Comparar métodos

	Método KKR	Teoria do Funcional da Densidade	Modelo Tight-Binding
Área	Computação quântica	Computação quântica	Computação quântica
Família	Machine learning	Machine learning	Machine learning
Ano de origem	1947	1965	1954
Autor original	Joop Korringa and Walter Kohn	Walter Kohn	John Slater and George Koster
Tipo	Electronic structure method	Electronic structure method	Simplified electronic structure model
Fonte seminal	Korringa, J. (1947). On the calculation of the energy of a Bloch wave in a metal. Physica, 13, 392–400.	Kohn, W., Sham, L. J. (1965). Self-consistent equations including exchange and correlation effects. Physical Review, 140, A1133–A1138.	Slater, J. C., Koster, G. F. (1954). Simplified LCAO method for the periodic potential problem. Physical Review, 94, 1498–1524.
Outros nomes	KKR, multiple scattering	DFT, Kohn-Sham equations	TB model, hopping model
Relacionados	3	4	3
Resumo	The Korringa-Kohn-Rostoker (KKR) method is a powerful multiple-scattering approach for calculating electronic band structures and properties of periodic and disordered solids. Developed in the late 1940s, KKR treats electrons as scattering from atomic potentials in a muffin-tin geometry, enabling efficient calculations for both crystalline and amorphous systems.	Density Functional Theory (DFT) is a computational method for determining the properties of materials and molecules by modeling the ground state electron density. Developed by Walter Kohn and Lu Jeu Sham in the 1960s, DFT reduces the complexity of quantum chemistry from tracking individual electron coordinates to optimizing the total electron density, enabling efficient simulations of large molecular and condensed-matter systems.	The Tight-Binding (TB) model is a simplified semi-empirical approach for computing electronic band structures and properties of solids. Formulated by Slater and Koster in 1954, TB treats electron hopping between atomic sites as the dominant interaction, enabling efficient calculations of band dispersion for a wide variety of materials.