Masters Project:
Construction and Calibration of a Spark Discharge
Generator to Create Mono-disperse Metallic Aerosol
Nanoparticles
By: Jonathan E. Pautler
Project supervisors:
Knut Deppert, Maria E. Messing, and Bengt O. Meuller
Lund University 2012
1
Abstract:
A Spark Discharge Generator is a versatile device which can be used to generate
nanoparticles from any two conducting sources. The device constructed during this thesis
project was to make metallic mono-disperse aerosol nanoparticles towards applications in
catalysis and nanowire growth. The operating principle is two electrodes separated by a gap
with an applied voltage above the discharge voltage. This high potential creates an
ionization channel and a spark is discharged between the two electrodes causing a high local
temperature on the ends of the electrodes which causes thermal evaporation of the
material into the surrounding gas. These initial particles with sizes on the atomic scale
collide and adhere by a process called coagulation creating larger nanoparticles which may
then be filtered, reshaped, counted, and deposited. A theoretical introduction is presented,
a description of the components is included, some techniques for calibration of the device
are described, and initial data is shown.
2
Acknowledgments:
I have been given the warmest welcome in Sweden by both the people and the
department at Lund. I acknowledge those who have helped me most with my sincerest
of gratitude and for those who I have forgot to mention here for brevity you are in my
thoughts.
First is of course my advisors; to Knut for giving me the opportunity to perform in the
lab, for the time, concern, and effort he has continually given to help me be the best
student, and to keep me on the right path in research.
To Maria for all the laughs, wit, and encouragement enclosed within scientific
discussions. You’re a source of never-ending energy and efficiency, and I find I am much
more productive when I am having fun.
To Bengt for being the person who was with me most days handling the real challenges
of building the device; your wisdom and expertise has driven this project forward. Life is
much easier when you have someone else to wonder, “what is going on with this thing”
with! Bengt has been a founding designer of the system and completed the vast majority
of the building of the device before and during my time here at Lund.
To Sebastian who has been the best of partners, a close friend; as well as, the other
fellow who has with me wondered “what is going on.” I am glad it seems we have
figured most of the problems out. I wish you the best of futures and I hope we work
together again. Sebastian also deserves credit for much of the work performed in this
thesis, and is a contributor to several segments of the data, SEM images, and
considerations on much of the analysis.
Special thanks goes to Marcus from Prevas who was hired to create an updated
structure to the Labview™ code, I have learned a lot from the new version and it
certainly made the data acquisition at the end much faster.
To Saiful, Mo, Henrick, Nick, Richard, Kristian, Dmitry and all the others who have given
insight into many problems of this project and are great friends.
Finally the personal side of things to my Mom and Dad for being a constant source of
love and have guided me to be who I am and helped in making me into the person I am
today.
Lastly to Anna who has been at my side this time and is a reason for why I have chosen
to do what I am doing.
3
Contents:
1. Introduction
2. Theory
2.1 Spark Discharge Generator Theory
2.2 Spark and Plasma Theory
2.3 Parameter Calculations
3. Methods
3.1 Machine Outline
3.2 Component Description
3.3 Lab-view/DAQ Summary
4. Results and Discussion
4.1 DMA Calibration and Accuracy
4.2 ESP and Deposition time calibration
4.3 Size distribution for various parameters such as current and gap size
4.4 Reshaping Temperature
4.5 Varying Electrode Size
4.6 Other Elements
5. Conclusions
6. Future work
7. References
8. Appendix
8.1 Major Component List
8.2 SDG Operating Procedure
4
1. Introduction/aim:
Nanoparticles are a major source of interest in modern research due to the large surface to
volume ratio and the capacity to demonstrate reduced dimensionality giving rise to
quantized states of matter. What this means is that nanoparticles are different in many
ways to their bulk counterparts; for example some gold nanoparticles are red or purple in
color, many nanoparticles are sticky, and many new phenomena happen in this territory
that baffles the mind and sends the imagination into overdrive.
Many next generation technologies could be centered on this already multibillion dollar
industry. Electronics have a high potential to be formed from nanoparticle and nanowire
technology especially those based on semiconductors due to the incredibly small size. These
prototype nano-devices have demonstrated that they can change their state of matter
faster and consume far less power than existing devices. This means better video games,
faster simulation speeds, and less time until we can see what our friends are doing on
Facebook. Additionally many Solar Technologies have nanoparticle centered cell types [1].
There are many methods to create nanoparticles: evaporation, sputtering, annealing of thin
films, and so forth. The thesis focuses on the Spark Discharge Method.
The aim of this thesis is to give a brief review of the theory behind nanoparticle generation
in the Spark Discharge Generator, the specific components and technology used within the
device constructed during the thesis, additionally the initial calibration data is presented
and described; as well as, a short summary of future work.
5
2. Theory:
2.1 Spark Discharge Generator:
The Spark Discharge Generator (SDG) comes in many forms. The basic form consists of a
carrier gas through a chamber, with two electrodes separated by a small gap, and a voltage
source applied to the electrodes to create a breakdown voltage. After the breakdown
voltage is reached, a high energy spark is created across the gap. The electrical energy is
converted to heat causing a high local temperature that rapidly evaporates part of the
electrodes resulting in nanoparticles in the carrier gas.
Figure 2.1.1: A SDG while in operation
Special thanks to Saiful Islam for photography
In a SDG many parameters can be adjusted to affect particle generation. Some examples
such as the type of carrier gas, flow of the carrier gas, pressure which is often near
atmospheric, and spark energy are critical to the type of particles produced. Additionally
after the particles leave the surface of the electrode the small initial particles collide and
stick together through a coagulation phase which leaves them as a stretched out chain of
connected primary particles which are called agglomerates as seen in Image 2.2. After
6
generation the particles are sent through a charger to give a known electrical distribution,
transported to a Differential Mobility Analyzer (DMA) for size selection, a compaction
furnace to reshape the agglomerated particles into spherical particles, a second DMA, an
Electrometer to give a particle count, and finally an Electrostatic Precipitator (ESP) to focus
charged particles onto a collector electrode where a substrate is placed for deposition [2].
Finally the gas exits the chamber and is filtered before returning to the atmosphere.
Image 2.1.2: Large Coagulation of gold nanoparticles: The photo exemplifies how both large and
small clusters can form together. These particular particles have undergone a surface coagulation
technique so some of the formations are larger than the aerosol particle clusters.
7
Gas in
Spark
Charger
DMA 1
Circuit
Furnace
DMA 2
ESP
Electrometer
Pump out
Figure 2.1.3 Schematic of the Spark Discharge Generator System
In Summary:
1. The Spark Generator creates the particles.
2. A charger gives a Boltzmann distribution of the particles charges [3].
3. The first DMA is used to filter out particles based on their mobility diameter in an
electric field [3].
4. A compaction furnace is used to control the shape of the particles by reshaping them
into spheres [2].
5. The second DMA is used to filter out particles based on their mobility diameter but
now that they are more uniformly spherical we have a more precise distribution.
This step is critical to getting mono-disperse particles because the furnace reshapes
the particles and when the furnace is over 500°C it might alter the number of
charges on some of the agglomerates [3].
6. A) An Electrometer is used to give a particle count.
8
B) Or an Electrostatic Precipitator (ESP) is used to focus charged particles onto a
collector electrode where a substrate is placed for deposition [2].
Each component will be explained in detail later on.
9
2.2 Spark and Plasma Theory:
During the spark process a constant flow of a carrier gas such as N2 goes between two
electrodes that are sparking. A plasma channel seen by the spark is caused by the wellknown phenomenon of having a high potential difference between two electrodes. As the
current passes from metal to carrier gas back to metal a large resistance causes energy from
the circuit to be transferred to the metal as heat causing electrode loss, which generates the
particles.
Figure 2.2.1: Circuit Diagram of the SDG
The circuit consists of a power source with a capacitor in parallel to cause regular discharges
based on the total capacitance (Figure 2.2.1). The spark itself can be thought of by its
equivalent circuit as a resistor that blocks the circuit until the breakdown voltage is reached
as a kind of switch resistor. The inductance in the wire determines the length of spark
duration. A diode is needed to protect the circuit from a current backflow, and there is a
resistor used to create a load which causes the capacitors to charge properly.
10
The Breakdown voltage, Vb, is governed by Pashcen’s Law:
𝑉𝑏 =
𝐴∗𝑝∗𝑑
ln(𝑝 ∗ 𝑑) + 𝐵
where
p = Pressure
d = Gap Distance
A & B are constants with values of:
A=4.36*10^7 V/(atm*m)
B=12.8 [4]
This breakdown voltage is reached when the electric field of the spark exceeds the dielectric
field strength of the surrounding gas forming an ionized conducting channel [5].
The conducting channel is formed by the excessive field, which first causes large numbers of
electrons to be released. Then the free elections collide with the neutral gas. The collisions
can be split into two categories Elastic and Inelastic collisions. Elastic collisions do not
change the internal energy of the neutral species but raise their kinetic energy. Inelastic
collisions modify the electronic structure of neutral species when energy is high enough
turning an innate gas into either an excited species or an ion at the cost of kinetic energy
[6].
These ions if given sufficient energy will collide and cause more excited species to form.
These excited species create a conductive channel, which then discharges current forming a
spark. The spark itself is the current flowing through this conductive channel.
In practice the spark has a delay from when breakdown voltage is reached and the discharge
occurs, and thus has an overvoltage. It sparks at a real voltage called the discharge voltage
𝑉𝑑 = 𝑉𝑏 + 𝑉𝑜 which is generally greater than the breakdown voltage.
1
The energy transferred via the spark is calculated using 𝐸 = 2 ∗ 𝐶 ∗ 𝑉𝑑 ^2
The spark frequency is given via 𝑓 =
𝐼𝑐
𝐶∗𝑉𝑑
where Ic is the current, C is the capacitance, and
Vd is the discharge voltage.
The total energy released, as a rate of time, is a function of the frequency times the energy,
which is the power [7], [8].
11
2.3 Parameter Calculations
The breakdown voltage is completely governed by the electrode gap and the pressure, so
we vary the gap size in Table 2.3.3 the pressure in Table 2.3.4. The current or frequency can
be varied to give a larger or smaller amount of energy transfer. These calculated values are
shown in Table 2.3.5 and Table 2.3.6.
This can be compared to the energy required to evaporate the metal to give a rough
estimate of the evaporation rate of the electrodes via the specific heat Q=m*c*ΔT which is
in J/Kg*K. The specific heat tells us the required energy to melt bulk metal. The specific heat
can be found in table 2.3.1 and is useful because it can estimate the amount of time it takes
under different conditions to generate a mass of nanoparticles, also it indicates that there
will be more or less mass loss for certain elements meaning smaller or larger particle counts
for identical conditions. For example with gold and copper we see copper is over 3 times as
high so we would expect less mass to be lost for the same conditions. To determine how
much of a finished product can be produced is a different question. Additionally losses
should be factored such as the filtering process in the DMAs and losses in the tubes, but this
works as a rough estimate as to how quickly electrodes disappear.
c (J/kg*K)
Melting Point (K)
Q (J)
Copper
386
1,083
408,002
Gold
126
1,064
130,788
Silver
233
962
218,088
Table 2.3.1: Specific Heat of Metals: Room temperature was assumed to be 26 °C [9]
Another consideration we can see from Figure 2.3.2 is a physical limitation to the frequency
of around 1 MHz where the plasma follows thermal laws instead of the electric field;
however, most frequencies tested in the lab are on the order of 300 Hz because higher
frequencies than 1kHz requires the capacitors in the circuit to be able to bear the strain of a
large power throughput. The value in Table 2.3.6, which is at 800 kHz, frequency makes it
clear why larger frequencies are not performed in the lab since the power consumption is
quite extreme.
12
Figure 2.3.2: Plasma frequency and behavior: fpi and fpe are the names of the regimes where
the plasma is ion or electron dominated [6]
Gap Size Breakdown
(mm) Voltage (kV)
Current
(mA)
0.5
2
1.0
3
1.5
4
2.0
6
2.5
7
3.0
9
3.5
10
4.0
11
4.5
13
5.0
14
10.0
28
20.0
54
30.0
80
50.0
132
Table 2.3.3: Varying Gap Size:
Energy per
spark (mJ)
Frequency
(Hz)
30
27
30
104
30
229
30
400
30
617
30
879
30
1,186
30
1,537
30
1,933
30
2,372
30
9,131
30
35,172
30
77,435
30
209,353
Calculated from Paschen’s
Power (W)
Power
(kW/Hr)
998
2.7
0.2
509
5.3
0.3
344
7.9
0.5
260
10.4
0.6
209
12.9
0.8
175
15.4
0.9
151
17.9
1.1
133
20.4
1.2
118
22.8
1.4
107
25.3
1.5
54
49.7
3.0
28
97.4
5.8
19
144.6
8.7
11
237.8
14.3
Law at Atmospheric Pressure and
subsequent calculations. The capacitance was 24 nF. The voltage shown is assumed to be the
breakdown voltage Vb but the real voltage or discharge voltage Vd is different due to the
overvoltage, the energy per spark will be shown to be much lower because of this. Larger gap sizes
produce larger particles due to the higher energy per spark.
13
Gap Size Pressure Breakdown
(mm)
(Atm) Voltage (kV)
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
0.01
0.1
0.5
1
2
3
4
10
20
Current
(mA)
0.1
0.6
2.9
5.8
11.3
16.8
22.2
54.1
106.3
30
30
30
30
30
30
30
30
30
Energy per
spark (mJ)
Frequency
(Hz)
0.05
4.59
104.06
399.83
1,537.43
3,381.48
5,916.27
35,172.12
135,573.48
Power (W)
22,546
2,427
509
260
133
89
68
28
14
Energy
(kW/Hr)
0.1
1.1
5.3
10.4
20.4
30.2
40.0
97.4
191.3
0.07
0.67
3.18
6.23
12.22
18.13
23.98
58.47
114.79
Table 2.3.4: Varying Pressure: Calculated from Paschen’s Law. As we can see from the table a
change in pressure allows us to increase or decrease the breakdown voltage required for a spark,
also there are various advantages and disadvantages to different pressures.
Gap Size Breakdown
(mm) Voltage (kV)
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
5.8
5.8
5.8
5.8
5.8
5.8
5.8
5.8
5.8
5.8
5.8
5.8
5.8
5.8
Current
(mA)
5
10
15
20
25
30
35
40
45
50
100
1,000
5,000
10,000
Energy per
spark (mJ)
400
400
400
400
400
400
400
400
400
400
400
400
400
400
Frequency
(Hz)
43
87
130
173
217
260
303
346
390
433
866
8,662
43,311
86,621
Power (W)
1.7
3.5
5.2
6.9
8.7
10.4
12.1
13.9
15.6
17.3
34.6
346.5
1,732.4
3,464.9
Energy (kW/Hr)
1.0
2.1
3.1
4.2
5.2
6.2
7.3
8.3
9.4
10.4
20.8
207.9
1,039.5
2,078.9
Cu Mass Loss Au Mass Loss
(Hr/Kg)
(Hr/Kg)
3,925.2
1,962.6
1,308.4
981.3
785.0
654.2
560.7
490.6
436.1
392.5
196.3
19.6
3.9
2.0
1,258.2
629.1
419.4
314.6
251.6
209.7
179.7
157.3
139.8
125.8
62.9
6.3
1.3
0.6
Table 2.3.5: Varying Current: A higher current means a much higher amount of mass particle
production; however, as larger amounts of energy are inputted the size distribution is altered.
Specific heat was used to calculate mass loss over time, but there are many losses in the system so
it simply acts as an estimate of electrode material lost over time.
14
Gap Size Breakdown
(mm) Voltage (kV)
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
2.0
5.8
5.8
5.8
5.8
5.8
5.8
5.8
5.8
5.8
Current
(mA)
69
139
277
693
1,385
6,927
13,853
69,267
110,827
Energy per
spark (mJ)
400
400
400
400
400
400
400
400
400
Frequency
(Hz)
500
1,000
2,000
5,000
10,000
50,000
100,000
500,000
800,000
Power (W)
20
40
80
200
400
2,000
4,000
20,000
32,000
Energy (kW/Hr)
12
24
48
120
240
1,200
2,400
12,000
19,200
Cu Mass Loss Au Mass Loss
(Hr/Kg)
(Hr/Kg)
340.0
170.0
85.0
34.0
17.0
3.4
1.7
0.3
0.2
108.99
54.50
27.25
10.90
5.45
1.09
0.54
0.11
0.07
Table 2.3.6: Varying Frequency: The table clearly shows how an increase in frequency will cause a
larger theoretical gain in particle mass. However achieving the upper limits will be a severe test for
the circuits used. Specific heat was used to calculate mass loss over time, but there are many losses
in the system so it simply acts as an estimate of electrode material lost over time.
To reach industrial scale production optimizing the mass transferred from bulk material into
nanoparticles is critical. Several things become apparent from the formulas and the tables.
First is the larger the gap size, the larger the voltage, and thus the larger the energy
transferred. Second is the higher the pressure, the higher the voltage, the higher the energy
transfer. Third is the higher the current, the higher the frequency, the higher the energy
transfer. Since the total energy release is a function of the frequency measuring the current
versus production levels was tested. A fourth way out of the scope of the tables to increase
the energy would be to alter the inductance to have longer sparks. Another would also be to
add an external electric field to allow the plasma form easier.
Of all of these parameters that can be changed testing each one individually is needed to
see how it affects size distribution as parameter changes to size distributions is not always
as direct and simple and many applications of nanoparticles requires specific sizes for their
effects to work. Also there are stability problems near the extreme ends of the spectrum;
even in the early phases of testing several processes were unstable due to being at the
lower edge of where a spark was created. By unstable we mean that the spark would
change voltages, the frequency would vary dramatically during the process, or the device
would simply not spark at all.
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2.4 Growth processes
The initial particles formed by the localized thermal process on the electrodes and are on
the atomic size range. At particle diameters of smaller than 100 nm it is assumed all
particles adhere with every collision. Provided there is enough particle density for collisions
they will form clusters of particles via coagulation, which is sometimes called agglomeration.
That is when particles collide in a gas and form larger particles. For a monodisperse flow this
process is well modeled but for a non-homogeneous flow (which the spark process is) an
exact description is complicated and geometry dependent. To the authors knowledge
simplified numerical solutions are available but were not used in the course of this thesis
work [10]. A full theoretical model would be incredibly useful towards understanding the
effect of parameters on size distribution.
After formation the particles are flushed by the chamber flow. The rate at which they are
flushed is based on the flow of the process, which is typically a few liters per minute, and
the collision rate is affected by the flow.
Under higher levels of particle generation a higher flow may be necessary to keep the
particles from coagulating too much and exceeding the nanoparticle regime. Conversely
when larger particles are desired a lower flow, or a coagulation chamber may be added to
increase particle diameter.
In this system a coagulation chamber may be added after the charger before sorting and
sintering to create larger particles by giving them a larger volume where they can collide
and form larger particles.
16
3. Methods
3.1 Machine Outline
Figure 3.1.1: Highlighted Picture of Spark Discharge Generator at Lund University
17
Equipment list:
1) Spark Chamber
2) MFC 1
3) MFC 2
4) Charger
5) DMA1
6) Furnace
7) DMA 2
8) MFC 3
9) MFC 4
10) ESP- Electrostatic Precipitator
11) EM-Electrometer
12) Capacitor Bank
13) DAQ
14) HV Source
15) Pump
Most of the connections used were VFC© or Swagelok©
Our range of capacitances can be varied, but for all experiments used in this thesis the value
is fixed to 24 nF.
Component description:

1) Spark Chamber: A pressurized chamber that holds the electrodes of the device
and protects the surrounding environment from exposure to nanoparticles; as well
as, containing the sheath flow of an inert carrier gas such as pure nitrogen or a noble
gas. Nitrogen was used for all parts of the work performed during this document,
and if the resultant nanoparticles are reactive to nitrogen should be considered in
future work.

2,3,8,9) MFCs: Mass Flow Controller a device used to control gas flow inside a
pressurized system.
18
The operating principle for a mass flow controller is a small bypass tube with two
resistance thermometers or thermocouples. The gas flowing through the tube and
the cooling rate creates a temperature differential that is measured electronically
3.1.2 Operational Principle of a Mass Flow Controller [11].
The temperature differential is based upon mass flow, which is a function of density,
specific heat, and flow rate. It may be important to consider that during rapid
changes in values the measurement is inaccurate; however, for this SDG it is kept
constant at about 1.7 l/min because this is approximately 1/6 of the default 10 l/min
sheath flow of the DMAs and is a requirement for particle selection [3], [11].

4) Charger: Radioactive source which bombards particles passing through the device
giving a known Boltzmann charge distribution [3].

5,7) DMAs: A Differential Mobility Analyzer is a metal tube with a sheath flow and an
inlet and outlet connected to the particle flow. Inside the metal tube is a rod that is
19
charged to create an electric field between the wall of the tube and the inner rod.
The electric field sorts the incoming particles via their electrical mobility diameter by
only allowing specific values to continue and is thus a size selection device [3].
An important consideration when operating a DMA is to remember that the particles
are sorted by electrical mobility and not their geometrical diameter. For spherical
particles the mobility diameter is the geometrical diameter but because the particles
come out as agglomerates or fluffy elongated particles a furnace is used to reshape
the particles so the mobility diameter is uniform with the geometrical diameter [10],
[2].
The transfer function governs the voltage required to get specific electrical mobility
diameters. As this is a problem solved by my predecessor I will simply ask you to see
Martin Karlsson’s thesis for a detailed explanation of the transfer function and its
derivation.
The DMA’s used in the device measure between 0-100 nm in range, because of the
way the signal is analyzed to achieve particles below 10 nm or above 90 nm a special
low voltage control was needed. The voltage divider functions by splitting the signal
and then using a second 0-10 volt control to represent 0%-10% of the input. This
should give the DMA’s accuracy down to 1% range or 1 nm particles; although at that
range the particles have other sorting problems such as charging [12].
20
Figure 3.1.3 Schematic of DMA 1 (red circle number 5 in Fig. 3.1.1) TSI model 3080 Long
DMA [13]

6) Sintering Furnace: A furnace is used to exceed 2/3 the melting point of the bulk
property of the nanomaterial to allow reshaping of the particles to form spherical
objects. There are two primary reshaping processes a compaction process and a
reshaping process. 600 °C seem to be a sufficient temperature to reshape gold
particles from agglomerates into spherical particles [2].

10) ESP: Electro-Static Precipitator uses an electric field to direct the charged
particles towards a center ring where it forms a spray for deposition either on a
substrate such as thin film silicon, a liquid, or whatever the final form would be [14].

11) An Electrometer, abbreviated as AE or EM, is a tool for measuring the total
number of particles in the gas flow. As particles come into the chamber they are
21
collected by a Faraday cup and the current is used to calculate the number
concentration via 𝐼 = 𝑁 ∗ 𝑛𝑝 ∗ 𝑒 ∗ 𝑞𝑒 where 𝐼 is the electrometer current, 𝑁 is the
aerosol concentration, 𝑛𝑝 is the average number of charges per particle, 𝑒 is the
elementary unit charge, and 𝑞𝑒 is the volumetric aerosol flow [15].

12) Capacitor Bank: A set of parallel capacitors used in the circuit.

13) DAQ: Data Acquisition device from National Instruments. Connects the voltage as
a digital or analogue signal to the computer via USB port where Labview™ controls
the hardware.
Several power supplies are required for voltage to control the signals to the various
devices, as well as a ground. An external ground is critical to an accurate signal as the
SDG creates a huge electric field interfering with the interpretation of the wire
signals.
The output signal is compared with the external set point signal, which directs the
connected device.
The output signal is measured as a percentage of the total volume normalized to the
maximum capacity i.e. for MFC using a control voltage of 0-10 V on a 20 l/min
maximum flow 3 volts would correspond to 3/10 of the total flow or 30% of 20 l/min
which is a flow of 6 l/min. Signals in and out of the DAQ are accurately measured
based on the gain but for this system between 10-90% is accurate and the control
circuit becomes less predictable between the extreme regions of 0-10% and 90100%.

14) High Voltage Source: Provides the power required to cause the potential
difference for the spark.

15) Vacuum pump: Drives flow through the system and removes excess particles
from the chamber. Particles are filtered before they are returned to the atmosphere
to prevent inhalation of nanoparticles.
3.2 Labview™/DAQ
Labview™ was used to control many of the components via a computer interface.
Digital and Analogue signal input and output was performed through the NI-DAQ.
22
4. Results and Discussion:
The operational method is shown in the appendix.
To reach full functionality a new SDG’s following parameters must be tested or calibrated:
4.0 First Data Sets
4.1 DMA Calibration and Accuracy
4.2 ESP and Deposition Time Calibration
4.3 Reproducibility of Size Distributions
4.4 Reshaping Temperature
4.5 Varying Electrode Size and Gap Size
4.6 The Other Elements
4.0 First Data Sets
Particle Count in millions [#/cm3]
Size Distribution for a 2 mm gap
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
0
10
20
30
40
50
60
70
80
90
100
Particle Diameter [nm]
Figure 4.0.1: Particle density for a gold electrode with 3 mm diameter with bypassed DMA 1
and furnace. Settings of 2 mm gap, 5.5 kV, and 30 mA.
The first sets of data were performed on 3 mm gold electrodes. The primary research
interest for this device is predicted to be with gold nanoparticles so making system
settings for gold electrodes seemed a proper place to start.
Figure 4.0.1 shows the size distribution notice the y-axis is in units of millions (10^6).
Here the particles are gold which has a much lower specific heat than for copper which
might explain why there are more particles in the gold data than for copper or silver.
23
4.1 DMA Calibration and Accuracy
The new SDG system was tested in order to calibrate all the components to ensure they
will work properly. The scans were performed by fixing one DMA at a defined particle
diameter value while the other is scanned across the range of particle diameters the EM
was used to collect a particle count.
Furthermore particles were reshaped to spherical ones, in a furnace at 600 °C, scanned
with DMA 2, and deposited on a silicon surface. The particles on the surface were
investigated by SEM and analyzed with nanoDim: a Matlab program developed by
Kristian Storm that measures particle size and shape [16]. The average particle
diameters were compared with the values of the mobility diameters gained from DMA 2.
DMA Calibration Graph 1
Mobility diameter of scanning DMA 1 [nm]
100
90
80
70
60
y = 0.8857x + 0.0267
R² = 0.9996
50
40
30
20
10
0
0
20
40
60
80
100
120
Mobility diameter of fixed DMA 2 [nm]
Figure 4.1.1: DMA Calibration Graph 1 showing the maximum mobility diameter values of
DMA 1 while DMA 2 was fixed at several set points
DMA 2 was set at fixed mobility diameters (10, 20, 30, 40, 50, 60, 70, 80, 90 and 100 nm)
while DMA 1 was scanned for each of these set points. Gold electrodes and a gap of 2
mm were used. A voltage of 5.5-6 kV and a current of 30 mA were applied between the
electrodes which led to a breakdown voltage of 2.3-2.5 kV and a spark frequency of 300
Hz. The experiments were accomplished under room temperature (ca. 20 °C) and
standard pressure (ca. 1013 kPa or 1 atm). The nitrogen carrier gas flow was set to 1.68
24
l/min. Figure 4.1.1 above shows a linear increase of maximum mobility diameter values
with increasing fixed diameters of DMA 2. The increase is lower than 1, which indicates
that the DMA’s have a small divergence between each other. This means DMA 2 might
show mobility higher than in reality or DMA 1 displays lower mobility diameter than
reality. Because DMA 2 is the final sorting device its accuracy is critical to process
control. Additional information on the accuracy of the DMA’s is provided by several
scans with fixed DMA 1 diameter and varying DMA 2 the positions are shown in Figure
4.1.2 below. Because these results are not a perfect correlation we know at least one of
the DMAs is offset.
DMA Calibration Graph 2
Mobility diameter of scanning DMA 2 [nm]
120
100
80
y = 1.2233x - 1.7222
R² = 0.9861
60
40
20
0
0
10
20
30
40
50
60
70
80
90
100
Mobility diameter of fixed DMA 1 [nm]
Figure 4.1.2: DMA Calibration Graph 2 showing the maximum mobility diameter values of
DMA 2 while DMA 1 was fixed at several points
SEM was performed to determine actual size of the DMA’s to the produced particles.
Spherical particles were deposited on silicon surfaces, for the deposited particles the
original gold electrodes (3 mm diameter) were employed and 600 °C furnace
temperature was chosen. Also, due to the high erosion rate and the significant cost of
gold larger copper electrodes were utilized (6 mm diameter) for later scans.
25
The sparking conditions were standard pressure, room temperature, 2 mm gap distance,
300 Hz frequency, 4-8 kV applied voltage, 30 mA current and a nitrogen flow of 1.68
l/min. Due to long spark times which caused significant ablation of the thin electrodes
there were deviations of up to 20% of those base values. Particles with diameters of 10,
20, 40, 60 and 80 nm were deposited to investigate the accuracy of the DMAs. The
image below shows a deposition of copper on silicon at a set DMA 2 mobility diameter
of 40 nm employing the already mentioned conditions but with 1000 °C reshaping
temperature. For this paper anytime a specific value for particle size is mentioned
instead of a range it should be taken to mean that the particles have been reshaped
through the furnace and through both DMA’s set to that value which dramatically
lowers the overall particle concentrations. For all samples in this thesis the ESP
deposition voltage was set to the maximum voltage of 10 kV in order to deposit the
highest possible amount of particles. In practice the device reads 9.66 kV when set to 10
kV so all values seen as 10 kV should be assumed to be 9.66 kV.
The particle diameters were investigated by utilizing SEM and nanoDim. The image 4.1.3
below shows 3 of the thousands of SEM images that were captured during the project.
26
Image 4.1.3: SEM Images
A) 40 nm Copper particles which were deposited on silicon for 5 minutes
B) NanoDim analysis program calculating radius of 74 particles and giving
a distribution of diameters varying between 5 and 10 nm
C) 20 nm Copper particles on silicon deposited for 5 minutes
D) Distribution of Gold nanoparticles on silicon made during calibration to
a density of 1 particle/ 𝜇 m 2
The particle sizes were plotted against the mobility diameters seen in Figure 4.1.4
below. The graph demonstrates a slope of almost 1 and the values show a maximum of
12% deviation on the extreme value. It should be noted that as the particle size
increases the number of particles captured per image decreases so the last two data
points had less particles for statistics while the early points had several thousand points.
There were only 200 points for 60 nm and 10 points for 80 nm and thus these values are
less accurate. The author assumed the 12% deviation is from this and thus from the
statistics the output of DMA 2 is well known and is extremely accurate, and thus the
optimization values for DMA 1 are now known from the same data.
27
Average Size Distribution
Deposited diameter [nm]
80
70
60
50
40
30
Average Size Distribution
20
10
0
0
20
40
60
80
100
DMA 2 diameter [nm]
Figure 4.1.4: Statistically analyzed spherical particles with SEM are demonstrated towards the
diameter given by DMA 2. Each data point is a statistical average over thousands of particles
except for the 60 nm and the 80 nm. The author ascribes the nonlinearity of data point 80 nm
to the lack of statistics.
4.2 ESP and Deposition Time Calibration
Another parameter to investigate is the time required to achieve specific levels of
surface density. To determine the time required samples of each of the conditions above
were deposited at different lengths of time (30 s, 1 min, 2 min, 5 min) and a linear
regression was performed.
Figure 4.2.1 below shows not the surface density but a quotient of density and
electrometer current observed before and after the deposition, due to the fact that
when depositing many of the particles are diverted to the sample. As expected, the
graph shows higher increases in the slope of smaller particles.
28
Surface Density/Electrometer Current [#/pA*µm2]
ESP-Calibration
30
y = 2.4448x
R² = 0.9988
25
20 nm Density/Current
40 nm Density/Current
20
60 nm Density/Current
15
Linear (20 nm Density/Current)
y = 0.6974x
R² = 0.9884
10
Linear (40 nm Density/Current)
Linear (60 nm Density/Current)
5
y = 0.2297x
R² = 0.8448
0
0
2
4
6
8
10
12
Time [min]
Figure 4.2.1: Surface density, measured with a SEM and analyzed with nanoDim, divided by the
electrometer current before and after the deposition is plotted against the deposition time
The increase of the slopes of the 3 different particle sizes over time is used as a
calibration factor and introduced in the following figure. With those three points an
exponential function describing the behavior of the ESP system to different particle sizes
is approximated. This function shown in Figure 4.2.2 is inserted to the LabView™
program controlling the SDG and DMA-scanning process and now the calculated values
for surface density are inside the program so it can determine the proper time required
for a desired surface density with this specific system.
29
Calibration Factor [#/pA*s*µm2]
Density-Size Regression
9
8
7
y = 7.78823e-0.05913x
R² = 0.99878
6
5
Density-Size Regression
4
3
Expon. (Density-Size
Regression)
2
1
0
0
20
40
60
80
100
120
Particle Size [nm]
Figure 4.2.2: A calibration factor gained from this figure is plotted against the particle size to
get a density-size regression for the deposition time calibration
4.3 Reproducibility of Size Distributions
For the parameters of current and gap distance, size distribution data was taken
consecutively to see if they would be identical. The gold electrodes were used up in the
previous data set so larger 6 mm copper electrodes were used for the reproducibility tests.
All conditions were standard pressure, room temperature, and a nitrogen flow of 1.68 l/min.
Other settings were the minimum voltage required for a spark which varied from 4, 5, and 6
kV for 1, 1.5, and 2 mm gap size respectively and the standard 24 nF for capacitance. The
current was varied and thus the frequency varied with it as well as the gap size as seen in
the data.
30
Particles in millions [#/cm3]
Size Distribution for a 1 mm gap 1st run
0.25
0.2
5 mA
0.15
10 mA
0.1
20 mA
0.05
30 mA
0
40 mA
0
10
20
30
40
50
60
70
80
Particle diameter [nm]
Figure 4.3.1: Size distributions of particles generated at different currents at a gap distance of
1 mm with a copper electrode with 6 mm diameter
Particles in millions [#/cm3]
Size Distribution for a 1 mm gap 2nd run
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
5 mA
10 mA
20 mA
30 mA
40 mA
0
10
20
30
40
50
60
70
80
90
Particle diameter [nm]
Figure 4.3.2: Size distributions of particles generated at different currents at a gap distance of
1 mm with a copper electrode with 6 mm diameter
31
Particles in millions [#/cm3]
Size Distribution for a 1.5 mm gap 1st run
1.2
1
5 mA
0.8
10 mA
0.6
20 mA
0.4
30 mA
0.2
40 mA
0
0
20
40
60
80
100
120
50 mA
Particle diameter [nm]
Figure 4.3.3: Size distributions of particles generated at different currents at a gap distance of
1.5 mm with a copper electrode with 6 mm diameter
Particles in millions [#/cm3]
Size Distribution for a 1.5 mm gap 2nd run
1
0.8
5 mA
0.6
10 mA
0.4
20 mA
30 mA
0.2
40 mA
0
0
20
40
60
80
100
120
50 mA
Particle diameter [nm]
Figure 4.3.4: Size distributions of particles generated at different currents at a gap distance of
1.5 mm with a copper electrode with 6 mm diameter
32
Particles in millions [#/cm3]
Size Distribution for a 2 mm gap 1st run
1.4
1.2
5 mA
1
0.8
10 mA
0.6
20 mA
0.4
30 mA
0.2
40 mA
0
0
20
40
60
80
100
120
50 mA
Particle diameter [nm]
Figure 4.3.5: Size distributions of particles generated at different currents at a gap distance of
2 mm with a copper electrode with 6 mm diameter
Particles in millions [#/cm3]
Size Distribution for a 2 mm gap 2nd run
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
5 mA
10 mA
20 mA
30 mA
40 mA
50 mA
0
20
40
60
80
100
120
60 mA
Particle diameter [nm]
Figure 4.3.6: Size distributions of particles generated at different currents at a gap distance of
1 mm with a copper electrode with 6 mm diameter
As we can see from the size distribution a larger current means a higher overall number
of particles. The frequency varies with the current and with the circuit used here is
limited to less than 1 kHz. The size distribution shifts upward to the right as higher
current is reached meaning more particles are created and larger nanoparticles are
generated. The peak production for smaller nanoparticles is given by lower currents as
seen in the distribution data in Figures 4.3.1-4.3.6. One important aspect is that under
identical conditions a significant difference is seen in the number of particles produced
sometimes in excess of 30% of the peak particle densities. Figures 4.3.7 and 4.3.8 are the
peak curve graphs: created from this distribution data taking the highest data point for
33
each of the current curves. This makes it quite clear that as current is increased the
number of particles increases as does the average diameter of the particles. However
from the reproducibility tests we can clearly see that the total number of particles at a
given size varied heavily from scan to scan as well as that the peak particle diameter is
not completely reproducible and some of them are exceptionally wide peaks, but is in
general in the same range.
Particle diameter [nm]
Average Peak Particle Diameter
80
70
60
50
40
30
20
10
0
1 mm
1.5 mm
2 mm
0
10
20
30
40
50
60
70
Current [mA]
Figure 4.3.7: Maximum particle diameters of 3 investigated gap sizes gained from the size
distributions at different currents for a copper electrode with 6 mm diameter
Particles in millions [#/cm3]
Average Peak Particle Density
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
1 mm
1.5 mm
2 mm
0
10
20
30
40
50
60
70
Current [mA]
Figure 4.3.8: Maximum particle densities of 3 investigated gap sizes gained from the size
distributions at different currents for a copper electrode with 6 mm diameter
The breakdown voltage and frequency data was measured during the distributions. The
breakdown voltage is clearly decreasing as the current increases. Additionally the
frequency chart shows a very linear regime early on, but later begins to increase more
34
rapidly for the smaller gap sizes. More data is needed but these two trends could be
indicative that the ability to form a plasma channel becomes easier at a given point since
the larger gap sizes remains linear for a higher current.
Breakdown Voltage
3
Voltage [kV]
2.5
2
1 mm
1.5
1.5 mm
1
2 mm
0.5
0
0
10
20
30
40
50
60
70
Current [mA]
Figure 4.3.9: Breakdown voltages of 3 investigated gap sizes gained for a copper electrode
with 6 mm diameter at different currents
Frequency
Frequency [Hz]
1000
800
600
1 mm
400
1.5 mm
200
2 mm
0
0
10
20
30
40
50
60
70
Current [mA]
Figure 4.3.10: Frequencies of 3 investigated gap sizes gained at different currents for a copper
electrode with 6 mm diameter
35
Energy per Spark
Energy/Spark [mJ]
120
100
80
60
1 mm
40
1.5 mm
20
2 mm
0
0
10
20
30
40
50
60
70
Current [mA]
Figure 4.3.11: Energies per spark of 3 investigated gap sizes gained at different currents for a
copper electrode with 6 mm diameter
Energy per Second
Energy per Second [W]
25
20
15
1 mm
10
1.5 mm
5
2 mm
0
0
10
20
30
40
50
60
70
Current [mA]
Figure 4.3.12: Energies per second of 3 investigated gap sizes gained at different currents for a
copper electrode with 6 mm diameter
Figure 4.3.11 and figure 4.3.12 show the energy per spark and the energy per second
respectively. These graphs were calculated from the frequency data including the 24 nF
capacitance using the formulas presented in the theory section and the voltage as
measured across the gap which was typically between .5-3 kV. The energy per spark is a
decreasing function due to the increased frequency, but the energy per second is an
increasing function also due to the increased frequency as the total energy input has
been increased.
36
4.4 Reshaping Temperature
Particle diameter [nm]
Copper Reshaping
90
80
70
60
50
40
30
20
10
0
80 nm
50 nm
30 nm
0
200
400
600
800
1000
1200
Furnace temperature [°C]
Figure 4.4.1: Particle diameter scanned by DMA 2 is shown after varying temperatures in the
reshaping furnace for 30, 50, and 80 nm particles determined with DMA 1
Values for 30, 50, and 80 nm particles under various temperatures were taken in order
to determine the amount of reshaping that occurs over time. From the graph we can see
that the values level off around 600 °C where they become spherical which is roughly
2/3 of the bulk material property as expected from the group’s previous work [2]. This
also provides an indication that the particle material is pure copper whose melting point
is 1085 °C, because this does not correspond to the values expected for copper oxide
which is 1200 °C and oxides reshapes at a much higher temperature unlike pure metals
[9],[17].
4.5 Varying Electrode Size and Gap Size
Similar distribution data was acquired for copper with a smaller 3 mm diameter
electrode.
The length of time the electrodes lasted was as we expect. Over dozens of hours of run
time one pair of the thinner 3 mm gold electrodes were eroded away completely, and a
second pair of 3 mm copper electrodes was eroded visibly while the thicker 6 mm
copper electrodes showed little wear over a much larger time frame. A future
experiment would be to precisely measure the electrode weight over time to see how
37
closely it corresponds to specific heat calculations, but in general this trend seems to be
true.
Size Distribution for a 1 mm gap
Particles in millions [#/cm3]
0.7
0.6
0.5
5 mA
0.4
10 mA
0.3
20 mA
0.2
30 mA
0.1
40 mA
0
0
20
40
60
80
100
120
Particle diameter [nm]
Figure 4.5.1: Size distributions of particles generated at different currents at a gap distance of
1 mm with a copper electrode with 3 mm diameter
Particles in millions [#/cm3]
Size Distribution for a 1.5 mm gap
0.7
0.6
0.5
0.4
5 mA
0.3
10 mA
0.2
20 mA
0.1
30 mA
0
0
20
40
60
80
100
120
Particle diameter [nm]
Figure 4.5.2: Size distributions of particles generated at different currents at a gap distance of
1.5 mm with a copper electrode with 3 mm diameter
38
Particles in millions [#/cm3]
Size Distribution for a 2 mm gap
0.7
0.6
0.5
5 mA
0.4
10 mA
0.3
20 mA
0.2
30 mA
0.1
40 mA
0
0
20
40
60
80
100
120
Particle diameter [nm]
Figure 4.5.3: Size distributions of particles generated at different currents at a gap distance of
2 mm with a copper electrode with 3 mm diameter
Peak Particle Diameter
Particle diameter [nm]
80
70
60
50
40
1 mm
30
1.5 mm
20
2 mm
10
0
0
10
20
30
40
50
60
Current [mA]
Figure 4.5.4: Maximum particle diameters of 3 investigated gap sizes gained from the size
distributions at different currents for a copper electrode with 3 mm diameter
39
Millions
Particle Count[#/µm2]
Peak Particle Density
0.7
0.6
0.5
0.4
1 mm
0.3
1.5 mm
0.2
2 mm
0.1
0
0
10
20
30
40
50
60
Current [mA]
Figure 4.5.6: Maximum particle densities of 3 investigated gap sizes gained from the size
distributions at different currents for a copper electrode with 3 mm diameter
The peak of the size distributions seems unaffected by the change in electrode diameter,
but for two sets of data this is inconclusive. One point of note is the gap size changes
visibly over time when smaller electrodes are used and this is very clear from acquiring
the reshaping data as the frequency changed by several hundred hertz over hours of
usage on the smaller electrodes; however, for the data here the gap is adjusted to be
kept constant and to keep the frequency steady at increasing values relatively consistent
with each other.
The most unexpected and perhaps interesting part of the data is that for the larger gap
size there is an inconsistency in the peak particle diameter. This seems due to the
smaller gap distance having a very broad peak while at the largest gap size the peaks are
sharper. Additionally for the 1.5 mm gap data in figure 4.5.2 the size distribution
decreases for an increased current from 20 mA to 30 mA. This is not terribly surprising
as the consistency tests in section 4.3 showed large variance in particle densities from
run to run, and the larger sets of 6 mm copper electrode data have several instances of
crossover between increasing current scans.
40
4.6 The Other Elements
The initial silver data although far from conclusive displays a few general trends,
primarily the peak points and size distribution data for silver is roughly similar to that of
copper and a larger difference would be expected if the particle density followed a linear
correlation to the specific heat. A higher voltage was required to cause a spark to form
at values of 5, 6, and 6 kV for 1, 1.5, and 2 mm gap. More data or identical data is
needed to make a strong statement on any comparisons between elements, but current
data shows that as the current is increased the particle density increases and the peak
diameter is increased with increasing current. This should be true for increasing gap size,
but for the 2 mm gap the measured voltage had a sharper drop than expected and
despite the increased current and decreased voltage the frequency became lower. Too
low to agree with the previous data and went to 70 Hz on the 40 mA setting when the
expected value should have been 400-500 Hz to be consistent with the other 2 mm silver
scans and should be between 600-800 Hz to be consistent with the rest of the data sets.
Size Distribution for a 1 mm gap
Particles in millions [#/cm3]
0.7
0.6
0.5
5 mA
0.4
10 mA
0.3
20 mA
0.2
30 mA
0.1
40 mA
0
0
20
40
60
80
100
120
Particle diameter [nm]
Figure 4.6.1: Size distributions of particles generated at different currents at a gap distance of
1 mm with a silver electrode with 3 mm diameter
41
Particles in millions [#/cm3]
Size Distribution for a 1.5 mm gap
1
0.8
5 mA
0.6
10 mA
0.4
20 mA
0.2
30 mA
0
40 mA
0
20
40
60
80
100
120
Particle diameter [nm]
Figure 4.6.2: Size distributions of particles generated at different currents at a gap distance of
1.5 mm with a silver electrode with 3 mm diameter
Particles in millions [#/cm3]
Size Distribution for a 2 mm gap
0.6
0.5
0.4
5 mA
0.3
10 mA
0.2
20 mA
0.1
30 mA
40 mA
0
0
20
40
60
80
100
120
Particle diameter [nm]
Figure 4.6.3: Size distributions of particles generated at different currents at a gap distance of
2 mm with a silver electrode with 3 mm diameter.
42
Peak Particle Diameter
Particle diameter [nm]
80
70
60
50
40
1 mm
30
1.5 mm
20
2 mm
10
0
0
10
20
30
40
50
60
Current [mA]
Figure 4.6.4: Maximum particle diameters of 3 investigated gap sizes gained from the size
distributions at different currents for a silver electrode with 3 mm diameter
Particle Count[#/µm2]
Peak Particle Density
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
1 mm
1.5 mm
2 mm
0
10
20
30
40
50
60
Current [mA]
Figure 4.6.5: Maximum particle densities of 3 investigated gap sizes gained from the size
distributions at different currents for a silver electrode with 3 mm diameter
43
Energy per Spark
Particle Count[#/µm2]
120
100
80
60
1 mm
40
1.5 mm
2 mm
20
0
0
5
10
15
20
25
30
35
40
45
Current [mA]
Figure 4.6.6: Energies per spark of 3 investigated gap sizes gained at different currents for a
silver electrode with 3 mm diameter
The measured values for the frequency did not increase according to the theory, and the
measured voltage dropped significantly. This can be seen in Figure 4.6.6 since the energy
here is calculated from the measured voltage across the gap. Perhaps the plasma
formation takes more energy because the settings were at the lower edge of what
creates a spark. The frequency was very low so perhaps ion channel formation had a
higher overall resistance because of recombination between sparks. Another possibility
is because of the very small electrodes there could be a formation of localized turbulent
flow. Also due to the geometry of the smaller electrodes there is a difference in the
electric field; perhaps this difference is enough to cause changes in ion channel
formation and particle formation.
44
5 Conclusions
The methods and tools described in the methods section can be applied to all new Spark
Generator Systems.

For the 6 mm copper data an increase in the current causes an increase in the
frequency and an increase in the number of particles formed. The increased current
means there is a larger amount of energy in the process and causes a shift in the
curve towards larger particle formation. For an increase in the gap size we find an
increase in the peak particle size, and the total particle density was increased.

For the 6 mm electrodes an increase in the current causes the number of particles
formed to increase and a shift towards larger particles as expected. However, for
some the data acquired during the thesis work the gap size has the opposite effect
than the 3 mm electrodes! Both sets of particle peak data show a dual peak in the 1
mm gap and a decrease in the 2 mm gap. Additionally the max particle data is
inconclusive as well. There is much less data for the 3 mm electrodes, and perhaps
this anomaly is just due to lack of data and having an unstable process. Still this
happening repeatedly could be indicative of a real physical process and further
investigation is needed.

One of the more interesting trends is that for the 3 mm electrodes the 1 mm gap on
both silver and copper has a dip in the maximum values. A more detailed
investigation into smaller gaps would be interesting to see if there is a dual peak in
the production which might indicate there are two competing stable particle
formations.

Also the measured frequency is not linear to the current increase, this could be due
to a lack of data, or these could be indicative that plasma channels form easier under
higher frequencies since the ion channel may not have time to dissipate fully.

Electrode material loss seems to follow specific heat calculations. A comparison of
the weight of the electrodes before and after use under a stable process to be
conclusive about how correlated to the energy required to evaporate metal is to
particle formation would also be of future interest.
45
6 Future Work
Future work includes varying the types of material and making various samples for use in
work such as catalysis and nanowire synthesis. Creating known catalyst particles such as
Gold-55, silver, and nickel particles will be necessary. Core shell particles are a possibility by
adding a particle formation process in the furnace to create a shell, also creating bimetal
particles by having two different electrodes. Janus particles or particles with their own p-n
junction, or other shaped particles could also be a possibility. Control over the synthesis
process would be needed but nanoparticles with desired electrical properties such as GaAs,
InAs, or GaInAs and varying the doping in these particles to engineer band gaps could be
interesting. Developing a method to create solutions out of aerosol nanoparticles, and
measuring the refractive index by matching dielectric constant of the solution could also be
of interest. Additionally a solar cell made by nanoparticles that are hydrophobic or
hydrophilic is a possibility.
46
7. References:
[1] Tsakalakos, (2010). Nanotechnology for Photovoltaics. 1st ed. Boca Raton Fl. USA.: CRC
Press.
[2] M. Messing: Engineered Nanoparticles Generation, Characterization, and Applications.
Lund University, Division of Solid State Physics, Department of Physics 2011
[3] Martin Karlsson, (2004). Methods to Generate Size- and Composition Controlled
Aerosol Nanoparticles. 1st ed. Sweden: Media Tryck. ISBN 91-628-6034-8 [ONLINE]
Available at:
http://lup.lub.lu.se/luur/download?func=downloadFile&recordOId=467000&fileOId=1779
071 [Last Accessed 6/19/2012].
[4] Friedrich Paschen,(1889). Ueber die zum Funkenübergang in Luft, Wasserstoff und
Kohlensäure bei verschiedenen Drucken erforderliche Potentialdifferenz. Annalen der
Physik. 273 (5), pp.69-96 [ONLINE] Available at:
http://onlinelibrary.wiley.com/doi/10.1002/andp.18892730505/abstract [Last Accessed
6/19/2012].
[5] J. M. Meek, (1940). A Theory of Spark Discharge. Physical Review. 57 (57), pp.722
[ONLINE] Available at: http://prola.aps.org/pdf/PR/v57/i8/p722_1 [Last Accessed
6/19/2012].
[6] Claire Tendero, Christelle Tixier, Pascal Tristant, Jean Desmaison, Philippe Leprince,
(2006). Atmospheric pressure plasmas: A review.Spectrochimica Acta. 61 (B), pp.2-30
[7] N. S. Tabrizi, M. Ullmann, V. A. Vons, U. Lafont, A. Schmidt-Ott: Generation of
nanoparticles by spark discharge. J Nanopart Res., 2009, DOI 10.1007/s11051-008-9407-y
[8] B. Mueller: Generation of Nanoparticle Aerosols by Spark Discharge. Aerosol Science &
Technology. AST-REV-2011-18, 2011
[9] Carl Yaws, (October 1, 1998). Chemical Properties Handbook: Physical,
Thermodynamics, Engironmental Transport, Safety & Health Related Properties for
Organic & Inorganic Chemical. 1st ed.: McGraw-Hill Professional.
[10] Hinds, ( January 19, 1999). Aerosol Technology. 2nd ed. New York: Wiley-Interscience.
47
[11] (2012). Fundamentals of Mass Flow Control. [ONLINE] Available at:
http://www.advanced-energy.com/upload/File/White_Papers/SL-MFCFUND-270-01.pdf.
[Last Accessed 6/19/2012].
[12] R. Nave (2012). Voltage Divider. [ONLINE] Available at: http://hyperphysics.phy-
astr.gsu.edu/hbase/electric/voldiv.html. [Last Accessed 8/22/2012].
[13] TSI (2009). Series 3080 Electrostatic Classifiers . [ONLINE] Available at:
http://cires.colorado.edu/jimenez-group/Manuals/SMPS_3080_manual.pdf. [Last
Accessed 9/12/2012].
[14] TSI, June 2002, Model 3089 Nanometer Aerosol Sampler Instruction Manual Revision
A, TSI Incorporated, Saint Paul, Mn. USA.
[15] TSI, Oct. 2009, Model 3068B Aerosol Electrometer User’s Manual Revision B,
TSI Incorporated, Shoreview, Mn. USA.
[16] K. Storm (2012). About NanoDim. [ONLINE] Available at: http://www.nanodim.net/.
[Last Accessed September 5th 2012].
[17] M. N. A. Karlsson, K. Deppert, L. S. Karlsson, M. H. Magnusson, J. -O. Malm and N. S.
Srinivasan, (2005). Compaction of agglomerates of aerosol nanoparticles: A compilation of
experimental data. Journal Of Nanoparticle Research. 7 (1), pp.43-49
48
8 Appendix:
8.1 Major Component list:

MFC:
o Aero FC – 7700 CU
o Aero FC - 7710 CU
o 2x Brokhorse NL 7261

DMA:
o 1) TSI 308010

High Voltage Source:
o Technix CCR15-P-750

Spark Chamber:

DAQ:
o NI 9403
o NI 9205
o NI 9264

Power Supply:
o FUG HCN 7E – 3500
o FUG HCN 7E - 6500

Sintering Furnace:
o Linn Eurotherm

ESP
o TSI 3089

EM
o TSI 3068 B
49
8.2 SDG Operating Procedure
By Jonathan E. Pautler
Startup
1. Turn on Computer
a. ID: Gotta
b. Pass: Ask
2. Set Electrode Distance
3. Connect Oscilloscope Probe
a. Turn on Oscilloscope be sure to set channel 1 to frequency and channel 3 to current
4. Turn on Lab view Program (Version 2011)
a. close all windows (3 opens close 2) except main
5. Check all things are plugged in and gas flow from wall is on.
6. Simultaneously (or as close as possible)
a. Turn all pneumatic valves DOWN
i. Note: Bypass valve is labeled off as on. Turn it off (down) now.
ii. EXCEPT gas flow 2 (last lever) leave that off unless you are using it.
b. Turn on Vacuum Pump
7. Check Pressure and flow
a. Stabilize pressure at 1015±5 mbar by adjusting needle valve (See program for value)
b. Stabilize flow by adjusting the outlet valves if needed (Read from EM screen)
i. Values for MFC’s should be ( 1.68 , 0 , 10 , 10 )
8. Turn key to on position at HV source
9. Test Spark by (using the program)
i. Disable “Disable” button by clicking 2x and then turn “On” button on.
ii. The value from the source to create a breakdown voltage depends on the
gap size and other things but setting to say 6kV and 30mA is a good starting
point. This should generate a signal around 2.5kV in the program as read on
the screen.
iii. SPARK IS LIMITED TO UNDER 1KHz DO NOT GO OVER THIS LIMIT OR
CAPACITOR BANK COULD BREAK!
10. Furnace to desired temperature
i. Note: Takes ~20+ minutes to get desired temperature
50
Operating Procedure
1. Check values for flow and pressure
2. Connect system to proper gas flow
TO CHANGE ANY VALVES:
BE SURE TO OPEN FIRST AND CLOSE SECOND SO THE GAS ALWAYS HAS A PATH!!!
a. To Bypass DMA 1
i. Open Valves 1
ii. Close Valve 2, 3
b. Bypass Furnace, Use DMA 2
i. Open Valves 4 outward, 5, 6, 9
ii. Close Valve 7, 8
c. Use Furnace, Bypass DMA 2
i. Open Valves 4 inward, 7, 8
ii. Close Valve 5, 6, 9
d. Use Furnace, Use DMA 2
i. Open 4 inward, 6, 7, 9
ii. Close 5, 8
e. Bypass Furnace, Bypass DMA 2
i. Open 4 outward, 5, 8
ii. Close 6, 7, 9
f. To Open ESP
i. Open Valves 10
ii. Close Valve 11, 12
g. To reverse any of these simply switch the open and close numbers. I.E. to close the
ESP you would OPEN 11,12 and Close 10.
3. Turn Spark to Desired Settings
4. Check that EM is working properly
5. To Run Scans
a. Goto Scan Menu and adjust Settings
6. To Deposit
a. Place Sample in ESP
b. While ESP is offline turn on and set to desired deposition voltage
c. Open gas line to ESP (See 2f)
d. Turn on ESP
e. Turn off ESP when Deposition time has been reached
f. Close gas line to ESP
51
Shutdown
1. Turn off Spark by using Program
2. Turn off and disable HV Source (via program)
3. Turn off key to HV Source
4. Turn off Furnace
5. Simultaneously (or as close as possible) Close down gas flow
a. Turn all pneumatic valves UP
i. Note: Bypass valve is labeled off as on. Turn it on now.
b. Turn off Vacuum Pump
6. Close Lab view Program (hit Stop then Exit)
7. Turn off Oscilloscope
8. Turn off power to All plugs (on side)
Valve Labels
1 DMA 1 Bypass
2 DMA 1 Inlet
3 DMA 1 Outlet
4 Three way valve for Furnace Inlet, DMA 2 Inlet, or DMA 2 Bypass
5 DMA 2 Bypass
6 DMA 2 Inlet when Furnace is bypassed
7 DMA 2 Inlet
8 DMA 2 Bypass
9 DMA 2 Outlet
10 Electrometer
11 ESP
12 ESP
13 Outlet Bypass
IN CASE OF EMERGENCY:
CONTACT BENGT MUELLER @ --- --- ---OR JONATHAN PAUTLER @ --- --- ----
Known Bugs
1. If the Program FREEZES
a. Immediately turn off spark and gas line manually.
i. Turn off Spark by the key and button on HV supply
ii. Turn off Gasline by closing pneumatic valves and
pump
52
b. Restart the program
2. If the power goes out
a. Turn off system so when the power is restored the machine
will not start
53