Standard Addition Calculator
Concentration from the x-intercept, when the matrix interferes.
Work out Standard Addition. Concentration from the x-intercept, when the matrix interferes. Names the sign error before you make it.
Start with 0 for the unspiked sample. Comma separated.
Absorbance, peak area or counts. Must line up with the additions.
Original concentration in the sample
2
y = 0.1x + 0.2 · R² = 1.00000
Standard addition finds the concentration from the x-intercept: extrapolate the line back to zero signal, and the magnitude of where it crosses is what was in the sample to begin with. It exists because it beats an ordinary calibration curve whenever the sample matrix changes the response — seawater, blood, soil extracts. The standards are added to the sample itself, so any suppression or enhancement applies equally to them and cancels out. The cost is that the answer comes from an extrapolation rather than an interpolation, which magnifies any scatter in the points. A poor R² hurts far more here than on a normal calibration curve, and dilution from the added volume must be corrected for if it is significant.
How the Standard Addition Calculator works
Enter the concentration added at each step and the signal measured, and this fits the line and extrapolates back to the x-intercept. The method exists for samples where the matrix changes the response — seawater, blood, soil — because the standards experience the same matrix and it cancels.
Also known as: method of standard additions · matrix effect calculator · spike recovery calculator · standard addition x intercept
Frequently asked questions
How does standard addition work?
Spike the sample with known amounts, plot signal against added concentration, and extrapolate to zero signal. The magnitude of the x-intercept is the original concentration.
When should I use it instead of a calibration curve?
Whenever the sample matrix suppresses or enhances the signal. Because the standards are added into the sample itself, the matrix effect applies equally to them and cancels out — an external curve cannot do that.
Why is a good R² more important here?
Because the answer comes from extrapolating beyond the data rather than reading within it, which amplifies any scatter. The same R² that would be acceptable on a calibration curve gives a much larger uncertainty here.
Do I need to correct for dilution?
Yes, if the added volume is a significant fraction of the sample. Either keep the added volumes small relative to the sample, or use concentrated spikes so the dilution stays negligible.
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