Download Amsterdam Modeling Suite 2026.103 + license
Download Amsterdam Modeling Suite (AMS) 2026 with license and SCM Bumblebee It is one of the most powerful computational chemistry software for chemists. Amsterdam Modeling Suite software includes various modules as ADF، BAND، DFTB، Quantum Espresso، MOPAC، ReaxFF، PLAMS، COSMO-RS.
Bumblebee is a simulation tool used to model the long-term behavior of OLED materials by tracking the diffusion of carriers, molecular emissions and device degradation over time. It helps researchers understand how defects form, how materials age, and how charge carriers move within OLED layers, crucial for improving device efficiency and lifespan.
- ADF: A powerful density functional theory program for molecules, particularly strong in spectroscopy and inorganic chemistry.
- BAND: A very accurate periodic density functional theory program for condensed matter, including bulk, surfaces, and nanowires.
- DFTB: Density Functional Tight Binding: fast approximate DFT for molecules, 1D, 2D, and 3D. DFTB module also includes fast semi-empirical MOPAC engine, also with any periodicity.
- MLPot: Machine Learning Potential backend to explore potential energy surfaces with the AMS driver.
- ReaxFF: Reactive force-field for large-scale molecular dynamics simulations with chemical reactions.
- COSMO-RS: Instant fluid thermodynamics from quantum mechanics and property predictions from group contributions.
- ParAMS is a module for ReaxFF and DFTB (GFN1-xTB) parametrization, distributed together with the Amsterdam Modeling Suite.
Download Amsterdam Modeling Suite
The new ParAMS or scm functionality lets you easily parametrize ReaxFF and DFTB with a helpful graphical user interface. We also offer many other new features and improvements, mainly centered around catalysis (reactivity) and organic electronics.
With parametrized models, such as ReaxFF and DFTB you can simulate larger systems for longer timescales. Sometimes the available parameters may be inaccurate or lacking for your system. Reparametrizing ReaxFF and DFTB models is complex, but ParAMS is here to help! ParAMS is a powerful and user-friendly toolkit with graphical user interface and command-line tools.
ParAMS: powerful parametrization toolkit
- Easily import, build, and visualize training data sets
- Use data from AMS, VASP, Quantum ESPRESSO, and experiments
- Properties: energies, forces, geometry, stress tensors, charges,
- PES scans for bonds, angles, dihedrals, lattices
- Use a validation set to prevent overfitting
- Parametrize DFTB and ReaxFF parameters
- Submit training jobs to remote machines from the GUI
- GUI tutorials for DFTB and ReaxFF parametrization
Other changes for ParAMS 2024:
- The Results Importer class provides a shortcut for reading structures, reference results, and engine settings from finished reference job.
- The Logger output structure has been changed, with many new useful output files
- Job-dependent engine settings using the JCEntry.extra_engine attribute
- Parameter interfaces can be stored in text .yaml format
- Exact restarts with the CMA-ES optimizer
- Support for reading in VASP OUTCAR files and Quantum ESPRESSO .out files
- Weights schemes for setting individual datapoint weights for array reference values (for example, to weight large force components less than small force components)
- Initialize an empty ReaxFFParameters using ReaxFFParameters(None)
- Copy blocks of parameters from ReaxFF force field files
- New class names: ReaxParams → ReaxFFParameters, xTBParams → GFN1xTBParameters
- Scalar weights for array reference values are interpreted as the sum of weights: weight = 1 for an array of length 3 gives each point a weight of 0.3333 (before, the scalar value was broadcasted so the total weight would be 3).
- Faster reading of Job Collections
- Support for gzip-compressed job collections and training sets
- All extractors have explicit default units and sigma values
- Distance, angle, and dihedral extractors use the minimum image convention under periodic boundary conditions by default
- The params main script supports validation sets
Organic Electronics: deposition, GFN-FF, GW
- Workflows to deposit molecules & average properties over layers
for multiscale device-level modeling - Database common amorphous OLED materials + calculated properties
- GFN-FF: generic, polarizable force field for most elements
- qsGW (quasi-particle self-consistent GW) and beyond: G3W2
- Transfer integrals with DFTB
- Improved speed & memory usage Franck-Condon factors
- QM/FQFμ: QM + fluctuating dipoles & charges, compatible with FDE
- Spin-orbit coupled MP2
Reactivity: reaction discovery, kinetics
- Reaction rates and fluxes from reactive MD (ChemTraYzer2)
- Graphical and python interface for kinetic Monte Carlo (Zacros)
- Automatic reaction mapping: ACE-Reaction & reactmap (Python only)
AMS Driver new features
- Rattle/Shake for constrained molecular dynamics
- Distance constraints with the FIRE optimizer
- PES scan also allows scanning lattice degrees of freedom
- Fragmented states for barrierless adsorption processes during PES exploration
- Automatically reoptimize geometries not converged to a minimum
- Deposit molecule mixtures for ALD, CVD, etching
- Replay task for recomputing properties of a trajectory with a different method
- Properties from trajectories: mean squared displacement, viscosity
- Command-line only: tribology features (shear stress)
Additional new ADF, BAND & DFTB features
- ADF: Improvements in 3D-RISM and Interacting Quantum Atoms
BAND: - Visualization of spinors, Fermi surface & spin-orbit coupled DOS
- Alternative elements (modified nuclear charges)
- Electron Energy Density Function
DFTB: - Visualize orbitals for any parametrization, QTAIM for QuasiNaNo
- Fragment orbital analysis
Other new Amsterdam Modeling Suite functionality
- Conformer module, including CREST (Python)
- COSMO-RS-PDH: includes long-range electrostatics
- APPLE&P: polarizable force fields for battery electrolytes, ionic liquids
- Quantum ESPRESSO updated to 7.0
ADF
- Polarizable force field: QM/FQ Quantum Mechanics/Fluctuating Charges
- Unrelaxed dipole moment excited states
- Transition dipole moment between excited states
- POLTDDFT for fast excitation spectra: more fit sets for most elements
- r2SCAN-D4 XC functional (also for BAND)
- Eigenvalue-only self-consistent GW (evGW),
- New TZ3P and QZ6P basis sets for Many Body Perturbation Theory
- New Ligand-Field DFT(LFDFT) spectroscopy: ESR g-tensor doublets, XMCD
ADF & BAND
- 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)
DFTB
- GFN1-xTB is the new default model
- Much faster GFN1-xTB calculations with many k-points
- Use as higher or lower level engine in multi-layer calculations
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)
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
ReaxFF
- Default via AMS driver: easy module switching
- Can now treat 1D and 2D periodic systems
- Tapered bond orders
- Charge constraints
COSMO-RS
- (Graphical) User Interface improvements
- Package manager to (de)install additional components (COSMO-RS database, Quantum ESPRESSO, Machine Learning Potentials, Ligand-Field DFT)
- Option to output results into a spreadsheet
- Graceful interactive termination, also via GUI
- Improved UI to handle multiple molecules
- Sinkbox and Safebox for MD with molecule gun
- Support for PES exploration and other new features
Release Note AMS 2026
ML Potentials: Coverage and Performance
New model families (eSEN, MACE, UMA), trained on large datasets, extend the applicability of ML potentials while improving efficiency and accuracy.
Extended coverage includes:
- Charged and magnetic molecules
- Biomolecules and polymers
- Metal complexes and catalytic interfaces
- MOFs and molecular crystals
- Inorganic materials
Performance improvements:
- Near chemical accuracy for many applications
- Optimized performance on GPUs
- Benchmarked and documented models
- Easy install via package manager
These capabilities support a range of workflows, including:
- Conformer screening
- Preoptimization
- Thermochemistry and reactivity studies
- Active learning (including MACE and M3GNet fine-tuning)
ADF
New functionality has been added to support a wider range of electronic structure and spectroscopic applications:
- GW with FQ (Fμ) embedding (polarizable)
- wFQ for plasmonic spectroscopies (surface-enhanced Raman scattering)
- Solvation Model 12 (SM12) analytical gradients
- Frozen-core approximation with LibXC
- ROKS-TDA and ROKS-TDA-SOC now include spin-flip-down excited states (improved description of unpaired electrons in TDDFT with Spin-orbit coupling)
- Excited-state geometry optimizations for open-shell TD-DFT+TB
- NMR chemical shielding with LibXC and range-separated XC functionals
OLED and Multiscale Workflows
Updates to OLED workflows improve integration with OLED device modeling (Bumblebee) and analysis capabilities:
- NEW Bumblebee GUI & integration into OLED workflows
- Improved communication with Bumblebee
- Expanded analysis of transient behavior
- Support for exciton profiles, quenching, recombination, and degradation
Graphical User Interface
The GUI has been updated to simplify model setup and system construction:
- New structure builders (nanoparticles, nanotubes, micro-solvation)
- More compact and streamlined menus
- Improvements to AMSview and visualization tools
These updates aim to make common tasks more efficient while maintaining flexibility.
COSMO-RS
New tools have been introduced for modeling complex mixtures:
- Liquid–liquid equilibrium solver for identifying tie lines
- Stability testing for miscibility and phase separation
- Support for multi-component systems
- Integration with Python workflows for phase behavior analysis
AMS Driver & MD
The AMS driver has been updated to provide more control and robustness in simulations:
- Fast, rigid PES scans (“non-optimizing mode”) without relaxing other degrees of freedom
- Inclusion of Gibbs free energy in PES exploration
Improved molecular dynamics driver
- Stability detection
- Smaller engine files and performance optimizations
- Advanced SHAKE constraints
- More flexible reflective boundary conditions
- Use AMS MD with InfRETIS path sampling
VASP Integration
VASP 6.4 is now supported as an external engine within AMS (not included in the Amsterdam Modeling Suite), enabling closer integration between workflows:
- Improved compatibility with AMS scripting and automation
- Support for active learning workflows
- Consistent output formats within AMS
- Expanded examples and tutorials
This integration supports materials modeling workflows within a unified environment.
Python Examples and Scripting
The Python ecosystem has been expanded to improve usability and reproducibility.
Richer and more structured example library:
- Reusable examples across engines and applications (ADF, COSMO-RS, Batteries, etc.)
- Easier transition from GUI workflows to Python-based automation
Additional improvements include:
- More accessible AMSPython scripting for a wide range of users
- Support for automated and programmatic workflows
- Compatibility with LLM-assisted scripting approaches
Release Note AMS 2025
OLED Device Modeling & Organic Electronics
- Bumblebee 2025 – OLED Device Modeling beyond the 1D drift-diffusion model
- Advanced OLED Modeling: Explicit 3D morphologies, Molecular disorder and complex host-guest distributions, Layer interfaces and Exciplex materials
- Comprehensive Process & Interaction Analysis: Multiresonant TADF emitters, Hyperfluorescence, Exciton Annihilation, Polaron Quenching and Triplet Harvesting
- Optical Outcoupling for Light Management
- 10-50x faster than standard kinetic Monte Carlo
- Experimental or modeled input parameters
Much faster Multiscale OLED Workflow via AMS
- Bumblebee input parameters from scratch
- Speedup: 5x faster
- GPU support via LAMMPS
ADF
- ROKS-TDA excited states for open shell molecules with well-defined spin
- Accurate ionization potentials: New vertex correction beyond GW
- Exciton transfer integrals with ROSE or Fragment Orbital Constrained DFT (FOCDFT)
- Charge transfer integrals with FOCDFT
New Machine Learning Potentials
- Latest Machine Learning Potentials
- Instructions for how to run CHGNet, FairChem, MACE, MatterSim, ORB, and many more via AMS
- ASE calculators from any Python environment
New GUI Features
- Better Packmol Builder
- Much improved usability
- Easily pack by density, mole fraction, and more
- Support for Jupyter Notebooks in AMSjobs
- Faster startup
IR, Raman, Work Function, and Phonons with Quantum ESPRESSO
- IR and Raman spectra
- Work functions for surfaces
- Phonon band structures and thermodynamic properties
All-around improvements:
- Updated Grimme’s D3 and D4 dispersion correction, now also available for actinides
- Broader range of exchange-correlation functionals: LAK MetaGGA, Libxc 7.0.0
- Improved prediction of fluid thermodynamic properties and phase equilibria for associating fluids via COSMO-SAC DHB-MESP
- Full unscreened hybrids (like PBE0, B3PW) for band gaps
Release Note AMS 2024
Train your own machine learning potential
- Train custom M3GNet ML potentials with ParAMS
- Fine-tune the universal M3GNet potential for your chemistry
- Committee models for uncertainty estimation
- Simple active learning workflow
- Set up any MD simulation and reference engine
- Generate training data and retrain the model on-the-fly
- AIMNet2: new pre-trained ML model suitable for molecules and ions
- Non-metallic elements
- Very good for generating or ranking conformers
Quantum ESPRESSO as an AMS engine
- Use the plane-wave DFT program Quantum ESPRESSO as an AMS engine to
- explore the potential energy surface with the AMS Driver, or
- train ML potentials, ReaxFF, or DFTB with ParAMS
- New reliable pseudopotential libraries
- Standard Solid-State Pseudopotentials (SSSP) enabled by default
- Standalone QE no longer supported in AMSinput
Reactions discovery and reactivity
- Reactions Discovery workflow:
- Quickly generate plausible reactions with enhanced reactive MD
- Automatically extract and rank potential side reactions
- Transition state search and nudged elastic band:
- Dimer method for transition state search
- Initial NEB paths with the image dependent pair potential (IDPP)
- Reaction boost (targeted MD) restraints
- Enforce chemical reactions or other structural changes during MD
- Suitable for generating training data for custom ML potentials
GUI improvements in AMS2024
- AMSinput
- Export to PLAMS: save as a Python script that you can easily customize
- Improved support for importing run scripts
- Import multiple molecules from files or SMILES
- AMSview
- Visualize fields along a line + integrate perpendicular
- Powder X-ray diffraction (PXRD)
- AMSmovie: visualize uncertainties computed by ML potentials during MD
- and much more
Other new features in AMS2024
- ADF: procedure to calculate paramagnetic NMR (pNMR) chemical shieldings
- ADF: include environment effects, DRF or COSMO, with G0W0 (experimental)
- BAND: restart DOS and/or BandStructure from previous calculation
- MLPotential: auto-GPU detection
- ReaxFF: six new force fields included & improved force field selection dialog in AMSinput
- APPLE&P parameters updated to version 1.13
- COSMO-RS: database module & CRS Manager in pyCRS
- Stop MD trajectories early with exit conditions
- Store trajectory properties: individual thermostat temperatures, total BondBoost, Reactor restraint energy
- PISA: Python Input System for AMS – alternative for PLAMS settings.input with autocompletion and type hinting
Release Note AMS 2023
New engines: M3GNet ML potentials, ASE, QE
- Geometries, stress tensors, MD of almost any material with Chen and Ong’s universal graph neural network potential M3GNet-UP-2022
- Access external codes and scripting tools with the Atomic Simulation Environment (ASE) interface for AMS and PLAMS
- Quantum ESPRESSO 7.1 has been integrated with the AMS driver (only on Linux/Mac)
Improvements for Organic Electronics
- Accurate excitation energies with qsGW+BSE, including spin-orbit coupling
- Many improvements in the OLED workflows including more accurate electronic and excitonic properties and faster deposition with GPU-accelerated LAMMPS
- Vibrational polarizabilities
Reactivity: reaction discovery, kinetics
- GUI support for quick reaction network discovery with ACE-Reaction
- Promote chemical reactions with the molecular dynamics Nanoreactor
- Improvements in PES exploration & characterization
- Create kinetic data as input for CatalyticFOAM for reactor-scale modeling
- Improved ChemTraYzer2 trajectory analysis: population statistics
Productivity & accuracy improvements
- Faster ADF calculations
- Python Packmol interface for generating liquid and gas mixtures
- ASE Calculator for AMS
- ADFCOSMORSCompoundJob and pyCRS: easy COSMO-RS python workflows
- ParAMS: running & controlling multiple optimizers in parallel (GloMPO)
- Conformer generation, optimization & refinement across different levels
- Multi-stepper SCF algorithm for BAND and DFTB
- Non-equilibrium MD (NEMD): viscosity, tribology.
- Improved Apple&P polarizable force field parameters for ionic liquids and electrolytes (tutorial on viscosity)
- New method to quickly predict sigma profiles based on subgraphs
- QSPR synthetic accessibility and liquid viscosity predictions for pure compounds
Other new DFT features
TASKCC functional: better atomization energies for TASKxc
ADF
- Fast, robust & reliable composite DFT method r2SCAN-3c(STO)
- Fast beyond-RPA energies with the sigma-functional
- Open-shell capabilities: ROKS for high spin open shell molecules, excitations with approximate TDDFT methods
- Calculate entropies of solvation with 3D-RISM
- Circular Dichroism (CD) spectra with spin-orbit coupling
- Excited state geometry optimizations with TD-DFT+TB
- Analysis: new NOCV options, quasi-particle orbitals in terms of SFOs, PolTDDFT analysis options, IQA open-shell
BAND:
- Gaussian-type orbitals (GTOs)
- MP2, RPA, GW for molecules
What’s new in different AMS2023 components
- The items below link to a comprehensive list of new features for each manual.
- ReaxFF users will benefit from improvements in the AMS driver, the GUI, ParAMS, and PLAMS.
- AMS driver: central driver for MD, MC, vibrational spectra, PES exploration
- PLAMS: powerful and flexible python interface for AMS and other atomistic modeling software
- ParAMS: training and parametrization toolkit
- AMSGUI: Graphical User Interface
- ADF: molecular DFT with strong relativistic and spectroscopy capabilities
- BAND: all-electron AO-based periodic DFT for 1D, 2D, and 3D
- DFTB: fast, approximate DFT with Slater-Koster and xTB parametrizations
- MLPotentials: Machine Learning potentials
- COSMO-RS: fluid thermodynamics and other property predictions
- New: ASE Engine, Quantum ESPRESSO Engine
- Utilities: ChemTraYzer2-2023, Trajectory Analysis, OLED workflows
- pyZacros for multiscale reactor modeling
Software details
- File Size 2024: Windows 2024 1.7 GB + Linux 2024 5.6 GB +macOS 2 GB
- File Size 2023: Windows 2023 1.95GB + Linux 2023 2.2 GB +macOS 2023 3.01 GB
- File Size 2022: Windows 2022 1.81GB + Linux 2022 1.96 GB +macOS 2022 2.02 GB
- Operating System: Windows x64-x86 + Linux pc64-x86 + Mac OS X
- Activation Method: Licence
- Licence type: for 1PC (lifetime and permanent) and includes all modules
- Database: COSMO-RS ADFCRS-POLYMERS + COSMO-RS Database ADFCRS
- Note: If you need older versions of the software, please contact us.
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