The goal of Learn Molecular Simulations with Python is to write a simple code containing most of the basic functionalities of molecular simulations:
- Energy minimization,
- Molecular dynamics
- Monte Carlo displacement/insertion/deletion
The target audience is people either completely new to molecular simulations, or users of user-friendly codes such as LAMMPS and GROMACS wanting to better understand what is hiding behind those codes.
The Python code that will be written here will be used to realize some simple scientific projects. Note that the code is slow and that efficiency is not the objective of the present project.
Although some basic knowledge in coding, thermodynamics, and statistical physics is recommended to fully understand molecular simulations, Learning molecular simulations with Python can be followed even without deep knowledge in those fields. Annexes with key concepts and suggested readings are given when necessary.
- molecules
- thermostats and barostats other than Berendsen
- energy minimization methods other than the steepest descent
- non-cubic boxes
I am a computer physicist in soft matter and fluids at interfaces. You can find more information on my personal webpage.
All the inputs, scripts, and data files are released under the GNU general public license v3.0.
This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 101065060.
