Example Trajectory Data and Jupyter Notebooks Showing How to Compute Various Properties with STACIE

Example Trajectory Data and JupyterNotebooks Showing How to ComputeVarious Properties with STACIEGözdenur Toraman† and Toon Verstraelen✶¶† Soete Laboratory, Ghent University, Technologiepark-Zwijnaarde 46, 9052 Ghent, Belgium¶ Center for Molecular Modeling (CMM), Ghent University, Technologiepark-Zwijnaarde 46, B-9052,Ghent, Belgium✶E-mail: [email protected]UsageTo run the example notebooks, you need to:1.Install STACIE and Jupyter Labpip install stacie jupyterlab 2.Download and unpack the archive with notebooks and trajectory data.unzip examples.zip 3.Finally, you should be able to start Jupyter Lab and run the notebooks.jupyter lab Overview of included filesSome Jupyter notebooks generate data and then analyze it, while others directly analyze existing data.Examples that do not need existing trajectory data:•minimal.py: Minimal example of how to use STACIE, with detailed description of outputs.•error_mean.py: Uncertainty of the mean of time-correlated data•applicability.py: Applicability of the Lorentz model•surface_diffusion.py: Diffusion of an argon atom on a surfaceExamples that analyze existing trajectory data:•lj_shear_viscosity.py: Shear viscosity of a Lennard-Jones fluid•lj_bulk_viscosity.py: Bulk viscosity of a Lennard-Jones fluid•lj_thermal_conductivity.py: Thermal conductivity of a Lennard-Jones fluid•molten_salt.py: Ionic electrical conductivity of a molten salt systemThis second set of notebooks use MD data from the following sources:•lammps_lj3d: LAMMPS simulations of Lennard-Jones 3D systems•openmm_salt: OpenMM simulations of molten salt systems