-elements, 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, XC, CMBJ, CMBJA, CMBJB, CMBJE, SMBJ, RSMBJ, LASPH, LMAXTAU, LMIXTAU, LASPH, AMGGAX, AMGGAC, Band-structure calculation using meta-GGA 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://libxc.gitlab.io
- ↑ J. Tao, J. P. Perdew, V. N. Staroverov, and G. E. Scuseria, Climbing the Density Functional Ladder: Nonempirical Meta–Generalized Gradient Approximation Designed for Molecules and Solids, Phys. Rev. Lett. 91, 146401 (2003).
- ↑ J. P. Perdew, A. Ruzsinszky, G. I. Csonka, L. A. Constantin, and J. Sun, Workhorse Semilocal Density Functional for Condensed Matter Physics and Quantum Chemistry, Phys. Rev. Lett. 103, 026403 (2009).
- ↑ 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. Mejía-Rodríguez 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).
- ↑ H. Francisco, A. C. cancio, and S. B. Trickey, Reworking the Tao–Mo exchange-correlation functional. I. Reconsideration and simplification, J. Chem. Phys. 159, 214102 (2023).
- ↑ D. Mejía-Rodríguez and S. B. Trickey, Deorbitalization strategies for meta-generalized-gradient-approximation exchange-correlation functionals, Phys. Rev. A 91, 052512 (2017).
- ↑ D. Mejia-Rodriguez and S. B. Trickey, Deorbitalized meta-GGA exchange-correlation functionals in solids, Phys. Rev. B 98, 115161 (2018).
- ↑ D. Mejía-Rodríguez and S. B. Trickey, Meta-GGA performance in solids at almost GGA cost, Phys. Rev. B 102, 121109(R) (2020).
- ↑ a b A. D. Kaplan and J. P. Perdew, Phys. Rev. Mater. 6, 083803 (2022).
- ↑ H. Francisco, A. C. cancio, and S. B. Trickey, Reworking the Tao–Mo exchange–correlation functional. II. De-orbitalization, J. Chem. Phys. 159, 214103 (2023).
- ↑ 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, Improving the modified Becke-Johnson exchange potential, Phys. Rev. B 85, 155109 (2012).
- ↑ T. Rauch, M. A. L. Marques, and S. Botti, Local Modified Becke-Johnson Exchange-Correlation Potential for Interfaces, Surfaces, and Two-Dimensional Materials, J. Chem. Theory Comput. 16, 2654 (2020).
- ↑ a b T. Rauch, M. A. L. Marques, and S. Botti, Accurate electronic band gaps of two-dimensional materials from the local modified Becke-Johnson potential, Phys. Rev. B 101, 245163 (2020).