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Determination of Crystal Structures01:29

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In the late 1800s, the revelation that light extended beyond visible wavelengths led to the discovery of X-rays by Wilhelm Roentgen. Recognized as high-energy electromagnetic radiation with short wavelengths, X-rays prompted exploration into their interaction with crystals. Max von Laue proposed in 1912 that the periodic arrangement of atoms, ions, or molecules in crystals would cause them to diffract X-rays, a hypothesis confirmed through experiments with copper sulfate and zinc sulfide...

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Related Experiment Video

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Novel Algorithm for Radon Real-Time Measurements with a Pixelated Detector.

Alessandro Rizzo1, Francesco Cardellini2, Claudio Poggi3

  • 1Radiation Protection Institute (IRP)-Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Via Anguillarese 301, 00123 Rome, Italy.

Sensors (Basel, Switzerland)
|January 22, 2022
PubMed
Summary

Radon gas exposure is a major health risk, causing lung cancer. This study introduces a novel algorithm for pixelated silicon detectors to accurately measure radon in real-time, even in simple configurations, aiding risk assessment and mitigation.

Keywords:
MediPixTimePixpattern recognition algorithmradonreal-time measurements

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Area of Science:

  • Environmental Science
  • Nuclear Physics
  • Health Physics

Background:

  • Radon gas exposure is a significant public health concern, identified as the second leading cause of lung cancer.
  • Radon's properties, including its relatively long half-life and diffusion from building materials, lead to variable indoor concentrations.
  • Real-time monitoring of radon is crucial for risk evaluation and implementing effective countermeasures.

Purpose of the Study:

  • To develop and validate a novel pattern recognition algorithm for measuring radon using pixelated silicon detectors.
  • To enable simple, 'bare' measurement configurations without specialized collection or electrostatic systems.
  • To assess the performance of the developed algorithm in discriminating alpha particles from other radiation types and recognizing radon emissions.

Main Methods:

  • A novel pattern recognition algorithm was developed for pixelated silicon detectors (TimePix family).
  • The algorithm utilizes cluster shape and energy dispersion generated by alpha, beta, and gamma particles.
  • Calibration was performed using alpha (Am-241) and beta (Sr-90) sources, followed by testing in a radon facility under 'bare' conditions.

Main Results:

  • The algorithm demonstrated effective alpha/beta discrimination and alpha recognition efficiency.
  • The detector system showed linear response over a range of radon concentrations.
  • The 'bare' configuration proved viable for simple, active radon measurements.

Conclusions:

  • The developed algorithm enables effective radon measurement with pixelated silicon detectors in a simplified 'bare' setup.
  • This technology offers potential for small, portable devices for real-time radon monitoring.
  • The findings contribute to improved radon risk assessment and mitigation strategies.