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## Background
Example problem on Data Processing - Optical Emission Spectroscopy
- Import xls data into Python
- Plot the Intensity [a.u.] vs pixels
- Interpolate and convert x-axis from pixels to nm (true wavelength) using Hg lamp data (using data in file: Lampa_Calibrare_Mercur.xlsx)
- Find response function of the spectrometer using the tungsten lamp data from file: "Calibrare Intensitate Oxigen.xlsx)": R=I_measured/I_true (where True is computed by Planck's law of radiation (see notes in the pptx above)
- Convert y-axis from Intensity [a.u.] into Intensity in [W/(cm^2*sr*nm)] by dividing the measured Oxygen spectrum with the response function: I_oxygen_true=I_oxygen_measured/R
- Once the spectra is in real units: compute the density of one of the oxygen lines by integrating underneath one of the peaks (see equation from Slide 39 - bottom). We will give all of the constants that are in this equation (see the "Intensity_Calibration_Oxygen_Discharge_Solution.xlsx")
Problem 1: Import the data as a pandas dataframe.
Problem 2: Using the known wavelength intensities of mercury, identify the wavelengths.
Problem 3:
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