eDoping 0.4.0

A high-throughput software package for evaluating point defects

eDoping

A high-throughput software package for evaluating point defects.

Online Documentation

• English: https://jianbohit.github.io/eDoping/en/
• 简体中文: https://jianbohit.github.io/eDoping/

Installiation

The eDoping package is built on Python3, so please ensure that it is properly installed on your system. If the network is available, the most efficient way to install (or update) the eDoping package is via pip (or pip3):

pip install -U eDoping

If you do not have internet access or are interested in the source code, You can download the source code from GitHub using the following command:

git clone https://github.com/JianboHIT/eDoping.git

For users in mainland China, the source code is also available on Gitee. You can clone it using a similar command:

git clone https://gitee.com/joulehit/eDoping.git

After downloading the source code, navigate to the folder (make sure to unzip it if you downloaded it as a zip file) and ensure your internet connection is stable. Then, you can use pip (or pip3) to automatically install the package along with its dependencies, which primarily include NumPy and SciPy:

pip install .

Once the installation is complete, you can start using the eDoping package with the edp command. To verify that the installation was successful, you can use the -h (or --help) option to display the help information:

edp -h

This will print out the help information for the eDoping package, including all available sub-commands.

How to Cite

[1] J. Zhu, J. Li, Z. Ti, L. Wang, Y. Shen, L. Wei, X. Liu, X. Chen, P. Liu, J. Sui, Y. Zhang, eDoping: A high-throughput software package for evaluating point defect doping limits in semiconductor and insulator materials, Materials Today Physics, 55 (2025) 101754, https://doi.org/10.1016/j.mtphys.2025.101754.

[2] J. Li, J. Zhu, Z. Ti, W. Zhai, L. Wei, C. Zhang, P. Liu, Y. Zhang, Synergistic defect engineering for improving n-type NbFeSb thermoelectric performance through high-throughput computations, Journal of Materials Chemistry A, 10 (46) (2022) 24598-24610, https://doi.org/10.1039/d2ta07142h.