MonaLisa
The multi-level optimizer for molecules and extended systems
Description
Monalisa is an optimizer for molecules and extended systems.
The unique feature is a generalized subtractive QM:QM:... scheme, i.e. a system (molecule) can be divided into arbitrary number of sub-parts which can be treated using different quantum chemistry methods. MonaLisa drives the optimization of the supersystem.
Key features of the program:
- structure minimizations, a transition state search, and a molecular dynamics module
- thermodynamic properties calculations within harmonic and decoupled anharmonic approximations
- interfaces to most of the popular quantum chemistry programs: Turbomole, ORCA, VASP, CP2K, gulp, Crystal, Gaussian and MOLPRO
Documentation
The full user manual is available here, the older documentation is available here
Access to MonaLisa source code
MonaLisa is a free software which may be obtained from the authors of the code on request after signing the license agreement. To get the code please send us the scan of the licence agreement to rybickim@chemie.hu-berlin.de
After that you should:
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Login to the GitLab server of Huboldt-University or create a guest account (valid for two weeks).
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Go to the git repository of the MonaLisa project and click Request Access button next to the project logo. The access will be granted by the code maintainer as soon as possible.
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After gaining the access, you should be able to download the latest release of the source code (Project overview -> Releases) or clone the source code of the project.
How to cite MonaLisa
Until now the code has not been published. Therefore if you use MonaLisa please cite the code as:
M. Alessio, F. Bischoff, J. Sauer Chemically Accurate Adsorption Energies for Methane and Ethane Monolayers on the MgO(001) Surface, Phys. Chem. Chem. Phys. 20 (2018) 9760-9769
and:
F. Bischoff, M. Alessio, F. Berger, M. John, M. Rybicki and J. Sauer, Multi-Level Energy Landscapes: The MonaLisa Program (https://www.chemie.hu-berlin.de/de/forschung/quantenchemie/monalisa/), Humboldt-University: Berlin, 2019