**Density functional theory** (**DFT**) is a computational quantum mechanical modelling method used in physics, chemistry and materials science to investigate the electronic structure (principally the ground state) of many-body systems, in particular atoms, molecules, and the condensed phases. Using this theory, the properties of a many-electron system can be determined by using functionals, i.e. functions of another function, which in this case is the spatially dependent electron density. Hence the name density functional theory comes from the use of functionals of the electron density. DFT is among the most popular and versatile methods available in condensed-matter physics, computational physics, and computational chemistry.

DFT has been very popular for calculations in solid-state physics since the 1970s. However, DFT was not considered accurate enough for calculations in quantum chemistry until the 1990s, when the approximations used in the theory were greatly refined to better model the exchange and correlation interactions. Computational costs are relatively low when compared to traditional methods, such as exchange only Hartree–Fock theory and its descendants that include electron correlation.

Despite recent improvements, there are still difficulties in using density functional theory to properly describe: intermolecular interactions (of critical importance to understanding chemical reactions), especially van der Waals forces (dispersion); charge transfer excitations; transition states, global potential energy surfaces, dopant interactions and some strongly correlated systems; and in calculations of the band gap and ferromagnetism in semiconductors.^{[1]} The incomplete treatment of dispersion can adversely affect the accuracy of DFT (at least when used alone and uncorrected) in the treatment of systems which are dominated by dispersion (e.g. interacting noble gas atoms)^{[2]} or where dispersion competes significantly with other effects (e.g. in biomolecules).^{[3]} The development of new DFT methods designed to overcome this problem, by alterations to the functional^{[4]} or by the inclusion of additive terms,^{[5]}^{[6]}^{[7]}^{[8]} is a current research topic.

In the context of computational materials science, *ab initio* (from first principles) DFT calculations allow the prediction and calculation of material behaviour on the basis of quantum mechanical considerations, without requiring higher order parameters such as fundamental material properties. In contemporary DFT techniques the electronic structure is evaluated using a potential acting on the system’s electrons. This DFT potential is constructed as the sum of external potentials *V*_{ext}, which is determined solely by the structure and the elemental composition of the system, and an effective potential *V*_{eff}, which represents interelectronic interactions. Thus, a problem for a representative supercell of a material with *n* electrons can be studied as a set of *n* one-electron Schrödinger-like equations, which are also known as Kohn–Sham equations.^{[9]}

Although density functional theory has its roots in the Thomas–Fermi model for the electronic structure of materials, DFT was first put on a firm theoretical footing by Walter Kohn and Pierre Hohenberg in the framework of the two **Hohenberg–Kohn theorems** (H–K).^{[10]} The original H–K theorems held only for non-degenerate ground states in the absence of a magnetic field, although they have since been generalized to encompass these.^{[11]}^{[12]}

The first H–K theorem demonstrates that the ground state properties of a many-electron system are uniquely determined by an electron density that depends on only three spatial coordinates. It set down the groundwork for reducing the many-body problem of *N* electrons with 3*N* spatial coordinates to three spatial coordinates, through the use of functionals of the electron density. This theorem has since been extended to the time-dependent domain to develop time-dependent density functional theory (TDDFT), which can be used to describe excited states.

The second H–K theorem defines an energy functional for the system and proves that the correct ground state electron density minimizes this energy functional.

In work that later won them the Nobel prize in chemistry, The H–K theorem was further developed by Walter Kohn and Lu Jeu Sham to produce Kohn–Sham DFT (KS DFT). Within this framework, the intractable many-body problem of interacting electrons in a static external potential is reduced to a tractable problem of noninteracting electrons moving in an effective potential. The effective potential includes the external potential and the effects of the Coulomb interactions between the electrons, e.g., the exchange and correlation interactions. Modeling the latter two interactions becomes the difficulty within KS DFT. The simplest approximation is the local-density approximation (LDA), which is based upon exact exchange energy for a uniform electron gas, which can be obtained from the Thomas–Fermi model, and from fits to the correlation energy for a uniform electron gas. Non-interacting systems are relatively easy to solve as the wavefunction can be represented as a Slater determinant of orbitals. Further, the kinetic energy functional of such a system is known exactly. The exchange–correlation part of the total energy functional remains unknown and must be approximated.

Another approach, less popular than KS DFT but arguably more closely related to the spirit of the original H–K theorems, is orbital-free density functional theory (OFDFT), in which approximate functionals are also used for the kinetic energy of the noninteracting system.

As usual in many-body electronic structure calculations, the nuclei of the treated molecules or clusters are seen as fixed (the Born–Oppenheimer approximation), generating a static external potential *V* in which the electrons are moving. A stationary electronic state is then described by a wavefunction Ψ(*r*_{1}→,…,*r _{N}*→) satisfying the many-electron time-independent Schrödinger equation

where, for the *N*-electron system, *Ĥ* is the Hamiltonian, *E* is the total energy, *T̂* is the kinetic energy, *V̂* is the potential energy from the external field due to positively charged nuclei, and *Û* is the electron–electron interaction energy. The operators *T̂* and *Û* are called universal operators as they are the same for any *N*-electron system, while *V̂* is system-dependent. This complicated many-particle equation is not separable into simpler single-particle equations because of the interaction term *Û*.

There are many sophisticated methods for solving the many-body Schrödinger equation based on the expansion of the wavefunction in Slater determinants. While the simplest one is the Hartree–Fock method, more sophisticated approaches are usually categorized as post-Hartree–Fock methods. However, the problem with these methods is the huge computational effort, which makes it virtually impossible to apply them efficiently to larger, more complex systems.

Here DFT provides an appealing alternative, being much more versatile as it provides a way to systematically map the many-body problem, with *Û*, onto a single-body problem without *Û*. In DFT the key variable is the electron density *n*(*r*→), which for a normalized Ψ is given by

This relation can be reversed, i.e., for a given ground-state density *n*_{0}(*r*→) it is possible, in principle, to calculate the corresponding ground-state wavefunction Ψ_{0}(*r*_{1}→,…,*r _{N}*→). In other words, Ψ is a unique functional of

and consequently the ground-state expectation value of an observable *Ô* is also a functional of *n*_{0}

In particular, the ground-state energy is a functional of *n*_{0}

where the contribution of the external potential ⟨ Ψ[*n*_{0}] | *V̂* | Ψ[*n*_{0}] ⟩ can be written explicitly in terms of the ground-state density *n*_{0}

More generally, the contribution of the external potential ⟨ Ψ | *V̂* | Ψ ⟩ can be written explicitly in terms of the density *n*,

The functionals *T*[*n*] and *U*[*n*] are called universal functionals, while *V*[*n*] is called a non-universal functional, as it depends on the system under study. Having specified a system, i.e., having specified *V̂*, one then has to minimize the functional

with respect to *n*(*r*→), assuming one has reliable expressions for *T*[*n*] and *U*[*n*]. A successful minimization of the energy functional will yield the ground-state density *n*_{0} and thus all other ground-state observables.

The variational problems of minimizing the energy functional *E*[*n*] can be solved by applying the Lagrangian method of undetermined multipliers.^{[13]} First, one considers an energy functional that does not explicitly have an electron–electron interaction energy term,

where *T̂* denotes the kinetic energy operator and *V̂*_{s} is an external effective potential in which the particles are moving, so that *n*_{s}(*r*→) ≝ *n*(*r*→).

Thus, one can solve the so-called Kohn–Sham equations of this auxiliary noninteracting system,

which yields the orbitals *φ _{i}* that reproduce the density

The effective single-particle potential can be written in more detail as

where the second term denotes the so-called Hartree term describing the electron–electron Coulomb repulsion, while the last term *V*_{XC} is called the exchange–correlation potential. Here, *V*_{XC} includes all the many-particle interactions. Since the Hartree term and *V*_{XC} depend on *n*(*r*→), which depends on the *φ _{i}*, which in turn depend on

**Notes**

- The one-to-one correspondence between electron density and single-particle potential is not so smooth. It contains kinds of non-analytic structure.
*E*_{s}[*n*] contains kinds of singularities, cuts and branches. This may indicate a limitation of our hope for representing exchange–correlation functional in a simple analytic form. - It is possible to extend the DFT idea to the case of the Green function
*G*instead of the density*n*. It is called as Luttinger–Ward functional (or kinds of similar functionals), written as*E*[*G*]. However,*G*is determined not as its minimum, but as its extremum. Thus we may have some theoretical and practical difficulties. - There is no one-to-one correspondence between one-body density matrix
*n*(*r*→,*r*′→) and the one-body potential*V*(*r*→,*r*′→). (Remember that all the eigenvalues of*n*(*r*→,*r*′→) are 1.) In other words, it ends up with a theory similar to the Hartree–Fock (or hybrid) theory.

The same theorems can be proven in the case of relativistic electrons, thereby providing generalization of DFT for the relativistic case. Unlike the nonrelativistic theory, in the relativistic case it is possible to derive a few exact and explicit formulas for the relativistic density functional.

Let one consider an electron in a hydrogen-like ion obeying the relativistic Dirac equation. The Hamiltonian *H* for a relativistic electron moving in the Coulomb potential can be chosen in the following form (atomic units are used):

where *V* = −*eZ*/*r* is the Coulomb potential of a pointlike nucleus, *p*→ is a momentum operator of the electron, and *e*, *m* and *c* are the elementary charge, electron mass and the speed of light respectively, and finally *α*→ and *β* are a set of Dirac 2 × 2 matrices:

To find out the eigenfunctions and corresponding energies, one solves the eigenfunction equation

where Ψ = (Ψ(1), Ψ(2), Ψ(3), Ψ(4))^{T} is a four-component wavefunction and *E* is the associated eigenenergy. It is demonstrated in Brack (1983)^{[14]} that application of the virial theorem to the eigenfunction equation produces the following formula for the eigenenergy of any bound state:

and analogously, the virial theorem applied to the eigenfunction equation with the square of the Hamiltonian^{[15]} yields

- .

It is easy to see that both of the above formulae represent density functionals. The former formula can be easily generalized for the multi-electron case.^{[16]}

The major problem with DFT is that the exact functionals for exchange and correlation are not known except for the free electron gas. However, approximations exist which permit the calculation of certain physical quantities quite accurately.^{[17]} In physics the most widely used approximation is the local-density approximation (LDA), where the functional depends only on the density at the coordinate where the functional is evaluated:

The local spin-density approximation (LSDA) is a straightforward generalization of the LDA to include electron spin:

In LDA, the exchange–correlation energy is typically separated into the exchange part and the correlation part: *ε*_{XC} = *ε*_{X} + *ε*_{C}. The exchange part is called the Dirac (or sometimes Slater) exchange which takes the form *ε*_{X} ∝ *n*^{1⁄3}. There are, however, many mathematical forms for the correlation part. Highly accurate formulae for the correlation energy density *ε*_{C}(*n*_{↑},*n*_{↓}) have been constructed from quantum Monte Carlo simulations of jellium.^{[18]} A simple first-principles correlation functional has been recently proposed as well.^{[19]}^{[20]} Although unrelated to the Monte Carlo simulation, the two variants provide comparable accuracy.^{[21]}

The LDA assumes that the density is the same everywhere. Because of this, the LDA has a tendency to underestimate the exchange energy and over-estimate the correlation energy.^{[22]} The errors due to the exchange and correlation parts tend to compensate each other to a certain degree. To correct for this tendency, it is common to expand in terms of the gradient of the density in order to account for the non-homogeneity of the true electron density. This allows for corrections based on the changes in density away from the coordinate. These expansions are referred to as generalized gradient approximations (GGA)^{[23]}^{[24]}^{[25]} and have the following form:

Using the latter (GGA), very good results for molecular geometries and ground-state energies have been achieved.

Potentially more accurate than the GGA functionals are the meta-GGA functionals, a natural development after the GGA (generalized gradient approximation). Meta-GGA DFT functional in its original form includes the second derivative of the electron density (the Laplacian) whereas GGA includes only the density and its first derivative in the exchange–correlation potential.

Functionals of this type are, for example, TPSS and the Minnesota Functionals. These functionals include a further term in the expansion, depending on the density, the gradient of the density and the Laplacian (second derivative) of the density.

Difficulties in expressing the exchange part of the energy can be relieved by including a component of the exact exchange energy calculated from Hartree–Fock theory. Functionals of this type are known as hybrid functionals.

The DFT formalism described above breaks down, to various degrees, in the presence of a vector potential, i.e. a magnetic field. In such a situation, the one-to-one mapping between the ground-state electron density and wavefunction is lost. Generalizations to include the effects of magnetic fields have led to two different theories: current density functional theory (CDFT) and magnetic field density functional theory (BDFT). In both these theories, the functional used for the exchange and correlation must be generalized to include more than just the electron density. In current density functional theory, developed by Vignale and Rasolt,^{[12]} the functionals become dependent on both the electron density and the paramagnetic current density. In magnetic field density functional theory, developed by Salsbury, Grayce and Harris,^{[26]} the functionals depend on the electron density and the magnetic field, and the functional form can depend on the form of the magnetic field. In both of these theories it has been difficult to develop functionals beyond their equivalent to LDA, which are also readily implementable computationally.
Recently an extension by Pan and Sahni^{[27]} extended the Hohenberg–Kohn theorem for varying magnetic fields using the density and the current density as fundamental variables.

In general, density functional theory finds increasingly broad application in the chemical and materials sciences for the interpretation and prediction of complex system behavior at an atomic scale. Specifically, DFT computational methods are applied for the study of systems to synthesis and processing parameters. In such systems, experimental studies are often encumbered by inconsistent results and non-equilibrium conditions. Examples of contemporary DFT applications include studying the effects of dopants on phase transformation behavior in oxides, magnetic behaviour in dilute magnetic semiconductor materials and the study of magnetic and electronic behavior in ferroelectrics and dilute magnetic semiconductors.^{[1]}^{[28]} Also, it has been shown that DFT has a good results in the prediction of sensitivity of some nanostructures to environment pollutants like sulfur dioxide^{[29]} or acrolein^{[30]} as well as prediction of mechanical properties.^{[31]}

In practice, Kohn–Sham theory can be applied in several distinct ways depending on what is being investigated. In solid state calculations, the local density approximations are still commonly used along with plane wave basis sets, as an electron gas approach is more appropriate for electrons delocalised through an infinite solid. In molecular calculations, however, more sophisticated functionals are needed, and a huge variety of exchange–correlation functionals have been developed for chemical applications. Some of these are inconsistent with the uniform electron gas approximation, however, they must reduce to LDA in the electron gas limit. Among physicists, probably the most widely used functional is the revised Perdew–Burke–Ernzerhof exchange model (a direct generalized gradient parametrization of the free electron gas with no free parameters); however, this is not sufficiently calorimetrically accurate for gas-phase molecular calculations. In the chemistry community, one popular functional is known as BLYP (from the name Becke for the exchange part and Lee, Yang and Parr for the correlation part). Even more widely used is B3LYP which is a hybrid functional in which the exchange energy, in this case from Becke's exchange functional, is combined with the exact energy from Hartree–Fock theory. Along with the component exchange and correlation funсtionals, three parameters define the hybrid functional, specifying how much of the exact exchange is mixed in. The adjustable parameters in hybrid functionals are generally fitted to a 'training set' of molecules. Unfortunately, although the results obtained with these functionals are usually sufficiently accurate for most applications, there is no systematic way of improving them (in contrast to some of the traditional wavefunction-based methods like configuration interaction or coupled cluster theory). Hence in the current DFT approach it is not possible to estimate the error of the calculations without comparing them to other methods or experiments.

The predecessor to density functional theory was the **Thomas–Fermi model**, developed independently by both Thomas and Fermi in 1927. They used a statistical model to approximate the distribution of electrons in an atom. The mathematical basis postulated that electrons are distributed uniformly in phase space with two electrons in every *h*^{3} of volume.^{[32]} For each element of coordinate space volume d^{3}*r* we can fill out a sphere of momentum space up to the Fermi momentum *p*_{f}^{[33]}

Equating the number of electrons in coordinate space to that in phase space gives:

Solving for *p*_{f} and substituting into the classical kinetic energy formula then leads directly to a kinetic energy represented as a functional of the electron density:

where

As such, they were able to calculate the energy of an atom using this kinetic energy functional combined with the classical expressions for the nucleus–electron and electron–electron interactions (which can both also be represented in terms of the electron density).

Although this was an important first step, the Thomas–Fermi equation's accuracy is limited because the resulting kinetic energy functional is only approximate, and because the method does not attempt to represent the exchange energy of an atom as a conclusion of the Pauli principle. An exchange energy functional was added by Dirac in 1928.

However, the Thomas–Fermi–Dirac theory remained rather inaccurate for most applications. The largest source of error was in the representation of the kinetic energy, followed by the errors in the exchange energy, and due to the complete neglect of electron correlation.

Teller (1962) showed that Thomas–Fermi theory cannot describe molecular bonding. This can be overcome by improving the kinetic energy functional.

The kinetic energy functional can be improved by adding the Weizsäcker (1935) correction:^{[34]}^{[35]}

The Hohenberg–Kohn theorems relate to any system consisting of electrons moving under the influence of an external potential.

**Theorem 1.**The external potential (and hence the total energy), is a unique functional of the electron density.

- If two systems of electrons, one trapped in a potential
*v*_{1}(*r*→) and the other in*v*_{2}(*r*→), have the same ground-state density*n*(*r*→) then*v*_{1}(*r*→) −*v*_{2}(*r*→) is necessarily a constant.

- If two systems of electrons, one trapped in a potential

**Corollary:**the ground state density uniquely determines the potential and thus all properties of the system, including the many-body wavefunction. In particular, the H–K functional, defined as*F*[*n*] =*T*[*n*] +*U*[*n*], is a universal functional of the density (not depending explicitly on the external potential).

**Theorem 2.**The functional that delivers the ground state energy of the system gives the lowest energy if and only if the input density is the true ground state density.

- For any positive integer
*N*and potential*v*(*r*→), a density functional*F*[*n*] exists such that - obtains its minimal value at the ground-state density of
*N*electrons in the potential*v*(*r*)→. The minimal value of*E*_{(v,N)}[*n*] is then the ground state energy of this system.

- For any positive integer

The many-electron Schrödinger equation can be very much simplified if electrons are divided in two groups: valence electrons and inner core electrons. The electrons in the inner shells are strongly bound and do not play a significant role in the chemical binding of atoms; they also partially screen the nucleus, thus forming with the nucleus an almost inert core. Binding properties are almost completely due to the valence electrons, especially in metals and semiconductors. This separation suggests that inner electrons can be ignored in a large number of cases, thereby reducing the atom to an ionic core that interacts with the valence electrons. The use of an effective interaction, a pseudopotential, that approximates the potential felt by the valence electrons, was first proposed by Fermi in 1934 and Hellmann in 1935. In spite of the simplification pseudo-potentials introduce in calculations, they remained forgotten until the late 1950s.

A crucial step toward more realistic pseudo-potentials was given by Topp and Hopfield^{[36]} and more recently Cronin, who suggested that the pseudo-potential should be adjusted such that they describe the valence charge density accurately. Based on that idea, modern pseudo-potentials are obtained inverting the free atom Schrödinger equation for a given reference electronic configuration and forcing the pseudo-wavefunctions to coincide with the true valence wave functions beyond a certain distance *rl*. The pseudo-wavefunctions are also forced to have the same norm as the true valence wavefunctions and can be written as

where *R _{l}*(

The electrons of a system will occupy the lowest Kohn–Sham eigenstates up to a given energy level according to the Aufbau principle. This corresponds to the steplike Fermi–Dirac distribution at absolute zero. If there are several degenerate or close to degenerate eigenstates at the Fermi level, it is possible to get convergence problems, since very small perturbations may change the electron occupation. One way of damping these oscillations is to *smear* the electrons, i.e. allowing fractional occupancies.^{[37]} One approach of doing this is to assign a finite temperature to the electron Fermi–Dirac distribution. Other ways is to assign a cumulative Gaussian distribution of the electrons or using a Methfessel–Paxton method.^{[38]}^{[39]}

DFT is supported by many quantum chemistry and solid state physics software packages, often along with other methods.

- Basis set (chemistry)
- Dynamical mean field theory
- Gas in a box
- Harris functional
- Helium atom
- Kohn–Sham equations
- Local density approximation
- Molecule
- Molecular design software
- Molecular modelling
- Quantum chemistry
- Thomas–Fermi model
- Time-dependent density functional theory
- Car–Parrinello molecular dynamics

- List of quantum chemistry and solid state physics software
- List of software for molecular mechanics modeling

- ^
^{a}^{b}Assadi, M. H. N.; et al. (2013). "Theoretical study on copper's energetics and magnetism in TiO_{2}polymorphs".*Journal of Applied Physics*.**113**(23): 233913–233913–5. arXiv:1304.1854. Bibcode:2013JAP...113w3913A. doi:10.1063/1.4811539. **^**Van Mourik, Tanja; Gdanitz, Robert J. (2002). "A critical note on density functional theory studies on rare-gas dimers".*Journal of Chemical Physics*.**116**(22): 9620–9623. Bibcode:2002JChPh.116.9620V. doi:10.1063/1.1476010.**^**Vondrášek, Jiří; Bendová, Lada; Klusák, Vojtěch; Hobza, Pavel (2005). "Unexpectedly strong energy stabilization inside the hydrophobic core of small protein rubredoxin mediated by aromatic residues: correlated ab initio quantum chemical calculations".*Journal of the American Chemical Society*.**127**(8): 2615–2619. doi:10.1021/ja044607h. PMID 15725017.**^**Grimme, Stefan (2006). "Semiempirical hybrid density functional with perturbative second-order correlation".*Journal of Chemical Physics*.**124**(3): 034108. Bibcode:2006JChPh.124c4108G. doi:10.1063/1.2148954. PMID 16438568.**^**Zimmerli, Urs; Parrinello, Michele; Koumoutsakos, Petros (2004). "Dispersion corrections to density functionals for water aromatic interactions".*Journal of Chemical Physics*.**120**(6): 2693–2699. Bibcode:2004JChPh.120.2693Z. doi:10.1063/1.1637034. PMID 15268413.**^**Grimme, Stefan (2004). "Accurate description of van der Waals complexes by density functional theory including empirical corrections".*Journal of Computational Chemistry*.**25**(12): 1463–1473. doi:10.1002/jcc.20078. PMID 15224390.**^**Von Lilienfeld, O. Anatole; Tavernelli, Ivano; Rothlisberger, Ursula; Sebastiani, Daniel (2004). "Optimization of effective atom centered potentials for London dispersion forces in density functional theory" (PDF).*Physical Review Letters*.**93**(15): 153004. Bibcode:2004PhRvL..93o3004V. doi:10.1103/PhysRevLett.93.153004. PMID 15524874.**^**Tkatchenko, Alexandre; Scheffler, Matthias (2009). "Accurate Molecular Van Der Waals Interactions from Ground-State Electron Density and Free-Atom Reference Data".*Physical Review Letters*.**102**(7): 073005. Bibcode:2009PhRvL.102g3005T. doi:10.1103/PhysRevLett.102.073005. PMID 19257665.**^**Hanaor, D. A. H.; Assadi, M. H. N.; Li, S.; Yu, A.; Sorrell, C. C. (2012). "*Ab initio*study of phase stability in doped TiO_{2}".*Computational Mechanics*.**50**(2): 185–194. arXiv:1210.7555. Bibcode:2012CompM..50..185H. doi:10.1007/s00466-012-0728-4.- ^
^{a}^{b}Hohenberg, Pierre; Walter, Kohn (1964). "Inhomogeneous electron gas".*Physical Review*.**136**(3B): B864–B871. Bibcode:1964PhRv..136..864H. doi:10.1103/PhysRev.136.B864. **^**Levy, Mel (1979). "Universal variational functionals of electron densities, first-order density matrices, and natural spin-orbitals and solution of the*v*-representability problem".*Proceedings of the National Academy of Sciences*.**76**(12): 6062–6065. Bibcode:1979PNAS...76.6062L. doi:10.1073/pnas.76.12.6062. PMC 411802. PMID 16592733.- ^
^{a}^{b}Vignale, G.; Rasolt, Mark (1987). "Density-functional theory in strong magnetic fields".*Physical Review Letters*.**59**(20): 2360–2363. Bibcode:1987PhRvL..59.2360V. doi:10.1103/PhysRevLett.59.2360. PMID 10035523. **^**Kohn, W.; Sham, L. J. (1965). "Self-consistent equations including exchange and correlation effects".*Physical Review*.**140**(4A): A1133–A1138. Bibcode:1965PhRv..140.1133K. doi:10.1103/PhysRev.140.A1133.**^**Brack, M. (1983). "Virial theorems for relativistic spin-^{1}⁄_{2}and spin-0 particles" (PDF).*Physical Review D*.**27**(8): 1950. Bibcode:1983PhRvD..27.1950B. doi:10.1103/physrevd.27.1950.**^**Koshelev, K. (2015). "About density functional theory interpretation". arXiv:0812.2919 [quant-ph].**^**Koshelev, K. (2007). "Alpha variation problem and*q*-factor definition". arXiv:0707.1146 [physics.atom-ph].**^**Burke, Kieron; Wagner, Lucas O. (2013). "DFT in a nutshell".*International Journal of Quantum Chemistry*.**113**(2): 96. doi:10.1002/qua.24259.**^**Perdew, John P.; Ruzsinszky, Adrienn; Tao, Jianmin; Staroverov, Viktor N.; Scuseria, Gustavo; Csonka, Gábor I. (2005). "Prescriptions for the design and selection of density functional approximations: More constraint satisfaction with fewer fits".*Journal of Chemical Physics*.**123**(6): 062201. Bibcode:2005JChPh.123f2201P. doi:10.1063/1.1904565. PMID 16122287.**^**Chachiyo, Teepanis (2016). "Communication: Simple and accurate uniform electron gas correlation energy for the full range of densities".*Journal of Chemical Physics*.**145**(2): 021101. Bibcode:2016JChPh.145b1101C. doi:10.1063/1.4958669. PMID 27421388.**^**Fitzgerald, Richard J. (2016). "A simpler ingredient for a complex calculation".*Physics Today*.**69**(9): 20. Bibcode:2016PhT....69i..20F. doi:10.1063/PT.3.3288.**^**Jitropas, Ukrit; Hsu, Chung-Hao (2017). "Study of the first-principles correlation functional in the calculation of silicon phonon dispersion curves".*Japanese Journal of Applied Physics*.**56**(7): 070313. Bibcode:2017JaJAP..56g0313J. doi:10.7567/JJAP.56.070313.**^**Becke, Axel D. (2014-05-14). "Perspective: Fifty years of density-functional theory in chemical physics".*The Journal of Chemical Physics*.**140**(18): A301. Bibcode:2014JChPh.140rA301B. doi:10.1063/1.4869598. ISSN 0021-9606. PMID 24832308.**^**Perdew, John P.; Chevary, J. A.; Vosko, S. H.; Jackson, Koblar A.; Pederson, Mark R.; Singh, D. J.; Fiolhais, Carlos (1992). "Atoms, molecules, solids, and surfaces: Applications of the generalized gradient approximation for exchange and correlation".*Physical Review B*.**46**(11): 6671. Bibcode:1992PhRvB..46.6671P. doi:10.1103/physrevb.46.6671. hdl:10316/2535.**^**Becke, Axel D. (1988). "Density-functional exchange-energy approximation with correct asymptotic behavior".*Physical Review A*.**38**(6): 3098–3100. Bibcode:1988PhRvA..38.3098B. doi:10.1103/physreva.38.3098. PMID 9900728.**^**Langreth, David C; Mehl, M J (1983). "Beyond the local-density approximation in calculations of ground-state electronic properties".*Physical Review B*.**28**(4): 1809. Bibcode:1983PhRvB..28.1809L. doi:10.1103/physrevb.28.1809.**^**Grayce, Christopher; Harris, Robert (1994). "Magnetic-field density-functional theory".*Physical Review A*.**50**(4): 3089–3095. Bibcode:1994PhRvA..50.3089G. doi:10.1103/PhysRevA.50.3089. PMID 9911249.**^**Viraht, Xiao-Yin (2012). "Hohenberg–Kohn theorem including electron spin".*Physical Review A*.**86**(4): 042502. Bibcode:2012PhRvA..86d2502P. doi:10.1103/physreva.86.042502.**^**Segall, M. D.; Lindan, P. J. (2002). "First-principles simulation: ideas, illustrations and the CASTEP code".*Journal of Physics: Condensed Matter*.**14**(11): 2717. Bibcode:2002JPCM...14.2717S. CiteSeerX 10.1.1.467.6857. doi:10.1088/0953-8984/14/11/301.**^**Soleymanabadi, Hamed; Rastegar, Somayeh F. (2014-01-01). "Theoretical investigation on the selective detection of SO2 molecule by AlN nanosheets".*Journal of Molecular Modeling*.**20**(9): 2439. doi:10.1007/s00894-014-2439-6. PMID 25201451.**^**Soleymanabadi, Hamed; Rastegar, Somayeh F. (2013-01-01). "DFT studies of acrolein molecule adsorption on pristine and Al-doped graphenes".*Journal of Molecular Modeling*.**19**(9): 3733–3740. doi:10.1007/s00894-013-1898-5. PMID 23793719.**^**Music, D.; Geyer, R. W.; Schneider, J. M. (2016). "Recent progress and new directions in density functional theory based design of hard coatings".*Surface & Coatings Technology*.**286**: 178–190. doi:10.1016/j.surfcoat.2015.12.021.**^**(Parr & Yang 1989, p. 47)**^**March, N. H. (1992).*Electron Density Theory of Atoms and Molecules*. Academic Press. p. 24. ISBN 978-0-12-470525-8.**^**Weizsäcker, C. F. v. (1935). "Zur Theorie der Kernmassen" [On the theory of nuclear masses].*Zeitschrift für Physik*.**96**(7–8): 431–458. Bibcode:1935ZPhy...96..431W. doi:10.1007/BF01337700.**^**(Parr & Yang 1989, p. 127)**^**Topp, William C.; Hopfield, John J. (1973-02-15). "Chemically Motivated Pseudopotential for Sodium".*Physical Review B*.**7**(4): 1295–1303. Bibcode:1973PhRvB...7.1295T. doi:10.1103/PhysRevB.7.1295.**^**Michelini, M. C.; Pis Diez, R.; Jubert, A. H. (25 June 1998). "A Density Functional Study of Small Nickel Clusters".*International Journal of Quantum Chemistry*.**70**(4–5): 694. doi:10.1002/(SICI)1097-461X(1998)70:4/5<693::AID-QUA15>3.0.CO;2-3.**^**"Finite temperature approaches – smearing methods".*VASP the GUIDE*. Retrieved 21 October 2016.**^**Tong, Lianheng. "Methfessel–Paxton Approximation to Step Function".*Metal CONQUEST*. Retrieved 21 October 2016.

- Parr, R. G.; Yang, W. (1989).
*Density-Functional Theory of Atoms and Molecules*. New York: Oxford University Press. ISBN 978-0-19-504279-5. - Thomas, L. H. (1927). "The calculation of atomic fields".
*Proc. Camb. Phil. Soc*.**23**(5): 542–548. Bibcode:1927PCPS...23..542T. doi:10.1017/S0305004100011683. - Hohenberg, P.; Kohn, W. (1964). "Inhomogeneous Electron Gas".
*Physical Review*.**136**(3B): B864. Bibcode:1964PhRv..136..864H. doi:10.1103/PhysRev.136.B864. - Kohn, W.; Sham, L. J. (1965). "Self-Consistent Equations Including Exchange and Correlation Effects".
*Physical Review*.**140**(4A): A1133. Bibcode:1965PhRv..140.1133K. doi:10.1103/PhysRev.140.A1133. - Becke, Axel D. (1993). "Density-functional thermochemistry. III. The role of exact exchange".
*The Journal of Chemical Physics*.**98**(7): 5648. Bibcode:1993JChPh..98.5648B. doi:10.1063/1.464913. - Lee, Chengteh; Yang, Weitao; Parr, Robert G. (1988). "Development of the Colle–Salvetti correlation-energy formula into a functional of the electron density".
*Physical Review B*.**37**(2): 785. Bibcode:1988PhRvB..37..785L. doi:10.1103/PhysRevB.37.785. - Burke, Kieron; Werschnik, Jan; Gross, E. K. U. (2005). "Time-dependent density functional theory: Past, present, and future".
*The Journal of Chemical Physics*.**123**(6): 062206. arXiv:cond-mat/0410362. Bibcode:2005JChPh.123f2206B. doi:10.1063/1.1904586. PMID 16122292. - Lejaeghere, K.; Bihlmayer, G.; Bjorkman, T.; Blaha, P.; Blugel, S.; Blum, V.; Caliste, D.; Castelli, I. E.; Clark, S. J.; Dal Corso, A.; de Gironcoli, S.; Deutsch, T.; Dewhurst, J. K.; Di Marco, I.; Draxl, C.; Du ak, M.; Eriksson, O.; Flores-Livas, J. A.; Garrity, K. F.; Genovese, L.; Giannozzi, P.; Giantomassi, M.; Goedecker, S.; Gonze, X.; Granas, O.; Gross, E. K. U.; Gulans, A.; Gygi, F.; Hamann, D. R.; Hasnip, P. J.; Holzwarth, N. A. W.; Iu an, D.; Jochym, D. B.; Jollet, F.; Jones, D.; Kresse, G.; Koepernik, K.; Kucukbenli, E.; Kvashnin, Y. O.; Locht, I. L. M.; Lubeck, S.; Marsman, M.; Marzari, N.; Nitzsche, U.; Nordstrom, L.; Ozaki, T.; Paulatto, L.; Pickard, C. J.; Poelmans, W.; Probert, M. I. J.; Refson, K.; Richter, M.; Rignanese, G.-M.; Saha, S.; Scheffler, M.; Schlipf, M.; Schwarz, K.; Sharma, S.; Tavazza, F.; Thunstrom, P.; Tkatchenko, A.; Torrent, M.; Vanderbilt, D.; van Setten, M. J.; Van Speybroeck, V.; Wills, J. M.; Yates, J. R.; Zhang, G.-X.; Cottenier, S. (2016). "Reproducibility in density functional theory calculations of solids".
*Science*.**351**(6280): aad3000. Bibcode:2016Sci...351.....L. doi:10.1126/science.aad3000. ISSN 0036-8075. PMID 27013736.

- Walter Kohn, Nobel Laureate Freeview video interview with Walter on his work developing density functional theory by the Vega Science Trust.
- Capelle, Klaus (2002). "A bird's-eye view of density-functional theory". arXiv:cond-mat/0211443.
- Walter Kohn, Nobel Lecture
- Density functional theory on arxiv.org
- FreeScience Library -> Density Functional Theory
- Argaman, Nathan; Makov, Guy (2000). "Density Functional Theory -- an introduction".
*American Journal of Physics*.**68**(2000): 69–79. arXiv:physics/9806013. Bibcode:2000AmJPh..68...69A. doi:10.1119/1.19375. - Electron Density Functional Theory – Lecture Notes
- Density Functional Theory through Legendre Transformationpdf
- Burke, Kieron. "The ABC of DFT" (PDF).
- Modeling Materials Continuum, Atomistic and Multiscale Techniques, Book
- NIST Jarvis-DFT

ABINIT is an open-source suite of programs for materials science, distributed under the GNU General Public License. ABINIT implements density functional theory, using a plane wave basis set and pseudopotentials, to compute the electronic density and derived properties of materials ranging from molecules to surfaces to solids. It is developed collaboratively by researchers throughout the world.A web-based easy-to-use graphical version, which includes access to a limited set of ABINIT's full functionality, is available for free use through the nanohub.

Amsterdam Density FunctionalAmsterdam Density Functional (ADF) is a program for first-principles electronic structure calculations that makes use of density functional theory (DFT). ADF was first developed in the early seventies by the group of E. J. Baerends from the Vrije Universiteit in Amsterdam, and by the group of T. Ziegler from the University of Calgary. Nowadays many other academic groups are contributing to the software. Software for Chemistry & Materials (SCM), formerly known as Scientific Computing & Modelling is a spin-off company from the Baerends group. SCM has been coordinating the development and distribution of ADF since 1995. Together with the rise in popularity of DFT over the last decade, ADF has become a popular computational chemistry software package used in the industrial and academic research. ADF excels in spectroscopy, transition metals, and heavy elements problems. A periodic structure counterpart of ADF named BAND is available to study bulk crystals, polymers, and surfaces. The ADF Modeling Suite has expanded beyond DFT since 2010, with a GUI to Stewart's semi-empirical MOPAC code, and the Quantum_ESPRESSO plane wave code, a density-functional based tight binding (DFTB) module, a reactive force field module ReaxFF, and an implementation of Klamt's COSMO-RS method.

Atomistix ToolKitAtomistix ToolKit (ATK) is a commercial software for atomic-scale modeling and simulation of nanosystems. The software was originally developed by Atomistix A/S, and was later acquired by QuantumWise following the Atomistix bankruptcy.Atomistix ToolKit is a further development of TranSIESTA-C, which in turn in based on the technology, models, and algorithms developed in the academic codes TranSIESTA, Physical Review B 65, 165401 (2002). and McDCal, employing localized basis sets as developed in SIESTA.

BigDFTBigDFT is a free software package for physicists and chemists, distributed under the GNU General Public License, whose main program allows the total energy, charge density, and electronic structure of systems made of electrons and nuclei (molecules and periodic/crystalline solids) to be calculated within density functional theory (DFT), using pseudopotentials, and a wavelet basis.

CASTEPCASTEP (originally from CAmbridge Serial Total Energy Package) is a shared-source academic and commercial software package which uses density functional theory with a plane wave basis set to calculate the electronic properties of crystalline solids, surfaces, molecules, liquids and amorphous materials from first principles. CASTEP permits geometry optimisation and finite temperature molecular dynamics with implicit symmetry and geometry constraints, as well as calculation of a wide variety of derived properties of the electronic configuration. Although CASTEP was originally a serial, Fortran 77-based program, it was completely redesigned and rewritten from 1999-2001 using Fortran 95 and MPI for use on parallel computers by researchers at the Universities of York, Durham, St. Andrews, Cambridge and Rutherford Labs.

CONQUESTCONQUEST is a linear scaling, or O(N), density functional theory (DFT) electronic structure code. The code is designed to perform DFT calculations on very large systems containing many thousands of atoms. It can be run at different levels of precision ranging from ab initio tight binding up to full DFT with plane wave accuracy. It has been applied to the study of three-dimensional reconstructions formed by Ge on Si(001), containing over 20,000 atoms. Tests on the UK's national supercomputer HECToR in 2009 demonstrated the capability of the code to perform ground-state calculations on systems of over 1,000,000 atoms.

CP2KCP2K is a freely available (GPL) program, written in Fortran 2003, to perform atomistic simulations of solid state, liquid, molecular and biological systems. It provides a general framework for different methods: density functional theory (DFT) using a mixed Gaussian and plane waves approach (GPW) via LDA, GGA, MP2, or RPA levels of theory, classical pair and many-body potentials, semi-empirical (AM1, PM3, MNDO, MNDOd, PM6) Hamiltonians, and Quantum Mechanics/Molecular Mechanics (QM/MM) hybrid schemes relying on the Gaussian Expansion of the Electrostatic Potential (GEEP).

CP2K provides editor plugins for Vim and Emacs syntax highlighting, along with other tools for input generation and output processing.

Car–Parrinello molecular dynamicsCar–Parrinello molecular dynamics or CPMD refers to either a method used in molecular dynamics (also known as the Car–Parrinello method) or the computational chemistry software package used to implement this method.The CPMD method is related to the more common Born–Oppenheimer molecular dynamics (BOMD) method in that the quantum mechanical effect of the electrons is included in the calculation of energy and forces for the classical motion of the nuclei. However, whereas BOMD treats the electronic structure problem within the time-independent Schrödinger equation, CPMD explicitly includes the electrons as active degrees of freedom, via (fictitious) dynamical variables.

The software is a parallelized plane wave / pseudopotential implementation of density functional theory, particularly designed for ab initio molecular dynamics.

DMol3DMol3 is a commercial (and academic) software package which uses density functional theory with a numerical radial function basis set to calculate the electronic properties of molecules, clusters, surfaces and crystalline solid materials

from first principles. DMol3 can either use gas phase boundary conditions or 3d periodic boundary conditions for solids or simulations of lower-dimensional periodicity. It has also pioneered the use of the conductor-like screening model COSMO Solvation Model for quantum simulations of solvated molecules and recently of wetted surfaces. DMol3 permits geometry optimisation and saddle point search with and without geometry constraints, as well as calculation of a variety of derived properties of the electronic configuration. DMol3 development started in the early eighties with B. Delley then associated with A.J.Freeman and D.E.Ellis at Northwestern University. In 1989 DMol3 appeared as DMol, the first commercial density functional package for industrial use by Biosym Technologies now Accelrys. Delley's 1990 publication was cited more than 3000 times.

DP codeDP is a free software package for physicists implementing ab initio linear-response TDDFT (time-dependent density functional theory) in frequency-reciprocal space and on a plane wave basis set.

It allows to calculate both dielectric spectra, such as EELS (electron energy-loss spectroscopy), IXSS (inelastic X-ray scattering spectroscopy) and CIXS (coherent inelastic X-ray scattering spectroscopy), and also optical spectra, e.g. optical absorption, reflectivity, refraction index.

The systems range from periodic/crystalline solids, to surfaces, clusters, molecules and atoms made of insulators, semiconductors and metal elements. It implements the RPA (random phase approximation), the TDLDA or ALDA (adiabatic local-density approximation) plus other non-local approximations, including or neglecting local-field effects. It is distributed under the scientific software open-source academic for free license.

HORTON (software)HORTON, the Helpful Open-source Research TOol for N-fermion systems, is an open-source modular quantum chemistry program written primarily in Python. It is composed of several quantum mechanical methods for electronic structure calculations and tools for post-processing wave functions and densities.

ONETEPONETEP (Order-N Electronic Total Energy Package) is a linear-scaling density functional theory software package able to run on parallel computers. It uses a basis of non-orthogonal generalized Wannier functions (NGWFs) expressed in terms of periodic cardinal sine (psinc) functions, which are in turn equivalent to a basis of plane-waves. ONETEP therefore combines the advantages of the plane-wave approach (controllable accuracy and variational convergence of the total energy with respect to the size of the basis) with computational effort that scales linearly with the size of the system. The ONETEP approach involves simultaneous optimization of the density kernel (a generalization of occupation numbers to non-orthogonal basis, which represents the density matrix in the basis of NGWFs) and the NGWFs themselves. The optimized NGWFs then provide a minimal localized basis set, which can be considerably smaller in size, but of equal or higher accuracy, than the unoptimized basis sets used in most linear-scaling approaches.

ONETEP has been developed by a UK-centric group of academics based at the universities of Cambridge, Southampton, Warwick, Imperial College London and Gdańsk University of Technology. It is available to academics at a reduced rate, and licenses can be obtained for non-academic usage from the developers or through Accelrys' Materials Studio package.

ORCA (quantum chemistry program)ORCA is an ab initio quantum chemistry program package that contains modern electronic structure methods including density functional theory, many-body perturbation, coupled cluster, multireference methods, and semi-empirical quantum chemistry methods. Its main field of application is larger molecules, transition metal complexes, and their spectroscopic properties. ORCA is developed in the research group of Frank Neese. The free version is available only for academic use at academic institutions.

Octopus (software)octopus is a software package for performing Kohn–Sham density functional theory (DFT) and time-dependent density functional theory (TDDFT) calculations.octopus employs pseudopotentials and real-space numerical grids to propagate the Kohn–Sham orbitals in real time under the influence of time-varying electromagnetic fields. Specific functionality is provided for simulating one-, two-, and three-dimensional systems. octopus can calculate static and dynamic polarizabilities and first hyperpolarizabilities, static magnetic susceptibilities, absorption spectra, and perform molecular dynamics simulations with Ehrenfest and Car–Parrinello methods.

The code is written predominantly in Fortran, with some C and Perl. It is released under the GPL.

PARSECPARSEC is a package designed to perform electronic structure calculations of solids and molecules using density functional theory (DFT). The acronym stands for Pseudopotential Algorithm for Real-Space Electronic Calculations. It solves the Kohn–Sham equations in real space, without the use of explicit basis sets.One of the strengths of this code is that it handles non-periodic boundary conditions in a natural way, without the use of super-cells, but can equally well handle periodic and partially periodic boundary conditions. Another key strength is that it is readily amenable to efficient massive parallelization, making it highly effective for very large systems.Its development started in early 1990s with James Chelikowsky (now at the University of Texas), Yousef Saad and collaborators at the University of Minnesota. The code is freely available under the GNU GPLv2. Currently, its public version is 1.4.4. Some of the physical/chemical properties calculated by this code are: Kohn–Sham band structure, atomic forces (including molecular dynamics capabilities), static susceptibility, magnetic dipole moment, and many additional molecular and solid state properties.

Quantum ESPRESSOQuantum ESPRESSO is a software suite for ab initio quantum chemistry methods of electronic-structure calculation and materials modeling, distributed for free under the GNU General Public License. It is based on Density Functional Theory, plane wave basis sets, and pseudopotentials (both norm-conserving and ultrasoft). ESPRESSO is an acronym for opEn-Source Package for Research in Electronic Structure, Simulation, and Optimization.The core plane wave DFT functions of QE are provided by the PWscf component, PWscf previously existed as an independent project. PWscf (Plane-Wave Self-Consistent Field) is a set of programs for electronic structure calculations within density functional theory and density functional perturbation theory, using plane wave basis sets and pseudopotentials. The software is released under the GNU General Public License.

The latest version QE-6.3.0 was released on 5 July 2018.

Time-dependent density functional theoryTime-dependent density functional theory (TDDFT) is a quantum mechanical theory used in physics and chemistry to investigate the properties and dynamics of many-body systems in the presence of time-dependent potentials, such as electric or magnetic fields. The effect of such fields on molecules and solids can be studied with TDDFT to extract features like excitation energies, frequency-dependent response properties, and photoabsorption spectra.

TDDFT is an extension of density functional theory (DFT), and the conceptual and computational foundations are analogous – to show that the (time-dependent) wave function is equivalent to the (time-dependent) electronic density, and then to derive the effective potential of a fictitious non-interacting system which returns the same density as any given interacting system. The issue of constructing such a system is more complex for TDDFT, most notably because the time-dependent effective potential at any given instant depends on the value of the density at all previous times. Consequently, the development of time-dependent approximations for the implementation of TDDFT is behind that of DFT, with applications routinely ignoring this memory requirement.

Vienna Ab initio Simulation PackageThe Vienna Ab initio Simulation Package, better known as VASP, is a package for performing ab initio quantum mechanical calculations using either Vanderbilt pseudopotentials, or the projector augmented wave method, and a plane wave basis set. The basic methodology is density functional theory (DFT), but the code also allows use of post-DFT corrections such as hybrid functionals mixing DFT and Hartree–Fock exchange, many-body perturbation theory (the GW method) and dynamical electronic correlations within the random phase approximation.

Originally, VASP was based on code written by Mike Payne (then at MIT), which was also the basis of CASTEP. It was then brought to the University of Vienna, Austria, in July 1989 by Jürgen Hafner. The main program was written by Jürgen Furthmüller, who joined the group at the Institut für Materialphysik in January 1993, and Georg Kresse. VASP is currently being developed by Georg Kresse; recent additions include the extension of methods frequently used in molecular quantum chemistry (such as MP2 and CCSD(T)) to periodic system.

VASP is currently used by more than 1400 research groups in academia and industry worldwide on the basis of software licence agreements with the University of Vienna.

WIEN2kThe WIEN2k package is a computer program written in Fortran which performs quantum mechanical calculations on periodic solids. It uses the full-potential (linearized) augmented plane-wave and local-orbitals [FP-(L)APW+lo] basis set to solve the Kohn–Sham equations of density functional theory.

WIEN2k was originally developed by Peter Blaha and Karlheinz Schwarz from the Institute of Materials Chemistry of the Vienna University of Technology. The first public release of the code was done in 1990. Then, the next releases were WIEN93, WIEN97, and WIEN2k.

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