With BigDFT, atomistic modeling is more powerful and accessible
Versatile and flexible solutions for in-silico characterization of challenging materials and bio-systems
Wavelets
Wavelets form a flexible, systematic and accurate basis set on an adaptive mesh.
Their features are the origin of the outstanding properties of the code.
Linear scaling
The accurate and robust linear scaling approach implemented in BigDFT provides a computational technique for efficient calculations in systems with thousands of atoms.
Boundary conditions
BigDFT offers calculations for periodic systems, surfaces, wires, and isolated molecules. Implicit electrostatic solvents are also available in the isolated directions.
Fragments
BigDFT allows to partition automatically large systems into fragments and to evaluate
associated fragment quantities, such as charges, dipoles or interaction strengths.
Platforms integrating BigDFT
Nextmol is a cloud-based platform for the design of new chemicals through molecular modeling and artificial intelligence
AiiDA is an open-source Python infrastructure to help researchers with automating, managing, persisting, sharing and reproducing the complex workflows associated with modern computational science and all associated data.
