Designing and Testing a Low Cost

Gamma Detector

A project submitted to the National University of Ireland, Galway in partial fulfillment for the degree of BSc (Hons) in Physics with Medical Physics.

By Christopher Mitchell

Department of Physics, National University of Ireland, Galway

Project Supervisor: Dr. Mark Foley April 2015

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Signed Copy of Plagiarism Statement

National University of Ireland, Galway

School of Physics

Fourth Year Laboratory Programme

Plagiarism Statement I have received copies of (1) the plagiarism guidelines for the Fourth Year Physics programme and (2) the University Code of Practice for Dealing with Plagiarism. I have read and understood these documents. All work that I shall submit for assessment purposes shall be my own, and written in my own words, except where explicitly referenced using the appropriate norms and formats. Name (Block Capitals Please): _____________________________________________ Signature: _____________________________________________ Date: _____________________________________________

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Abstract. Smartphone cameras have the ability to be converted into ionising radiation detectors by covering the lens. The lens detects high-energy photons emitted by a variety of gamma radiation sources. The gamma detector is limited by its inability to differentiate between the energies of the radiation fields it is detecting, however the detector can be calibrated to give the estimated dose (μSv/hr). It has the ability to be used as a personal dosimeter. The detector is not very sensitive and is subject to thermal noise. The radiation intensity detected varies from phone to phone. However linearity plots of counts versus dose rate can be obtained regardless of noise or sensitivity values. The measurements of the detector are sensitive to the position and angle of the source. The following parameters were tested as part of this investigation: Calibration of device with sources, thermal noise, distance of source, shielding effects, resolving time of detector, variance of count rate with angle and absolute efficiency comparison to semiconductor detectors. The detector follows the radiation theory tested such as the inverse square law and the law of absorption. The Smartphone detector is a low cost dose meter that can provide estimated dose readings of radiation sources, although it is not as efficient as other semiconductor detectors, this low cost detector is much cheaper than its professional detector counterparts and there are more smartphones available than detectors. So the smartphone at times may be the best gamma detector available.

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Acknowledgments. I would like to thank Dr. Mark Foley for his consummate guidance, knowledge and patience during this project.

I would also like to thank all the academic and technical staff of the Physics department including James Nallen for his support during this undertaking.

Finally I would like to thank Robert Johnson for his help with understanding the concepts behind, and providing the data for the Cadmium Telluride (CdTe) x-ray and gamma ray detector.

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Table of Contents

Signed Copy of Plagiarism Statement ........................................................................... i

Abstract. ................................................................................................................................. ii

Acknowledgments. ........................................................................................................... iii

Introduction ......................................................................................................................... 1 Radioactivity ................................................................................................................................. 1

Decay of the Nucleus ............................................................................................................................. 2 Background Radiation ....................................................................................................................................... 2

Gamma Radiation ........................................................................................................................................ 3 The inverse Square Law .................................................................................................................... 4

Detectors .............................................................................................................................................. 5 How a CMOS Sensor Detects Radiation ......................................................................... 6

Summary ................................................................................................................................... 7

Aims ......................................................................................................................................... 7

Materials ................................................................................................................................ 7

Method .................................................................................................................................... 8

Results ................................................................................................................................. 18

Discussion .......................................................................................................................... 27

Conclusion .......................................................................................................................... 29

Limitations ......................................................................................................................... 30

Recommendations ........................................................................................................... 30

References .......................................................................................................................... 31

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Introduction

Radioactivity Alpha, Beta and Gamma emission occur as a result of the decay of unstable nuclei into less energetic nuclei. Respectively, these forms of emission consist of He4 nuclei, positron or electron, and high-energy photons. The types of decays that occur depend on the instability of the nuclei. Some radioactive materials emit more than one type of radiation. This is the case if the original radioactive parent nuclei produce in decay chain radioactive daughter nuclei. The three forms of radiation can de deflected and separated by a magnetic field. Alpha decay occurs with the emission of a helium nucleus with two neutrons and two protons, which results in the original nuclei being reduced by an atomic number and mass of two and four respectively. If a nuclei that has too many or too few neutrons with respect to the number of protons can cause the nuclei to become unstable. If the nuclei are flooded with neutrons, there is a probability that one will undergo a change into a proton with the emission of an electron and an antineutrino. This electron has a high rate of energy and is referred to as a beta particle. This process is called β- decay. Likewise if there are too few protons present then there is a probability that one will change into a neutron with the emission of a positron (which is a negative electron) and a neutrino. This process is called β+ decay, however the positron is very difficult to detect as it usually reacts with an electron and annihilates producing gamma rays in the form of high-energy photons. Gamma radiation occurs as a result of alpha and beta decay causing the nucleus to be left in a high-energy state. The nucleus can emit photons to go from a higher energy level to one of a lower energy level. These photons have very high energies and are called gamma rays. (Siegbahn, 2012)

Figure 1. Radioactivity (Alpha, Beta and Gamma emission) [7]

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Decay of the Nucleus The decay of a nucleus occurs randomly. In each infinitesimally event of time, there is a probability of the unstable nuclei in the radioactive sample to decay. Poisson statistics can be used to describe the number decays that occur in a certain finite period of time.

𝑃𝑟𝑜𝑏𝑎𝑏𝑖𝑙𝑡𝑦 𝑜𝑓 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑑𝑒𝑐𝑎𝑦𝑠 = (𝜆𝑡)𝑛𝑒−𝜆𝑡

𝑛!

λ is the mean number of decays in a second; n is the probability of the number of decays that occur in a time interval of t, n is a factorial. The square root of the number of decays that occur is equal to the standard deviation of the number of decays that occur throughout a certain time interval t. The standard deviation is used to see if a measured set of counts deviates from the overall mean of the results. This relationship between the mean and the standard deviation can be used to gauge the number of counts that are needed to

achieve a certain level of accuracy. √𝜆 Represents the average number that

deviates from the mean λ, therefore the √𝜆

𝜆=

1

√𝜆 so the accuracy is increased as

the square root of the number of counts. (Wahlström, 1995)

Background Radiation External sources have an impact on any recorded counts of a detector. It represents a percentage of all recorded count events. These external background counts can be as a result of sources including cosmic rays, or radioactive elements that are airborne or found in close by building materials or even other radioactive sources which are present close enough to be detected as they are not correctly shielded with e.g. lead. Before any radiation counting experiment is attempted, the background radiation of the surrounding area must first always be recorded. The data measured can then be more accurately determined for any source by subtracting the recorded value for the background radiation. The recorded radiation values can never be fully accurately determined, as the count events of radiation emitted by both radioactive sources and naturally occurring background radiation are completely random events. This introduces a certain level of uncertainty and noise into any data measurements. As Poisson statistics can be used to determine the background radiation, it follows that the uncertainty will be the square root of the mean number of background counts. The total uncertainty of different sources is calculated by using the following equation. 𝜎𝑡𝑜𝑡𝑎𝑙

2 = 𝜎𝑠𝑜𝑢𝑟𝑐𝑒 12 +𝜎𝑠𝑜𝑢𝑟𝑐𝑒 2

2 …. The effects of the uncertainty of noise caused by the background radiation counts on the accuracy of recorded counts can be decreased by increasing the count rate of the radioactive source in comparison to the count rate of the background radiation. Other methods of decreasing the effects of added background radiation include moving the source closer to the detector or increasing the amount of radioactive source used to increase the count rate ratio to background counts. Also the effects can be negated by using shielding such as lead, around the source being measured to block out the effects of the background counts. (Knoll, 2010) [5]

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Gamma Radiation Gamma radiation is comprised of photons with very high energies. These photons have wavelengths equivalent to less than 10-10 meters. Visible light has a wavelength of approx. 10-6m. The emission of gamma particles comes before alpha or beta emission, which leaves the nucleus in an excited state. A nucleus in an excited state can go to a lower state by emitting a photon such as a gamma ray. This is comparable to an emission of a photon and an electron changes from a higher to a lower orbital. The nuclear energy state spacing occurs with energy in the order of Millions of electron Volts (MeV). Electron orbital energies only occur in the order of electron Volts (eV). The energy of a photon E = hf can be substituted into the equation describing wavelength and frequency, c = fλ

λ =c

f=

hc

E=

1240 MeV ∗ femtometers

1 MeV= 1240 fm

In the visible light, a material absorbs gamma rays at a linear rate. An equal fraction of the remaining light is absorbs for every unit of distance that the radiation travels through the material. Such as if radiation is passed through absorption plates made up of the same materials of equal thickness. The half thickness of the material is the thickness at which it absorbs half the gamma rays that pass through it. After the gamma rays pass through the first absorbing plate, the intensity of the rays is halved. After it passes through a second plate, then the rays half again leaving one quarter of the original intensity. After it passes through a third plate, then the intensity is one eight. This is an exponential decrease, which is described by the Lambert’s law.

I(X) = I0 e−μX

ln (I

I0) = −μX

μ is the coefficient of linear absorption. The half thickness of a material is given by the following equation.

I (𝑋12

) = 0.5 I0 = I0e−μ𝑋1

2

𝑋12

=−ln (1 2)⁄

μ=

0.693

μ

Gamma rays can be absorbed by a number of ways including pair production at high energies, Compton effect at medium energies and the photoelectric effect at very low energies. The μ (the coefficient of linear absorption) is calculated by a combination sum of all three processes. (Lilley, 2013) [5]

Figure2. Compton Scattering, Pair Production, Photoelectric effect [8],[9],[10]

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μ = τ(Photoelectric) + 𝜎(𝐶𝑜𝑚𝑝𝑡𝑜𝑛) + 𝐾(𝑃𝑎𝑖𝑟 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛) A number of different factors also decrease the beam energy such as Bragg scattering, Rayleigh scattering, Photodisintegration and nuclear resonance scattering. The absorption of Gamma by the photoelectric effect occurs as a result of gamma rays ionising an atom. The density of the interacted material is proportional to τ the rate of absorption by photoelectric effect. This increases with atomic number,

𝜏 = 0.0089𝜌𝑧4.1

𝐴𝜆𝑛

ρ is the materials density, the atomic number and mass are Z and A respectively, λ is the wavelength and n is 3 for Carbon, Nitrogen and Oxygen and 2.85 for the rest of the elements that have an atomic no less than Fe (Iron). The greater the wavelength, the stronger the photoelectric effect due to lesser energetic gamma rays. The photoelectric effect greatly increases with atomic number. (Gilmore, 2011) [5]

The inverse Square Law The direction is random of particles that are emitted during nuclei decay. So the emission of the particles is evenly distributed in every direction if the absorption is neglected in a radioactive source. If they are centered on the source, a set of concentric spherical surfaces surrounding it and none of the particles are absorbed, then each of the spheres has more of a surface area then the inner sphere. As a result there is a higher density of radiation nearer the source. The surface area of a sphere is

𝑠 = 4𝜋𝑑2 Even if absorption radiation is not present, the radiation intensity levels decrease as a reciprocal of distance from the source squared. This is the inverse square law. (Bloor, 2013) The fraction of radiation totally emitted from a source that is placed near the detector window of a Geiger molar counter and detected in the direction of the window, is given by the geometry G factor.

𝐺 = 𝑆′

4𝜋𝑑2

A Geiger molar counter has a round window with a radius r, and an area of πr2, as long as the source is not placed directly at the detector window. (Spiers, 1941)

𝐺 = 𝜋𝑟2

4𝜋𝑑2=

𝑟2

4𝑑2

When the detector is moved away from the radiation source, there is an increase in the total spherical surface area of the window by a distance squared. However the enclosed area of S’ stays the same throughout. The inverse square law results in a drop off in intensity of radiation levels as the particles spread away from the source. If the sources are moved away from the detector at different distances, or likewise the geometry size of the detector window is changed, then the G factor must be used to compare any results. The benefits of the inverse square law are that it can be implemented to change the count rate if it is too low by simple moving the source closer to the detector window, or vice versa if it is too high.

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Figure 3. The Inverse Square Law [11]

Detectors There are a wide variety of Semiconductor detectors available fro the detection of ionising radiation. They usually implement a semiconductor such as germanium or even silicon to detect the absorption of photons. Photons are not directly in the form of ionising radiation particles e.g. gamma particles. However the energy of the photons can be converted into particles charged with kinetic energy. The energy of these charged particles are then measured to obtain the energy of the gamma particles.(Bushberg and Boone, 2011) Scintillation detectors : A gamma ray interacts with the scintillator e.g. Thallium-activated sodium iodide (NaI(TI)). This produces a pulse of light that is converted into an electrical pulse by a Photo Multiplier Tube (PMT). The PMT consists of a photocathode, a focusing electrode and dynodes that multiply the number of electrons, which strike it. There are two types of scintillation detectors that will be used. A well detector has a large 3”x 3” detector window. Shielding which allows it to obtain more accurate results surrounds the detector. The second type is just a stand alone (NaI(TI)) detector which has the PMT built into its body. The well scintillation detectors have a higher efficiency at recording the decays of a radioactive source due to the shielding. [1] Another type of detector is a Cadmium Telluride (CdTe) detector. This is a thermoelectrically cooled X-ray detector, which used CdTe diodes in a preamplifier. The Gamma rays interact with the CdTe atoms in the preamplifier to create on average one electron hole pair for every 4.43KeV it detects as being lost in the CdTe. The efficiency of the detector to stop incoming radiation increases by increasing the thickness of the CdTe. [4]

Figure 4. (NaI(TI)) Figure 5. (NaI(TI)) Well Figure 6. CdTe

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How a CMOS Sensor Detects Radiation A CMOS sensor creates an image using pixels, which are usually comprised of several million-sensor cells. In the typical use of the camera, it creates an image by implementing the photoelectric effect in conjunction with the cells, which are p-n diodes and are only micrometers in dimension. The photoelectric effect promotes electrons from the valence band into the conduction band when the photons interact with the crystalised silicon (Kuhn et al., 2014). The junction of the semiconductor is sensitive also to radiation in the form of Beta particles and Gamma rays. They cause a release of electrons by ionising the individual atoms of the chip. These electrons are then captured by the CMOS sensor chip and create a white pixel. Due to the lack of an intrinsic layer, the CMOS sensor has a weaker sensitivity to Gamma radiation. Preventative measures are taken to decrease the external ambient light from reaching the sensor by placing black electrical tape over the lens. This makes the white pixels created by the gamma rays hitting the lens visible to the user and it also prevents alpha particles from being detected due to their low penetrating ability. The “Radioactivity Counter “application acts as the software analysis tool which visualizes the data from the sensor. The software is limited by the frame rate of the smartphone (approx. 30 frames/second). In a designated time period, the application records the sum total of the detected particles interacting with the sensor. In the Application interface, the camera display is shown, and the application alters the settings of the camera so that any black pixel changes into a white pixel. (Bushberg and Boone, 2011) The recorded measurements in this experiment where all evaluated and carried out using this software analysis application with two different smartphone camera devices, The Sony Xperia Go ST27i, and the Alcatel One Touch 903.

Figure 7. Phone lens covered Figure 8. CMOS Sensor

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Summary With the increased popularity of smartphones and portable devices, there has been a large growth in the number of applications which can be downloaded and which provide a wide variety of functionalities and utilities. An application called Radioactivity Counter, which is available commercially, claims that it allows for the accurate detection of radiation dose to a user given in microGray per hour (μGy/h) by implementing the camera of a smartphone. The camera is sensitive to both visible light and also gamma photons, which are of a higher energy. The application utilizes the sensitivity of the on Board complementary metal oxide semiconductor (CMOS) sensor to detect the surrounding radiation levels. This silicon-based sensor is present in most modern smartphone cameras. The CMOS sensors are on-board small silicon chips, which are used in the device for the detection of visible light. However the sensor also has the ability to detect gamma radiation, which operates on a higher wavelength. The signal of the ionising radiation, when compared to visible light, is undetectable because of the small acquisition time of the image of approximately 100 milliseconds. This means that the responses of the camera to the radiation are not normally shown to the user. However by making a small configuration in the form of black electrical tape, which is applied over the lens of the camera, it eliminates all of the visible light. The response of the gamma rays hitting the sensor can now be observed. The radiation counter application implements the phone cameras ability to detect the gamma rays and records the number of times the sensor detects the interactions. Once the device is calibrated, the phone can then convert the recorded number of interactions into a dose rate per hour. This project aims to design, test and understand this setup to determine its effectiveness as a low cost gamma detector. (Gröber et al., 2014)

Aims To design a detector using a smartphone camera with CMOS sensor To compare the sensitivity of different phones To compare the efficiency of the detector to semiconductor detectors To see if the detector can be used as a dosimeter

Materials Two Smartphones: Sony Xperia Go ST271, Alcatel One Touch 903 4 Gamma Sources: Am-241 (0.1μCi), Co-60 (1μCi), Cs-137 (1μCi), Ra-226 (5μCi). Black Electrical tape Ruler and Protractor Retort Stand Two Dosimeters: Mini Rad series 1000, Mini 6100 series EPD Lead shielding Thallium-activated NaI(TI) scintillation detectors 3”x3” well detector 905 Series Ortec Thallium-activated NaI(TI) scintillation detector Amptek XR-100T-CdTe X-Ray & Gamma Ray Detector

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Method Detector Application Design and layout

Figure 9. Software Analysis Application Layout The upper right portion of the application displays the image of the camera. This should be displaying black when covered with black tape. When the gamma rays interact with the sensor chip, white pixels appear. The application only has the ability to display a maximum value of 200 white ray pixels per image frame. This can result in only part of the rays being displayed in the presence of a high radiation field. If the lens cover is removed, then there will be a dramatic increase in the number of white pixels measured by the software analysis tools. A warning message is then displayed. The number of Counts Per Minute is displayed on the upper left corner of the application, and below it is the dose reading in μGy/h. This dose value changes from a red to green colour once calibration is complete to define adjustments of CPM values for corresponding μGy/h values. When the sensor experiences an increase in the radiation field, this value is automatically adjusted to mGy/h or Gy/h values respectively. When measuring the radiation dose, the value will turn green after 5 minutes of values are recorded. [3] The text values located below the timer each have a corresponding meaning. “n” represents the noise value of the phone with values of units. The lower the value the higher the sensitivity of the phone. An increase in one unit results in approximately 10% decrease in sensitivity. “e” represents the exposure time. This is only displayed if the value is changed from the default value. The default value is 0. Increasing the exposure time increases the sensitivity of the phone but also increases noise value. “t(/5min)” represents the standard deviation over the last 5 minutes of measurements. It displays values in minutes out of a total of 5 minutes e.g t(3/5min). The higher the standard deviation percentage, the more stable the radiation measurements in the current environment. “fps” represents the frames per second. The higher the frame rate of the phone implies an increase in phone sensitivity. “t” represents the internal temperature of the device battery. An increase in the temperature can results in an increase in noise. No temperature correction is implemented in the algorithm of the applications software if the temperature interferes with the sensitivity of the phone.

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The name of the phone is also displayed along with the Application program interface level. There are three buttons below the text values: Stop log/Start log A button, which can be toggled, is available once the noise value of the phone has been defined. If a log is initiated, a test field appears and the name of the log file can be entered. Once the log has been named, the software records the CPM value as well as each corresponding text value including a temperature stamp. These log files are stored on the phones internal memory/memory card and can be accessed from the settings menu. Clear button The CPM values (the measurements recorded) are deleted and the device resets the counts. The CPM values are red and turn green once 5 minutes of data has been recorded once again. Spect button (Spectrum button) A bar chart or a spectrum can be displayed of the CPM in the lower right side of the software display. The Spect button toggles between the two options. The maximum amount of time, which can be displayed as a bar chart, is 60 minutes. The Application Menu The menu has a six available buttons.

Figure 10. Application Menu Options Help button This option displays a text option of a detailed user manual for the software application. Settings button The settings option allows for a number of parameters to be adjusted. Interval: the interpolation interval time for the spectrum display can be adjusted in increments of 5, 10, 15 or 30 minutes. Border: Increasing this value reduces sensitivity but it is useful for phones, which have a high level of noise around the lens border. Enable Alarm: An audible alarm can be set and displayed in the main software interface.

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Figure 11. Application Settings Menu Frontcam: this option is only available if the device has a front camera. It changes the spectrum to be taken from the front lens and not the back camera. Front lenses are more sensitivity to light, but they also have an increased noise value. In cameras where the back lens sensor does not have a high sensitivity, the front camera can be used instead if available. Set noise button This allows for the noise value to be recalibrated and determined. Calc button This is a unit converter. This allows for rough estimates between dose and equivalent dose calculations. This allows for easy conversions and manipulation of data result values by changing the units as need from Sievert, Gray, Curie or Becquerel.

Figure 12. Application Calculation Converter

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Statistics Button This menu option is where the data from the logged files is saved in bar chart form of Counts Per Minute where each bar represents one minute of counts. The logged file can be saved as a CSV or html file. It can also be emailed as a CSV file attachment. There is also an option to delete the logged file. In the graph saved of the logged file there are a number of options. The display can be changed from a bar chart to a dot, lines notation. The logged file is stored every minute with the automatic set noise (n) value as well as n+1 and n+2 values. This allows for useable data to still be obtained if the camera sensor had an increase in noise during the data acquisition process. The cpm0 (background radiation determined) reading allows for the mean value of CPM to be automatically adjusted to cancel out the CPM-noise of the background radiation from all future counts.

Figure 13. Application Statistics Menu Adjust button This menu allows for up to four CPM values to be given corresponding dose values in μGy/h. A dose curve shows the resulting data as a graph of μGy/h versus Counts Per Minute. An alarm value can also be set here, which once the alarm threshold has been reached, an audible sound and warning symbol will occur. The CPM-noise value can also be adjusted here. The value is determined on the measurements entered. If the value is too high, then the noise value should be increased to lower the value. Repeat the process and if the values do not match use the default CPM-noise value to calculated original value.

Figure 14. Application Adjust Menu

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Disclaimer: Two mobile phones are used in this setup and compared against each other. They are the Sony Xperia Go (ST271) and the Alcatel One Touch (OT – 903). Calibration of Noise The Lens of the camera must first be covered with black tape, so as not to allow any light into the camera. To determine if the tape is effective at being totally light dense the camera lens should then be placed in front of a light source, and the number of counts should not increase. It the sensor registers additional counts; this will decrease the accuracy of the phones readings as it is recording false counts. To compensate the lens can be double or triple taped with or without aluminum foil to block out the light. It is important to note that if the phone has a front camera, then it too should be covered, as the application also has the ability to measure counts using the front lens.

Figure 15. Phone Camera Lens covered with black tape The Noise level of the phone must first be determined. The noise level varies from phone to phone. It can range anywhere from values of 2-60. It is impossible to cancel out the noise entirely, however the lower the noise value, the greater the sensitivity of the phone. The noise value can be determined using the calibration function. The function will measure the sensitivity of the sensor to light and find a zero count rate in order to start accurate measurements. The calibration takes approximately one minute. It is recommended that the phone be surrounded in lead shielding during the set noise phase if the location has a higher than normal background radiation.

Figure 16. Calibrating Noise Level

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Once the noise value has been set, the application will run a mean calibration for a recommended 6-10 minutes. This allows for an accurate measurement of the background zero count to be determined. The phone should produce an audible click noise, which represents photons interacting with the sensor cell and being recorded by the software tools. The counts of the white pixels carried out by the application occur in segments of one minute. The displayed values are given in units of Counts Per Minute (CPM). The application should be recording on average a background radiation of 1-10 CPM.

Figure 17. Determining mean CPM calibration If a phone is displaying a very high CPM this may be a result of a very high noise value. The noise value can be decreased but with the loss of sensor sensitivity. If the CPM is too low and no counts are being measured, the noise level should be adjusted and increased in order that a reasonable background radiation level can be obtained. If there are white dots in a circle or elliptical pattern, then the lens cover may need to be adjusted to make sure it is not allowing light to reach the sensor. Retest by checking if there is an increase in CPM on front of a bright light source. The filter can be changed in the filter settings; this allows an adjustment in the size of the display spectrum. The exposure can also be lowered in the settings. Background Counts (CPM -0) Once the detector has been calibrated and the noise level determined, the phone application is now ready to begin recording data. Before any measurements are recorded, the CPM – 0 (Background Counts) of the phone should be recorded. This allows for more accurate measurements to be taken later on of radiation sources as the background CPM value can be taken away from the recorded radiation source to obtain a true CPM reading. The detector should be placed in the same position/location for the whole experiment. In order to obtain an accurate CPM – 0 reading all radiation sources and external sources should be removed from the detector area. The longer the data is recorded for, the more accurate the Background counts will be. Therefor the detector should be left running for approximately 10 hours. The mean counts can then be obtained from the data and the CPM-0 can be implemented into the adjust menu in the application. This takes the Background counts out of any future recorded data.

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Testing Radiation Sources A variety of different Gamma Radiation Sources are available including Americium 241(Am–241), Cobalt 60(Co-60), Cesium 137(Cs-137) and Radium 226(Ra-226). These sources are placed in front of the detector Camera lens/window. In order to obtain accurate CPM mean value counts for each gamma source, the detector must be used to measure each source over a long period of time (10 hours). Using the software analysis application, the data can be sent to a computer in a CSV file and converted to an .xlc file. This allows the data to then be plotted and graphed in excel. Obtaining Radiation dose of Sources In order to calibrate the Phone camera detector to accurately measure dose, the radiation sources must all have their dose levels determined. Two different dosimeters are used to verify the dose readings, an analog counter- “Mini rad 1000 Series Monitor” [2] and a digital counter- “Mini 6100 series Electronic Personal dosimeter (EPD).

Figure 18. Mini Rad series 1000 Figure 19. Mini 6100 series EPD The Mini Rad has an x on either side of the measurement screen to represent the detector window. The Mini 6100 has three circles to represent the detector window. The devices have already been calibrated. The dose measurement is given in μSV/hr values. Measurements should be taken by placing the different radioactive sources at the detctor window and also at other positions of the detcteor in order to gauge an acurate reading. Dose Calibration of Detector The ability of the Phone Camera detctor to acuratly detect a dose reading in μSV/hr must be calibrated. The mean CPM values for each Radioactive source over 10 hours is implemented with the mean dose reading recorded from both the digital and analog dosimeters. These values are imputted into the adjust menu in the software application settings menu. (refer to figure.) This allows for a dose calibration curve to be obtained. Depending on the acuracy of the imputted data, the Software should now give a μSV/hr dose reading at the detector window. The CPM-0 value should also be recorded here to give a base line cut off to cancel out the background radiation for a more acurate result.

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By taking each individual mean CPM for of the four radioactive sources, the value for one CPM can be obtained for each source. Using these 4 values for one CPM. A mean of all four values should be obtained. This value can them be used as the standard 1 CPM value for calibration. This allows for higher values such as 1000μSV/hr to be estimated. The data can be exported to Excel and graphed and plotted. A linear Plot of Counts vs. Dose(μSV/hr) should be obtained as in the following Plots taken from the Software manufacterer’s website. The results should be repeated and graphed for each Phone being tested.

Figure 20. Linear Plot Counts vs. Dose (μSV/hr) Thermal Noise evaluation The Software Application recordes the internal temperature(°C) of the phone for every CPM value. In order to determine the effects of the temperature on the CPM, there must be a large and substantial amount of data points recorded at each temperature. The larger the number of data aqusition points collected for each temperatuure, the greater the accuracy and reliability of the results. A least 100 minutes of data should be recorded for each temperature of the phone. The temperature range depends on the internal scematics of the phone. It may be difficult to obtain high temperatures due to the safety precautions which the phone takes in order to maintain a safe internal temperaure. The temperature of the phone increses by connecting it to a charging AC supply. The mean CPM value at each temperature should be recorded. The data should them be tabulated and graphed in excel in order to establish a signal noise realationship betweem Temperature and Counts. Investigation of Detector performance to the Inverse square Law The investigation is carried out into the Camera detector to confirm to the law that there is a realationship that exists between the decreses in radiation intensity with an increase in distance due to the geometrical fact that the surface of a sphere increases with distance squared (d2). This realationship can be determined with a simple setup. A retort stand is used to hold a rdaioactive source (Cs-137)in position. It is imperitive that the source is directly in line with the camera detector window. This is to make sure acurate results are obtained, as misallinment of the source can cause errors in the counts. The data CPM is rcorded at a certain positional distance of the source to the detcetor e.g. 5cm. This distance can then be incresed on equal incriments.It is important to note

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that the same number of counts should be recorded at each position and the overal geometry position in the x and y plane should not change. The larger the number of counts that are recorded, the more acurate the average data value will be. The usuable distance range for the measurements of position (rmin,rmax) are determined. rmin is obtained based on the fact that the usuable distance of detection should be approximatly five times the diameter of the radiation source. The sources are usually 5mm in diameter. The rmax value varies depending on the detectors sensitivity which varies from phone to phone. Absorption effects of the air is negligable as the electrons (0.546/2.2 MeV) have a range of 1.5 -10m in air. These values are much higher than the usuable detector range of the CMOS sensor detcetors. Once the data has been obtained from the different positions, the data can be exported to excel, tabulated and a graph of Counts vs 1/disance2 (1/d2) should show a linear realationship through the origin. [6] Investigation into Variation of Counts to the angle of detection The Variation of the Count rate with respect to the angle of detection can be investigated by having the detector in a fixed position. The angle of the radioctive source being used (Cs-137) can be changed in increments of 10°. However the distance of the source to the detector window must be fixed for all measurements, and the source height must also be constant for all measurements. Again by keeping all of these parameters unchanged for each variable angle, and obtaining a reasonable amout of data points e.g. 100 Minutes of CPM. Then an accurate realationship of the number of Counts detected to the change in the angle of the source to the deetctor can be obtained and graphed. Investigation into the effects of lead shielding on the count rate The efects of lead (Pb) shielding can be examined on the count rate. The Detector should be set up at a certain distance from the a chosen radioactive source (Cs -137). The position of both should be fixed in position. Lead shileding should then be positioned between the detector and the sourse. The lead shielding used has a thickness of 3mm. A number of values are recorded for a constant amount of time in order to obtain vallid accurate results. The cumulative thickness of the lead shielding of the gamma source is increased in incriments of 0.3mm until a total of 24mm. This data is then plotted in excel of counts vs. Cumulative Pb thickness. Determination of Dead time using the two source method The dead/resolving time (τ) of a system can be obtained using the two source method. Two different radioactive sources muct be used. The first step is to place source 1(Cs-137) and source 2(Co-60) in combination together (m12) in front of the deterctor window at a fixed distance. In order to obtain acurate results, all data measurements must be carried out over a long period of time (10 hours), this is because the sources will have similar counting rates. The next step is to repeat the measurements seperatly with each source, source 1(m1) and source 2 (m2). However it is important to note that the sources must be kept in the same position as they were when the combined position measurements were taken. This allows for the solid angle to be preserved. The background counts (mb) for

17

the same length of time must also be implemented in the following calculations to obtain the resolving time of the camera phone detector.(Myers, 1956)

𝑋 = 𝑚1𝑚2 − 𝑚𝑏𝑚12 𝑌 = 𝑚1𝑚2 (𝑚12 + 𝑚𝑏) − 𝑚𝑏𝑚12(𝑚1 + 𝑚2)

𝑍 =𝑌(𝑚1 + 𝑚2 − 𝑚12 − 𝑚𝑏)

𝑋2

𝜏 = 𝑋(1 − √1 − 𝑍)

𝑌

Comparing Detector efficiencies Five detectors are compared in this investigation. Two smartphone cameras running the “Radioactivity Counter” software application and which have been calibrated using the previous methods. Two Thallium-activated NaI(TI) scintillation detectors are also used. One is a NaI(Ti) 3x3 well detector incased in a large metal casing. The other detector is 905 Series Ortec NaI(TI) scintillation detector. The Ortec detector is more hands free and has a built in Photo Multiplier Tube (PMT) whereas the Well detector requires an external PMT and a Multi Channel Analyser (MCA). Both detectors use the Software analysis tool Maestro produced by Ortec. The Final detector used is an Amptek XR-100T-CdTe X-Ray & Gamma Ray Detector, which is thermoelectrically cooled X-ray detector and preamplifier using CdTe diode. It uses its own Amptek Software analysis tools. The Counts are measured for all of the detectors using the Co-60 and the Cs-137 sources for exactly 10 hours. The phones generate bar graphs, which must then be exported into excel and graphed. The total counts can then be determined. For the other four detectors, a photopeak is obtained for both sources. The photopeak energy is then calibrated with the known energies of Cesium-137 (662KeV) and Cobalt-60 (1173 and 1332KeV). The total counts must be recorded at the photopeak for each source. The absolute detector efficiency can be obtained for each detector and compared as a percentage. The efficiency of a detector is given by the ratio of number of particles detected/ number of particles emitted. (Kadum and Dahmani, 2014)

𝜖 = 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒𝑠 𝑜𝑓 𝑟𝑎𝑑𝑖𝑎𝑡𝑖𝑜𝑛 𝑑𝑒𝑡𝑒𝑐𝑡𝑒𝑑

𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒𝑠 𝑜𝑓 𝑟𝑎𝑑𝑖𝑎𝑡𝑖𝑜𝑛 𝑒𝑚𝑖𝑡𝑡𝑒𝑑 𝑋 100

There are a number of other important parameters, which are important when comparing detectors such as, Efficiency Resolution, Intrinsic efficiency or Full energy Peak efficiency. However the data from the Phone Camera detectors is limited as it only gives Counts Per minute and not the Energies.

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Results Noise Calibration and Determination of Background Counts:

Figure 21. Sensor Spectrum of the Sony Xperia Phone This Spectrum represents the area of the Camera lens over which the most signal is being recorded. The maximum value of noise, which is recorded by the Application, is n = 15. Note: A Sensor Spectrum was also obtained for the Alcatel One Touch Phone. A Noise value of n = 33 was recorded. Noise calibration cannot be exported to CSV so Screenshot must be taken. Alcatel Phone has no Screenshot feature. But a large noise peak was shown with maximum value centered on 28 with a highest noise reading occurring at 33.

Figure 22. Background Count of Sony Xperia Phone Figure 23. Background Count of Alcatel

The Background counts were determined by running both the Sony Xperia Phone and Alcatel One touch detectors without the presence of any radioactive source over a period of 600 minutes (10 hours). A mean value of the Background Radiation (CPM zero) of the Sony Xperia ST27i phone was determined to be 4.51 CPM. A mean value of the Background Radiation (CPM zero) of the Sony Xperia ST27i phone was determined to be 20.73 CPM.

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Testing Radiation Sources Figure 24. CPM Sony Phone for Cs-137 source Figure 25. CPM Alcatel Phone for Cs-137 source Figure 26. CPM Sony Phone for Co-60 source Figure 27. CPM Alcatel Phone for C0-60 source

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Figure 28. CPM Sony Phone for Am-241 source Figure 29. CPM Alcatel Phone for Am-241 source

Figure 30. CPM Sony Phone for Ra-226 source Figure 31. CPM Alcatel Phone for Ra-226 source

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Obtaining Radiation dose of Sources

Source Sony Mean CPM Alcatel Mean CPM

Analog Dose (μSv/hr)

Digital Dose (μSv/hr)

Background 4.51 20.73 NA NA

Am-241 21.62 177.49 0.55 1

Co-60 39.61 285.5 14.5 17

Cs-137 42.42 469.7 19 21

Ra-226 545.18 3773 100 105 Figure 32. Radiation Dose values determined of each Source Dose Calibration of Detector

Figure 33. Calibration Dose Linear Curve For Sony and Alcatel Phones

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Thermal Noise evaluation

Figure 34. Thermal Noise in Sony Phone

Figure 35. Thermal Noise in Alcatel Phone

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Investigation of Detector performance to the Inverse square Law

Figure 36. Counts vs. Distance Sony Phone Figure 37. Counts vs. Distance Alcatel Phone Figure 38. Counts vs. 1/d2 Sony Phone Figure 39. Counts vs. 1/d2

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Investigation into Variation of Counts to the angle of detection

Figure 40. Counts Vs. Angle Variation Sony Phone Figure 41. Counts Vs. Angle Variation Alcatel Phone

Investigation into the effects of lead shielding on the count rate Figure 42. Counts Vs. cumulated Pb Shielding Sony Phone Figure 43. Counts Vs. cumulated Pb Shielding Alcatel Phone

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Determination of Dead time using the two source method

Detector M1 (CPM) M2 (CPM) M12 (CPM)

Mb (CPM)2

Alcatel 342 388.2 518.4 20.73

Sony 28.22 22.89 34.75 4.51 Figure 44. Two source method results (CPM) Detector M1 (CPS) M2 (CPS) M12 (CPS) Mb (CPS)

Alcatel 5.7 6.47 8.64 0.346

Sony 0.47 0.382 0.58 0.076

Figure 45. Two source method results (CPS)

Detector X Y Z τ (seconds)

Alcatel 33.889 295.013 0.818 0.065

Sony 0.135 0.08 0.857 1.049

Figure 46. Detector calculated Dead/Resolving times. Comparing Detector efficiencies Detector Cs-137 Counts Total Cobalt-60 Counts Total

NAI(TI) Well 2076569 248775

NaI(TI) 873439 103085

CdTe 191897 20383

Alcatel 281829 171279

Sony 25451 23766 Figure 47. Detector Counts Comparison

Detector Cs-137 Decays/Second Co-60 Decays/second

NAI(TI) Well 57.68247222 6.910416667

NaI(TI) 24.26219444 2.863472222

CdTe 5.330472222 0.566194444

Alcatel 7.828583333 4.75775

Sony 0.706972222 0.660166667 Figure 48. Detector Decays/second Comparison

Detector Efficiency (%)

NAI(TI) Well 14

NaI(TI) 10

CdTe 3

Alcatel 1.215

Sony 0.104 Figure 49. Detector Efficiencies

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Figure 50. NAI(TI) Well Cs-137 Figure 51. NAI(TI) Well Co-60

Figure 52. NAI(TI) Cs-137 Figure 53. NAI(TI) Co-60

Figure 54. CdTe Cs-137 Figure 55. CdTe Co-60

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Discussion A gamma detector using two smartphone cameras to detect high-energy photons being released by radioactive gamma sources was successfully designed and tested following the above method preciously. The noise calibration of both devices revealed that the noise value can and does fluctuate for each phone. This noise value is determined by the phone manufacturer’s internal design and setup of the device. The Alcatel phone registered a noise value of over double that of the Sony phone, indicating that it is more sensitive but also more susceptible to signal noise. The Background CPM-0 counts were found for both phones. The results revealed that the added noise value in the Alcatel phone caused it to be more sensitive to photons and detect more counts than the Sony phone. The Alcatel phone recorded five times the Counts. The phone detectors were tested with a variety of sources and showed that they have the resolution ability to differentiate between different sources by producing different CPM mean values for each with increased CPM for sources with a higher activity consistent with detector theory. It should be noted that the Alcatel phone had between 5 and 11 times more counts than the Sony phone depending on the source being tested. By recording the dose rates of each of the four sources on both an analog and digital dosimeter, accurate values of dose rate values were found. These values were then implemented with the corresponding CPM mean values to create a calibration dose curve. The values above 100μSv/hr were estimated based on an average value for 1 CPM. The graph of counts verses dose revealed a linear relationship between counts and dose for both phones. As the Dose rate increases, the counts directly proportionally increase. The Alcatel had higher count values than the Sony phone, however despite the higher noise value it has, it still produces count dose linearity. These results are consistent with the dose calibration curves, which were carried out by the manufacturer for a wide variety of phone model. An examination was carried out into the effects thermal noise has on the count rate. Both phones were set up with a Cs-137 source for the course of several days. One hundred data points were recorded at each temperature. The results showed a relationship between the counts and the degrees Celsius. As the temperature is increased, the count rate also increases. Some of the values decrease but it is assumed that by obtaining a greater number of data points to use as the baseline measurements, that a more consistent graph would be obtained with counts increasing exactly proportional to the temperature rise. This noise effect was observed in both phones. However it was noted that the Sony phone operated on a much higher and wider temperature scale. This could be as a result of the phone battery being integrated and non removable in the phone, unlike the Alcatel phone, which uses a removable battery. Therefore the temperature of the battery could have a greater effect on the noise on the counts of the Sony phone, but the Sony phone has a smaller noise value and count rate than the Alcatel phone. This could be because the Sony phone is more expensive and modern and may have failsafe procedures built into the system coding architecture to decrease the effect signal thermal signal noise has on the phone.

28

As part of testing the performance of the Gamma camera, an investigation was conducted into a wide variety of gamma radiation properties under detectors. This properties and results did not differ overall from expected results based on data collected for other types of detectors and the theory behind the relationships. An investigation was carried out to determine the effects of distance on the count rate of the gamma camera. The setup and procedure was followed and the results were tabulated and graphed. It was found that the results verified the Inverse Square Law for both phone detectors. When a graph was created of counts versus the distance of the source to the detector window, it was found that there was an exponential decrease in the number of counts recorded as the distance was increased. When the distance was doubled the count intensity was decreased approximately by (1/d2). A graph was plotted of Counts vs. 1/d2. This showed a straight-line graph. This clarifies the relationship that as the counts are increased then the corresponding 1/(d2) values also increase and are directly proportional to each other. It was found that the Alcatel phone had a detection range of five times that of the Sony phone. This shows that it has a greater sensitivity range and again shows that the Alcatel phone is more susceptible to the photons. An investigation was carried out into the detectors performance to a change in the angle of the source the detector window. The setup was followed according to the method, and a graph for both phone gamma cameras were obtained. They showed consistent results. As the angle was increased, the count rate decreased exponentially. This shows the importance of the source position with respect to the lens window in order to obtain accurate results. Both phones showed that at approximately 40° the CMOS sensor could no longer detect high-energy penetrating photons from the camera and only recorded CPM-0 background radiation. An investigation was carried out into the effects of increased lead shielding on the counts recorded of gamma sources. The procedure was followed as in the method. The lead shielding was increased in increments of 0.3mm. The results were plotted and graphed and showed that there is an exponential decrease in counts recorded by the gamma phone as the lead shielding is increased. The half thickness value recorded which reduced the count rate by half was 8.2mm The values were recorded for periods of 10 minutes at each shielding measurement thickness. The expected half thickness of lead is 5mm. This large error in the result of the half thickness could be improved by running the measurement for longer periods of time to obtain a more consistent exponential curve. Using the two-source method with Cs-137 and Co-60 sources and measured background radiation, the resolving/dead time was calculated using the formulas found in the method. A resolving time of the detector is the interval of time until the detector can record another event. In order to obtain accurate detector results, a small dead time is required. The dead time for the Sony phone was 1.05 seconds. This is not a particularly good result as a Geiger molar counter has a dead time in the region of microseconds (μs). The dead time was recorded for the Alcatel detector to be 65milliseconds (mS). It would be assumed that the detector dead time should be approx. the same for similar detector system such as a CMOS sensor detector. The low dead time recorded for the Sony phone could be as a result of inconstant data with high variations in recorded results.

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Finally the absolute efficiency of the gamma detectors were compared to that of a variety of more sophisticated and different gamma detectors. The efficiency of the recorded photons/second for the phones was very small in comparison to the NaI(TI) detectors in both the well and stand-alone detector. The Cadmium Telluride detector had a very low absolute efficiency value due to the energy specificity of the detector. As the energy of the source (KeV) is increased the total efficiency decreases. The efficiency of the Alcatel Phone was very high. This again may be due to the over sensitivity to noise when compared to the Sony gamma detector.

Conclusion A low cost Gamma detector can successfully be designed through a simple manipulation by covering the lens with a black tape. This setup can measure high-energy photons, which penetrate the tape and are detected by the CMOS sensor in the Phone. It is an unconventional application for a Smartphone to measure radiation, however it can be implemented to provide qualitative proof of ionising radiation. The device is limited as it cannot measure the energy of a source, so the source cannot be identified, but once the device has been calibrated, it can provide a reasonable measurement the surrounding radiation field dose rate. Dose rates measured are quite accurate but not for sources under 10μSv/hr. and for determining the background radiation approx. 0.15μSv/hr. This is due to the gamma phone detectors lower sensitivity when compared to that of professional semiconductor detectors and Geiger counters. The sensitivity varies greatly from phone to phone. The Alcatel phone detected over 10 times the number of counts in comparison to the Sony phone. This is due to the detector’s internal setup such as CMOS sensor area, phone pixels, noise interference and current leakage. However despite this, the phones detected gamma radiation and also followed a number of pre-established theories regarding the detection of gamma rays such as- the inverse square law and the law of absorption. A number of factors affect the intensity of the counts and cause noise such as the internal temperature. Also the phone is limited by the geometrical position of the source to the detector lens. There are many detectors, which provide greater efficiencies and more accurate gamma detection. However the cost of these detectors range in the thousands. The prevalence of Smartphones in the modern era is widespread. This Phone gamma detector has a future in the detection of radiation. The number of detectors is limited, and by simple manipulation and use of the software analysis application, a smartphone can be turned into a useable gamma detector. It may not be the most accurate or sensitive but it is the most widespread. In conclusion the Phone detector has proved that it is a useable, reasonably accurate, low cost gamma detector.

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Limitations There are a wide variety of limitations associated with this phone camera detector. The sensitivity of the gamma detector varies from phone to phone. In order to obtain accurate results, the detector needs to be run for long periods of time. This limitation poses an array of limitations; such as the battery power length of the phone runs out quickly when using the software. This means that the software can be run at night but will shut down after only a few hours running. The radiation sources used must be handled with care. The sources cannot be brought outside of the laboratory space. Therefore this means that time management is crucial to obtain all of the data required in the limited time available. To stop the detector from losing power and cutting off detections, the phone can be left charging to an AC power supply. However this usage must be limited as charging increases the internal temperature of the phones battery, resulting in thermal noise and increase inaccuracies in the data values obtained. Due to the time cost of a smartphone capable of running the software, there is a limited availability to the number of smartphones, which can be measured. In this experiment another phone (Alcatel) was purchased. Finally the phone is limited with respect to the inability to determine the energy of sources. When comparing the detector to other semiconductors, which are able to detect energy, then this limits the variety and amount of efficiency calculations, which may be carried out. The activity of sources that can be used in this experiment is limited. The highest activity was the Ra-226, which had an activity of 5μCi. Using sources any stronger could result in damaging the CMOS sensor and leaving a permanent “black spot” on the detector lens.

Recommendations In order to improve this experimental investigation the number of smartphone devices used to implement the gamma detector should be increased. This will give a greater field of information on noise and count intensity. Also phones with a front camera could be recorded and the sensitivity and noise of the radiation intensity compared. The number of radioactive gamma sources could also be increased. This would allow for a more accurate calibration dose curve to be obtained, as it is lacking linearity from 0-10μSv/hr. If the experiment were repeated, a Geiger molar counter would also be used as a comparison for each data value investigation routine. The smartphone detector is effectively a Geiger molar counter and cannot be used to measure energy; this limits the efficiency calculations in comparison to semiconductor detectors. However direct counting comparisons can be made to a Geiger molar counter and this would improve the quality of the analysis.

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References

Papers BLOOR, E. F. 2013. Developing Methods to Measure Small Attenuation Coefficients Using Short Distance Radiation Detection. BUSHBERG, J. T. & BOONE, J. M. 2011. The essential physics of medical imaging, Lippincott Williams & Wilkins. GILMORE, G. 2011. Practical gamma-ray spectroscopy, John Wiley & Sons. GRÖBER, S., MOLZ, A. & KUHN, J. 2014. Using smartphones and tablet PCs for β−-spectroscopy in an educational experimental setup. European Journal of Physics, 35, 065001. KADUM, A. & DAHMANI, B. 2014. Efficiency Calculation Of Nai (Tl) 2x2 Well Detector. KNOLL, G. F. 2010. Radiation detection and measurement, John Wiley & Sons. KUHN, J., MOLZ, A., GRÖBER, S. & FRÜBIS, J. 2014. iRadioactivity—Possibilities and Limitations for Using Smartphones and Tablet PCs as Radioactive Counters. The Physics Teacher, 52, 351-356. LILLEY, J. 2013. Nuclear physics: principles and applications, John Wiley & Sons. MYERS, R. T. 1956. Dead time of a Geiger-Mueller tube by the double-source method. Journal of Chemical Education, 33, 395. SIEGBAHN, K. 2012. Alpha-, beta-and gamma-ray spectroscopy, Elsevier. SPIERS, F. 1941. Inverse square law errors in gamma-ray dose measurements. The British Journal of Radiology, 14, 147-156. WAHLSTRÖM, B. 1995. Understanding radiation, Medical Physics Publishing Corporation.

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Manuals [1] 905 Series-Ortec www.ortec-online.com/download/905-series.pdf (Accessed April 2015) [2] Series 1000 'Mini Rad' http://rp-alba.com/index.php?filename=MR1000.php (Accessed April 2015) [3] Radioactivity Counter Application http://www.hotray-info.de/html/radioa_help.html (Accessed January 2015) [4] XR-100T-CdTe X-Ray & Gamma Ray Detector http://www.amptek.com/products/xr-100t-cdte-x-ray-and-gamma-ray-detector/ (Accessed April 2015) Documents [5] Alpha Beta and Gamma Radiation Lab- Northwestern University http://courses.physics.northwestern.edu/new335/PDF/alphabeta.pdf (Accessed April 2015) [6] Ortec Geiger Counting http://www3.nd.edu/~wzech/Application-Note-AN34-Experiments-Nuclear-Science-Experiment-2.pdf (Accessed April 2015) Images [7] Radiation http://physics.tutorcircle.com/waves/gamma-decay.html (Accessed April 2015) [8] Compton Scattering http://www.fesaus.org/glossary/lib/exe/fetch.php?media=terms:glsp22f1.gif (Accessed April 2015) [9] Pair Production and annihilation http://electrons.wikidot.com/pair-production-and-annihilation (Accessed April 2015) [10] Photoelectric effect http://drgstoothpix.com/wp-content/uploads/2012/10/photoelectric-effect-1.jpg (Accessed 2015) [11] Inverse Square law http://hyperphysics.phy-astr.gsu.edu/hbase/acoustic/invsqs.html (Accessed April 2015)

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Appendix

Fig 56. Example Americium-241 interaction with CMOS

Fig 56. Example Cobalt-60 interaction with CMOS

Fig 56. Example Cesium-137 interaction with CMOS

Fig 56. Example Radium-226 interaction with CMOS

34

Fig 57. NaI(TI) detector

Fig 58. NaI(TI) well detector

Fig 59. CdTe detector

Fig 60. Detector window of mini rad digital dosimeter

35

Fig 60. Americium-241 Source

Fig 61. Cobalt 60 Source

Fig 62. Cesium-137 Source

Fig 63. Radium-226 Source

36

Fig 64. Phone gamma detector setup

Fig 65. Phone gamma detector setup (Angle variation) no date time cpm cpm n+1 cpm n+2

1 02/16/2015 16:49:54 71 29 13

2 02/16/2015 16:50:55 37 10 3

3 02/16/2015 16:51:56 45 26 12

4 02/16/2015 16:52:57 30 12 4

5 02/16/2015 16:53:58 28 10 3

6 02/16/2015 16:54:59 59 25 4

7 02/16/2015 16:56:00 47 22 8

8 02/16/2015 16:57:01 50 20 9

9 02/16/2015 16:58:02 71 19 2 uG/h mean(5) cpm mean(5) stddev (%) deg C

22.5 71 0 39

17.1 54 63 40

16.2 51 37.7 39

14.5 45.8 55.8 39

13.3 42.2 55.9 39

12.6 39.8 62.6 39

13.2 41.8 33.8 40

13.5 42.8 36.5 39

16.2 51 53.8 39 Fig 66. Example Raw data for Cesium-137 (Sony)