The process is more involved than it seems at first, nasty toluene is required and only mentioned once in the methods section.
The chemical treatment is a bit different, but I would expect similar results and difficulties as NileRed found when following the previous method from the same research group in 2016: https://onlinelibrary.wiley.com/doi/full/10.1002/adma.201600...
In principle that is a good idea and nice digital version of analog pulse shaping. However, the pulses have a very distinctive shape (not visible in the blog post picture, but here in figure 7/9: https://www.mdpi.com/1424-8220/19/19/4264).
My programs use the trigger level just to select which waveform snippets are recorded. The peaks themselves are then identified by their steep slopes which shows up nicely in the derivatives: https://github.com/ozel/DIY_particle_detector/blob/90c180207...
That is a typical kind of shape for a particle detector, though the time constants are very long which is a good thing because it's the result of the preamp doing some shaping to remove high frequency noise, which helps make the numerical integration less essential. However, I think you will find a trap filter will allow you to push to lower trigger thresholds more reliably. Calculating the slope from one sample to the next is equivalent to the output of a trap filter with peak time of 1 and gap time of 1. Once you enter the regime where the signal amplitude at each recorded sample is comparable to the magnitude of noise, especially for slow signals and fast background, the derivitive without any integration will start going crazy. What should matter most is recovering the area under the signal peak independent of noise on top of it, which will ultimately average to 0. An alternative method is to just integrate the entire signal over a window and then do baseline subtraction, but this still requires a robust trigger signal to indicate when to start integrating, which brings things back to the trap filter.
The pulse detection works really quite satisfactory with the current method and for beta-decay electrons and alphas. I also prefer that the derivative is easy to understand for students since this is still mainly an educational project. For detecting lower energy particles like fluorescence x-rays, your proposal would be certainly something to investigate. However, for improving the SNR I would in general first redesign the amplifier. It's really optimized for super low part count and costs at the moment.
That said, I will definitely keep you suggestion in mind. Thanks!
The circuit used in the blog article is a very much simplified version of the Maxim one. And probably not so much worse in terms of signal to noise ratio: https://github.com/ozel/DIY_particle_detector/
The ion chambers are impressive because even lower-cost. But they also detect the presence of people, touches and what not. :) My favourite aspect of silicon sensors like those PIN diodes is that you get the absorbed particle energy as well. In particular with alpha particles that gets quite interesting when measuring for example old ceramics painted with uranium glaze ('Fiestaware').
yes totally. There is a great DIY project for doing that https://www.fourmilab.ch/hotbits/
It's not required to have the particle energy measured for making random numbers, detecting precisely the arrival time of particles is more important plus having a high hit rate is usually desired. My DIY detectors are not optimized in that way but it would work in principle. Timestamps are already recorded by the python scripts on github, it would be just a matter of evaluating them.
Yes, this project is very much doable for electronic beginners with a knack for science (16-year olds who have never soldered manage it well if guided a little bit). The parts are easy to solder and ordering the circuit board will make your life much easier in order to get it working.
BTW, no one earns money with the kitspace website above. This is community-run and intended to make open hardware projects easier to build by simplifying the ordering procedures. The parts and board suppliers linked on kitspace should cover most of the world.
Also the drastic change of 1 mm thick balsa wood from rigid to foillike around 00:27-28 in the "Movie S2" of the supplemental material is quite surprising: https://advances.sciencemag.org/content/suppl/2021/01/25/7.5...