Welcome to PyTASER’s documentation!#
Introduction#
PyTASER
is a Python
(3.9+) library built for simulating transient absorption spectroscopy (TAS) features from
DFT calculations. The goal of this library is to simulate TAS spectra for comparison with and interpretation of
experimental spectra. The main features include:
An interactive TAS spectrum for a pristine semiconducting crystal
Isolated spectra for individual band transitions
Spectra for different conditions: temperature and carrier concentrations
Consideration of non-magnetic and magnetic materials
Capability to input calculated bandstructures and density of states inputs with support for https://materialsproject.org.
Background#
TAS is a powerful pump-probe tool to characterise the excited states of materials. It can be used to understand microscopic processes in photochemical and electrochemical transformations, including phenomena such as electron trapping and carrier recombination.
The drawback is that TAS spectra are difficult to interpret, especially for crystals where the specific valence and conduction band structure can give rise to complex features. Our goal here is to predict TAS features from first-principles starting from the most simple models of static excitations through to the kinetics of relaxation of the excited state back to the ground state.
Installation#
To install the module with pip
(recommended):
pip install pytaser
To install directly from the git repository:
pip install git+https://github.com/WMD-group/PyTASER
To do a manual build and installation:
python3 setup.py build
python3 setup.py install
Developer’s installation (optional)#
For development work, PyTASER
can also be installed from a copy of the source directory:
Download PyTASER
source code using the command:
git clone https://github.com/WMD-group/PyTASER
Navigate to root directory:
cd PyTASER
Install the code with the command:
pip install -e .
This command tries to obtain the required packages and their dependencies and install them automatically.
Dependencies#
PyTASER
is currently compatible with Python 3.9+
and relies on a number of open-source python packages, specifically:
matplotlib for plotting the spectra
Visualisation#
The preferred method is to generate a Jupyter
Notebook, as shown in the examples folder.
Alternatively, you can setup a Python
file to run it in the command line of the terminal:
python3 <filename.py>
Contributing#
We appreciate any contributions in the form of a pull request.
Additional test cases/example spectra performed with PyTASER
would be welcomed.
Please feel free to reach out to us if there are any questions or suggestions.
Future topics we plan to build on:
Incorporating finite-temperature effects (particularly for indirect bandgaps)
Description of more complex optical processes (e.g. stimulated emission)
Direct treatment of pump-probe time delay
Incorporating spin-flip processes for spin-polarised systems
Description of defective crystals
Acknowledgements#
Developed by Savyasanchi Aggarwal and Alex Ganose. Aron Walsh helped to design the project. Thanks to group members for their support, especially Seán Kavanagh, Youngwon Woo, Anahita Manchala and Liam Harnett-Caulfield.