Practical design of radiation detectors

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Department of Physics

Synopsis:

[1] Introduction to radiation and detection methods

Students will be introduced to the basic types of ionizing radiation (alpha, beta, gamma, cosmic muons) and their interactions with matter. Various types of detectors will be discussed, from gas and scintillation detectors to semiconductors. In the practical part, demonstrations using simple devices like a cloud chamber or Geiger counter will allow students to see radiation effects with their own eyes.

[2] Basics of semiconductor detectors

We will explain the working principle of a p-n junction and how electrical signals are generated in semiconductors when radiation passes through. Students will learn why diodes are reverse-biased and how this creates a sensitive region for radiation detection. Practically, they will experiment with using a regular photodiode first as a light sensor and then prepare it for radiation detection.

[3] Introduction to microcontroller use

Students will learn to work with microcontrollers and use them for data collection from sensors. Basic concepts such as analog and digital inputs/outputs, interrupts, and working with serial ports will be explained. Everyone will upload a simple program to a microcontroller and read values from a sensor a fundamental skill for further detector work.

[4] Signal processing and data collection

This part focuses on processing weak signals from detectors, which must be amplified and conditioned for correct evaluation. Students will build a simple amplifier using an operational amplifier and learn to use a comparator to reliably detect signal pulses. They will then program the microcontroller to count pulses and record them for further analysis.

[5] Detector construction and calibration

Students will assemble a complete detector that includes a light-shielded diode, amplifier, and microcontroller for data acquisition. They will learn how to shield the detector from external noise and set a threshold for reliable detection. They will then perform initial background measurements to verify their device's functionality.

[6] Data analysis in Python

In this section, students will learn how to analyze their data in Python. Using widely used libraries, they will load recorded data, calculate basic statistics, and create graphs showing the measurement results. They will learn to distinguish noise from real detection events and interpret the results to draw conclusions from the measured data.

[7] Coincidence detection and cosmic ray tracking

Students will learn how using multiple detectors can reduce noise and improve the reliability of cosmic muon detection using coincidence principles. They will stack two detectors and observe how the number of random pulses decreases. This principle will be practically demonstrated and students will understand how similar methods are used in large-scale physics experiments to track particle trajectories.

[8] Advanced topics and extensions

This lesson expands student knowledge with advanced detector improvement options, such as using larger diode areas, adding scintillators, or using more sensitive sensors. Basic energy measurement techniques and the use of advanced software tools for data processing will also be introduced. Students will choose a short project to explore some of these advanced methods.

[9] Data collection and experiments

In this lesson, students will conduct their own measurements based on an experiment they design. For example, they might investigate the effect of shielding on radiation detection, differences in radiation intensity in different environments, or measure how detection rates vary with detector orientation. They will follow the scientific method and learn to work with experimental data.

[10] Presentation and course summary

At the end of the course, students will present their projects and measurement results. They will share their experience building the detector, solving problems, and present the data they collected. The course will conclude with a discussion on further project development and practical applications of the skills learned in science and technology.

[11] Optional extensions depending on time availability

If time permits, students can further develop their practical skills through additional activities. For example, they may learn the basics of 3D printing and design their own mechanical parts for mounting and shielding detectors. Another option is an introduction to working with the professional software environment LabVIEW for advanced measurement system control and data processing. These optional activities will broaden students technical horizons and enhance their ability to work with modern technologies across disciplines.

Requirements:

The knowledge is controlled during active participation in lectures and exercises.

Syllabus of lectures:

Syllabus of tutorials:

Study Objective:

The aim of this course is to teach students how to design and build ionizing radiation detectors using easily accessible hardware and software. The focus is on semiconductor detectors (simple diodes and photodi-odes) as sensors, and on using Arduino microcontrollers or Raspberry Pi computers for data acquisition and analysis. The course is based on project-based learning students will build and program their own radiation detector and learn how to process the measured data in Python.

Study materials:

Recommended literature:

[1] Glenn F. Knoll, Radiation detection and measurement, Willey, 2010

[2] Gerhard Lutz: Semiconductor Radiation Detectors, Springer-Verlag 2007

[3] S. M. Sze and K. K. Ng, Physics of Semiconductor Devices, John Wiley & Sons, Ltd, 2006.

[4] L. Rossi, P. Fischer, T. Rohe, and N. Wermes, Pixel Detectors: From Fundamentals to Applications, Springer-Verlag, Berlin Heidelberg, 2006

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans: