[ChemRxiv] | [Paper]
Welcome to DebyeCalculator! This is a simple tool for calculating the scattering intensity I(q) through the Debye scattering equation, the Total Scattering Structure Function S(q), the Reduced Total Scattering Function F(q), and the Reduced Atomic Pair Distribution Function G(r) from an atomic structure. The Debye scattering equation can be used to compute the scattering pattern of any atomic structure and is commonly used to study both crystalline and non-crystalline materials with a range of scattering techniques like powder diffraction (PD), total scattering (TS) with pair distribution function (PDF) and small-angle scattering (SAS). Although the Debye scattering equation is extremely versatile, its applicability has been limited to smaller atomic structures because of the computation of the double sum scales as O(n2) with the number of atoms. However, here we provide an optimised code for the calculation of the Debye scattering equation on Graphics processing units (GPUs) which accelerate the calculations with orders of magnitudes.
Currently DebyeCalculator is not avaible through PyPI or conda so the package needs to be downloaded manually Run the following command to install the DebyeCalculator package.
pip install .
or
python setup.py install
# Authors
__Frederik L. Johansen__<sup>1</sup><sup>, 2</sup>
__Andy S. Anker__<sup>1</sup>
<sup>1</sup> Department of Chemistry & Nano-Science Center, University of Copenhagen, Denmark
<sup>2</sup> Department of Computer Science, University of Copenhagen, Denmark
Should there be any questions, desired improvements or bugs please contact us on GitHub or
through email: __frjo@di.ku.dk__ and __andy@chem.ku.dk__.
# Cite
If you use our code or our results, please consider citing our paper. Thanks in advance!
@article{Johansen_anker2023debye, title={A GPU-Accelerated Open-Source Python Package for Rapid Calculation of the Debye Scattering Equation: Applications in Small-Angle Scattering, Powder diffraction, and Total Scattering with Pair Distribution Function Analysis}, author={Frederik L. Johansen, Andy S. Anker, Ulrik Friis-Jensen, Erik B. Dam, Kirsten M. Ø. Jensen, Raghavendra Selvan}, journal={XXXX} year={2023}}