Electronic structure theory: Fundamentals to frontiers. 2. Density functional theory

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1 Electronic structure theory: Fundamentals to frontiers. 2. Density functional theory MARTIN HEAD-GORDON, Department of Chemistry, University of California, and Chemical Sciences Division, Lawrence Berkeley National Laboratory Berkeley CA 94720, USA

2 Outline 1. Basics 2. Limitations of standard functionals 3. Range-separated functionals

3 Branches of the family tree Wavefunction-based electronic structure theory: Minimize the energy by varying the wavefunction Tremendously complicated unknown function:! =!( r! 1, r! 2,..., r )! n Modeling the wavefunction yields model chemistries Density functional theory ( ) The unknown is very simple:! =! r! Hohenberg-Kohn theorem guarantees that: E = E! r! True functional is unknown and probably unknowable Modeling the functional gives DFT model chemistries. { ( )}

4 A brief overview of density functional theory First Hohenberg-Kohn theorem (1965): 1:1 mapping between ground state electron densities and Hamiltonians. Proof by contradiction: let H 1 and H 2 have the same ρ(r) E 1! 2 Use Ψ 2 as trial function in H 1 problem Use Ψ 1 as trial function in H 2 problem E { 1! } 2 =! ˆ 2 T + V ˆ! 2 + v 1 " E { 2! } 1 =! ˆ 1 T + Vˆ ee! 1 + v 2 " { } > E 1 E { 2! } 1 > E 2 # dr >! ˆ 1 T + V ˆ! 1 + # v 1 " dr # dr >! ˆ 2 T + Vˆ ee! 2 + # v 2 " dr Contradiction:! 2 ˆ T + ˆ V ee! 2 >! 1 ˆ T + ˆ V ee! 1! 1 ˆ T + ˆ V ee! 1 >! 2 ˆ T + ˆ V ee! 2

5 A brief overview of density functional theory First Hohenberg-Kohn theorem (1965): 1:1 mapping between ground state electron densities and Hamiltonians. Ground state energy E is determined directly from the Hamiltonian Hence E is given in terms of the density, ρ(r). A formal construction exists for the exact functional, E = E! r! Constrained search over all wavefunctions yielding ρ(r) (!!!) So, in practice the functional must be modeled. { ( )} Given a functional, and an external potential (nuclear field) ρ(r) is found by minimizing over allowed densities.

6 Construction of model density functionals To model kinetic, exchange, correlation functionals 1A) Find a model problem where the functional can be obtained H atom? Uniform electron gas? 1B) Assume a form for the functional and fix the parameters by Known exact conditions (e.g. get model problems right) Minimizing the errors on known data

7 2) Transfer the functional to problems of interest Test, test, test. If validation is encouraging enough, predict In one of your problems, you will extract the kinetic energy functional that solves the uniform electron gas problem. It is not much more difficult to extract the corresponding exchange functional. These are the main ingredients of the Thomas-Fermi model which is a Hohenberg-Kohn density functional.

8 Kohn-Sham density functional theory Largest (unknown) energy contribution is the kinetic energy. No satisfactory kinetic energy functional yet exists. Kohn-Sham framework (a beautiful sidestep): Use the kinetic energy of a non-interacting system with the same electron density (a Hartree-Fock type wavefunction). Leaves exchange and electron correlation (XC) to specify. Kohn-Sham computational cost: similar to Hartree-Fock. Still cheap enough to apply to large systems.

9 Modern Kohn-Sham density functionals Local density approximation (LDA): 1960 s, 1970 s Functional depends only on the density at each point, ρ(r) LDA overbinds as much as Hartree-Fock (mean field) underbinds! Generalized gradient approximations (GGA s): 1988 Functional depends on density ρ(r) and its gradients at each r Greatly improved results! 4-6 kcal/mol error for BLYP, PBE etc. Exact exchange mixing (adiabatic connection): 1992 Mix some Hartree-Fock exchange with GGA s (Becke) Best yet! 2-3 kcal/mol error for B3LYP

10 Classes of Kohn-Sham density functionals Local spin density approx 1966 E XC = { ( )} " dr! XC # r Example: SVWN G3/99 test set Generalized gradient approx 1985 E XC = " dr! XC #( r),$# r Example: BLYP { ( )} Hybrid density functionals 1993 Wave function exchange Example: B3LYP 223 atomization energies Mean abs errors (kcal/mol)

11 Multiple choice questions. In Kohn-Sham DFT, which energy contribution is not strictly a functional of the electron density? (a) electron-nuclear attraction (b) exchange-correlation (c) kinetic energy Which of the following properties is obeyed by B3LYP? (a) variationality (b) exact for the uniform electron gas (c) exact for 1-electron systems (d) size-consistency

12 Outline 1. Basics 2. Limitations of standard functionals 3. Range-separated functionals

13 Challenges for density functionals Accuracy: lack of systematic improvability confronts (1) Limitations of the exchange functional Self-interaction (2) Limitations of the correlation functional London forces Strong correlations

14 B3LYP dissociation of H 2 + (0.65Å to 3Å) 0 relative energy (kcal/mol) HF B3LYP 0.65Å 3Å

15 B3LYP dissociation of H 2 + (3Å to 13Å) 0 relative energy (kcal/mol) HF B3LYP 3Å 13Å

16 Alkali halide dissociation curves B3LYP products have fractional charges -- due to electronegativity difference

17 Charge transfer states in time-dependent DFT! CT ( r) " IP ZnBC + EA BC # 1 / R " 2.7eV BLYP/6-31G* CT states are too low & lack Coulomb attraction!

18 Importance of long-range exact exchange Ground state potential energy surfaces Diatomic cation dissociation problem (H 2+, Ar 2+, etc) Barrier height problems: generally too low Electrons tend to be too delocalized Charge-transfer excited states D-A Coulomb attraction is missing! Magnitude of CT states is greatly underestimated Contaminates the TDDFT spectrum of large molecules

19 Reducing self-interaction: Range-separation long-range exchange via erf(ωr) erf(ωr): long-range. Do exactly. erfc(ωr): short-range. Do GGA. 1 r 12 = erfc(! r 12 ) r 12 + erf (! r 12 ) r 12 Key contributions: Savin (1996): concept Gill et al (1996): solved short-range LSDA exchange Hirao et al (2001): long-range corrected (LC) functional Handy, Gerber & Angyan, Scuseria, Perdew, Yang, One can view this as justified within a generalized Kohn-Sham framework, or via adiabatic connection.

20 Dispersive effects: e.g. supramolecular interactions fullerene-porphyrin dimer binding is 31 kcal/mol GGA s give little or no binding energy Y. Jung, MHG, Phys. Chem. Chem. Phys. 8, 2831 (2006)

21 Recovering Van der Waals interactions: Empirical dispersion (-D) corrections Additional non-local correlation energy contribution: E disp =! atoms ij C 6 " f damp R ij i< j R ij 6 ( ) C 6 ij = C i j 6 C 6 f damp = " # 1+ a(r ij / R r )!12 C 6 i are atomic C 6 factors; f damps at short-range Greatly improves dispersion-dominated interactions: R. Ahlrichs, R. Penco, G. Scoles, Chem. Phys. 19, 119 (1977) Q. Wu and W.T. Yang, J. Chem. Phys. 116, 515 (2002) S. Grimme, J. Comput. Chem. 25, 1463 (2004); 27, 1787 (2006) Not actually a density functional, but... Computationally free Physically reasonable (but double counting problem)!1 $ %

22 Recovering Van der Waals interactions: Double hybrid functionals (assigned paper) Gorling-Levy perturbation theory motivates mixing 2nd order perturbation theory (for correlation) with semilocal correlation functionals... Physically, PT2 includes non-local long-range correlation that is missing in semilocal functionals... But, there is again a double counting problem...

23 Strongly correlated molecules Cope rearrangement Oxygen-evolving complex: Mn4O4

24 No easy answers for strong correlations... Either requires a tremendously powerful correlation functional, or,... lies beyond generalized Kohn-Sham theory. For instance using a multi-configuration reference wave-function... While this is an important challenge, it is one that is not yet satisfactorily answered today...

25 Outline 1. Basics 2. Limitations of standard functionals 3. Range-separated functionals

26 Functional ingredients... and parameters... B97 XC density functional: 12 linear parameters (M=4) E B97 =! LSDA dr " # M ( j =0 c j # $ % ( ) f s # 2 s! = "#! / #! 4 /3 Long-range exact exchange: 1 non-linear parameter (ω) E X LR! HF =! 1 2 % ij dr 1 " # i r 1 ( )# j r 1 & ' j erf ( $r ( ) dr 12 ) 2 " # i ( r 2 )# j r 2 r 12 ( ) Short-range exact exchange: 1 linear parameter (cx) E X SR! HF =! c X 2 % ij dr 1 " # i r 1 ( )# j r 1 erfc ( $r ( ) dr 12 ) 2 " # i ( r 2 )# j r 2 r 12 ( )

27 2 types of non-local correlation corrections Empirical atom-atom dispersion (-D): 1 parameter (a) E disp =! atoms ij C 6 " f damp R ij i< j R ij 6 ( ) C 6 ij = C i j 6 C 6 f damp = " # 1+ a(r ij / R r )!12 Similar to R. Ahlrichs, W.T. Yang, S. Grimme... Computational cost is zero, but not a density functional!1 $ % Or: Double hybrid perturbation theory: 2 parameters E PT 2 = c OS E (2) OS + c SS E SS (2) Includes effect of unoccupied orbitals Significantly more computational expense

28 4 long-range corrected B97 functionals (Jeng-Da Chai) ωb97: 100% long-range exact exchange (13 parameters)! E B97 LR" XC = E HF SR" X + E B97 B97 X + E C ωb97x: adds some short-range exact exchange (14)! B97 E X LR" XC = E HF SR" X + c X E HF SR" X + E B97 B97 X + E C ωb97x-d: adds empirical dispersion (15)! B97 X " E D LR" XC = E HF SR" X + c X E HF SR" X + E B97 X + E B97 disp C + E C ωb97x-2: adds non-local second order correlation (16)! B97 X E "2 LR" XC = E HF SR" X + c X E HF SR" X + E B97 X + E B97 PT 2 C + E C

29 Why must these functionals be trained? All parameters should be determined self-consistently... subject to constraints that preserve the LDA limit hence cannot adopt existing B97 values For ωb97 and ωb97x: GGA parameters: short-range exchange; semi-local correlation Range separator: compromise across problems of interest For ωb97x-d: Additionally minimize the correlation double-counting error

30 Training set: 412 data points (Jeng-Da Chai) Bond-breaking energies: G3/99 dataset (296) Curtiss, Raghavachari, Redfern, Pople, JCP 112, 7374 (2000) Barrier heights for simple chemical reactions (76) Zhao, Truhlar et al, JPC A 108, 2715 (2005), 109, 2012 (2006) Non-covalent interactions (22) Jurecka, Sponer, Cerny, Hobza, PCCP 8, 1985 (2006) Absolute atomic energies (18) Chakravorty, Gwaltney, Davidson, Parpia, Fischer, PR A 47, 3649 (1993)

31 Comparison of optimizable functionals: All trained identically (Jeng-Da Chai) HCTH*: 12 parameter GGA (like ωb97 with ω=0) B97*: 13 parameter hybrid (like ωb97x with ω=0) ωb97: 13 parameter range-separated. ω opt =0.4 ωb97x: 14 parameter range-separated hybrid ω opt =0.3, c X =0.16 ωb97x-d: 15 parameter, with dispersion ω opt = 0.2, c X = 0.22 All are exact for the uniform electron gas (constraints)... What is the value of range separation? And dispersion?

32 223 G3/99 atomization energies (Jeng-Da Chai) Training set data range-separated family hybrid GGA

33 38 non-hydrogen transfer barriers (Jeng-Da Chai) Training set data range-separated family hybrid GGA

34 22 intermolecular interactions (Jeng-Da Chai) Training set data range-separated family hybrid GGA

35 Test performance for energies (Jeng-Da Chai) Test set data

36 Alanine tetrapeptide conformational energies Compare against basis set limit MP2 27 conformations Calculations by Daniel Lambrecht

37 Conclusions and open issues For molecular problems, particularly where selfinteraction is significant, range-separated functionals are a significant improvement over hybrids ωb97, ωb97x, and ωb97x-d are widely useful though significant weaknesses remain... and further testing & comparison is desirable (e.g. vs M06) Challenges include strong correlation (unresolved) can self-interaction can be further reduced? increased exact exchange degrades performance for metals *

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