KKR

Important Note

KKR is a METHOD, not standalone software. It is implemented in various codes including:

• SPR-KKR (spin-polarized relativistic KKR)
• AkaiKKR (Akai's KKR implementation)
• JuKKR (Jülich KKR)
• KKRnano (massively parallel KKR)

Method Overview

KKR (Korringa-Kohn-Rostoker) is a Green's function-based DFT method particularly powerful for disordered alloys (via CPA), spectroscopy, and magnetic materials. Unlike standard DFT codes, KKR uses multiple scattering theory and Green's functions, making it especially suited for substitutional disorder, spectroscopy calculations, and systems requiring advanced magnetic treatments.

Method type: Green's function DFT, multiple scattering
Primary implementations: SPR-KKR, AkaiKKR, JuKKR, KKRnano

Method Characteristics

Green's Function Approach:

• Multiple scattering theory
• Direct Green's functions
• Spectroscopy natural
• Transport properties
• Advanced formalism

Coherent Potential Approximation (CPA):

• Substitutional disorder
• Random alloys
• No supercells needed
• Exact statistical treatment
• Concentration effects

Applications:

• Random alloys
• Spectroscopy (XAS, XMCD)
• Magnetic materials
• Transport properties
• Disordered systems

Implementations

SPR-KKR:

• Fully relativistic
• Spectroscopy focus
• Magnetism
• LMU Munich

AkaiKKR:

• CPA for alloys
• Widely used
• Japanese development
• Free software

JuKKR:

• Jülich implementation
• Modern code
• Python interface
• Active development

KKRnano:

• Massively parallel
• Large-scale
• HPC focus
• Extreme scaling

Recommendation

For KKR calculations, use established implementations:

• SPR-KKR: Spectroscopy, relativistic
• AkaiKKR: Alloys, CPA
• JuKKR: Modern, Python interface
• KKRnano: Large-scale parallel

Verification & Sources

Status: ✅ METHOD VERIFIED

• KKR is a well-established DFT method
• Multiple production implementations available
• Not standalone software - use SPR-KKR, AkaiKKR, JuKKR, or KKRnano