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
(COSMORS), 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.
.
ADF
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) allelectron 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 rangeseparated hybrids
 selfconsistent
spinorbit coupling TDDFT
 charge transfer
integrals, NEGF
 scrutinize
chemical bonding interactions
 Slatertype
orbitals: correct nuclear cusp (NMR, EPR)
 environments:
DIM/QM, FDE, COSMO, SM12

BAND
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 lowdimensional 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, Qtensor, EELS
 Analysis:
(p)DOS, orbitals, band structures, COOP, QTAIM, ELF, bonding analysis
 Lattice
optimization, phonons
 Metal dielectric
functions: TDCDFT polarization functional for optical response
 Latest
functionals, e.g. D3(BJ), SCAN, MVS, MN15L
 Specialized
band gap functionals: GLLBsc, TBmBJ, GGA+U

COSMORS
Fluid thermodynamics from quantum mechanics
The COnductorlike Screening MOdel for Realistic Solvents calculates
thermodynamic properties of fluids and solutions based on quantum
mechanical data. Properties from COSMORS have predictive power outside
the parametrization set, as opposed to empirical models (e.g. UNIFAC).

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

DFTB
Fast approximate DFT for molecules, 1D, 2D and 3D
DensityFunctional based TightBinding (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 precalculated parameters, a minimal basis and
only nearestneighbor interactions. Longrange interactions are
described with empirical dispersion corrections and thirdorder
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 preoptimizer for full molecular and periodic DFT calculations
with ADF and BAND.

Selected
features
 modern xc
functionals, including dispersion and rangeseparated hybrids
 selfconsistent
spinorbit coupling TDDFT
 charge transfer
integrals, NEGF
 scrutinize
chemical bonding interactions
 Slatertype
orbitals: correct nuclear cusp (NMR, EPR)
 environments:
DIM/QM, FDE, COSMO, SM12

ReaxFF
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 bondorder 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, nonreactive or reactive molecular dynamics
 includes all the
latest ReaxFF force fields
 thermal
conductivity (TNEMD)
 model reactions
of millions of atoms in a 3D box
 well
parallelized and linearscaling

benchmark input files for ReaxFF (based on the
LAMMPS PETN benchmark)
 ACKS2 charge
equilibration: correct longrange charge behavior (batteries, enzymes)
 eReaxFF:
explicit electrons

MOPAC
Fast semiempirical with integrated GUI
MOPAC could bring the quantum precision you need to study large
molecules or periodic systems. A good tradeoff between speed and
accuracy is achieved through a minimal basis and parameterization
against experimental data, with parameters available for most elements.
Like DFTB, the semiempirical 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 preoptimization,
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 preoptimization
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. 
