New in Amsterdam Modeling Suite AMS 2020

The molecular DFT code ADF is now fully integrated with the AMS driver. This enables you to more easily and efficiently explore potential energy surfaces, for example to find transition states (see video). Now it is also easier to screen molecules for desired properties and to set up workflows across different methods.

Researchers can perform a larger variety of multi-layer calculations for molecules as well as for periodic systems with the new hybrid engine. Any quantum mechanics and force field-based methods can be combined in any number of layers with mechanical embedding through a subtractive scheme. Electrostatic embedding through additive QM/MM is available for 2-layer systems with ADF, BAND or DFTB as the quantum mechanical region.

Explore conformers, reaction energies, and potential energy surfaces with fast and accurate high-dimensional neural network potentials (HDNNPs) ANI-1ccx and ANI-2x or use your own machine learning potentials.

The central AMS driver has several new analysis tools, improvements in the MD driver and geometry optimizer, enabling them for all atomistic engines in the Amsterdam Modeling Suite. COSMO-RS can now deal with conformers, multiple protonation states and explicit solvent coordination.

AMS driver

AMS 2020: AMS Driver


AMS 2020: ADF


  • Scalar relativistic ZORA treatment by default
  • QM/MM and QM/QM’ calculations with any periodicity (Hybrid Engine)
  • STO basis sets for hypothetical elements Uue (Z=119) and Ubn (Z=120)


AMS 2020: DFTB

Machine learning potentials

  • Interface between the AMS driver and several ML potential backends
  • Pre-parametrized high-dimensional neural network potentials:
    ANI-2x (H,C,N,O,F,S,Cl)
    ANI-1ccx (H,C,N,O)
AMS 2020: Machine learning potentials

Multi-layer calculations

  • Hybrid Engine: easily set up QM/MM, QM/QM’, MM/MM’, and multi-layer
    • QM engines: ADF, BAND, DFTB, MOPAC
    • MM engines: ReaxFF, ML Potentials
    • new Force Field engine (UFF, GAFF, Amber, Tripos)
  • Electrostatic embedding for two-layer QM/MM, with DFT or DFTB
AMS 2020: Multi-layer calculations


AMS 2020: ReaxFF


  • More accurate fluid thermodynamics with multiple species, e.g.
    • Different protonation and dissociation states
    • Aggregation to dimers and oligomers
    • Explicit solvation
    • Conformers