Measuring nuclear-radiation of potassium from cigarette ashes

In the previous post I've presented a simple way of extraction compounds from ashes, today I will measure radioactivity of obtained sample by using my homemade Geiger counter. Below is a quick view of the setup that I used.

Measurements

Each measurement was made during 1 minute, with 3 parallel STS-5 tubes, so the amount of counts is (roughly) tripled.

The GM counter that I've used wasn't calibrated, because as a regular person I don't have access to calibration samples or a lab where I/someone could do the calibration. I can only measure the current amount of pulses (natural background radiation) without sample and compare it to the amount when a sample is present. The results are relative to background radiation (% of radiation increase).

Mentioned 10 measurements without sample, a base for comparison to the rest of measurements: 57, 48, 73, 62, 75, 58, 63, 55, 61, 70.

Extracted potassium sample placed on the sensor: 69, 60, 61, 50, 69, 61, 59, 57, 66, 67. As visible, results are basically the same as without sample - this is because Petri dish glass completely blocks this small amount of radiation.

Extracted potassium sample placed on the sensor: 182, 160, 149, 166, 149, 166, 162, 183, 183, 166. When there isn't obstacle between the sensors and the sample, it's visible that the measured amount of the radioactivity is increased.

Results for ashes that stayed after potassium extraction: 99, 123, 89, 96, 103, 96, 88, 91, 86, 98. They are also increased, maybe because extraction has been made only once and a lot of potassium stayed undissolved in the sample.

Summary and analyze

Environmental radiation
[counts/minute]
Potassium sample above sensor
(Petri dish glass between sample and sensor)
[counts/minute]
Potassium sample above sensor
(no obstacles between sample and sensor)
[counts/minute]
Ash remaining after potassium extraction
(no obstacles between sample and sensor)
[counts/minute]
Mean 62.2 61.9 166.6 96.9
Standard deviation 8.443275 5.989806 12.738393 10.650509

All charts and data analyze were made in R programming language, scripts are available on my GitHub.

2 comments:

  1. No ciekawe bardzo, nie przypuszczałem, że popiół może mieć takie właściwości.

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  2. Możesz mi pomóc napisać prosty ELF binary?

    Stawiam pierwsze kroki
    https://gist.githubusercontent.com/texrg/7daf6dae2fd38cecfb46/raw/332483c8b3d5566df5e795ae3c8bd9929cf05986/gistfile1.txt
    g3e4ek(w)lin8999ux.pl mój email nie zawiera cyfr

    ReplyDelete