QuantEXAFS

QunatEXAFS is a Python based toolkit that assists in automated fitting of Extended X-ray Absorption Spectroscopy Fine Structures (EXAFS) data using X-ray Larch modules. Larch is an open-source library for processing and analyzing different kinds of x-ray data from synchrotrons. This automated fitting toolkit was developed for atomically dispersed catalysts on transition metal oxide (TMO) supports. The first application of this toolkit was submitted/accepted …link to the paper.

Installation

1. Python
2. X-ray Larch
3. Xraylib
4. Atomic Simulation Environment
5. Clone the QuantEXAFS repository
6. Similarity Measures

Usage This toolkit focusses on using a database of density functional theory (DFT) optimized structures to fit the EXAFS data. The automated nature of the code enables fitting EXAFS for hundreds of structures (whatever number of structures are present in the database) and generating a fit report, k-space and r-space plots along with similarity measures of the plots from experimental and model data using Fréchet distance. The toolkit also contains a code (Atoms2Feff) that converts the atoms object to FEFF input file. Thus, making the EXAFS fitting interface completely automated.

INPUT

1. EXAFS experimental data from beamline (Athena.prj) can be any other format this is just for consistency
2. Database of DFT optimized structures in ase.db format
3. The user needs to define the k-range based on the quality of data and select the absorbing atom for the Atoms2Feff code.

OUTPUT

1. Report generated by Larch
2. Plots in k-space and r-space of the data and the model
3. A text file with similarity measures of the data and the model
4. Feff.inp file that was used to run FEFF calculation

While the current code focuses on the atomically dispersed catalysts the current efforts are directed towards expanding this to other catalytic materials.