2. Contents
Introduction ..................................................................................................................................................3
Motivation.................................................................................................................................................3
Design Goals..............................................................................................................................................4
Design............................................................................................................................................................5
Detection Method.....................................................................................................................................5
Selecting a Geiger Muller Tube.............................................................................................................5
Power Supply ............................................................................................................................................7
Creating the Board................................................................................................................................9
Counting Electronics ...............................................................................................................................10
Data Collection........................................................................................................................................11
Programing the Arduino .........................................................................................................................11
Radiation and Testing .................................................................................................................................13
Background Radiation.............................................................................................................................15
Differentiating Between Background and a Sample...............................................................................17
How Volume Effects CPM .......................................................................................................................18
Determining Activity of a Sample from CPM Data......................................................................................19
Absorption Coefficient of Food...............................................................................................................22
Conclusion...................................................................................................................................................24
Bibliography ................................................................................................................................................25
Figure 1 - Tube Comparason.........................................................................................................................6
Figure 2- Comparison between SBM-20 and SBM-19 tubes. Background radiation as well as an
unspecified amount of KCL was used to compare the tubes .......................................................................6
Figure 3 - Schematic of the DC-DC converter ...............................................................................................7
Figure 4 - Transfer Characteristic of the Schmitt Trigger (74HC14)..............................................................8
Figure 5 - Output of the Schmitt Trigger (green) controlled by the voltage of the capacitor (blue).
Controls switching MOSFET..........................................................................................................................8
Figure 6 - Pulse from GM tubes (in yellow) vs the output of the comparator (in blue) .............................10
Figure 7- LCD connected to the Arduino.....................................................................................................11
Figure 8 - Sending data to Gobetwino........................................................................................................11
Figure 9 - Main Loop ...................................................................................................................................12
Figure 10 - Decay Scheme of Cs-137...........................................................................................................13
Figure 11- Decay Scheme of I-131 ..............................................................................................................13
Figure 12 - Decay Scheme of K-40 ..............................................................................................................14
Figure 13 - Background radaition recorded over 26 hours.........................................................................15
Figure 14 - Standard Normal Distribution of Background Radiation..........................................................16
3. Figure 15- Bell Curves of different KCL samples dissolved in Jello. ............................................................17
Figure 16 - Detected CPM vs Changes in Volume.......................................................................................18
Introduction
Motivation
The motivation for this project originates with the Fukushima Daiichi nuclear disaster in 2011 and the
global repercussions that followed in its wake. On March 11, 2011 a 9.0 magnitude earthquake struck
near the island of Honshu producing a large tsunami in Japan. The combination of the earthquake and
subsequent tsunami crippled the nuclear power plant in the Fukushima Prefecture of Japan, taking out
primary and secondary power sources that are needed to run the reactors cooling systems. As a result,
uncontrollable heat and pressure within the reactors led to explosions and meltdowns that effected
three out of the six reactors and one spent fuel pool [1]. This caused large amounts of radionuclides to
be released into the atmosphere as well as the ocean. The Woods Hole Oceanographic Institution,
estimated 16.2 petabecquerels of radioactive cesium leaked in the ocean and a similar amount into the
atmosphere. This is over 100 times more than a typical nuclear bomb [2]. Furthermore, due to leaks in
large water containment pools, and the “controlled discharge” of contaminated water, radioactive
contaminants have been consistently released into the ocean ever since the disaster in 2011 and is still
continuing today. In fact, on December 4, 2013 TEPCO publicized plans to continue with the controlled
discharge of contaminated water as a long term strategy to stabilize the facility [3].
It is no secret that fish and food grown local to the Fukushima area are unfit for human consumption do
to contamination of radionuclides, but the effects on the broader environment and food chain remain
questionable. Although the FDA maintains that there is no public health risks from the Fukushima
incident in the U.S food supply [4], Independent studies have shown elevated levels of cesium in U.S
drinking water [5], fish and other sea creatures caught in the pacific [6], as well as in U.S milk products
[7].
Although elevated levels of radionuclides have been detected, in most cases they do not exceed the
limits for food based radiation in North America which is 1,200 becquerels (bq, decays per second) per
kilogram for radioactive cesium, which is why the FDA and mainstream media outlets say that the risks
to public health are low. However, the limits in North America are much higher than Japans current limit
of 100 bq/kg [8]. It is unclear if these limits are set too high or what the long term consequences are for
ingesting contaminated foods. According to the National Academy of Sciences, there are no safe doses
of radiation and that any exposure will increases the chances of developing cancer. Furthermore, they
add that consuming contaminated foods is particularly harmful as these radioactive particles continue to
irradiate the body as long as they are present. Depending on the particular radionuclide, they may stay
in the body for a long period of time and concentrate in organs such as the thyroid, bones, or other
organs [5]. Based on this statement and the fact that elevated levels of radionuclides are being found
throughout the food supply, it seems likely that there will be at least some consequences to public
health in North America.
The product being developed is a radiation detector capable of detecting relatively small amounts of
radionuclides contained in foods. This product is intended to provide the public the means to reduce
their intake of food based radionuclides, and potentially prevent illnesses from occurring in the future.
4. Design Goals
The two dominant factors that drive the design of this product are cost and sensitivity. The final product
is to cost less than $500 to the end user, enabling a large portion of the general public to be able to
afford the device for personal use if they choose. Food based radiation detectors on the market today
costs thousands of dollars and are intended for laboratory use. These devices use expensive gamma
scintillators which are extremely sensitive and also allow for the identification of the specific
radionuclides present. In order to meet the <500$ criteria this technology will not be available. Other
cheaper technologies which are generally not fit for food based radiation detection will need to be used,
such as Geiger Muller tubes.
For the device to be useful, it will also need to be sensitive enough to detect food based radiation at at
least as low a concentration as the lowest recognized regulatory limits for radionuclide contamination in
food. Japan currently holds the lowest regulatory limits, at 100bq/kg of cesium137, thus, the detector
must be able to detect levels as low as this, if not lower.
These two factors, cost and sensitivity, present a significant design challenge that may or may not be
achievable. This report is a documentation of the development of such a product and seeks to
determine whether or not such a device, under these design criteria, is feasible.
5. Design
Detection Method
The ideal method of detection for a food based radiation detector is gamma scintillation. These devices
contain a material which exhibits luminescence when excited by ionizing radiation such as gamma rays.
A light sensor is used to detect each luminescence event and can determine the energy level of the
incoming radiation by the intensity of the luminescence. Gamma scintillation can be nearly 100%
efficient to gamma rays at lower energy levels and, since they can determine the energy levels of
incoming gamma rays, are able to identify the specific isotopes that are emitting the radiation [9].
However, these devices are very expensive costing upwards of $500 and are fairly big and bulky. The
next best method of detection is to use Geiger Muller tubes.
Geiger Muller Tubes (GM tubes) consist of a chamber filled with a low pressure inert gas along with two
electrodes, one being a metal rod in the middle of the tube, and the other being the metal exterior of
the tube. A high voltage is applied between the two electrodes, typically 400-900 volts. When ionizing
radiation enters the tube, some of the gas molecules are ionized, creating charged ions and electrons.
Because of the electric field in the tube, the electrons are accelerated towards the anode. These
electrons gain sufficient energy to ionize other gas molecules causing a chain reaction. The result is the
generation of an electric pulse which is usually used to increment a counter. The disadvantages of using
GM tubes are that they aren’t very sensitive to gamma radiation (1-4%) and they are unable to
differentiate between different radionuclides.
Although other detection methods exists, such as semiconductor based detectors, spark chambers, etc,
it was determined that GM tubes had the best sensitivity characteristics for the price and are size
appropriate for the device, thus this project was based around this technology.
Selecting a Geiger Muller Tube
Geiger Muller tubes come in a wide range of sizes, sensitivity characteristics, and sensing capabilities.
Larger tubes have the benefit of a larger sensing area, which increases the chances that an emitted
gamma or beta ray will interact with the detector. Furthermore, some GM tubes are much more
sensitive than others. Geiger tubes manufactured to detect high levels of radiation are purposely made
to be less sensitive so that the count rate does not go to saturation.
Through conversations with a Geiger counter enthusiast as well as a GM tube vendor it was suggested
that modern GM tubes which cost $100+ each have very similar characteristics to old surplus tubes
which cost <$20 each. Furthermore, some surplus tubes are available in quantities that could support
low to mid volume production runs. Because of this, it was decided to use the cheaper surplus tubes for
this project. Figure 1 below is a comparison of some common surplus tubes. Cesium 137 is one of the
main radionuclides from the Fukushima fallout, so a tube with a high sensitivity to this would be ideal.
Judging by the table in Figure 1, the LND 7317 and LND 5979 tubes have the best characteristics,
however these are pancake style Geiger tubes, are much more expensive than some of the other tubes,
and aren’t available in large quantities. Therefore the SBM-20 tubes as well as the SBM-19 tubes was
determined to be the best candidates for this project and several of each were ordered. Both have
similar characteristics and similar cost (<$20) however the SBM-19 tubes are much larger and thus
register more counts per minute. Figure 2 shows a comparison of the SBM-20 and SBM-19 tubes to
background radiation as well as an unidentified amount of KCL (KCL is slightly radioactive). Note that the
6. fluctuations in CPM is quite significant over the 20 minute sample period, this will pose a problem when
measuring the activity of food samples.
Figure 1 - Tube Comparason
Figure 2- Comparison between SBM-20 and SBM-19 tubes. Background radiation as well as an unspecified amount of KCL was
used to compare the tubes
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CPM
Time (20 min total)
SBM-20 & SBM-19 Comparison
SBM-20 Background
SBM-19 Background
SBM-20 KCL
SBM-19 KCL
7. Power Supply
As stated previously, Geiger Muller tubes require a voltage typically between 400-900 volts for optimum
performance. The recommended voltage for the tubes to be used in this project is 400, but slightly
higher voltages will not negatively affect performance. The applied voltage is used to accelerate
electrons created from the ionization of gas within the tube, therefore very little current draw is
required (on the order of micro amps). Since the Arduino that will be used with this project operates off
of a 5V supply, it was decided that for simplicity, the high voltage power supply should have a 5V input.
Ideally the power supply would also be compact enough to fit inside the device and have a low current
draw so that the battery life is reasonable.
Maxim Integrated released a support document detailing the design for a 470V DC-DC converter
intended for Geiger Muller tubes. Their design was compact, had a low input current (80 micro amps),
and had a 5V input, perfectly meeting all the requirements for the intended power supply. Therefore,
instead of designing a power supply from scratch, this was used as a template. The design consists of
two main stages - a boost converter increasing the 5V input voltage to nearly 70V, and then a 7 stage
voltage multiplier, further increasing the voltage to around 475V. Figure 3 shows the schematic of the
device [10]. Presumably a two stage design was used in order to allow for a smaller sized inductor, thus
reducing the space requirements of the device.
Figure 3 - Schematic of the DC-DC converter
The circuit was simulated in LTSpice to better understand how it would operate, and to determine if any
alterations would be beneficial.
The boost converter stage is a swiched-mode power supply which uses a 4.7µH inductor and a switching
MOSFET to generate a voltage. The switching frequency of the MOSFET is controlled by the 100pF
capacitor as well as the 100kΩ and 10kΩ resistors. The voltage of the capacitor then acts as an input to
the Schmitt Trigger (74HC14) which is active low and has a 2.6V positive-going threshold and a 1.7V
negative-going threshold for a 5V supply voltage. See Figure 4 for the transfer characteristics of the
Schmitt Trigger. While the output of the Schmitt Trigger is low, the 100pF capacitor is charged from the
op amp through a 100kΩ current limiting resistor until the voltage over the capacitor reaches the
8. positive-going threshold of the Schmitt Trigger and the output goes high (5V). In this case the capacitor
is discharged through the 10kΩ resistor until the negative-going threshold of the Schmitt Trigger is
reached. This process creates a switching frequency of 262KHz. Figure 5 depicts the relationship
between the capacitors charge and the output of the Schmitt Trigger. The blue waveform is the voltage
on the 100pF capacitor, and the green waveform is the input of the MOSFET.
Figure 4 - Transfer Characteristic of the Schmitt Trigger (74HC14)
Figure 5 - Output of the Schmitt Trigger (green) controlled by the voltage of the capacitor (blue). Controls switching MOSFET.
Once the desired voltage from the boost converter is obtained (70V) the feedback loop prevents the
voltage from raising higher by switching the output of the Op Amp to 0V.
9. The 7 stage voltage multiplier then increases the 70V output from the boost converter, essentially
doubling the voltage each stage (minus diode losses) until the output is 475V.
Creating the Board
The initial goal of this project was to develop a production ready product in only 4 months. In order to
cut down on development time it was essential to create a prototype that was as close as possible to
what the finished product would be. This meant engineering for low power consumption and a compact
design. To do this, surface mount components were essential. To use surface mount components
however, a PCB must be specially made. This was be done by transferring the toner from a printed
model of the PCB onto a blank copper PCB, and using an etching solution to dissolve the excess copper.
The model was designed in Altium Designer. The design has been mirrored such that it would have the
correct orientation after being transferred onto the copper board. The image is printed onto an ultra-
glossy paper, then placed on top of the copper board. Heat is applied via a clothing iron which melts the
toner and binds it to the copper board. The board is then placed into a Ferric Chloride solution which
dissolves the copper which is not covered by toner. The next step is to solder all the components onto
the board. The finished product is shown in Figure 7 below. Note – two were made on one board to
increase the chances of one having all traces intact.
Figure 7 - Finished PCB
Testing of the PCB showed that it worked as intended and produced a stable voltage of around 460V.
10. Counting Electronics
Geiger tubes generate an electric pulse when ionizing radiation interacts with gas inside of the tube.
Electrically this can be modelled as a normally open switch connected to some internal resistance. When
radiation is detected, the switch closes for a fraction of a second, generating a voltage on the output.
For the prototype, an Arduino development board is used to count these pulses as well as do other
function such as analytics, user interfacing, etc.
In order to interface the Geiger tubes to the Arduino’s interrupt capable port, which is a digital input
port, the analog signal from the Geiger tube needed to be converted to a 0-5V digital signal. To do this a
comparator or Schmitt Trigger can be used. In this case a comparator with hysteresis was used in order
to avoid any oscillations between HIGH and LOW as the analog signal approaches the threshold voltage.
The threshold voltage was set at 2.5 volts via a voltage divider. The anodes of the tubes are connected
to a 2MΩ current limiting resistor, and the cathodes of the tubes are connected together and fed
directly into the comparator with a parallel resistance. The resistance values were chosen via trial and
error to ensure all pulses entering the comparator were at least 5V, while low enough to avoid causing
harm to the chip. It was found that using a 22kΩ resistor was ideal, allowing for enough current to flow
for a quick response time, and keeping the voltage high enough such that no pulses would be missed.
This method may not be the best solution for the production version as the tubes aren’t properly
grounded, however for a prototype it was a quick and effective to begin testing.
Figure 6 - Pulse from GM tubes (in yellow) vs the output of the comparator (in blue)
The comparator was made to output an active low signal, falling from 5V down to 0V when radiation is
detected. This was achieved by using a pull up resistor on the pin which is grounded when active. This
provides a faster rise (fall) time compared to an active high orientation which is ideal for a TTL or CMOS
gate input [13]. This signal from the comparator is inputted into the Arduinos interrupt enabled digital
input.
11. A 16x2 character LCD was also connected to the Arduino in order to display relevant information such as
counts per minute. The LCD occupies 6 digital i/o ports on the Arduino, leaving 8 remaining pins.
Figure 7- LCD connected to the Arduino
Data Collection
The Arduino does not have the capability to collect data over a long period of time for export into an
excel sheet or other formats. To do this an additional flash memory module would need to be added, or
the Arduino would need to send the data to another device such as a PC. A program called Gobetwino
provides an interface that allows the Arduino to send commands and data through its serial port to a PC.
The commands and data are interpreted by Gobetwino which then carries out the intended task such as
writing data to a text file. This program was used to autonomously collect data from the Arduino.
Programing the Arduino
In order to get the device working quickly to proceed with testing, a simple program was written to
obtain and log the counts per minute (CPM) data. Interrupts were used to increment a counter
whenever a pulse was detected. After 60 seconds this counter resets, and the data is sent serially to a PC
where the program Gobetwino writes it to a text file.
Figure 8 - Sending data to Gobetwino.
12. Figure 9 - Main Loop
The output of the Arduino, in counts per minute, was visually compared with pulses seen on the
oscilloscope, verifying the accuracy of the device. In this test only one SBM-20 tube was used to reduce
the counts per minute to around 30, making visual counting easier. The oscilloscope trigger was set to 2
or 3 volts in order to capture each event. Each time the oscilloscope updated, indicating a new pulse, it
was counted and compared to the counts measured from the Arduino. Both counts were the same,
indicating that there was no missed pulses, or false positives. Since no amplifiers are used, generating a
false count from internal noise is unlikely. The noise level in the device would need to spike to at least
2.5 volts in order to cross the threshold voltage of the comparator. A pull up resistor on the input pin to
the Arduino also prevents the input voltage from ‘floating’ and registering false positives. From this test
it was concluded that each registered count indicated a genuine detection of an energetic
particle/photon.
13. Radiation and Testing
The primary release of radionuclides from the Fukushima Daiichi Nuclear Disaster - both in the
atmosphere and the ocean - was in the form of cesium and iodine isotopes. Strontium and Plutonium
have also been found, but at lower quantities [11]. The decay scheme of both Cesium-137 and Iodine-
131 are shown in Figures 10 & 11 below. Both decay via the emission of a beta particle into a secondary
unstable isotope which then decays via the emission of a high energy photon (gamma ray) into a stable
ground state. The largest difference between these two isotopes is their half-life. Cesium has a half-life
of 30 years, whereas iodine has a half-life of around 8 days.
Figure 10 - Decay Scheme of Cs-137
Figure 11- Decay Scheme of I-131
For this project to be successful, the device must be able to detect small amounts of these elements
(cesium and iodine) in a variety of different food mediums. Preliminary calculations showed that this
would not be difficult to do since Geiger tubes are very efficient to the detection of beta particles (80%
is a common figure). If a sample contained 10bq of cesium-137 for instance, this means that cesium-137
would break down and release a beta particle 10 times per second. 94% of the time, the cesium would
break down into Barium-137, further releasing another 9.4 gamma photons per second to detect in
addition to the beta particles. With a beta efficiency of close to 80%, and a sensing area taking up at
least 40% of the total possible area a particle or photon could travel in (dependent on the number and
size of tubes used), it was calculated that the Geiger tubes should detect 3.2 counts per second (or 192
CPM) from beta particles alone of a 10bq sample.
14. 𝑒𝑚𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑠 𝑝𝑒𝑟 𝑠𝑒𝑐𝑜𝑛𝑑 ∗ 𝑐ℎ𝑎𝑛𝑐𝑒 𝑡𝑜 ℎ𝑖𝑡 𝑡ℎ𝑒 𝑑𝑒𝑡𝑒𝑐𝑡𝑜𝑟 ∗ 𝑐ℎ𝑎𝑛𝑐𝑒 𝑡𝑜 𝑏𝑒 𝑑𝑒𝑡𝑒𝑐𝑡𝑒𝑑
= 𝑑𝑒𝑡𝑒𝑐𝑡𝑖𝑜𝑛𝑠 𝑝𝑒𝑟 𝑠𝑒𝑐𝑜𝑛𝑑
10 ∗ .40 ∗ .80 = 3.2
If this were true, the construction of such a device would almost be trivial, however this is not the case.
Overlooked in the preliminary calculations was the fact that beta particles can only travel a few
millimeters in most materials. This means that the chance to hit the detector is much lower than the
estimated 40%, due to most of the beta particles being re-absorbed by the medium.
This fact came to light while doing an experiment with Potassium Chloride (KCL). Roughly 1 out of every
8,500 potassium atoms is the isotope K-40, which is radioactive (see the decay scheme below). Although
potassium is consumed by humans on a daily basis, the amount of potassium stored in the body is kept
relatively constant by the body, and the organs that use potassium have adapted to the small amounts
of radiation it gives off - therefore potassium is relatively harmless to the human body. Since this
substance is widely available in the form of salt alternatives, it was used as an analog to test the
performance of the Geiger tubes. As you can see, K-40, like Cs137 emits both gamma and beta radiation,
however it should be noted that KCL emits a larger ratio of Beta particles to gamma particles than Cs137
and I133.
Figure 12 - Decay Scheme of K-40
The table below show the results of placing KCL first on a piece of paper on top of the GM tubes, and
then placing the same amount of KCL inside a Jello mixture. The Jello is intended to simulate the
reabsorption that may be found in a food sample. Data was collected for each case over a period of at
least an hour and the averages were taken.
Sample Average CPM
0.62g KCL (approx. 10bq) on paper 169
0.62g KCL (approx. 10bq) Dissolved in Jello 74
7.29g KCL (approx. 117pq) on paper 438
7.29g KCL (approx. 117bq) Dissolved in Jello 229
Background Readings 69
15. This experiment shows that a significant portion of the beta particles are reabsorbed in the Jello
compared to when placed on a piece of paper and that the initial calculations were flawed. Accounting
for the background radiation, the 10bq Jello sample only produced about 5 counts per minute (74 - 69),
while a 10bq sample without Jello produced around 100 CPM (169 - 69). Using Jello as a medium caused
a decrease of detections by a factor of 20 in this case. This experiment also showed that this factor may
not be linear. The 117bq sample placed on paper produced 369 CPM (438 – 69) above the average
background radiation. However placing the same amount in Jello reduced that to 160 CPM (229 – 69),
only reduced by a factor of 2.3. One plausible explanation for this is that the 117bq sample, when placed
on a piece of paper, produced a pile of salt which would have its own internal absorption much higher
than the much smaller pile of the 10bq sample.
Background Radiation
Another factor which wasn’t taken into account in the preliminary calculations was the variation in
background radiation, and variation in readings from a given sample. As seen in Figure 2, over a short
period of time, the radiation readings vary quit significantly. Below shows the background radiation
readings taken over a 26 hour period on November 26 – 27. Although there is a significant variation on a
minute by minute basis, the average CPM remains somewhat constant over the time period. Also shown
below is a standard normal distribution of the measured CPM.
Figure 13 - Background radaition recorded over 26 hours.
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6/27/2003 0:006/27/2003 4:486/27/2003 9:366/27/2003 14:246/27/2003 19:126/28/2003 0:006/28/2003 4:486/28/2003 9:36
CPM
Time
Background Radiation (Nov 26-27)
26 Hour Duration
16. Figure 14 - Standard Normal Distribution of Background Radiation
Because of the variation in background radiation, particularly in the short term, as well as the fact that
very little counts per minute from a food sample will be registered due to internal absorption (as
discussed in the previous section), measurements in the order of minutes would not provide statistically
significant results. For this device to work, measurements will need to be taken over hours.
0
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CPM
Background Radiation (Nov 26-27)
Normal Distribution
17. Differentiating Between Background and a Sample
The following experiment is intended to determine if it is possible to adequately differentiate between
the background radiation and a low activity sample dissolved in Jello, as well as differentiate between
samples with various activities. 25bq, 50bq, 100bq, 200bq, and 300bq samples were tested, all dissolved
in approx. 250ml of Jello of the same shape and measurements were taken over a 4 hour period. This
translates in to samples that are approximately 100bq/kg, 200bq/kg, 400bq/kg, 800bq/kg, and
1200bq/kg. Below shows the probability distribution of each test.
Figure 15- Bell Curves of different KCL samples dissolved in Jello.
This shows that the 50 bq sample is not distinguishable from the background radiation, however the
100bq sample, who’s mean is nearly one standard deviation away from the mean background radiation
may be within the detection capabilities of the device. 200bq and above are clearly able to be
distinguished from background, and increments of 100bq are also easily differentiated. Furthermore,
KCL which was used as the radioactive source in this experiment may not be as easily detected as Cs-137
or I-131 which also goes through a secondary decay, producing low energy gamma radiation, and thus
providing more potential events to pick up. Low energy gamma is also more readily detected than high
energy gamma, (which is emitted from KCL) since it has a higher probability of interacting with the tube.
Figure 13 below illustrates how the measured average CPM varies with sample activity (in bq) of KCL
dissolved in Jello. It is unknown why activities below 100bq do not cause as much change in detected
CPM when compared to the slope seen at higher activity samples. Perhaps the added counts from the
-0.05
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Probability
CPM
Normal Distribution of Various KCL Sample Activities Disolved in
Jello
Control
50 bq
100bq
200bq
300bq
18. sample is matched by the reduction in background radiation blocked by the sample. This would need to
be studied further.
How Volume Effects CPM
Another experiment similar to the above involved varying volume instead of activity. Unfortunately, the
Arduino board mysteriously stopped working before all the data could be collected, however below
shows the results of a 100bq KCL sample in 0.5 cups of Jello, 0.75 cups of Jello, and 1 cup of Jello. The
variation in results occurs because with a larger volume, a larger percentage of Beta particles will be
absorbed.
Figure 16 - Detected CPM vs Changes in Volume
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CPM
Activity (bq)
Detected CPM vs Sample Activity in Jello
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CPM
Cups of water used to make Jello
Detected CPM of KCL vs Volume of Jello
19. Determining Activity of a Sample from CPM Data
There are a number of factors that need to be taken into account in order to most accurately determine
the activity in bq/kg of a sample from the measured CPM data. These include:
Volume of the sample (effects Beta particle absorption)
Samples Beta absorption coefficient (may be linear with density)
Efficiency of the GM tubes to Gamma and Beta radiation
It is currently unknown how volume could be measured easily and inexpensively, this will have to either
be approximated by the mass of the object, or a technique to estimate/ measure it would need to be
developed. One idea was to use a grid of infrared LED’s and detectors on either side of the sample.
Lighting each LED at a time and sampling the detectors to see the shadow cast from each LED may
provide a means to estimate the shape and volume of the sample by compiling that information. If
volume could be determined, determining the density would only require measuring the samples
weight. This would need to be done regardless in order to calculate the bq per kilogram that many
standards are based on.
Thanks to the efforts of Dr. Mihai Sima, a number of radioactive calibration sources were able to be
borrowed from UVic’s Physics Department. These were used to measure the Beta and Gamma efficiency
of the tubes, as well as the absorption characteristics of some food samples. The sources borrowed
include Cs-137, Pb-210, and Na-22.
Cs-137 undergoes Beta decay into Ba-137m. This then gamma decays into a ground state.
Pb-210 undergoes Beta decay into Bi-210 which then Beta decays into a ground state.
Na-22 is a positron emitting isotope that undergoes electron capture, secondary decay is via gamma
emission.
The first experiment involved determining the Beta and Gamma efficiency of the tubes. Pb-210 is a pure
Beta emitter and would be used to determine the Beta efficiency. It came as a long, thin rod about 1mm
thick, therefore it was expected that the internal absorption within the material would be small. The
other sources were incased in a plastic die and would not be ideal for measuring Beta radiation due to
an unknown amount of Beta particles being absorbed within the material. For measuring Gamma
efficiency, the Cs-137 source would be used. This is ideal since it is the same radionuclide, and thus the
same energy level as what is found in the Fukushima contamination. Although Cs-137 is technically a
Beta emitter, it undergoes a secondary decay emitting Gamma rays of 0.6617 MeV. The majority of the
Beta particles will be blocked with a metal plate approximately 1mm thick.
20. Experiment 1: Beta Efficiency
Pb-210: Activity of 0.1μCi in October 1984
Present day activity of 0.04µCi or 1480 bq (using online calculator)
1480 * 60 = 88800 decays per minute
46% chance for any given particle to have a path intersecting the detector. (calculated under a point
approximation)
Expected CPM = Decays per minute * probability of hitting the detector
= 88800 * .46
= 40848 CPM
Actual Measurement = 2635 CPM
Average Background = 830 CPM
Total counts from sample = Measured – Background
= 2635 – 830
= 1805 CPM from sample
This equates to a 4.4% efficiency
This is much lower than expected. General rule of thumb from research is an 80% efficiency to Beta.
Experiment 2: Gamma Efficiency
Cs-137: Activity of 0.1μCi as of July, 1990 (gamma= 0.6617 MeV)
Present day activity of 0.0583µCi or 2146 bq
2146 * 60 = 128,760 decays per minute
46% chance for any given particle to have a path intersecting the detector. (calculated under a point
approximation)
Expected CPM = Decays per minute * probability of hitting the detector
= 128,760 * .46
= 59229 CPM
Actual Measurement = 1470 CPM
Average Background = 830 CPM
Total counts from sample = Measured – Background
= 1470 – 830
21. = 649 CPM from sample
This equates to a 1.1% efficiency
This is also a bit lower than expected. Values between 1-3 % are commonly stated online.
Gamma Efficiency using Na-22
Na22: 9.896µCi as for March, 2000 (gamma = 1.274MeV)
Present day activity: 0.255µCi or 9435 bq
9435 * 60 = 566100 decays per minute
46% chance for any given particle to have a path intersecting the detector. (calculated under a point
approximation)
Expected CPM = Decays per minute * probability of hitting the detector
= 566,100 * .46
= 260,406 CPM
Actual Measurement = 12479 CPM
Average Background = 830 CPM
Total counts from sample = Measured – Background
= 12479 – 830
= 11649 CPM from sample
This equates to a 4.5% efficiency
This is larger than expected and may be due to the energy level being higher. Note: Two metal plates
were used in this case since the penetrating power of the positrons seemed higher.
22. From these experiments it seems like the gamma efficiency is quite dependent on energy level. Even
though two metal plates were used instead of just one with the Na-22 sample which produces gamma
radiation at an energy level of 1.27 MeV. The Cs-137 produces 0.662MeV gamma radiation and was
found to have an efficiency of 1.1% compared to 4.5% in the case of the higher energy gamma rays.
Cs-137 is however one of the radionuclides that the device will be calibrated to detect. Therefore the
value of 1.1% will likely be used.
The calculated Beta efficiency (4.4%) was a lot lower than expected. This may be due to internal
absorption within the lead rod, however this was only around 1mm thick and seems unlikely to be
responsible for such a significant difference. The expected value should be around 80%.
Absorption Coefficient of Food
The goal of these experiments was to find the absorption coefficient of Beta particles in salmon.
Beta absorption using Pb-210:
CPM of Pb-210 with no salmon = 2635 CPM – 830 (background) = 1805 CPM
CPM of Pb-210 on top of 1mm piece of salmon = 876 CPM – 830 (background) = 46 CPM
CPM of Pb-210 on top 2mm piece of salmon = 878 CPM – 830 (background) = 48 CPM
The second result doesn’t correlate to the first.
Using the following equation:
𝑇 =
𝐼
𝐼0
= 𝑒−𝛼𝑥
T = Transmission, x = Material Thickness, α = Absorption Coefficient
For first result: x = 1mm
𝑇 =
𝑀𝑒𝑎𝑠𝑢𝑟𝑒𝑑 𝐵𝑙𝑜𝑐𝑘𝑒𝑑
𝑀𝑒𝑎𝑠𝑢𝑟𝑒𝑑 𝑈𝑛𝑏𝑙𝑜𝑐𝑘𝑒𝑑
=
46
1805
= 0.0255
Solving for α:
𝑙𝑛𝑇 = −𝛼𝑥
ln(0.0255) = −𝛼(1)
𝛼 = 3.669
Second result: x = 2mm, T = 0.0266
ln(0.0266) = −𝛼(2)
𝛼 = 1.81
23. Beta absorption using Cs-137:
Cs137 directly on tubes: 1761 CPM
Cs137 with beta blocked by metal plate: 1470 CPM
Cs137 adjusting for gamma and background = 1761 – 1470 (background and gamma) = 291 CPM
Cs137 on 1mm of salmon: 1594 CPM - 1470 (background and gamma) = 124 CPM
Cs137 on 2mm of salmon: 1566 CPM – 1470 (background and gamma) = 96 CPM
Using the following equation:
𝑇 =
𝐼
𝐼0
= 𝑒−𝛼𝑥
T = Transmission, x = Material Thickness, α = Absorption Coefficient
For first result: x = 1mm
𝑇 =
𝑀𝑒𝑎𝑠𝑢𝑟𝑒𝑑 𝐵𝑙𝑜𝑐𝑘𝑒𝑑
𝑀𝑒𝑎𝑠𝑢𝑟𝑒𝑑 𝑈𝑛𝑏𝑙𝑜𝑐𝑘𝑒𝑑
=
124
291
= 0.426
Solving for α:
𝑙𝑛𝑇 = −𝛼𝑥
ln(0.426) = −𝛼(1)
𝛼 = 0.8533
For first result: x = 2mm
𝑇 =
𝑀𝑒𝑎𝑠𝑢𝑟𝑒𝑑 𝐵𝑙𝑜𝑐𝑘𝑒𝑑
𝑀𝑒𝑎𝑠𝑢𝑟𝑒𝑑 𝑈𝑛𝑏𝑙𝑜𝑐𝑘𝑒𝑑
=
96
291
= 0.330
Solving for α:
𝑙𝑛𝑇 = −𝛼𝑥
ln(0.330) = −𝛼(2)
𝛼 = 0.554
Although this provided better results than the previous experiment, both values of α should be the
same. More studies would need to be done to determine α with more precision, not only for salmon,
but for a wide range of foods.
24. Conclusion
Creating a device that could measure small amounts of radiation in foods proved more complicated than
originally thought. Although this project has shown some merit to using this technology for the
detection of food based radiation, successful implementation would require a lot more research, data
collection/ analysis, and fine tuning.
Although the large variation in background radiation, and low efficiency of GM tubes make it difficult,
detecting food samples as low as 100bq is possible.
In order to use the data collected from this device to estimate the activity of the sample in bq/kg a
number of variables must be known and understood. This includes the tube efficiency to Beta and
Gamma radiation, the absorption characteristics of the food sample, and possibly the shape or volume
of the sample. Although some tests were conducted in order to measure tube efficiency and absorption
characterizes, the results varied quite significantly depending on the type of radioactive material used.
More experiments need to be done in order to determine accurately the efficiency and absorption
characteristics, particularly in the presence of Cs-137 and I-131, which are the main radionuclides
present in Fukushima contaminated foods.
25. Bibliography
[1] Timeline of the Fukushima Daiichi Nuclear Disaster,
http://en.wikipedia.org/wiki/Timeline_of_the_Fukushima_Daiichi_nuclear_disaster
[2] Ocean Still Suffering From Fukushima Fallout, http://www.nature.com/news/ocean-still-suffering-
from-fukushima-fallout-1.11823
[3] Tepco Plans to Dump All Fukushima Radiation into the Ocean, http://www.globalresearch.ca/tepco-
plans-to-dump-all-the-fukushima-radiation-into-the-ocean/5361714
[4] FDA Response to the Fukushima Dai-ichi Nuclear Power Facility Incident,
http://www.fda.gov/newsevents/publichealthfocus/ucm247403.htm
[5] Radiation Levels Up to 1000 Times Higher than Current “Safety Levels”,
http://www.globalresearch.ca/radiation-levels-up-to-1-000-times-higher-than-current-safety-
levels/24147
[6] http://www.globalresearch.ca/fukushima-the-ticking-nuclear-bomb-over-800-tons-of-radioactive-
material-pouring-into-pacific-ocean/5356276
[7] http://biontologyblogging.com/radiation-fukushima/
[8] Fukushima Food Facts, http://www.nuclearcrimes.org/fukushimafaqs.php
[9] Scintillation Counter, http://en.wikipedia.org/wiki/Scintillation_counter
[10] Bias Supply Powers Low-Power Geiger-Mueller Tube, http://www.maximintegrated.com/app-
notes/index.mvp/id/3757
[11] Radiation Effects from the Fukushima Nuclear Disaster,
http://en.wikipedia.org/wiki/Radiation_effects_from_the_Fukushima_Daiichi_nuclear_disaster#Total_e
missions
[12] The Circuit Designers Companion 3rd
edition, Peter Wiliams
