# Difference between revisions of "Radiation Attenuation over Different Materials"

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=Protocol (Basic Laboratory)= | =Protocol (Basic Laboratory)= | ||

The suggested protocol for this experiment in the Basic Laboratory is the following: | The suggested protocol for this experiment in the Basic Laboratory is the following: | ||

− | # Study the variation of the radiation | + | # Study the variation of the radiation intensity as the distance changes, given by the detector's output; |

− | # Verify the linear absorption rate of the | + | # Verify the linear absorption rate of the different materials, trying to establish a theoretical law that relates the intensity with the surface mass of each element; |

− | # For copper, infer | + | # For copper, infer length of semi-reduction, i.e. the length it takes to halve the number of Geiger-Müller counts; |

# The user will observe that experiments conducted under the same conditions will give diferent values. This is caused by the randomness of nuclear processes. A way to prove this is to verify that the number of counts in the same conditions follow a Binomial or Poisson Distribution due to the extremelly low probability of the event. | # The user will observe that experiments conducted under the same conditions will give diferent values. This is caused by the randomness of nuclear processes. A way to prove this is to verify that the number of counts in the same conditions follow a Binomial or Poisson Distribution due to the extremelly low probability of the event. | ||

Because of this last factor, the experimental error can be atenuated by adding several values of radioactive decay under the same conditions. | Because of this last factor, the experimental error can be atenuated by adding several values of radioactive decay under the same conditions. | ||

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# Verify the mathematical law for Radioactive Decay. | # Verify the mathematical law for Radioactive Decay. | ||

# For the same material and distance, record a large number of decays. | # For the same material and distance, record a large number of decays. | ||

− | # Fit a Gaussian function to the data and see if the fitting improves by adding more experimental data | + | # Fit a Gaussian function to the data and see if the fitting improves by adding more experimental data. |

Line 92: | Line 92: | ||

==Radioactive Decay== | ==Radioactive Decay== | ||

− | The mathematical law that describes radioactive decay tells us that the variation of the number of radioactive nuclei, i.e. the number of decays at a given | + | The mathematical law that describes radioactive decay tells us that the variation of the number of radioactive nuclei, i.e. the number of decays at a given moment is proportional to its quantity: |

\[ | \[ |

## Revision as of 20:45, 20 October 2013

## Contents

# Description of the Experiment

This laboratory uses a Geiger-Müller detector to measure the radiation from a radioactive source (\( ^{241}Am_{95} \), Amerício), and study the absorption of radiation of different materials by putting them between the source and the detector.

**Links**

- Video: [indisponível]
- Laboratory: Intermediate em e-lab.ist.eu[1]
- Control room: Radiare
- Level: ***

# Experimental Apparatus

The user can set the distance between source and detector (between 6cm and 20cm), and choose which material to place between the two parts.

The available materials are:

Position | Material | Thickness |
---|---|---|

1 | Wood | 10 mm |

2 | Corticite | 10 mm |

3 | Brick | 10 mm |

4 | Copper | 0,2 mm |

5 | Copper | 0,4 mm |

6 | Copper | 0,8 mm |

7 | Copper | 1,6 mm |

8 | Copper | 3,2 mm |

9 | Control window (air) | 0,5 mm |

10 | Lead | 6 mm |

The tenth position is, actually, "closing" the source.

# Protocol (Basic Laboratory)

The suggested protocol for this experiment in the Basic Laboratory is the following:

- Study the variation of the radiation intensity as the distance changes, given by the detector's output;
- Verify the linear absorption rate of the different materials, trying to establish a theoretical law that relates the intensity with the surface mass of each element;
- For copper, infer length of semi-reduction, i.e. the length it takes to halve the number of Geiger-Müller counts;
- The user will observe that experiments conducted under the same conditions will give diferent values. This is caused by the randomness of nuclear processes. A way to prove this is to verify that the number of counts in the same conditions follow a Binomial or Poisson Distribution due to the extremelly low probability of the event.

Because of this last factor, the experimental error can be atenuated by adding several values of radioactive decay under the same conditions.

# Advanced Protocol (Intermidiate Laboratory)

A slightly more advanced protocol is:

- Looking at Americium's (\(^{241}Am_{95}\)) half-life and at the database, compare the number of decays under the same conditions (material in between and distance) in the past and in the present.
- Verify the mathematical law for Radioactive Decay.
- For the same material and distance, record a large number of decays.
- Fit a Gaussian function to the data and see if the fitting improves by adding more experimental data.

# Theoretical Principles

## Geiger-Müller Detector

This device detects radiation levels, providing a number corresponding to how many radioactive particles go through it.

## Radioactive Decay

The mathematical law that describes radioactive decay tells us that the variation of the number of radioactive nuclei, i.e. the number of decays at a given moment is proportional to its quantity:

\[ \frac{dN}{dt} = - \lambda \times N \]

where \( \lambda \) is the decay constant. The solution of this equation tells us that, for a given time, the number of remaining nuclei is \[ N = N_0 \times e^{- \lambda t} \]

Differentiating in relation to time, we get the sample's rate of decay (i.e. how many decays occur per second) a.k.a. radioactivity. \[ R = \frac{dN}{dt} = N_0 \times \lambda \times e^{- \lambda t} \]

The half-life, as the name implies, is the time it takes for an initial sample to decay into half: \[ T_{^1/_2} = \frac{ln(2)}{\lambda} \]