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  • Amsterdam Modeling Suite
    Amsterdam Modeling Suite
    Atomistic Scale
    Electronic Structure
    ADF

    Understand and predict chemical properties with our fast and accurate molecular DFT code.

    Periodic DFT

    BAND & Quantum Espresso: Calculate reactivity, band gaps, optical response, and other properties for periodic systems.

    DFTB & MOPAC

    Model larger molecules and periodic systems, or prescreen many candidates, with the fast electronic structure methods DFTB and MOPAC.

    Interatomic Potentials
    ReaxFF

    Study large, chemically evolving systems with ReaxFF molecular dynamics.

    Machine Learning Potentials

    Use preparametrized ML potentials M3GNET, ANI-1ccx or your own models.

    Force Fields

    GFN-FF, Apple&P, UFF, and more- (polarizable) force fields.

    Meso- & Macroscale
    kMC and Microkinetics

    Predict catalytic turn-over frequencies with microkinetics and kinetic Monte Carlo.

    Bumblebee: OLED stacks

    3D kinetic Monte Carlo for simulating OLED device-level physics

    Fluid Thermodynamics
    COSMO-RS

    Quick physical property predictions, thermodynamic properties in solution, and solvent screening.

    Amsterdam Modeling Suite: computational chemistry with expert support to advance your chemistry & materials R&D

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    OLED workflows

    Automatic workflows to simulate physical vapor deposition and calculate properties for OLED device modeling.

    ChemTraYzer2

    Automatically extract reaction pathways and reaction rates from reactive MD trajectories.

    Conformers

    Easily generate, screen, refine, and select conformers. Pass on to other modules for conformational averaging.

    Reactions Discovery

    Predict chemical (side) reactions from nothing but constituent molecules.

    AMS Driver
    Properties

    Calculate frequencies, phonons, and more. Use forces and energies from AMS or external engines.

    PES Exploration

    Minimize structures, find transitions states, scan multiple coordinates.

    Molecular Dynamics

    Use advanced thermo- and barostats, non-equilibrium and accelerated MD, molecule gun.

    Monte Carlo

    Grand Canonical Monte Carlo to study absorption, (dis)charge processes.

    Interfaces
    ParAMS

    Versatile graphical and python scripting tools to create training sets and parametrize DFTB, ReaxFF, and machine learned potentials.

    PLAMS

    Versatile python scripting interface to create your own computational chemistry workflows

    GUI

    Powerful graphical interface to set up, run, and analyze calculations. Even across different platforms.

    VASP

    Interface to popular plane-wave code VASP. Easily set up PES Scans to create training data.

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    ams2025.102

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    ams2025.102

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Home > Documentation

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  • Documentation
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  • Installation
Logo
  • Keywords Index
  • General
    • Introduction
    • Feature List
    • What’s new in Band 2024.1
    • What’s new in Band 2023.1
    • What’s new in Band 2022.1
    • What’s new in Band 2021.1
    • What’s new in Band 2020
    • Input
  • AMS driver’s tasks and properties
  • Model Hamiltonians
  • Accuracy and Efficiency
  • Spectroscopy and Properties
  • Analysis
  • Electronic Transport (NEGF)
  • Expert Options
  • Troubleshooting
  • Examples
  • Required Citations
  • Keywords
  • KF output files
  • FAQ
BAND
  • Documentation/
  • BAND/
  • General

General¶

  • Introduction
  • Feature List
    • Model Hamiltonians
    • Structure and Reactivity
    • Spectroscopy and Properties
    • Charge transport
    • Analysis
  • What’s new in Band 2024.1
  • What’s new in Band 2023.1
  • What’s new in Band 2022.1
  • What’s new in Band 2021.1
  • What’s new in Band 2020
  • Input
    • General remarks on input structure and parsing
    • Keys
    • Blocks
    • Including an external file
    • Units
Next Previous
AMS Modules
Electronic Structure
ADF: molecular DFT Periodic DFT DFTB & MOPAC
Interatomic Potentials
ReaxFF ML Potentials Force Fields
Kinetics
kMC and Microkinetics Bumblebee: OLEDs
Macroscale
COSMO-RS
Application Areas
Research Topics
Batteries Biotechnology Bonding Analysis Catalysis Heavy Elements Inorganic Chemistry Materials Science Nanoscience Oil & Gas OLEDs Perovskites Polymers Semiconductors Spectroscopy
Where to use AMS?
Industry Government Lab National Supercomputer Academic Research Teaching
Tools
Workflows
Conformers OLED workflows Reaction analysis Reaction discovery
AMS Driver
Hybrid Engine Molecular Dynamics Monte Carlo PES Exploration Properties
Python Utilities
ACErxn ParAMS PLAMS pyZacros
Interfaces
GUI VASP Parametrization
Documentation & Support
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