Does it matter? part 3: Natural background radiation

[With thanks to dr. Masato Ohnuma for bringing this to my attention]

It is all around us, and occasionally all through us, and every now and then, your small-angle scattering detector might see them: photons from┬ánature. Do we need to consider these all-natural organic photons in the data corrections we do, or can we safely neglect them as “present in homeopathic concentrations”?

The short answer: we absolutely need to take it into account! The slightly longer answer is a bit more nuanced.

Natural background should work the same as a darkcurrent measurement, it is detected independent of the state of the X-ray generator or sample transmission, indeed, it bypasses most of these. It should only be a function of time and location (and maybe wind direction…). Considering that some of this radiation might come from the giant nuclear reactor in the sky, could it be significantly dependent on time as well?

At hand we have: 1) a SAXS instrument in a state of institute-mandated shutdown, with a nice 100k (single-panel) PILATUS detector sitting idle, and 2) a week-end of time. Now that the week-end is over, 12 6-hour measurements have been collected of nothing but natural background on the detector. Surprisingly, the collected counts were quite numerous. Here listed in the sequence they were measured, divided over timeframes:

  • (A)fternoon (13:47 to 19:47)
  • (E)vening (19:47 to 01:47)
  • (N)ight (1:47 to 7:47)
  • (M)orning (7:47 to 13:47)

The total collected counts on the single PILATUS panel (195 x 487 pixels) were:

  1. A……64189
  2. E……64063
  3. N……64811
  4. M……65468
  5. A……63748
  6. E……63051
  7. N……64746
  8. M……64694
  9. A……64277
  10. E……65546
  11. N……63967
  12. M……63233

So, as we can see, significant count rates are collected for 6-hour measurements, and there is no clear indication of nature’s addiction to sunshine in these results (though statisticians should feel free to prove me wrong). With a mean of 64414.5 counts, and a standard deviation of 702.7 counts, spread over 94965 pixels and 21600 seconds, that works out to a countrate of 31.4 microHz (micro-counts-per-pixel-per-second, note that the number of significant digits roughly follows the accuracy indicated by the standard deviation).

One side-note, this natural radiation correction is not automatically taken care of by a normal background subtraction. That is to say, this correction is to be applied to the data before most other corrections are done. For example, transmission factor does not play a role here, nor incoming flux or geometry corrections (see equation 2.5 in the document linked to from this post). It behaves, for all intents and purposes, like a time-dependent variant of a dark-current correction. A normal background correction only corrects for this natural background radiation if your transmission factor is 1, for lower transmission factors the correction becomes increasingly necessary.

So how much does it matter? Well, to answer that question I have measured a sample with two different sample-to-detector positions. There should be a significant portion of the data that overlaps between the two geometries, and imperfections in the data may show up clearly here. This sample has a transmission factor close to 0.5, and was measured for a wholesome amount of time (6-12 hours). In Figure 1, a comparison before and after subtraction of a constant natural background radiation value is shown. As evident, a significant change can be ascribed to this simple subtraction!

So, to summarize: for long measurements of absorbing samples, even on very nice equipment, your data will be significantly affected by natural background radiation. You will not automatically know your data is affected by this, and therefore you are better off taking this correction into account just in case it matters for your analysis. Happy Scattering!

Figure 1: Effect of natural background subtraction for long measurements recorded with different sample-to-detector lengths (with a reasonably absorbing sample). Before (left) and after correction (right), showing marked improvements.

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