Scientific Computing – Scientific Computing - Amsterdam Modeling Suite

Amsterdam Modeling Suite - AMS

ADF, BAND, DFTB, ReaxFF and COSMO-RS

SCM produces a suite of software to model chemical and physical properties. The density functional theory programs are accurate and efficient and the approximate quantum-based codes offer fast insight in complex systems. The programs work, in parallel, out of the box on any popular system (Windows, Mac, Linux/UNIX). Jobs for all programs may be prepared, executed and analyzed via a uniquely integrated user-friendly Graphical User Interface (GUI).

The ADF Program for molecular modeling

With ADF structure, reactivity and spectroscopy of molecules is modeled with accurate and efficient DFT methods, including the latest xc functionals, relativistic effects and all-electron basis sets. The powerful molecular DFT code ADF is particularly strong in molecular properties and inroganic chemistry.

The periodic structure program BAND

Periodic structures (polymers, surfaces and crystals) can be modeled with the BAND program, featuring relativistic methods, modern xc functionals and many optical and spectroscopic properties. BAND shares a lot of functionality with ADF. Slabs are treated as real 2D systems, and nanotubes with proper 1D periodicity.

The approximate DFT programs DFTB and MOPAC

DFTB is a fast and effective Density Functional based approach to model molecules, crystals, polymers, and surfaces. It can be used as a pre-optimizer or to get quick insight in spectra and dynamical behavior.
MOPAC is a fast approximate method to study large molecules and big periodic systems and integrates the GUI.

ReaxFF for modeling chemical reactions

ReaxFF is available with use of the powerful GUI to run and analyze reactive molecular dynamics simulations based upon the reactive force field method of van Duin and coworkers.

COSMO-RS for fluid thermodynamics

With the COSMO-RS implementation including a database of over 1800 compounds many thermodynamic properties of solutions and mixtures can be predicted.

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