Software

The cutting-edge research at the Center for Molecular Modeling is often made possible by new software tools that we develop in-house. Notwithstanding our contributions to publicly available software, e.g. AMS, LAMMPS, Wien2k, we make most of our software available under open source licenses. You can support our work by using the tools we develop and by citing the corresponding papers.

The list below highlights our recent developments and provides links to important information, such as the documentation and how to cite it in publications using the software.

STACIE

STACIE is a Python package and algorithm that computes time integrals of autocorrelation functions. It is primarily designed for post-processing molecular dynamics simulations. However, it can also be used for more general analysis of time-correlated data. Typical applications include estimating transport properties and the uncertainty of averages over time-correlated data, as well as analyzing characteristic timescales.

Documentation | https://molmod.github.io/stacie/

Git repository | https://github.com/molmod/stacie

How to cite | [1] G. Toraman, D. Fauconnier, and T. Verstraelen “STable AutoCorrelation Integral Estimator (STACIE): Robust and accurate transport properties from molecular dynamics simulations” J. Chem. Inf. Model. 65(19), pp. 10445–10464 (2025) doi:10.1021/acs.jcim.5c01475, arXiv:2506.20438.

psiflow

Psiflow is a modular and scalable library for developing interatomic potentials. It uses Parsl to interface popular trainable interaction potentials with quantum chemistry software, and is designed to support computational workflows on hundreds or thousands of nodes.

Documentation | https://molmod.github.io/psiflow

Git repository | https://github.com/molmod/psiflow

How to cite | [1] S. Vandenhaute, M. Cools-Ceuppens, S. DeKeyser, T. Verstraelen, V. Van Speybroeck. Machine learning potentials for metal-organic frameworks using an incremental learning approach. npj Comput Mater , 9, 19 (2023). https://doi.org/10.1038/s41524-023-00969-x

GPXRDpy

GPXRDpy is a python wrapper for PXRD pattern calculation based on pyobjcryst, which allows for (i) an easy CLI-based PXRD calculation using .cif files, (ii) a similarity analysis of two PXRD patterns, (iii) a background signal removal, and (iv) the calculation of a dynamically averaged PXRD pattern using a trajectory .h5 file.

Documentation | https://molmod.github.io/gpxrdpy

Git repository | https://github.com/molmod/gpxrdpy

How to cite | [1] S. Borgmans, S.M.J. Rogge, J.S. De Vos, C.V. Stevens, P. Van Der Voort, V. Van Speybroeck. Quantifying the Likelihood of Structural Models through a Dynamically Enhanced Powder X-Ray Diffraction Protocol. Angew. Chem. Int. Ed., 60, 16 (2021). https://doi.org/10.1002/anie.202017153

MicMec

MicMec implements the micromechanical model, a systematic coarse-grained procedure to access larger length and longer time scales in mechanical simulations of nanostructured materials. As a hierarchical method, it takes atomic-level stiffness tensors and cell matrices at equilibrium for input, allowing for a straightforward comparison with experiment.

Documentation | https://molmod.github.io/micmec

Git repository | https://github.com/molmod/micmec

How to cite | [1] J. Vandewalle, J. S. De Vos and S. M. J. Rogge. MicMec: Developing the Micromechanical Model to Investigate the Mechanics of Correlated Node Defects in UiO-66. J. Phys. Chem. C, 127, pp. 6060-6070 (2023). https://doi.org/10.1021/acs.jpcc.3c00451 [2] S. M. J. Rogge. The micromechanical model to computationally investigate cooperative and correlated phenomena in metal-organic frameworks. Faraday Discuss., 225, pp. 271–285 (2020). https://doi.org/10.1039/C9FD00148D

ThermoLIB

ThermoLIB is a Python/Cython library to construct and manipulate free energy surfaces (FES) as a function of a (set of) priori chosen collective variable(s) from output of molecular simulations. The package allows to transform, project and deproject the FES a posteriori to different collective variables as well as to extract thermodynamic and kinetic properties. Furthermore, ThermoLIB also fully supports error estimation on these properties.

Documentation | https://molmod.github.io/ThermoLIB

Git repository | https://github.com/molmod/ThermoLIB

How to cite | M. Bocus, L. Vanduyfhuys, ThermoLIB - A Python Library for Constructing and Post-Processing Free Energy Surfaces to Extract Thermodynamic and Kinetic Properties, arXiv:2601.23071 (2026). https://doi.org/10.48550/arXiv.2601.23071

QuickFF

QuickFF is a software package to derive accurate force fields for isolated and complex molecular systems in a quick and easy manner. The force field parameters for the covalent interaction are derived from ab initio data, i.e. an equilibrium structure and a Hessian matrix, which needs to be produced by the user. QuickFF is a tool that can easily be used by anyone with a basic knowledge of performing ab initio calculations. As a result accurate force fields are generated with minimal effort.

Documentation | http://molmod.github.io/QuickFF

Git repository | https://github.com/molmod/QuickFF

How to cite | [1] L. Vanduyfhuys, S. Vandenbrande, T. Verstraelen, R. Schmid, M. Waroquier, V. Van Speybroeck. QuickFF: A Program for a Quick and Easy Derivation of Force Fields for Metal-Organic Frameworks from Ab Initio Input. Journal of Computational Chemistry, 36(13), pp. 1015-1027 (2015). https://doi.org/10.1002/jcc.23877 [2] L. Vanduyfhuys, S. Vandenbrande, J. Wieme, M. Waroquier, T. Verstraelen, V. Van Speybroeck. Extension of the QuickFF Force Field Protocol for an Improved Accuracy of Structural, Vibrational, Mechanical and Thermal Properties of Metal-Organic Frameworks. Journal of Computational Chemistry, 39(16), pp. 999-1011 (2018). https://doi.org/10.1002/jcc.25173

CheMPS2

A free open-source spin-adapted implementation of the density matrix renormalization group for ab initio quantum chemistry

Documentation | http://sebwouters.github.io/CheMPS2/index.html

Git repository | https://github.com/SebWouters/CheMPS2

How to cite | [1] S. Wouters, W. Poelmans, P. W. Ayers and D. Van Neck. CheMPS2: a free open-source spin-adapted implementation of the density matrix renormalization group for ab initio quantum chemistry. Computer Physics Communications, 185 (6), pp. 1501-1514 (2014). https://doi.org/10.1016/j.cpc.2014.01.019 [2] S. Wouters and D. Van Neck. The density matrix renormalization group for ab initio quantum chemistry. European Physical Journal D, 68 (9), 272 (2014). https://doi.org/10.1140/epjd/e2014-50500-1 [3] S. Wouters, T. Bogaerts, P. Van Der Voort, V. Van Speybroeck and D.Van Neck. Communication: DMRG-SCF study of the singlet, triplet, and quintet states of oxo-Mn(Salen). Journal of Chemical Physics 140 (24), 241103 (2014). https://doi.org/10.1063/1.4885815 [4] S. Wouters, V. Van Speybroeck and D. Van Neck. DMRG-CASPT2 study of the longitudinal static second hyperpolarizability of all-trans polyenes. Journal of Chemical Physics 145 (5), 054120 (2016). https://doi.org/10.1063/1.4959817

TAMkin

TAMkin is a post-processing toolkit for normal mode analysis, thermochemistry and reaction kinetics. It uses a Hessian computation from a standard computational chemistry program as its input. CHARMM, CP2K, CPMD, GAMESS, GAUSSIAN, QCHEM and VASP are supported. Multiple methods are implemented to perform a normal mode analysis (NMA). The frequencies from the NMA can be used to construct a molecular partition function to derive thermodynamic and kinetic parameters.

Documentation | http://molmod.github.io/tamkin

Git repository | https://github.com/molmod/tamkin

How to cite | [1] A. Ghysels, T. Verstraelen, K. Hemelsoet, M. Waroquier, V. Van Speybroeck. J. Chem. Inf. Model., 50, pp. 1736-1750 (2010). http://dx.doi.org/10.1021/ci100099g

HORTON

Motivated by our frustration with the difficulty of adding new features to existing quantum chemistry programs, we decided to create our own Helpful Open-source Research TOol for N-fermion systems (HORTON). The emphasis here is on the world helpful. HORTON is not intended to be a replacement for existing quantum chemistry software, but a helpful supplement to it. Our ambition is to provide a research tool that is computationally-efficient enough to be helpful, without compromising code-readability and user-friendliness. Our hope is that users will find HORTON helpful for developing and exploring new methods, for interpreting the results of electronic structure calculations, and for interacting with other computational modeling software.

Documentation | http://theochem.github.io/horton

Git repository | https://github.com/theochem/horton

How to cite | [1] M. Chan, T. Verstraelen, A. Tehrani, M. Richer, X. D. Yang, T. D. Kim, E. Vöhringer-Martinez, F. Heidar-Zadeh and P. W. Ayers "The tale of HORTON: lessons learned in a decade of scientific software development" (2024) J. Chem. Phys. 160(16). http://doi.org/10.1063/5.0196638

Yaff

Yaff is created to provide a good reference implementation of the force fields developed at the Center for Molecular Modeling at the Ghent University. In its current version, Yaff is general and flexible enough to handle a large variety of force field models.

Documentation | http://molmod.github.io/yaff

Git repository | https://github.com/molmod/yaff

How to cite | [1] T. Verstraelen, L. Vanduyfhuys, S. Vandenbrande, S. M. J. Rogge. Yaff, yet another force field, http://molmod.github.io/yaff/.

MD-Tracks

MD-Tracks is a trajectory analysis toolkit for molecular dynamics and Monte Carlo simulations. It is designed to interact with several simulation codes that generate trajectory data: CP2K, CPMD, DLPOLY, GROMACS, LAMMPS. The trajectory output files are first converted into a in a uniform binary format, which can then be processed with a bundle of analysis scripts, e.g. for the analysis of vibrational spectra, diffusion constants, radial distribution functions, and so on.

Git repository | https://github.com/molmod/md-tracks

How to cite | T. Verstraelen, M. Van Houteghem, V. Van Speybroeck, M. Waroquier. J. Chem. Inf. Model., 48, pp. 2414-2424 (2008). http://dx.doi.org/10.1021/ci800233y

Zeobuilder

Zeobuilder is a user-friendly GUI toolkit for the construction of advanced molecular models (biological, inorganic, reactants in a catalyst, …). The program contains several advanced tools to build, align, manipulate and analyze molecular structures. Most of its novel functionality is based on a hierarchical data-structure of reference frames to represent a molecular structure. Furthermore, Zeobuilder is extensible. The core program is compact and nearly all of the functionality is implemented through a plug-ins.

Documentation | http://molmod.github.io/zeobuilder

Git repository | https://github.com/molmod/zeobuilder

How to cite | [1] T. Verstraelen, V. Van Speybroeck, M. Waroquier. J. Chem. Inf. Model, 48, pp. 1530-1541 (2008). http://dx.doi.org/10.1021/ci8000748

CmmDFT

CmmDFT is a python software package for running classical Density Functional Theory simulations for computing adsorption and diffusion properties of guest molecules confined in nanoporous materials.

Documentation | (coming soon)

Git repository | https://github.com/molmod/CmmDFT

How to cite | V. De Ridder, L. Vanduyfhuys, Fluid Phase Equilibrium 611 (2027), 114796, 10.1016/j.fluid.2026.114796

Our contributions

OpenMM

One of our PhD students has contributed to the open-source software OpenMM with a Monte Carlo pressure control algorithm that allows for fully anisotropic unit cell fluctuations.

[Website OpenMM] https://openmm.org

[Website algorithm] http://docs.openmm.org/latest/api-python/generated/openmm.openmm.MonteCarloFlexibleBarostat.html#openmm.openmm.MonteCarloFlexibleBarostat

[Publication] https://doi.org/10.3389/fchem.2021.718920