Subtract Radiated from Background Spectrum to Analyze Absorption Spectrum

In summary, the conversation is about using excel to subtract the background spectrum from the signal spectrum in order to analyze the absorption spectrum. The participants discuss whether to subtract the radiated or background spectrum, the units and concentration used, and the difficulty in getting a good subtraction spectrum due to the noise-to-signal ratio. They also discuss the shape and spread of the spectra and the importance of getting the correct x-axis units.
  • #1
Jhon81
12
0
Hi everyone,
I have an absorption spectrum that I obtained from a sample after radiation and I need to use the background sample as a reference, how can I do that using excel?

what I did is subtract the radiated from the background spectrum then plot it, is that right?

Thanks.
 
Physics news on Phys.org
  • #2
I would subtract the background from the signal not the opposite way, but anyway, that is just a sign.

If you don't run into a problem with statistical fluctuations that approach should be fine. More context would be useful, however.
 
  • #3
To do a correct subtraction you should do it in absorbance mode, not transmittance; but perhaps you already knew that.
 
  • #4
Thanks, mfb and mjc123 for your comments.
I subtracted the background from the signal but after plotting it seems that the points have spread! why is that?
subtraction.png

then I tried to add them and the shape of the plot was looking more nicer, could someone explain what happened to me?
adding.png
 

Attachments

  • adding.png
    adding.png
    9.5 KB · Views: 657
  • subtraction.png
    subtraction.png
    7.4 KB · Views: 666
  • #5
Why did you add them?
Can you show your sample and background spectra? It looks as if they are very similar, so the subtracted signal is much weaker than either spectrum. That's why the noise-to-signal ratio is much greater on your subtracted spectrum (I assume that's what you mean by the points "spreading").
What are your y-axis units? If they are mAU, then your spectrum looks a bit too strong for accurate quantitative analysis. Can you repeat the experiment at a lower concentration?
 
  • #6
mjc123 said:
Why did you add them?
Can you show your sample and background spectra? It looks as if they are very similar, so the subtracted signal is much weaker than either spectrum. That's why the noise-to-signal ratio is much greater on your subtracted spectrum (I assume that's what you mean by the points "spreading").
What are your y-axis units? If they are mAU, then your spectrum looks a bit too strong for accurate quantitative analysis. Can you repeat the experiment at a lower concentration?
I added them to see the shape of the spectrum.
This is the spectra of the background and the first irradiated sample, respectively:
background.png
1st irradiated.png

As for the unit, I am not sure as it was my first time using that spectrometer, I am going to check and let you know.
If you mean the concentration of irradiated sample it is very law ( I am using FXO with Fe+2 (0.3mM) & XO (0.05mM)) all of them dissolved in 50 mM of H2SO4.
 

Attachments

  • background.png
    background.png
    6.9 KB · Views: 555
  • 1st irradiated.png
    1st irradiated.png
    7.2 KB · Views: 575
Last edited:
  • #7
What are your x-axis units here? You have very similar spectra, but one with the maximum at ca. 650 (nm? that would make sense) and the other at ca. 1800 (what? is it simply data point number in excel? I doubt very much if you scanned down to 0 nm!)
If you ran your spectra in a 10 mm cuvette, try using a 1 mm cuvette.
But I think you'll find it difficult getting a good subtraction spectrum. The difference between the spectra is of the same order of magnitude as the noise - as you found!
 
  • #8
mjc123 said:
What are your x-axis units here? You have very similar spectra, but one with the maximum at ca. 650 (nm? that would make sense) and the other at ca. 1800 (what? is it simply data point number in excel? I doubt very much if you scanned down to 0 nm!)
If you ran your spectra in a 10 mm cuvette, try using a 1 mm cuvette.
But I think you'll find it difficult getting a good subtraction spectrum. The difference between the spectra is of the same order of magnitude as the noise - as you found!

The x-axis unite is nm. I tried to compare the 4th irradiated with the background
background spectra
background.png

4th irradiated spectra
4th irradiated.png

subtraction of the above spectrums
subtraction2.png

Is it good that the spectra are in the minus y-axis or not, but I noticed that the points are not very spread which makes the noise less right?
 

Attachments

  • background.png
    background.png
    6.8 KB · Views: 518
  • 4th irradiated.png
    4th irradiated.png
    10.8 KB · Views: 593
  • subtraction2.png
    subtraction2.png
    6.3 KB · Views: 549
  • #9
This is a bit better. You can see that the peak at 600 nm is reduced in the irradiated spectrum. This presumably corresponds to your negative peak at "1500" in the subtraction spectrum - get your x-axis units right. Yes, you should subtract the background from the irradiated spectrum, so your peak is negative.. Again, what do you mean by the points being "not very spread"?
 
  • #10
mjc123 said:
This is a bit better. You can see that the peak at 600 nm is reduced in the irradiated spectrum. This presumably corresponds to your negative peak at "1500" in the subtraction spectrum - get your x-axis units right. Yes, you should subtract the background from the irradiated spectrum, so your peak is negative.. Again, what do you mean by the points being "not very spread"?
what do you mean to get my x-axis unit right?
In this picture, you can see that the points are very spread ( the spectra is not smooth)
subtraction.png


but in the second one, it is smoother.

subtraction2.png
 

Attachments

  • subtraction.png
    subtraction.png
    7.4 KB · Views: 479
  • subtraction2.png
    subtraction2.png
    6.3 KB · Views: 543
  • #11
Jhon81 said:
what do you mean to get my x-axis unit right?
Your measured spectra are from 200 to 1100 nm. Why does the difference have x values of 0 to 3500?
Jhon81 said:
In this picture, you can see that the points are very spread ( the spectra is not smooth)
That tells you that there is some noise in the measurement. Not surprising.
Jhon81 said:
but in the second one, it is smoother.
The signal (the true difference) is stronger, so the signal to noise ratio is better.
 
  • #12
@Jhon81 In one case it appears you are graphing wavelength on the x-axis in nm and in the other case, you are apparently doing wavenumber=## \frac{1}{\lambda} ## (cm^-1). It is difficult to try to analyze the results unless this is consistent. You must at least state that you made the conversion. ## \\ ## Edit: But that doesn't appear to be the case either. It leaves us guessing...
 
  • #13
It can't be that because the spectra aren't reversed. It seems to be that sometimes you are plotting an x-y chart with wavelength as the x-value and absorbance as the y-value; other times you are just plotting a y chart, with the absorbance as the y value and the data point number (looks like you have about 3700 data points)appears as the x value. You want to get some more practice plotting charts in excel (or whatever you use).
 

What is the purpose of subtracting the radiated spectrum from the background spectrum?

The purpose of subtracting the radiated spectrum from the background spectrum is to isolate the absorption spectrum. This allows us to analyze the specific wavelengths of light that are being absorbed by a sample.

How is the radiated spectrum determined?

The radiated spectrum is determined by measuring the light emitted by a source without any sample present. This gives us a baseline to compare the background spectrum and absorption spectrum against.

What is the significance of the background spectrum?

The background spectrum represents the light that is not being absorbed by the sample. By subtracting it from the overall spectrum, we are left with only the wavelengths of light that are being absorbed, allowing us to identify the components of the sample.

What factors can affect the accuracy of subtracting the radiated spectrum from the background spectrum?

Factors such as ambient light, sensor noise, and instrument drift can affect the accuracy of subtracting the radiated spectrum from the background spectrum. It is important to control for these factors to ensure accurate results.

How does this method compare to other methods of analyzing absorption spectra?

Subtracting the radiated spectrum from the background spectrum is a common and reliable method used in spectroscopy. It allows for precise analysis of absorption spectra and is often used in combination with other techniques for a more comprehensive understanding of the sample's properties.

Similar threads

  • Atomic and Condensed Matter
Replies
2
Views
1K
Replies
3
Views
1K
  • New Member Introductions
Replies
5
Views
107
Replies
3
Views
370
  • Atomic and Condensed Matter
Replies
1
Views
2K
  • Astronomy and Astrophysics
Replies
17
Views
6K
Replies
29
Views
2K
Replies
4
Views
2K
  • Astronomy and Astrophysics
Replies
3
Views
904
Replies
2
Views
1K
Back
Top