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The tutorial 8th
Describes how PyXplore processes X-ray photoelectron spectroscopy (XPS) data.
coding
1. Save your XPS data to the root directory and rename the file to
int.csv.
# import PyXplore package
from PyXplore import WPEM
import pandas as pd
2. Parse your diffraction data (
bing energy, intensity) and perform background processing.
intensity_csv = pd.read_csv(r'int.csv',header=None )
var = WPEM.BackgroundFit(intensity_csv,segement=[[910,931],[948,952],[958,959],[966,970]],bac_num=120,Model='XPS',noise = 0.05,bac_var_type='multivariate gaussian')
3. After running the code, a new folder named
ConvertedDocumentswill be created in the root directory. This folder contains the background information.
Copy the two important files —
bac.csvandno_bac_intensity.csv— fromConvertedDocumentsinto the root directory, as they are required for the next steps.
A key difference with XPS is that the initial binding energy needs to be queried and input using two parameters: `AtomIdentifier` and `satellitePeaks`.**
AtomIdentifier = [['CuII','2p3/2',933.7,],['CuII','2p1/2',954,],]
satellitePeaks = [['CuII', '2p3/2',941.6,],['CuII','2p3/2',943.4],['CuII','2p1/2',962.5,],]
# The file name of non-background data
no_bac_intensity_file = "no_bac_intensity.csv"
# The file name of raw/original data
original_file = "int.csv"
# The file name of background data
bacground_file = "bac.csv"
# Execute the model
WPEM.XPSfit(
var, AtomIdentifier, satellitePeaks,no_bac_intensity_file, original_file, bacground_file,
bta = 0.80,iter_max = 50,
)
The results are saved in the
XPSFittingProfilefolder.