June 06, 2020, 10:15:14 AM
Forum Rules: Read This Before Posting

Topic: Data Analysis: Calibration Curve for ICP-OES  (Read 7456 times)

0 Members and 1 Guest are viewing this topic.

Offline MrHappy0

  • Regular Member
  • ***
  • Posts: 68
  • Mole Snacks: +1/-3
Data Analysis: Calibration Curve for ICP-OES
« on: March 28, 2014, 12:47:16 PM »
It's been a while since I've been on here. So I am back because I need help figuring out where I'm going wrong during data analysis for an ICP-OES lab. The objective is to quantify (ppm) certain metals in samples. Our methods involved Calibration Curves and Standard Addition. 20+ hours of data analysis and I'm still stuck on formulating calibration curves for each element and wavelength.

For each known stock solution we did two duplicate trials for statistical comparison. With the data from each calibration curve, I charted Intensity (corr) vs. Calculated Concentration (known). Attached is a screenshot of my excel work for Mg at 280.27nm. You will see the calibration curve is a nice straight line and it doesn't seem there are any visible outliers. I made a residual error plot to show how far each point comes from the linear regression line. There is also my statistical tests to determine if the slopes are equivalent. As you will see p<0.05 and my t>tcrit telling me the slopes are different.

I've spent hours trying outlier elimination and out of desperation and curiosity fudged data to see how I could make the slopes equivalent. Nothing really works for any of my elements!

I've concluded I must be making a terrible error somewhere and wanted to see if anyone could point it out. Please take a quick look at my attached document.

I'm thinking that maybe I should be converting the Intensity to something else or making background corrections from the DI water but not sure.

Also, I realize different elements and wavelengths might have different LOD, matrix effects but this doesn't explain why all my data isn't working out.

Offline Irlanur

  • Chemist
  • Full Member
  • *
  • Posts: 422
  • Mole Snacks: +32/-4
Re: Data Analysis: Calibration Curve for ICP-OES
« Reply #1 on: April 03, 2014, 09:51:14 AM »
So this are duplicates of something you expected to be the same? I don't think that the error lies in data-analysis, you don't have to do some fancy statistics to see that... they are obviously different^^.

It would be nice if you plotted the confidence intervalls. (and if you wouldn't use excel, but thats my opinion.)

I would guess: -systematic drift in the lamp, the gasflow the plasma or whatsoever.

-did you check if there was any backgrounddrift? I never practically used ICO-OES, but e.g. in UV-Vis the drifts of the lamp-power can be significant.

Offline MrHappy0

  • Regular Member
  • ***
  • Posts: 68
  • Mole Snacks: +1/-3
Re: Data Analysis: Calibration Curve for ICP-OES
« Reply #2 on: April 15, 2014, 11:16:26 PM »
Oh okay. I'm pretty there was no background drift. And yes, Excel is driving me crazy. Either I am using it terrible inefficient or it was not designed for scientific purposes!

Offline scwilson

  • Regular Member
  • ***
  • Posts: 9
  • Mole Snacks: +2/-0
Re: Data Analysis: Calibration Curve for ICP-OES
« Reply #3 on: April 18, 2014, 03:00:15 PM »
I want to start off by saying that I'm not rightly sure why you have such statistically-significant discrepancies in your curves. I performed a quick, little, ad-hoc analysis using your provided data almost certain that it would support Irlanur's assertion that your results could be explained by instrumental drift, but I don't believe that to be the case after looking over my ad-hoc analysis.

So, I thought I'd just try to add to the conversation in what way I can and see if it helps to elucidate things.

I took the liberty of assuming that you had an unknown that fell right smack dab in the middle of your calibration curve for each replicate measurement (signals of 8.0241E6 and 7.0058E6, respectively). The results were as follows:

Replicate 1: Unknown = 2.09 +/- 0.04 ppm
Replicate 2: Unknown = 1.82 +/- 0.03 ppm

Admittedly, I didn't double-check my work, but I do believe it is correct. Also, I corrected your y-values for the blank. I also did NOT include the blank as a data point (0,0) on your curves. Some analysts do and some don't. Personally, I choose not to. To me, the above results show that a theoretical unknown would yield VERY different values if analyzed by each curve, statistically-speaking. Assuming that your Excel sheet presents things in a chronological fashion, how far apart were these replicate measurements taken? Days, weeks? Minutes? Hours?

This is the part where I start asking you leading questions, MrHappy, and can't, unfortunately, share with you my interpretations. After all, our goal on these forums is to teach moreso than it is to just divulge the answers. But, I will say that I don't think there are absolute answers to all of these questions, only that some answers are more likely than others.

So, these results (again, assuming your Excel sheet is chronological in moving from left to right) suggest that your sensitivity (your slope) lessened with time. Let's assume any intercept problems are insignificant. Does this loss of sensitivity suggest that the concentration of your standards reduced with time (hence yielding lesser instrumental signal) or does it suggest that your instrument was no longer measuring the analytes in your standards as efficiently? Or is a mixture of both problems more likely? How stable were your solutions? What's the "Achilles heel" for instruments like Flame AAs and ICPs? For instance, for gas chromatography work, sample introduction (reproducibility of injection and inlet split) is the Achilles heel. Can you draw any comparisons for an ICP? Do you know the parameters for your ICP's torch, and was it the same across both analyses?

Also, this one detail confuses me deeply: did you really re-measure the DI water blank each time? Or only the first time? I ask because most of your standards had appreciable changes in signal from the first replicate to the second. But your blank, which should arguably have the worst precision (as it contains the least amount of analyte), has no change in signal. SEVEN sig figs? I mean that's better than an analytical balance. That's hard to believe. That would really only make sense if you didn't really re-measure the blank or if your standards were all outside of the working range of the instrument. I will say that some of your standards are a bit concentrated for ICP work. I like to keep things sub-ppm, but your linearity is fine, even wonderful, in fact, so it seems unlikely that that's the problem. Plus, Mg tends to have a much higher concentration working range than other metals, so your range seems fine.

If you REALLY DID re-measure the blank each time and had no change in signal, what does that tell you about the stability of your solutions with time? After all, that blank implies that you should be getting (roughly) 7 sig figs of reproducibility accross each replicate, and you're no where near that. That should REALLY tell you something about your solutions . . .

This should help get you started. Again, I can't rightly say that I know exactly what's going on. I do have some educated thoughts on the matter, but, also, a lot of my conclusions would rest on information only you have (sample prep procedure, sample matrix, primary standard used, instrumental parameters, etc., just to name a few).

I hope this helps at least some.

Offline ydes

  • New Member
  • **
  • Posts: 3
  • Mole Snacks: +1/-0
Re: Data Analysis: Calibration Curve for ICP-OES
« Reply #4 on: May 14, 2014, 04:26:07 PM »
realign the mirrors to max intensity

 with e.g 10-15ppm Mn 252nm
or other metals within that range ( in your case in range of Mg )
both radial and axial ( not needed to do both strictly speaking , depends on your method )

when the view is fixed at 'cooler' spots of the plasma it may give you unrepresentative data. the 2 slopes having to be significantly different is something I find quite hard to believe. usually slopes with bad increment show more error in interpolating X-values relative to slopes that are bigger

 and then offcourse as mentioned before ; correct the drift
ensure proper flow of the sample feed into the torch/plasma

prepare new standards and redo the experiment :)
( you may have already done sorry for the late reply but still, I'm giving you something to reminisce


Sponsored Links