New Product Release : Advance/OF-DFT

Deep Learned Orbital Free-DFT

Kohn-Sham DFT (KS-DFT) has long been the standard method in density functional theory (DFT). However, KS-DFT is computationally expensive and challenging for simulating large systems due to its reliance on orbital (wave function) representation. Orbital Free-DFT (OF-DFT), which directly optimizes electron density without using orbitals, offers extremely fast simulations at a much lower computational cost. The main challenge with OF-DFT has been the lack of a practical kinetic energy functional. AdvanceSoft Corporation has addressed this issue by applying its proprietary field deepening algorithm. We now offer services using our new product, Advance/OF-DFT, which incorporates the deep-learned kinetic energy functional AdvanceSoft25.

Kohn Sham-DFT vs Orbital Free-DFT

KS-DFTOF-DFTForce Field
Electron Densityavailableavailablenot available
Orbital (Wave Variables)availablenot availablenot available
Kinetic EnergyExplicitly
calculated in orbital
Deep Learned Functional :
AdvanceSoft25
Calculation AccuracyHighDepends on
the functional
Depends on
force field
Calculation Cost𝑂(𝑁3)𝑂(𝑁)𝑂(𝑁)
VersatilityApplicable to
all elements
Pseudo-potentials
should be expanded
(to be resolved in next version)
Ensure versatility
with GNNP

Analyzing electronic structure, but same speed as GNNP

  • The computational cost of OF-DF is proportional to the number of atoms (𝑁), denoted as (𝑂(𝑁)), so simulations can be performed at the same level of computational speed as Graph Neural Network Potential (GNNP).
  • Since information on electron density is retained, Bader charge can also be analyzed after convergence of the SCF calculation.
  • Doping of electrons and holes is possible, and in combination with the Effective Screening Medium (ESM), large-scale MD simulations with controlled electrode potentials can be realized (ESM is not implemented in the current version). Application of an external electric field is also easy.
  • The type of exchange-correlation functional can be selected at the time of SCF calculation, so non-local correlations corresponding to dispersion forces such as vdW-DF and rVV can also be used depending on the system; empirical functions such as DFT-D3 are not required.
  • Since the wavefunction information is not included, a separate KS-DFT calculation is required for band structure and density of states calculations.

Architecture of the deep learned
kinetic energy functional: AdvanceSoft25

Advancesoft25 En