Amsterdam Modeling Suite
Powerful Computational Chemistry

The Amsterdam Modeling Suite is an easy to deploy computational chemistry software, covering a wide range of tools. Besides DFT for molecules (ADF) & periodic systems (BAND, Quantum ESPRESSO), fast & approximate electronic structure methods (MOPAC, DFTB), a reactive force field (ReaxFF), a continuum fluid thermodynamics module (COSMO-RS), an advanced driver for complex MD and PES tasks (AMS driver), and a python scripting and workflow tool (PLAMS), it contains an integrated Graphical User Interface – all easy to install from a single package.

Powerful DFT software for modeling chemistry

Amsterdam Density Functional (ADF) is particularly strong in understanding and predicting structure, reactivity, and spectra of molecules.
ADF is frequently used for studying transition metal complexes and molecules with heavy atoms, since all elements in the periodic table can be modeled accurately and efficiently with the ZORA relativistic approach and Slater Type orbital (STO) all-electron basis sets. With these features, ADF offers unique capabilities to predict molecular properties of nanoparticles and organic electronics materials.
      Selected features
  • modern xc functionals, including dispersion and range-separated hybrids
  • self-consistent spin-orbit coupling TDDFT
  • charge transfer integrals, NEGF
  • scrutinize chemical bonding interactions
  • Slater-type orbitals: correct nuclear cusp (NMR, EPR)
  • environments: DIM/QM, FDE, COSMO, SM12


Periodic DFT for nanofibers, surfaces, and bulk

BAND is a periodic DFT code of the Amsterdam Modeling Suite. Using atomic orbitals for periodic DFT calculations has many advantages over plane waves like a proper treatment of surfaces, efficient computations of sparse matter, and more direct and detailed analysis methods.BAND is particularly well suited for studying low-dimensional periodic materials or sparse matter systems, for (core electron) spectroscopic properties, and/or to access orbital properties and advanced analysis methods.
      Selected features
  • Spectroscopy: EPR (g & A tensors), EFG, Q-tensor, EELS
  • Analysis: (p)DOS, orbitals, band structures, COOP, QT-AIM, ELF, bonding analysis
  • Lattice optimization, phonons
  • Metal dielectric functions: TD-CDFT polarization functional for optical response
  • Latest functionals, e.g. -D3(BJ), SCAN, MVS, MN15L
  • Specialized band gap functionals: GLLB-sc, TB-mBJ, GGA+U

Fluid thermodynamics from quantum mechanics

The COnductor-like Screening MOdel for Realistic Solvents calculates thermodynamic properties of fluids and solutions based on quantum mechanical data. Properties from COSMO-RS have predictive power outside the parametrization set, as opposed to empirical models (e.g. UNIFAC).

      COSMO-RS properties
  • solubilities, partition coefficients (log P, log kOW)
  • pKa values
  • activity coefficients, solvation free energies, Henry’s law constants
  • vapor pressures, boiling points, vapor-liquid diagrams binary and ternary mixtures (VLE/LLE)
  • excess energies, azeotropes, miscibility gaps
  • composition lines, flash points

Fast approximate DFT for molecules, 1D, 2D and 3D

Density-Functional based Tight-Binding (DFTB) allows to perform calculations of large systems over long timescales even on a desktop computer. Relatively accurate results are obtained at a fraction of the cost of DFT by using pre-calculated parameters, a minimal basis and only nearest-neighbor interactions. Long-range interactions are described with empirical dispersion corrections and third-order corrections accurately handle charged systems.

The DFTB module can treat molecular as well as periodic systems (1D for nanotubes, 2D for surfaces, 3D for bulk), and as such can be used as a fast pre-optimizer for full molecular and periodic DFT calculations with ADF and BAND.
      Selected features
  • modern xc functionals, including dispersion and range-separated hybrids
  • self-consistent spin-orbit coupling TDDFT
  • charge transfer integrals, NEGF
  • scrutinize chemical bonding interactions
  • Slater-type orbitals: correct nuclear cusp (NMR, EPR)
  • environments: DIM/QM, FDE, COSMO, SM12

Reactive MD with GUI and analysis tools

ReaxFF is a program for modeling chemical reactions with atomistic potentials based on the reactive force field approach. In collaboration with the van Duin group, SCM has parallelized and significantly optimized the original ReaxFF code. Reactions in complex chemical mixtures totaling hundreds of thousands of atoms can now be modeled on a modern desktop computer.

While traditional force fields have difficulties treating certain elements, such as transition metals, the bond-order based reactive force field can in principle deal with the whole periodic table. We include over 80 ReaxFF force field files for many different combinations of elements. Furthermore, (re)parameterization tools helps to refine force fields or build new parameter sets. ReaxFF has been used over the past decade in various studies of complicated reactive systems, including solvent environments, interfaces, and molecules on metal (oxide) surfaces.

      Other ReaxFF features
  • hybrid parallelization (MPI, openMP)
  • geometry optimization, non-reactive or reactive molecular dynamics
  • includes all the latest ReaxFF force fields
  • thermal conductivity (T-NEMD)
  • model reactions of millions of atoms in a 3D box
  • well parallelized and linear-scaling
  •      benchmark input files for ReaxFF (based on the LAMMPS PETN benchmark)
  • ACKS2 charge equilibration: correct long-range charge behavior (batteries, enzymes)
  • eReaxFF: explicit electrons

Fast semi-empirical with integrated GUI

MOPAC could bring the quantum precision you need to study large molecules or periodic systems. A good trade-off between speed and accuracy is achieved through a minimal basis and parameterization against experimental data, with parameters available for most elements.

Like DFTB, the semi-empirical MOPAC code uses the nearest neighbor and minimal basis set approximations, making it fast and linear scaling. MOPAC has been parameterized against an enormous set of thoroughly examined experimental data, in a huge, commendable effort by Dr. Jimmy Stewart. The latest parameterization set (PM7) is also the most accurate. Since AMS2019, the MOPAC and DFTB modules are now bundled together and only one license is needed to use both methods.

To accelerate your research, use MOPAC for quick pre-optimization, prescreening of a large number of molecules or crystals, or to get results on really large molecules which are out of reach for DFT or ab initio methods.

Access large systems or script workflows

With the integrated Graphical interface it is easy to run, set up and analyze MOPAC jobs, or use it as a pre-optimization tool.

You can fully unlock the strength of MOPAC through the integration to our powerful AMS driver for complex potential energy surface tasks and the PLAMS python scripting environment.

Exchanging data and results from MOPAC to other Engines of the Amsterdam Modeling Suite is easy. You can therefore for example easily extract a snapshot from a ReaxFF molecular dynamics run and examine its electronic properties with MOPAC. Likewise, MOPAC coordinates can be readily transferred to ADF for a more accurate DFT calculation on desired properties. Quickly set up your own workflows, such as taking snapshots from advanced MD runs, or quickly (pre)screening many candidate molecules or materials for specific properties.

With AMS you can also do complex potential energy surface scans, accelerated MD, Monte Carlo methods and many properties using MOPAC as an integrated library.

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