mDCThermalC is a modern implementation of the Debye-Callaway model for thermal conductivity calculation. But we expand this theory, optimize its calculating process. All of these efforts makes this software be able to calculating thermal conductivity quickly and accurately without needing any transcendental parameter, this is especially important for high-throughput calculation. Beside thermal conductivity, one can also obtain other useful information such as contribution rate of acoustic branch and optic branch repectively, scattering rate of different scattering mechanism like normal process and umklapp process. For more information, check out our article.
mDCThermalC has a DOI:10.5281/zenodo.3371097, you can cite this code like this:
Tao Fan. (2019, August 19). Baijianlu/mDCThermalC: mDCThermalC (Version v1.1.1). Zenodo. http://doi.org/10.5281/zenodo.3371097
mDCThermalC is a Python module. mDCThermalC's runtime requirements are Python version 3.5 or higher, and the Python libraries NumPy, SciPy, spglib and pymatgen. All of them can be easily obtained from the Python Package Index (PyPI), using tools such as pip. They may also be bundled with Python distributions aimed at scientists, like Anaconda, and with a number of Linux distributions. Here we recommend to use Anaconda so that dependencies should be resolved automatically.
Users installing from source must install the dependencies first and then run:
$ python setup.py install
The distribution includes four examples: diamond, Si, SnSe, Mg2Si. The former three examples are also described in the mDCThermalC paper. Read /doc/UserManual to learn how to use this software and more information about the output files.