Machine Learning Approach for Predicting Coordination Numbers from EXAFS Spectra

This dataset contains the following files:JSON files: Contain the original information for the models. XAS_Energy and XAS_Intensity correspond to the x-axis and y-axis of the XAS spectrum, respectively; group_test and group_test_k correspond to the spectral data in R-space and k-space; average_cn corresponds to the first-shell coordination number of the central atom in the model (since we only study models with integer coordination numbers, data where the coordination number is not an integer should be discarded).CSV files: Contain the raw information for machine learning.

The "XX_with_peaks.csv" file contains the x and y coordinates of the XAFS spectrum in R-space, the position and height of the R-space peaks, and the central atom coordination number corresponding to each data point. "FFT_Intensity_xx" describes the y-coordinate value corresponding to the R-space x-coordinate of xx; "peak1_freq" and "peak1_int" describe the x and y coordinates corresponding to the apex of the largest peak in R-space for that spectrum; "coordination_number" corresponds to the central atom coordination number for the spectrum.