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Sensing Enhancement of Surface-Based Graphene Nanosensors Using
Acoustic Bubbles
BY
ANDREA DE VELLISB.S., Politecnico di Torino, Turin, Italy, 2014
THESIS
Submitted as partial fulfillment of the requirementsfor the degree of Master of Science in Mechanical Engineering
in the Graduate College of theUniversity of Illinois at Chicago, 2016
Chicago, Illinois
Defense Committee:
Jie Xu, Chair and Advisor
David Eddington
Pietro Asinari, Politecnico di Torino
ACKNOWLEDGMENTS
I would like to express my gratitude to my advisor Dr. Jie Xu for the useful comments,
remarks and engagement through the learning process of this Master’s thesis. Furthermore, I
would like to thank my co-tutor at Politecnico di Torino Dr. Pietro Asinari for giving me the
opportunity to work on this Master’s thesis at UIC, as well for the support on the way. I also
would like to thank Dr. David Eddington as a member of the committee. Then, I like to express
my gratitude to Dmitry Gritsenko for introducing me to the topic and all the other members of
the Microfluidics Laboratory for the help and the suggestions given during the last year. I want
also to thank Prof. Wei Xue at Rowan University for providing sensing expertise, Dr. Xian
Zhang at Columbia University for providing microfabrication expertise and Prof. Zhenping
Wu at Beijing University of Posts and Telecommunications for providing nanomaterials for the
project.
Moreover, I would like to show my thankfulness to all the students from PoliTo and PoliMi
who came to UIC as colleagues and who are leaving as part of my family, Marc, Roberto,
Lorenzo, Andrea, Vittorio and Benedetto. I want also to thank all of my friends who supported
me during my academic career in Turin, Christian, Mauro, Daniele, Francesco and Matteo:
without them I would not have reached the final step of my MS. Furthermore, I want to express
my gratitude to Manuel, Adriano and Alessandro, who always supported me even though they
were not by my side. Eventually, I need to express my respect and thankfulness to my whole
family and in particular to my parents, who have always believed in me and who have supported
ii
ACKNOWLEDGMENTS (continued)
me throughout the entire process. I will always show gratitude for the huge opportunity you
gave me and I will be always grateful for your love.
ADV
iii
TABLE OF CONTENTS
CHAPTER PAGE
1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.1 Microfluidic Sensors . . . . . . . . . . . . . . . . . . . . . . . . . 11.1.1 Microfluidics and Lab-on-a-Chip . . . . . . . . . . . . . . . . . . 11.1.2 Microfluidics-Based Sensing . . . . . . . . . . . . . . . . . . . . . 51.2 Graphene Sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . 91.2.1 Carbon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91.2.2 What is Graphene? . . . . . . . . . . . . . . . . . . . . . . . . . . 111.2.3 Graphene Production . . . . . . . . . . . . . . . . . . . . . . . . 151.2.4 Graphene as a Sensing Material . . . . . . . . . . . . . . . . . . 171.3 Acoustic Bubbles . . . . . . . . . . . . . . . . . . . . . . . . . . . 241.3.1 Diffusion Limits . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241.3.2 Cavitation Microstreaming to Overcome Diffusion Limits . . . 271.3.3 Microbubbles Formation . . . . . . . . . . . . . . . . . . . . . . 301.3.4 Governing Equations of Acoustic Microbubbles . . . . . . . . . 351.3.5 Streaming Induced by Microbubbles . . . . . . . . . . . . . . . 37
2 FABRICATION AND EXPERIMENTAL SETUP . . . . . . . . . . 422.1 Sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 422.2 Micromachining and 3D Printing . . . . . . . . . . . . . . . . . 432.2.1 Micromilling PMMA and G-Code Programming . . . . . . . . 442.2.2 3D Printed Box . . . . . . . . . . . . . . . . . . . . . . . . . . . . 502.2.3 PDMS Cover . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 522.3 Electronic Devices . . . . . . . . . . . . . . . . . . . . . . . . . . 542.4 Final Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
3 RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 573.1 Natural Frequency . . . . . . . . . . . . . . . . . . . . . . . . . . 583.2 Sensor Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . 593.3 Sensing Period Reduction . . . . . . . . . . . . . . . . . . . . . . 613.3.1 Effects of Frequency . . . . . . . . . . . . . . . . . . . . . . . . . 633.3.2 Effects of Voltage . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
4 CONCLUSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 744.1 Future Applications and New Designs . . . . . . . . . . . . . . 76
APPENDICES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79Appendix A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
iv
TABLE OF CONTENTS (continued)
CHAPTER PAGE
Appendix B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
CITED LITERATURE . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
VITA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
v
LIST OF TABLES
TABLE PAGE
I GRAPHENE MECHANICAL PROPERTIES . . . . . . . . . . . . 15
II DIFFUSION COEFFICIENTS VALUES FOR IONS IN WATER 26
III PMMA MECHANICAL PROPERTIES . . . . . . . . . . . . . . . . 45
IV G-CODE DATA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
V PMMA PLATES DIMENSIONS . . . . . . . . . . . . . . . . . . . . 50
VI RESISTANCE SATURATION VALUES . . . . . . . . . . . . . . . 60
VII SENSING TIMES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
VIII EFFECTS OF FREQUENCY . . . . . . . . . . . . . . . . . . . . . 64
IX EFFECTS OF VOLTAGE . . . . . . . . . . . . . . . . . . . . . . . . 66
vi
LIST OF FIGURES
FIGURE PAGE
1 Microfluidic devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
2 Passive pumps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
3 Portable microfluidic device with optical detector. . . . . . . . . . . . 7
4 FET gas sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
5 Allotropic forms of carbon. . . . . . . . . . . . . . . . . . . . . . . . . . 10
6 Lattice structure of graphene . . . . . . . . . . . . . . . . . . . . . . . 12
7 Electronic dispersion in the honeycomb lattice . . . . . . . . . . . . . 13
8 Brilluoin zone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
9 Chemical vapour deposition (CVD) of graphene on Cu substrate . . 17
10 Mask-free fabrication process . . . . . . . . . . . . . . . . . . . . . . . 18
11 Example of a graphene sensor. . . . . . . . . . . . . . . . . . . . . . . . 19
12 Adsorption sites: H2O on graphene . . . . . . . . . . . . . . . . . . . . 20
13 Results of previous studies on graphene pH sensors . . . . . . . . . . 23
14 ANSYS simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
15 Microstreaming patterns . . . . . . . . . . . . . . . . . . . . . . . . . . 28
16 Bubble in a HSS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
17 Closed Container . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
18 Conditions for gas entrapment . . . . . . . . . . . . . . . . . . . . . . . 33
19 Cavitation microstreaming pattern . . . . . . . . . . . . . . . . . . . . 38
20 Cavitation microstreaming pattern at different frequencies . . . . . . 40
21 SLA and Milling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
vii
LIST OF FIGURES (continued)
FIGURE PAGE
22 3D Printer and MicroMilling Machine . . . . . . . . . . . . . . . . . . 45
23 Micromilling path . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
24 PMMA plate design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
25 Micromilled PMMA plate . . . . . . . . . . . . . . . . . . . . . . . . . . 49
26 3D-Printed Box . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
27 Final Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
28 Sensing times vs. R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
29 Resistance saturation values as a function of pH. . . . . . . . . . . . . 62
30 Comparison of sensing period with and without bubble activation . 70
31 Resistance as a function of time for different frequency values . . . . 71
32 Efficiency as a function of frequency. . . . . . . . . . . . . . . . . . . . 72
33 Effects of Voltage on time reduction . . . . . . . . . . . . . . . . . . . 73
34 Alternative design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
35 PMMA plate Type A: Technical drawing . . . . . . . . . . . . . . . . 80
36 PMMA plate Type B: Technical drawing . . . . . . . . . . . . . . . . 81
37 Box: Technical drawing . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
viii
LIST OF ABBREVIATIONS
CNT Carbon Nanotubes
CVD Chemical Vapor Deposition
DMM Digital Multimeter
FET Field-Effect Transistor
IO Optical sensor
IPA Isopropyl alcohol
LOC Lab-On-a-Chip
NW Nanowire
PDMS Polydimethylsiloxane
PMMA Poly(methyl methacrylate)
RP Rayleigh-Plesset
SLA Stereolithography
ix
SUMMARY
There is a high demand for ultrasensitive sensors in many situations, such as biodefense and
cancer detection. Current sensors are limited by the slow mass transport process in traditional
pressure-driven microfluidic setups. To overcome problems related to diffusion phenomena it
is necessary to force movement of target species towards the sensor surface: in a microfluidic
environment, this movement can be obtained thanks to the microstreaming flow generated by
oscillating microbubbles. The aim of this work is to demonstrate that sensing performance of
a nanosensor can be significantly enhanced using the microstreaming flow.
The sensor used for the experiments is a graphene sensor, a relatively new device that has a
very wide field of applications. Graphene was discovered in 2004 and since then it has received
a lot of attention due to its unique chemical, mechanical electrical and structural properties.
In this work the graphene sensor is used to determine the pH of a buffer solution.
Values of pH can be determined by analyzing the graphene resistance and thanks to a
digital multimeter (DMM), the change in the resistance is taken as a continued measurement.
Droplets of fluid under analysis are poured into a particular device placed over the sensor.
PMMA plates with micro-drilled cavities are fitted into this device: bubbles are trapped inside
these cavities and then activated at their resonance frequency to produce microstreaming flow
around the sensing element for sensing performance enhancement. Graphene resistance will
reach a saturation value in a certain amount of time, called sensing period: this time interval
x
SUMMARY (continued)
is expected to be reduced as a result of the additional streaming generated by the oscillating
bubbles.
The last part of the work consists in the analysis of data, in particular in the evaluation
of sensing period reduction. Eventually, experiments are carried out to study the effects of
frequency and voltage on bubbles actuation and sensing period reduction.
xi
CHAPTER 1
INTRODUCTION
This introductory chapter deals with all the theory necessary for the understanding of the
analyzed problem. In particular after a brief recall on microfludic applications, attention will
be focused on sensors (in particular surface-based graphene nano-sensors) and then on acoustic
theory, in order to explain how cavitation microstreaming takes place.
1.1 Microfluidic Sensors
1.1.1 Microfluidics and Lab-on-a-Chip
In the past two decades there has been an increasing interest in the microfluidic field. Mi-
crofluidics is the science and technology that deals with small amounts of fluids and microfluidic
devices often feature a characteristic dimension that does not exceed one millimeter [1].
It has been previously demonstrated that microfluidics has several unbeatable advantages,
especially in biochemical applications: in fact, it made possible to analyze and obtain the
desired results just with a low consumption of reagent volume. Biochemical analysis, drug
delivery, chemical synthesis and cancer detection can now be performed simply using micro-
liters of samples. Using small quantities of samples is obviously an economic advantage, not
only for the reduced amount of liquid wasted during the experiments, but also because smaller
devices are usually less expensive. Another feature of microfluidic apparatus is integration
ability. For example, a large amount of microvalves can be integrated into a US Dime-sized
1
2
device for microbial studies on a chip. (Figure 1). Other possible applications are in the
aerospace and automotive industries or even in the optical field [2].
Figure 1: A microfluidic chemostat used to study the growth of microbial populations nowroutinely incorporate intricate plumbing. This device includes a high density of pneumaticvalves. The colors are dyes introduced to trace the channels. Reproduced with permission fromreference [3].
Microfluidics importance grew in the last few years due to various newly discovered applica-
tions, especially in biology and chemistry as well as in interdisciplinary research. For example,
studies have recently been carried out on microfluidic bio-fuel cells [4], that use enzymes as a
catalyst to oxidize its fuel, rather than precious metals. These fuel cells can be considered part
of microfluidics since they satisfy all the requirements of this field:
3
• Reduced cost;
• Reduced amount of fluid (electrolyte);
• Portability;
• Reduced wastes.
These cells were originally designed to use chemical reactions to produce electrical energy and
they can be used as power supplies for implantable medical devices, such as pacemakers.
One important application related to fluid delivery to a desired location regards micropumps.
Pumps are usually divided into two sub-categories that are displacement and dynamic pumps
[5]: at the microscale level it is possible to exploit pumps that are not physically feasible at
macroscale [6]. For instance, some designs do not need mobile parts (like a bubble pump) [7]
whereas in others it is possible to exploit the surface tension present in droplets of liquid in
order to generate flow (Figure 2).
Figure 2: The passive pump relies on the surface tension of a drop of water to push fluidthrough a microchannel. A small drop has a higher internal pressure than a large drop (a).The difference in pressure will cause fluid to flow towards the larger drop (b). Reproduced withpermission from reference [6].
4
Other important microfluidics components are valves, that can be both active (require
energy for activation) or passive (no energy required for activation). In the case of active
valves, the energy required can be taken from an external device or from the fluid itself. For
example, Capanu et al. used a electromagnetically actuated microvalve to control a water flow
of 0.05 - 0.5 µL/s [8] whereas Unger et al. developed a air-driven pressure device, built in a
nontraditional elastomeric material [9]. On the other hand, passive valves are usually adopted
to restrain flow to one direction or provide a momentary flow stop.
Speaking of fluid movement it is worth underlining the presence of mixers: in this work,
attention is focused on active mixers, devices able to increase fluid streaming thanks to an
external source (PZT-based acoustic mixer). However, it is worth mentioning the presence of
so called passive mixers: if one is dealing with two fluids, passive mixers can be channels built
in such a way that area over which diffusion occurs increases [10]. They are particularly useful
especially in the laminar flow regime, when mixing is due to diffusion only.
Before studying this kind of active mixer, it is to introduce the concept of lab-on-a-chip
(LOC) devices which are probably the most innovative application in the microfluidics field.
Those are devices that combine one or more laboratory operations on a single chip with reduced
dimensions to achieve automation and high-throughput screening. Studies on LOC apparatuses
have drastically changed the research in biomedical field. Many new apparatuses with a high
number of features have been refined and utilized in many applications in the last years [11].
For instance, these LOC devices have been optimized for drug delivery [12] or bioassays and
immuneassays [13].
5
However, possibly the greatest application is related to the detection of target molecules in
blood samples: for example blood tests needs a relevant amount (milliliters) of a blood sample
and require analysis times longer than one hour. In microfluidics it is possible to miniaturize
laboratory apparatus and assays: this is translated in lower costs per measurement, abbreviated
sample test times and better reproducibility [14]. Other analyses regard the developing of
detection system for the rapid discovery of bacterial pathogens [15] [16], proteins or DNA [17].
For what concerns DNA analysis station, analysis times can be reduced from 10 min (clas-
sical conditions) to 25 s. At the same time, risks of error due to the human factor are decreased
[18]; the advantages of using these products are the low prices for mass production processes
and contemporary, small devices are synonymous of portability. [19].
When dealing with lab-on-a-chip it is worth remembering that it is more than an arrange-
ment of microchannels: it also includes other features according to the function such as elec-
tronic devices; flow control instruments such as pumps and valves, which were previously dis-
cussed; and finally sensors [17]. To integrate all these functioning units onto one device can be
rather challenging. In the next section, some of the sensors used in the microfluidic environment
will be summarized.
1.1.2 Microfluidics-Based Sensing
In the sensing world, many detection problems will emerge when devices are miniaturized.
Micro-scaled sensors have smaller detection surfaces, making this operation more difficult, even
if the analyzed volumes are downsized [20].
6
For microdluidic applications, optical sensors (IO) have acquired importance in the past
years: they are basically detectors that convert light, or a change in light, into an electric
signal (typical representation in Figure 3). The optical instruments utilized in these sensors
are basically a light source (which can be a LED for example) and diffractive and refractive
instruments. Some of the main advantages of IO with the respect to other micro-sensors are
[21]:
• Very low detection limit (down to some ppb);
• Immunity to electromagnetic interference; at the same time there is no possibility for
electrical shocks and electrically initiated explosions;
• High number of optical methods of detection, such as monitoring changes in absorption
coefficient, luminescence, refractive index, or even the emission of the detected target
material;
• Flexibility in choosing the materials and structures of the optical systems.
The main problems relates to these sensors are the ones typical in all optical systems such as
scattering due to inhomogeneities or contamination by chemical entities. Switching to surface-
based sensors, magnetic biosensors fits well all the requirements of medical diagnostics. More-
over they can be based on different magnetic effects such as magneto- and giant magnetore-
sistance, inductive, magneto-elastic and Hall effects, magnetoimpedance (MI) [22]. The latter
ones works by analyzing surface modification that is induced by changes of the geometry of
7
Figure 3: Typical schematic representation of a portable microfluidic device with optical detec-tor. From: foodmicro.foodsci.cornell.edu/fmlab/sensors.html.
the sensitive material, surface morphology and/or its anisotropy. A similar principal of work is
shared by surface electronic sensors.
Some of them are based on field-effect transistors (FETs) [23] and they are growing in
importance because of their great sensitivity, easiness of set-up, reduced price, miniaturization
of instruments and real-time detection [24]. Detection in electronic devices can be visualized in
the variation of conductance of FET material once target species have been adsorbed. Surface
adsorption of molecules by the semiconducting material can have two effects: a change in its
surface potential or doping the material to produce a modification of the FET conductivity
[24]. As a consequence, FETs are considered a great sensing mechanism with a versatile set-up,
high sensitivity and real-time capability. Moreover, diameters of these nonomaterials are of the
same order of magnitude of the biological and chemical species being sensed. Therefore, they
8
are exceptional primary transducers for generating signals that are meant to be transferred to
macroscopic devices.
These electronic sensors have been used in the past in many fields; the first device was used
for pH detection by simply modifying the silicon oxide surface with 3-aminopropyltriethoxysilane.
The amino and silanol moieties worked as receptors for H+ ions by experiencing protonation
and deprotonation reactions that produced a change in charge density on the surface of the
material.
Lately, linking pertinent receptors to the active surface of nanowire materials made it possi-
ble to detect biological macromolecules such as nucleic acids and proteins, that generally have
a charge in aqueous solution and so can be easily and selectively detected. The great sensitivity
of nanowire sensors is expected when dealing with DNA molecules, being the diameters of these
sensors of the same order of magnitude of the size of the DNA target molecules. As a result,
even a small number of DNA molecules binding on the sensor surface will cause detectable
signal changes [23].
In aqueous environments, FET sensors are able to detect gases as well and adsorption of
target species means doping of the semi-conducting material that leads to a change in the con-
ductive properties (Figure 4). Between all materials used for electronic sensors, one of the most
interesting is graphene because of its surprising chemical, electronic and mechanical proper-
ties. The mono-atomic thickness of the this material layers makes it exceptionally sensitive to
modification of the environment it is exposed to, a feature that makes it an ideal material for
electronic sensors. Its characteristics will be discussed in the next section.
9
Figure 4: (a) Typical back-gate GFET on Si/SiO2 substrate used as gas sensor. (b) Typicalsolution-gate GFET on flexible polyethylene tere- phthalate (PET) substrate used as chemicaland biological sensor in aqueous solution. Reproduced with permission from reference [24].
1.2 Graphene Sensors
In this work, a graphene pH sensor has been used for demonstrating the effect of mi-
crostreaming on the sensing performance of surface-based sensors. Graphene sensors have been
abundantly used in recent years because the unique properties of this material can fit well all
the requirements for a good sensor. Before analyzing how a graphene sensor works, it is better
to introduce what graphene is and how it can be used for sensing applications.
1.2.1 Carbon
Carbon is maybe the most interesting element in the periodic table. It exists in many
different forms: the most stable is graphite (stacked sheet of carbon with exagonal structure)
[25], whereas for higher pressure it becomes diamond (with a face-centered cubic crystal struc-
ture). In the form of a hollow sphere with hexagonal and pentagonal rings carbon is known as
fullerene, whereas if the nanostructure is cylindrical it is known as CNTs (carbon nanotubes)
(Figure 5).
10
Figure 5: Allotropic forms of carbon.
In 2004 Konstanin Novoselove, Andre Geim and their collaborators [26] at the University
of Manchester, UK, tried to isolate one single layer of graphite to perform some electrical
measuraments and this is how graphene was discovered. Graphene is the first 2D material to
be produced, being the pioneer for other single layer materials such as Boron-Nitride (BN),
black Phosphorus (P), and Molybdenum disolphate (MoS2). Those 2D materials have been
extensively studied, since their characteristics are often very different from the bulk form:
physiochemical, optical and physical properties change radically [27].
11
The very next step for those scientists was maybe the most difficult, because they had to
understand how to isolate a large amount of single sheets of carbon in order to determine the
unique properties of graphene. At the end of their successful research, the scientists won the
Nobel Prize for physics in 2010 for ”groundbreaking experiments regarding the two-dimensional
material graphene” [28].
1.2.2 What is Graphene?
After several years of studies, it is now possible to define graphene as a mono-layer of carbon
atoms arranged in a hexagonal (honeycomb) lattice also called chicken-wire like structure: the
distance between the atoms is 1.42 A and the thickness of the layer is about 3.35 A [26].
Chemically speaking, it is worth analyzing the bonds for each carbon atom: three of them are
σ type bonds (one with each of its coplanar neighbors) and the fourth is a π-bond that is directed
out of the layer. Actually, since it is a monolayer material, the forth electron delocalizes on the
whole graphene surface, which is translated into high electrical conductivity. This important
property can be explained by another peculiar graphene characteristic that is the low density of
defects in its crystal lattice: in fact, defects usually reduce charge mobility, limiting the electron
mean free path [29].
While analyzing orbitals it has been observed that an hybridization of s, px and py make up
the σ-bonds. The final electron in the pz orbitals constitutes the π-bond. These last mentioned
bonds from all the atoms hybridize together in order to form two of the so called bands, which
are named π and π∗; because just one electron is present in each of the pz orbitals, the π band
12
is half full. Unique electronic properties of graphene are related to these half-filled bands that
allows free-moving electrons [30].
Figure 6: Lattice structure of graphene, made out of two interpenetrating triangular lattices (a1)and a2) are the lattice unit vectors and δi, i=1,2,3 are the nearest-neighbor vectors. Reproducedwith permission from reference [31]
Hexagonal arrangement of carbon atoms is shown in Figure 6. The vectors which define the
lattice can be expressed as:
a1 =a2 (3,
√3), a2 =
a2 (3,−
√3)
where a is the atomic distance (1.42 A). It is possible to write the reciprocal lattice vectors:
13
Figure 7: Electronic dispersion in the honeycomb lattice. Reproduced with permission fromreference [31].
b1 =2π3a (1,
√3), b2 =
2π3a (1,−
√3)
The nearest-neighbors vectors are:
δ1 =a2 (1,
√3); δ2 =
a2 (1,−
√3); δ3 = −a(1, 0)
whereas the six second-closest nearby atoms can be found at δ′1 = ±a1, δ
′2 = ±a2, δ
′3 =
±(a2 − a1).
To explain the unique electronic properties of graphene it is worth underlining the presence
of the so called Dirac cones (conical valleys that touch at the high-symmetry and KK ′ points)
shown in Figure 7 and Figure 8. Near these points, the energy has a linear dependence with the
magnitude of momentum [32]. This means that electrons showed a quasi-relativistic particles
behavior, and they can be represented through the Dirac equation [33]. Electrons speed in
14
graphene layers can reach enormous values (∼ 106m/s): in fact it is only two order of magnitude
smaller than the speed of light (photons).
Figure 8: Brilluoin zone. The Dirac cones are located at the K and K′ points. Reproducedwith permission from reference [31].
Analyzing the mechanical characteristics graphene is expected to have an high intrinsic
strength since it combines the properties of 3D graphite and 1D carbon nanotubes [34]: statistic
studies were done in order to find out the stress-strain diagram [35] and results are summarized
in Table I.
Eventually, it is worth to specify thermal properties of graphene because the high thermal
conductivity (up to 5000 W/mK) makes this material very suitable for electronic applications,
since it is necessary to quickly cool down the device when heat is generated.
15
TABLE I: GRAPHENE MECHANICAL PROPERTIES
Property Value
Young Modulus E 1±0.1 TPa
Intrinsic stress σint 130±10 GPa
Strain εint 0.25
1.2.3 Graphene Production
In this section graphene production methods are summarized: first of all it is necessary to
divide these methods in three large subcategories that are:
• Mechanical exfoliation;
• Supported growth;
• Chemical vapour deposition.
The first method was developed by Novoselov and Geim and it basically consists of sticking
and peeling graphite layers with an adhesive tape a dozen times. After checking for small
fragmentsy, the graphene and graphite specimens are then moved to the disinfected substrate
[26]. The substrate material often consists in a SiO/SiO2 layer because of the better contrast:
graphene will appear bluish and will be easier to detect. Even if it is the simplest method, it
gives graphene the best electrical and structural properties, but it is not suitable for large scale
production.
If this is the case, supported growth is the preferred method; graphene could be grown
on a solid substrate thanks to chemical vapor deposition (CVD). This process requires very
16
high temperatures (>1100K) and it was already studied for carbon-nanotubes (CNT), but it is
challenging to control morphology and adsorption energy.
Chemical vapour deposition (CVD) is a way of locating gaseous reactants onto a substrate.
In CVD gas molecules that are present in a reaction chamber (which is normally set at ambient
temperature) are combined: material film on the substrate surface is created eventually, once
gases has come into contact with the substrate inside the reaction chamber (which is heated).
The waste gases are then pumped from the reaction chamber. Graphene production using CVD
takes place in two phases:
• Pyrolytic decomposition of a material to form carbon. This operation has to be conduced
onto the surface of the substrate to prevent the precipitation of soot during the gas phase.
• Formation of carbon structure of graphene using the disassociated carbon atoms. Usually
it takes place in presence of a catalyst since very high temperatures are required.
For this research, CVD is the technique used for graphene production with the help from
our collaborators. It has been carried out on a Cu substrate (as in Figure 9) at 1000 C; the
detailed description will be provided in section 2.1.
Another fabrication example consists in the pH sensors used by Lei et al. in their work [36]
(to which results are compared): they are fabricated by mechanical exfoliation of graphene from
bulk graphite with scotch tape irregularly installed on a silicon wafer of 285 nm SiO2 thickness,
that is the one which guarantees maximum graphene visibility.
17
Figure 9: Chemical vapour deposition (CVD) of graphene on Cu substrate. Re-produced with permission from Ajay Kumar and Chee Huei Lee (2013). Synthesisand Biomedical Applications of Graphene: Present and Future Trends, Advances inGraphene Science, Dr. M. Aliofkhazraei (Ed.), InTech, DOI: 10.5772/55728. Avail-able from: http://www.intechopen.com/books/advances-in-graphene-science/synthesis-and-biomedical-applications-of-graphene-present-and-future-trends
1.2.4 Graphene as a Sensing Material
There are many reasons why graphene has recently been explored as a sensing material:
it shows incredible features which are fundamental for a good sensor such as an important
surface-to-volume ratio, great optical properties, high electrical conductivity, significant carrier
mobility and density, large thermal conductivity and many other characteristics that can be
greatly beneficial for sensor functions [37]. First of all, having a the large surface-to-volume
ratio, the best in any known materials, means that every atom is a superficial atom and it is
a theoretical target for reactive species [32]. The strength of bonds with the target specie can
vary from weak (Van der Waals) to strong (covalent).
18
Figure 10: The mask-free fabrication process of a graphene sensor. Reproduced with permissionfrom reference [8].
Furthermore, the large surface area of graphene is able to improve the storing of aim
biomolecules: at the same time electrons conduction between biomolecules and the electrode
surface is exceptional due to small band gap and great conductivity.
Other biosensors applications regard the detection of some analytes like glucose, glutamate,
cholesterol, hemoglobin and others (Figure 11). Graphene also has the potential for improving
electrochemical biosensors, which works with direct electron transfer between the enzyme and
the electrode surface. In these cases, adsorbates can produce two opposite effects on graphene
conductance:
19
Figure 11: Example of a graphene sensor.
• Scattering of electrons or holes, and consequently decrease carrier mobility, i.e conduc-
tance [38];
• Decreasing in scattering effect thanks to the supporting substrate, increasing conductance
[39].
Moreover, graphene has a great sensitivity even for very low concentrations: Leenaerts et
al. demonstrated that it is able to detect NH3, CO, NO2 and H2O even if their concentration
is as low as 1 ppb (parts per billion) [40]. In the case of the first two molecules, graphene is
doped by electrones, whereas in the case of the latter two, this happens by holes [38]. These
unique sensing properties are derived from two important facts i.e.:
• 2D structure (surface dopants effects are maximized);
• High conductivity, even if considering zero carrier density.
20
Finally, the high mechanical properties assure that atomic distances are not altered in
presence of external stresses, avoiding changes in local electronic charges: this could have lead
to modifications in band gap electronic structure and in electrons transport [29].
Once all the unique properties of graphene have been explained, scientists studied sites
where adsorption takes places in the carbon structure and using water they found out three
different sites (Figure 12): with the reference to a carbon atom, adsorption cat take pace on
the top of it (T), at the center of a bond (B), or in the middle of an hexagonal cell. (C)[40].
Figure 12: Adsorption sites: H2O on graphene. Reproduced with permission from reference[40].
21
As mentioned above, having just surface atoms allows this material to create a large amount
of different bondings sites and that is why graphene sensors are widely used: they are often
modified in order to decrease the LOD (Limit Of Detection), which is defined as the lowest
quantity or concentration of a component that can be detected.
Analyzing the electrochemical field first, it is possible to mention sensors for H202 detection
(graphene modified by hemoglobin [41] or horseradish peroxidase (HRP) [42]), glucose detec-
tion (modification through GOD, RGO and polypyrrole [43] or through RGO and platinum
nanoparticles [44]), biomolecules detection (such as dopamine, via chitosan and RGO addition
[45]) or cellular detection (such as breast cancer cells with RGO-based sensor [46]).
Speaking of biomolecular detection, some proteins can bind to graphene via a π − π inter-
action inducing different responses on conductance which depends on some parameters of the
interacting proteins [47]: for example immonoglobulin E was detected thanks to IgE-specific
aptamers placed on the graphene surface. Field effect is responsible for the drastic decrease in
graphene conductance when the target is acquired [48].
Eventually, graphene as pH sensor will be discussed: Ang et al. were the first to anticipate
that the ambipolar characteristic of this material will allow the adsorption of both hydroxyl
(OH−) and hydroxonium (H3O+) ions [49]. They will change the conductance by doping ”holes”
or ”electrons”: charging process depends on where ions are going to bind, if at Helmhotz
inner plane or at the graphene/electrolyte interface. Further studies demonstrated that doping
happens in a different way for hydroxonium ions (H3O+) and hydroxyl ions (OH−): the first
ones make graphene n-doped whereas the others make it p-doped. It has been found that
22
Dirac points (points of minimal conductance) shifts towards positive direction when pH is
increased, meaning that pH detection happens thanks to change graphene electrical properties
[50]. Focusing on this work, change in graphene resistance is monitored as Xu et al. did in their
study: in particular their sensor was used to conduct tests and the same trend they obtained
for different pH values is expected Figure 13.
Before involving the actuation of the bubbles to increase the micromixing, it is necessary to
check that:
• Sensors resistance immediately drops when liquid is poured;
• After the initial drop, resistance grows up to a saturation level;
• Resistance decreases when pH value increases;
Afterward, a study on repeatability has to been carried out since even tough the sensors
share their fabrication process, their resistance is different [36]: production method does not
guarantee that every graphene layer has the same shape or thickness and this means that every
sensor will have different characteristics.
23
Figure 13: Results of previous studies: (a) Real-time resistance measurements of the graphenesensor when exposed to pH buffers from pH 4 to 10; (b) Compiled resistance data from multiplemeasurements plotted as a function of pH values [8].
24
1.3 Acoustic Bubbles
In the previous section all the unique properties of graphene as a sensing material have
been illustrated. However, even if adsorption happens in a rapid way and LOD is very low,
sensor can show long sensing time due to slowness of target species across the fluid sample.
In fact, in microchambers the movement of targets mainly relies on diffusion which is a rather
slow phenomenon: in this work, oscillating bubbles will generate a microstreaming which allows
movement of particles towards sensor surface, drastically decreasing sensing periods. To better
understand the benefits of this solution, a brief section on diffusion limits in microchannels and
microchambers is added.
1.3.1 Diffusion Limits
Inside microchannels, that have a characteristic dimension less then 1 mm [2], average speed
of fluid flow is usually in the range up to cm/s which is translated in a low Reynolds number,
typical for laminar flow. In this regime a fluid flows in parallel layers and particles move in
straight lines parallel to the pipe walls.
The low Reynolds number shows that shearing forces in the fluid are much more important
then inertial ones: in microchannels liquid velocity is zero at the walls and maximum in the
cross section center line (farthest point from the walls). In addition, since the streamlines are
parallel, there are no swirls of fluid that can cause lateral mixing (Figure 14): this fact can be
exploited in microdevices and it is possible to observe a multiphase flow using dyed water [10].
Two different liquids can be injected in the same microchannel and in the laminar flow regime
they will not mix: this phenomena has been used to extract carbaryl derivative. [51]
25
Figure 14: ANSYS simulation: diffusion limits. In a microchannel, two different fluids (laminarflow regime) will not mix completely. In this example ethanol and water have a partial mixingjust at the fluid interface.
On the other hand, the lack of the normal component of the velocity (towards the center
or the walls of the channel) can enormously increase the mixing time: in fact, with a very
low advection in the channel, the only possibility for particles to move is related to diffusion
phenomena which usually takes a great amount of time. In the sensing field, Squire et al.
analyzed problems related to long diffusion times in microchannels according to flow rate and
sensor dimensions, explaining the difference between reaction and diffusion limited operations
[52].
The situation can be even worse in micro-chambers, where dimensions are significantly
increased with respect to microchannels [53] and it can take several hours for a molecule to
diffuse from one corner to the opposite one. In this work, the amount of fluid used for every
test is in the order of 1 mm (fluid is poured using an insulin syringe): with the simplification
of 1D movement, it has been calculated that if a single H3O+ ion in the designed device can
26
TABLE II: DIFFUSION COEFFICIENTS VALUES FOR IONS IN WATER
Ion D [cm2/s]
H3O+ 7.0 × 10−5
OH− 5.3 × 10−5
take up to several hours to move from the fluid free surface to the graphene layer. Obviously
sensing times are shorter because the working conditions are different from the limit case of
just one target specie in the solution. The time necessary for a single ion to travel across the
fluid sample is calculated according to Table II; diffusion time equation is:
t ≈ x2
2D(1.1)
where:
• t is is diffusion time.
• x is the mean 1D distance traveled by the target specie in the time t.
• D is the diffusion coefficient of a target specie. It varies for each solute and it is determined
empirically. D depends on both the nature of the solute and of the medium. It is inversely
linked to the weight of the species and can be related on their molecular shape. Diffusion
coefficient also depends on temperature.
Diffusion coefficient values are taken from [54]: for H3O+ it is calculated subtracting from
the proton diffusion coefficient, 9.3 × 105 cm2/s, the water self-diffusion coefficient, 2.3 × 105
27
cm2/s. After having understood those problematics, this research has been conducted in order
to overcome diffusion limits in a fluid over a sensor, trying to reduce the sensing period and
improve sensors performances: movement of particles toward sensor can be forced inducing a
microstreaming thanks to oscillating bubbles.
1.3.2 Cavitation Microstreaming to Overcome Diffusion Limits
As previously discussed, when considering a laminar flow in a microchannel, mixing is
mainly based on diffusion, meaning that even after long times mixing efficiency is still poor
[55]. Various techniques were tested in order to enhance mixing: for instance, mechanical
rotation of the chamber lateral walls was used but appeared to be ineffective due to dominant
impact of viscous forces at microscale. More interesting are some mixing techniques specific for
the micro-scale such as hydrodynamic focusing [56] or electrokinetically driven mixing [57], but
one that gained interest due to its non-invasive nature and the remote activation possibility is
the acoustic-based mixer [58]: oscillating bubbles were first studied in the 50s [59], but only
nowadays are used to generate microstreaming in a microfluidic environment [53] [60] [61] [62]
[63].
The mechanism in which these acoustic bubbles work is quite simple: when a gas bubble
is trapped in an aqueous medium, its surface can behave as an actuator, meaning that it can
vibrate and at the interface between liquid and air there is the formation of fluid flow [64], the
so called acoustic or cavitation microstreaming (Figure 15).
Various experiments have been conducted with fluorescent particles [58] that were used
to allow the researchers to visualize the enhanced mixing in a microchannel and the effective
28
Figure 15: Quadrupole microstreaming pattern created by linear translation of a 232 µm radiusbubble attached to a horizontal surface and forced at 2.422 kHz at 30 V p-p; (a) streak image, (b)PIV velocity vector field and divergence (positive divergence zones at top and bottom of blackcircle representing bubble, negative zones at left and right). Circular vortex microstreamingpattern created by circular translation of a 224 µm radius bubble on surface forced at 1.188kHz at 30 V p-p, (c) streak image, (d) PIV velocity vector field and divergence (colour versiononline; weak positive and negative divergence alternate around bubble circumference). Dipolemicrostreaming pattern created by radial oscillation of a 267 µm radius bubble on surface forcedat 8.658 kHz at 30 V p-p, (e) streak image, (f) PIV velocity vector field and divergence (negativedivergence zone at top, positive below). Reproduced with permission from reference [64].
29
movement of particles towards the centerline of a channel when bubbles are activated. After
having proved the increasing in the mixing efficiency, some tests were taken to understand if
it was possible to mix two fluids with laminar regime in microchannels [55], showing that even
with a short lengthscale mixing can be achieved.
Figure 16: Schematic of a microchannel with a HSS in the center. Region 1, external to theHSS, is filled by a liquid (e.g., water) and region 2, inside the HSS, is occupied by air. Thedimensions of the HSS (a, b, and h) and the amplitude of the water-air interface (S) are labeledin the figure. A piezoelectric transducer is used for acoustic activation of the bubble trappedat the HSS.Reproduced with permission from reference [65].
However, efficient mixing occurs only when bubbles are excited at their natural frequency
and to determine its value is still pretty challenging. In the kHz range, frequency is related to
the bubble dimensions and the characteristic of the liquid:
30
2πaf =√
3γP0/ρ (1.2)
where a is the bubble radius, γ is the specific heat ratio of the gas, P0 is the hydrostatic
pressure and ρ is the density of the liquid. Some other formulas show how frequency is related
to the shape of the cavities where bubbles grows and Chindam et al. calculated it in the case
of a horse-shoe shaped structure (Figure 16) [65]. In this research cavities have a circular shape
with a dimension of 75 µm (diameter) and a depth of 100 µm. Bubbles that will be trapped
inside these cavities are expected to generate a streaming in the micro-chamber that is strong
enough to move target species faster than what they would do just in the diffusion phenomenon.
1.3.3 Microbubbles Formation
Before analyzing how bubbles are actuated and how they can introduce a turbulence in the
fluid it is worth underline how bubbles formation occurs in cavities. The study of nucleation is
necessary to understand mechanisms for stabilizing microbubbles within the liquid [66].
Presence of inhomogeneities, i.e. microbubbles or dirt particles, has always been expected
whenever scientists realized that the tensile strength of a given liquid was significantly less than
the theoretical predictions [68]: those inhomogeneities are considered important just if they can
survive for a sufficient amount of time in the liquid and that’s the reason why ”free bubbles”
are not considered as impurities. On the contrary, microbubbles that grows in crevices or in
small pockets are stable [67] for a matter of a difference in the value of concentration. In fact,
31
Figure 17: Diagram of a closed container partially filled with a liquid. The pressure in the spaceabove the liquid is equal to the sum of the vapor pressure pv, and the partial pressure of the gasdissolved in the liquidid pg. Within the liquid is a spherical bubble of radius R. Reproducedwith permission from reference [67].
considering a closed container as in Figure 17, if c is the concentration of the gas at partial
pressure pG, it is possible to use the Henry’s law in the proximity of air-liquid interface:
c = K(T )pG (1.3)
where K(T ) is a function of temperature only. The total pressure in the gap above the
liquid, neglecting hydrodynamic effects, will be pG + pv, where pv is the vapor pressure and at
the interface pG = pL − pv, meaning that the saturation concentration cs will be:
cs = K(T )(pL − pv) (1.4)
32
Considering a free bubble with radius R inside the liquid, it is possible to apply the Laplace
equation and it holds:
pG + pv = pL + σC (1.5)
where C is the curvature of the bubble equal to 2/R and it is considered positive if the
curvature center is on the gas side. At this point, since the Laplace pressure σC is positive, it
holds that pG > pL − pv and recalling the previous equations:
c > cs (1.6)
This means that the concentration of gas in the boundary of the bubble is higher than the
saturation concentration, i.e. concentration of gas in the liquid: this gradient of concentration
will lead to diffusion mechanisms and the final dissolution of the free bubble. So it has been
proved that free bubbles will dissolve in liquid that are not supersaturated with gas [69], but
what about bubbles in cavities?
When the liquid reaches the pocket, some air will be trapped on the bottom, and due to the
presence of the solid, the center of curvature of the liquid-gas interface will be on the liquid side
causing the Laplace pressure to be negative: in this way the gas concentration in the proximity
of the interface is equal or smaller then everywhere else and the bubble can exist indefinitely.
At this point, Bremond et al. [70] [71] analyzed the difference between bubbles generated by
a rough surface and another one where a series of cavities were performed: they investigated
33
Figure 18: Conditions for the entrapment of gas in the advance of a semiinfinite liquid sheetacross a groove. Reproduced with permission from reference [67].
the way bubbles can grow inside these cavities, once pressure in the liquid is lowered and how
cavities interact if placed at a certain distance.
Finally, it is important to study how bubbles can grow once liquid is poured on the surface,
in particular initially a two-dimensional flow on a flat surface as in Figure 18 will be studied:
if the X axis is the one along the flow direction and the Z axis as the one perpendicular to the
surface, it is possible to state that for X = 0, Z = −2B1/2, where:
B =γ
(ρL − ρG)g(1.7)
γ is the surface tension, ρL and ρG are the densities of the two fluids (liquid and gas),
whereas g is the gravitational acceleration [72]. Considering a flat surface, one principal radius
34
of curvature will be infinite whereas the other one is R and it will lead to the Gibbs [73]
condition:
Z = −B
R(1.8)
So, considering a layer of liquid advancing to the left, it holds:
X = B1/2
[log
(+
√4B
Z2− 1− 2B1/2
Z
)− 2
√B − Z2
4
](1.9)
whereas if considering a layer moving toward right, it is necessary to change signs before
square roots.
After having analyzed the advancing of a liquid on a flat surface, it is now necessary to
understand the behavior of the same liquid when encountering a groove or a hole, and study
the condition for which air remains trapped on the bottom of the pocket. Entrapment happens
if:
θ > 180− 2ϕ (1.10)
where ϕ is the angle defining the steepness of the considered conical cavities whereas θ is
the contact angle derived by the Young’s equation [74]:
γSG − γSL − γLG cos θG = 0 (1.11)
35
In the case of cavities obtained through drilling in a CNC machine, walls can be considered
almost verticals (ϕ → 90) and gas entrapment is guaranteed, especially when the liquid wets
the surface poorly (θ ≥ 90). Once it has been clarified that bubble formation happens in the
cavities that have been manufactured, it is possible to study the oscillation phenomenon in the
acoustic field.
1.3.4 Governing Equations of Acoustic Microbubbles
In this section governing equations of acoustic theory and induced streaming will be reported
in order to better understand the latter work. In particular, it is first of all necessary to
remember that the ultrasonic wave will propagate and finally stretch and compress the air
bubble in the cavities [75]. Vibration of the bubbles can be expressed through the Rayleigh-
Plesset (RP) equation, making the following simplifications:
• Intensity of the sound field is constant;
• Air in the bubble behaves as an ideal gas and its pressure is uniform;
• Movement of bubbles is spherically symmetric;
• Liquid around the bubble is incompressible.
Liquid compressibility can be found in the ODE when dealing with the Mach number. Mach
number can be expressed as the ratio between R, which is the radial component of the velocity
of the bubble, and cl, which is the speed of sound in water (in the considered liquid in general).
As long as the value of the Mach number is ≪1, (value that is typically reached when the
bubble is going to collapse) one can neglect its effects: in particular the incompressible limit
36
of the RP can be applied if Ma <0.2 [76]. This Rayleigh-Plesset is an ODE derived by the
potential of liquid motion and can be written as:
ρl
(RR+
3
2R2
)= ρg(R, t)− P (t) + P0 +
R
cl
d
dtpg(R, t)− 4ηl
R
R− 2σ
R(1.12)
Analyzing the right-hand side of this ODE, P0 is the ambient pressure (equal to 1 atm),
whereas P (t) is the sound wave which is treated homogeneous in space. This is translated as:
P (t) = −Pa cos(ωt) = −P0p cos(ωt) (1.13)
where p ≡ Pa/P0 is the dimensionless forcing pressure amplitude. On the right-hand side of
equation Equation 1.12, σ is the surface tension at the bubble-water interface (and it is equal
to 0.072 kg s−2), ηL is the water viscosity equal to 1.00×103 Pa s), whereas cl is the speed of
sound in the liquid (equal to 1480 m s−1 for water). The gas pressure pg(R, t) inside bubbles is
treated as it is following the van der Waals process and it is:
pg(R, t) = pgas(R(t)) =
(P0 +
2σ
R0
)(R0
3 − h3
R3(t)− h3
)κ
(1.14)
with R0 as the nominal bubble radius, h is the so called van der Waals hard-core radius and
κ ≈ 1 effective polytropic exponent [77].
The fact that the pressure inside the bubble is varying can be easily explained just consid-
ering a force equilibrium at the liquid-gas interface. In fact it holds:
37
pg − pl =2σ
R(1.15)
So, since the radius is varying according to the RP equation, pg will not be constant.
1.3.5 Streaming Induced by Microbubbles
Now that it has been explained why and how bubbles vibrate under application of an
acoustic field, it is possible to analyze the effects of this oscillation in the liquid, in particular
evaluating the induced streaming flow.
This study is rather difficult because it involves many physical quantities: Elder [59] was the
first to find the streaming patterns modifying some parameters involved in the problem such
as viscosity or amplitude (Figure 19) whereas Nyborg [78] gave the mathematical relation to
describe it. In the recent years, other researches were performed to characterize the streaming
in some particular cases such as lateral cavities [79] semicylindrical microbubbles [80] or bubbles
in teardrop cavities [81].
First of all, it is worth underlining that a sound field is generated by the bubble itself once
that it is reached by a sound-wave, which is treated as a pressure gradient [82]. This is the
reason why Nyborg evaluated the secondary radiation force that all the objects that are within
this sound field experience:
FSR = −VP∇P (1.16)
38
Figure 19: Cavitation microstreaming patterns for the various amplitudes and viscosities. Re-produced with permission from reference [59].
where Vp is the volume of the object which experiences radiation forces and ∇P is the
pressure gradient generated by the oscillating bubble. In the case of a rigid spherical particle,
like the one used in this work when resonance frequency has been used, Nyborg and Coakley
[83] reduced the magnitude of the secondary radiation to:
FSR = 4πρ
(ρ− ρpρ+ 2ρp
)ω2ϵ2R6R3
p
d5(1.17)
39
where ρp is the particle density, ω is the actuation frequency, d is the distance of the object
from the bubble and ϵ is a parameter related to the oscillation amplitude of the bubble and
it will be discussed later. Therefore, the nature of the force (attractive or repulsive) depends
on the liquid and particles densities. Moreover, it can be underlined that since ∇P decreases
moving farther from the bubbles, the force will be greater in the proximity of the bubble itself
[84].
Analyzing what happens in the proximity of the actuated bubble, a first-order u1(t) with
amplitude u1 and angular frequency ω = 2πf induces a second-order streaming flow us: this
is because of the balance between viscous forces and nonlinear inertial forces. The nonlinear
inertial forcing term fs = ρ⟨u1 · ∇u1⟩ is averaged and its amplitude is fs ∼ ρu21/l where l is the
length scale of the gradient of u1. The term representing the inertial forces is obtained by the
Navier-Stokes-Fourier set of equations:
• Mass Conservation Law
∂ρ
∂t+∇ · (ρu) = 0 (1.18)
• Momentum Equation
∂(ρu)
∂t+∇ · (ρu⊗ u) +∇p = ∇ ·Πν + ρa (1.19)
40
• Total energy conservation
∂(ρet)
∂t+∇ · (ρetu+ pu) = ∇ · (qα +Πν · u) (1.20)
Figure 20: Bubble streaming flow patterns at different driving frequencies,with arrows indicat-ing the orientations of the vortices. Outline of oscillatory bubble superposed over one cycle atdifferent frequencies (e) 9.6 kHz, (f) 20.6 kHz, (g) 48.6 kHz, and (h) 100.3 kHz. Reproducedwith permission from reference [85].
Only in the boundary layer the steady streaming force is compensated by viscous forces
fν = ν∇2us with amplitude fν ∼ νus/δ2 ∼ ρωs , and the boundary layer δ can be written as
[86]
δ ∼√
ν
ρω(1.21)
41
So, since fν ≈ fs, it holds:
us ∼u21ωl
(1.22)
The value of u1 can be found as:
u1 = ϵaω (1.23)
where a is the rest radius of the bubble and ϵ ≡ A/a ≪ 1 takes into account the oscillation
amplitude A.
It has been proved that streaming velocity us depends on the exciting external frequency
f and in Figure 20 it is possible to visualize the work done by Wang et al. [85] that shows
different streaming patterns and bubble oscillations for different frequencies.
CHAPTER 2
FABRICATION AND EXPERIMENTAL SETUP
In this section all the equipments used to perform experiments will be listed: in particular,
fabrication methods of the devices produced in the laboratory and functions of the electronic
devices used will be explained in detail.
2.1 Sensors
The graphene was grown by typical chemical vapor deposition on a Cu substrate at 1000 C.
Then, a layer of polymethyl methacrylate (PMMA) is spin-coated on the top of the graphene
for both protection and transfer. Afterwards, the samples were soaked in FeCl3 solution
overnight to dissolve the Cu substrates. After the Cu foil is etched, the separated floating
PMMA/graphene is subjected to de-ionized (DI) water several times to clean the iron ions,
followed by transferring to the Si wafer. After naturally and 110 C drying the sample for 30
minutes, acetone and DI-water were employed to clean the top PMMA layer. Measurements
will be taken connecting wires to electrodes in contact with graphene. In particular, Ti/Au
electrodes were deposited on the top of graphene using a shadow mask by radio frequency mag-
netron sputtering: this is a physical vapor deposition (PVD) method of thin film deposition
that consists in the ejection of material from a ”target” that is a source onto a ”substrate”.
However, every time probes or wires are placed upon electrodes to take measurements, they
42
43
can easily get scratched: it is consequently important to use a silver paint (SPI 05001-AB) in
order to re-establish the connection with the sensor and make the data acquisition possible.
2.2 Micromachining and 3D Printing
To generate cavitation microstreaming it is necessary to actuate bubbles at their natural
frequency: in this work bubbles are trapped in cavities generated by performing a drilling
operation on PMMA plates. Micromilling (Figure 21(b)) is a fabrication technology which
consists in the destruction of designed part of a workpiece material (PMMA in this work) by
a tool (carbide). [87]. When dealing with microfluidics devices lithographic processes (Figure
21(a)) are often used since they are capable to obtain small feature sizes since their resolution in
higher and at the same time they have to be used when undercuts are meant to be performed.
However, materials for stereolithography (SLA) manufacturing often are just polymers so it is
not useful when high-strength materials with good acoustic properties. Micromilling can solve
these SLA technology problems because of the possibility of machining complicated 3D shapes
in different engineering materials (alloys, composites, polymers, glasses and ceramics) [88].
Additive manufacturing is anyway used in this work to produce a box that will contain the
PMMA plates: its function will be explained better later on, but it is important to underline
why SLA was used. PMMA will be inserted inside this box, so it is required to obtain a device
with very deep and narrow cuts; using a 3D printer it is possible to build it layer by layer
without restrictions related to cut depth. In addiction, the use of a polymeric material allow
the deformability of the box, necessary to insert the plates and at the same time fix them.
44
(a) (b)
Figure 21: (a) : stereolitography (SLA) process used by the 3D printer; (b) : scheme of amilling machine
2.2.1 Micromilling PMMA and G-Code Programming
In this work, to produce cavities, a Minitech Mini-Mill/1 was used to micromachine PMMA
plates Figure 22(b). In particular, PMMA was chosen because it is a hard but and light material:
its density is ∼ 1.20 g/cm3, that is minor than half glass density. Among its characteristics
it is worth mentioning a good resilience, (higher than both glass and polystyrene) and that is
why it is often used for constructing residential and commercial aquariums; its characteristics
are reported in Table III.
These features make PMMA suitable for micromachining, even if some problems occurred
when chips had to be removed. By the way, one of the main reasons why PMMA was chosen
is the fact that it is transparent: in fact, thanks to its transparency it was possible to use a
microscope to visualize particles moving when the resonance frequency was researched, as it
will be discussed later.
45
(a) (b)
Figure 22: Devices used for equipment fabrication: Formlabs, Inc. Form1+ 3D printer on theleft and Minitech Mini-Mill/1 on the right
TABLE III: PMMA MECHANICAL PROPERTIES
Property Value
Young Modulus E 3.2 GPa
Density ρ 1.17 g/cm3
Ultimate tensile strength σs 70 MPa
Elongation at break 3%
46
According to previous studies, it has been found that the smaller the cavities (and so the
bubbles trapped in them), the higher the probability to generate a strong streaming; therefore
in a first moment, the smallest tool available was used (50 µm). However, this tool was very
fragile, and since it is not recommendable to perform a cut that is deeper than twice the
diameter of the tip, a bigger tool was necessary to perform deeper holes. For this reason a 75
µm carbide tool (0.002 in diameter Mini Carbide Drilling tool from Harvey Tool) was used to
perform an high number of cavities: commands were given to the machine thanks a G-Code,
written in order to have the desired number of holes, spaced in the correct way and with a
given depth; eventually feed rate and velocity of the spindle were set. Machining details are
summarized in Table IV .
Figure 23: Geometrical parameters for the holes milling
47
TABLE IV: G-CODE DATA
Data Type A Type B
Number of holes in the X direction 13 37
Number of holes on the Y direction 18 18
Value a 200 µm 200 µm
Value b 200 µm 200 µm
Angle A 0 0
Feed Rate (X,Y G00) 40 40
Feed Rate (X,Y G01) 20 20
Feed Rate (Z G00) 40 40
Feed Rate (Z G00) 20 20
Safe Z above surface 0.2 0.2
Moreover, it is important to specify that center-to-center distance between two cavities is
set equal to 200 µm because studies shown how if
a >√πD (2.1)
streaming generated by bubbles is stronger. In fact, if bubbles are too close to each other,
it is not possible to sum effects of their vibration. For an appropriate distance, sound waves
will sum up and microstreaming will be much more intense.
However, some other operations were done with the micromilling machine in order to obtain
the desired plates: first of all, before drilling flattening was necessary to reduce PMMA thick-
ness. As mentioned above PMMA samples are 3 mm thick: plates where drills are performed
48
Figure 24: PMMA plate design
need to be as thin as possible because they are going to be placed very close to each other inside
the 3D printed box (which will be introduced later). Thanks to flattering, performed by a 0.125
in (∼ 3 mm) diameter carbide cutter tool, a large area of the PMMA sample (2-3 times bigger
then the final plate) will have a reduced thickness (∼ 850 µm) and drilling is now possible: this
thickness was chosen because even if the material is now very thin, it is still resistant enough
to avoid bending during the following machining and it is thick enough to produce holes (total
depth ∼ 1/7 of thickness). At the end of this process, plates of the actual dimensions will be cut
49
and they will be ready to be placed in the box. To prevent cavities damage, an extra-amount of
space (∼ 500 µm) was left between the last holes row and the perimeter cutting path: anyway
this space needs to be as small as possible to avoid bubbles to be too far from the sensor. The
result of the machining is the micromilled plate shown in Figure 25.
Figure 25: Micromilled PMMA plate
50
TABLE V: PMMA PLATES DIMENSIONS
Dimension Type A Type B
Lenght [mm] 4.65 7.40
Width [mm] 1 1
Height [mm] 13.7 13.7
The design of micromilled plates is sketched in Figure 24 and dimensions are summarized
in Table V: for detailed scheme refer to Appendix A. To fix plates over the sensor a 3D printed
box has been designed.
2.2.2 3D Printed Box
As mentioned above, this box will accommodate the micromilled plates: the requirements
for this device are to take up as less space as possible in order to guarantee easiness in the final
set-up, in particular to improve the contact wires-electrodes and to keep PMMA plates (i.e.
cavities) as close as possible.
The device used to build this cage is a Formlabs, Inc. Form1+ 3D printer (Figure 22(a))
which uses SLA as technology and Hinged Peel Process as peeling mechanism. The resolution
of this machine (50 µm) allowed to create undercuts in which plate can be fit. As it is shown
in the design sketch, the undercut is made in a way that plates are fixed inside the box, but at
the same time, cavities will be in contact with fluid: strong clamping is the reason why plates
have a total height as great as three times the height of the microdrilled part. The fluid itself
is going to be poured through the orifice operated on the top side of the box and its diameter
51
(a) (b)
Figure 26: 3D-Printed Box: Isometric view and Sectioned view
has been choose big enough to fit the syringe needle: at the same time it can not be too big
because this hole need to be in the space between the box walls (that are placed as close as
possible to each other).
The resin used by the 3D printer is a Clear Resin (Mixture of methacrylic acid esters and
photoinitiator always bought from Formlabs, Inc.) which guarantee highest-quality output, and
at the same time make small details possible without sacrificing durability and toughness. To
improve toughness, after printing is complete the sample is soaked in IPA: moreover, in this way
it is possible to clean holes and remove impurities. This resin guarantee a minimum elasticity
and deformability that is anyway sufficient to initially fit the PMMA plates and then firmly
clamp them.
52
2.2.3 PDMS Cover
Once the box has been manufactured, a PDMS cover has been realized. PDMS is a silicone-
based organic polymer which is utilized in many microfluidics applications and it is particularly
famous for its unusual rheological properties. PDMS is transparent (one of its main advantages),
and it is usually, inert, non-toxic, and non-flammable; those are some of its main advantages
that make it very suitable for microfluidics applications. In particular, in this work PDMS is
produced by silicone elastomer base and curing agent from SYLGARD. After having assured
that air is removed thanks to a centrifugal rotation (centrifuge is a Heraeus Labofuge 400 R
form Thermo Scientific), the liquid polymer is poured in a container (Petri Dishes by Steve
Spangler Science) all around the 3D printed box: this has been covered by foil in order to make
sure that the polymer would not enter the undercuts. At this point PDMS is ready to be cured
under UV lights.
The cover will help to fix the mentioned box above the sensor and it is thought to reduce
leakages: in fact, if the box just lays on the sensor a good amount of liquid will flow out making
the bubble formation impossible (liquid will not stay in the box). PDMS will not only fix
the box, but it will stick on the dish used to hold the whole structure reducing leakages. In
addition, during PDMS curing two wires are inserted in the liquid polymer and they are placed
in such a way that they are going to be in contact with the sensor electrodes: this will make
measurements way easier because wires are very thin and they can assure a good surface of
contact. To improve wires performances reducing electromagnetic oscillation it is necessary to
53
perform a soldering process thanks to a WES50 soldering station by WELLER. Once the other
end of the wires is tighten to the probes, measurements can be taken.
54
2.3 Electronic Devices
As the bubble oscillates transversely, frictional forces are present at the interface between
the bubble membrane and the liquid and acoustic microstreaming is generated. To obtain
oscillation of the membrane (air-liquid inteface) it is necessary to produce an acoustic wave in
the proximity of bubbles and this can be done thanks to a piezoelectric transducer. In this work
a piezoelectric transducer which generates low intensity acoustic waves is located on the bottom
of the dish where the device is placed, and it is turned on and off by a function generator.
The device used is a DG1022A Arbitrary Waveform Function Generator by RIGOL which
allows the generation of square waves with maximum frequency 5MHz, but it has a maximum
Vpk−pk of 20 V. As it will be shown later, this voltage is quite low and the streaming generated
will be rather weak: so a 7602(M) Wideband Power Amplifier was purchased by Krohn-Hite
Corporation. The power amplifier is able to increase the voltage up to 200 Vpk−pk and once
connected to the piezo, this will generate a stronger acoustic waves.
The device used to collect data from the sensor is a 2701 Digital Multi-Meter (DMM) by
Keithley that has a very small sampling period (∼ 0.004 s) and can record continuously the
value of the resistance. It is connected to a laptop for data acquisition.
A final and equally important device used in this work was an Eclipse Ti-E inverted micro-
scope from Nikon which is useful to initially visualize microstreaming once fluid is poured on
the drilled PMMA plate: a Phanton Miro 310 High-Speed camera by Vision Research is used
later to take pictures and videos of the experiments.
55
2.4 Final Setup
Summarizing what was explained in the last chapter, the experiment is carried out pouring
liquid in a 3D printed box which is fixed in a PDMS cover which is located inside a dish. The
box accommodates four PMMA plates and bubbles are trapped in the cavities drilled in those
plates according to the mechanism described in subsection 2.2.1. The box containing walls is
placed above a sensor: graphene is used as sensing material and it is connected to two silver
electrodes on which two wires are collocated. Those wires are fixed between the sensor and the
PDMS cover and they are connected to a DMM. This device analyzes the values of the sensor
resistance that varies when liquid is poured: data from DMM are stored in a laptop thanks to
Kickstart software.
With this setup the first part of the experiment (sensor calibration) is carried out and it
will be possible to know the pH of a solution according to resistance value. By the way, this
measurement requires rather long times (> 5 min): sensing period reduction happens when
microstreaming is generated by bubbles oscillation. Actuation occurs when a sound field is
generated, in particular when a piezo placed under the dish containing the 3D printed box is
turned on. Piezo has to be connected to a function generator, which produces square waves
with the desired frequency. In this work connection happens through a power amplifier which
guarantees an higher voltage output level, that means greater amplitude of sound waves.
56
Figure 27: Piezo located in the proximity of the sensor can generate a sound field when anelectric signal is generated by the function generator and increased by the power amplifier.Laptop can store data collected by DMM which is connected to the sensor.
CHAPTER 3
RESULTS
In this section all the results of experiments are shown and commented. The first tests
regard the investigation of the natural frequency for the bubbles trapped in cavities. These
experiments are carried out varying the frequency of the function generator and analyzing the
movement of particles on the drilled plate placed underneath the microscope. When the particle
velocity is significantly increased (strong microstreaming), it means that natural frequency of
bubbles have been reached.
Once that drilled plates have been tested, it is possible to place them into the box and
start measurements on the graphene sensor. In particular, after having found the resistance
saturation value for each pH buffer tested (from 4 to 10), other tests are carried out when
bubbles are actuated. Time reduction in sensing period is proved for each of these pH values
even though the percentage of time reduction is different for each buffer.
Eventually, effects of frequency and voltage are tested by simply comparing the different
sensing period after moving from the natural frequency or decreasing the magnification of the
signal by the power amplifier.
57
58
3.1 Natural Frequency
Previous works showed that bubble oscillation is great (i.e. microstreaming is strong) only
if they are actuated close to the resonance frequency. Its dependence on bubbles size and the
liquid properties has been studied, and it has the value of
2πaf =√
3γP0/ρ (3.1)
In this study natural frequency is expected to be around 80 kHz but since the device
was fabricated directly in our laboratory, natural frequency research has been directly carried
out looking for particles streaming using microscope. Effects on streaming are visualized by
manually changing the frequency of the function generator with steps of 100 Hz in the range
1000 to 100000 Hz. In particular, one of the transparent PMMA plate is laid out horizontally
on a slide underneath the microscope (cavities axis normal to the glass surface and parallel
to microscope lens axis). Three solutions containing grey DUKE particles (1, 5 and 10 µm)
are prepared and poured on the drilled PMMA. A piezo is placed on the edge of the glass in
order to generate an acoustic field (source as close as possible to bubbles). Once it happened,
it is possible to visualize particles streaming thanks to the high speed camera: in particular,
for most of the frequency values no streaming is observed and particles moves just because of
diffusion with a very low speed. Varying the frequency, particle velocity increases remarkably
and it appears to be maximum at 23500 Hz. As shown in literature, particles are attracted by
bubbles (that can be seen from the top, since the transparent PMMA plate is placed horizontal)
59
and then follow a path as the one cited in section 1.3.5. As mentioned by Spengler et al. [89],
particles speed not only depends on bubble oscillation but even on particles size: in fact,
it cannot be thoroughly excluded that particle-particle interactions and gathering someway
happens. Repeating experiments it is observed that for more than one frequency values the
streaming is particularly intense, but only at 23500 Hz it is very strong for all the particles
dimension. In the range of 80 kHz, that is the frequency calculated with the conventional
formula, bubbles were observed to have a great oscillation which caused them to collapse very
quickly, without the possibility to generate a visible streaming.
The next step is to assure that this streaming happens even when plates are placed in their
final configuration, i.e. with cavities axis normal to the ground. To do that, the four PMMA
plates are fixed inside the box that is placed on the slide: box is not yet located on the sensor,
but on the transparent glass just to visualize the streaming. The final setup is to be tested
in order to check microstreaming inside the box, in particular in its center, the farthest point
from the walls. Moving the microscope objective it is possible to visualize a turbulent particle
movement all around the box edges once the function generator is turned on: this flow is less
intense in the middle of the box (1 mm far from bubbles), but results will show that this design
still assures a time reduction in the sensing period.
3.2 Sensor Calibration
The first experiment carried out actually using the sensor is its calibration: it is necessary
to look for the resistance final value for every pH buffer. Previous studies showed an increasing
trend for the resistance up to a saturation value (shape similar to a monotonic crescent function
60
TABLE VI: RESISTANCE SATURATION VALUES
pH R (Ω)
4 37000
5 34250
6 30550
7 27700
8 26750
9 23850
10 21800
with horizontal asymptote). Moreover, it is known how for an increasing value of pH, the
resistance saturation value is decreasing: by the way, the exact resistance depends on which
sensor is used, since there is no possibility to obtain the same configuration of the graphene
layers in different sensors.
Once one of them is picked, tests are made first without the microbubbles oscillation in
order to find the saturation value of the resistance and the sensing time for each buffer: graph
Figure 28 show how saturation is reached and tables summarized the different times.
Data recorded in Table VI are important for sensor calibration: once microbubbles are
activated it is necessary to know which is the final resistance value to be reached.
At this point the decreasing trend of the resistance is showed and as Lei et al. did [36], a
linear relationship ph-R has been found and the results are shown in Figure 29; the relative
equation is:
61
Figure 28: Sensing times and Resistance saturarion values for all the pH buffers tested.
R = −2508× pH + 46405 (3.2)
3.3 Sensing Period Reduction
In this section, effects of microstreaming will be quantified observing the time reduction in
sensing period: it will be shown how diffusion limits can be overcome when bubbles actuation
62
4 5 6 7 8 9 1 02 , 0 E + 0 4
2 , 5 E + 0 4
3 , 0 E + 0 4
3 , 5 E + 0 4
4 , 0 E + 0 4
R (
)
p H
Figure 29: Resistance saturation values as a function of pH.
occurs. For each value of pH, sensing time is analyzed when bubble are activated: since
calibration tests are already taken, it is just necessary to wait the resistance to reach the
known value. In the next graphs (Figure 30(a) - (f)) the two situations are compared.
Analyzing the results obtained in Table VII, it can be seen that not only the shape of the
resistance as a function of time is confirmed but even that time reduction in sensing period is
great for all the pH buffers.
Some of the graphs present a small signal oscillation that can be attributed to poor electrodes-
wires contacts or external electromagnetic signals: that can be deduced by the fact that oscilla-
tions are on average grater when the function generator is turned on and the piezo is generating
acoustic waves.
63
TABLE VII: SENSING TIMES WITH AND WITHOUT BUBBLES ACTUATION
pH Sensing time (s) Sensing time - Bubbles actuation (s)
4 780 35
5 760 45
6 740 35
7 475 35
8 490 50
9 270 70
10 460 55
3.3.1 Effects of Frequency
All the experiment showed in the previous section are carried out producing an acoustic wave
at bubbles resonance frequency: moving farther from this value (23500 Hz) the microstreaming
is supposed to be weaker and weaker and no time reduction in the sensing period is expected
eventually. Some other frequency values are tested and sensing times are evaluated for each
of them: resistance as function of time is showed in Figure 31. All the tests are carried out
using just pH 4 buffer solution. Once again the curve shape is confirmed and sensing periods
are reported in Table VIII.
These tests are carried out to obtain the resonance curve for the device where percentage of
time reduction (with the respect of the non-activated bubbles condition, in which sensing time
is considered to be 890 s in these set of experiments) is plotted as a function of frequency. This
percentage is calculated comparing sensing time in the actuated condition with the respect to
64
TABLE VIII: EFFECTS OF FREQUENCY
f (kHz) Sensing time (s) Efficiency (%)
8.5 885 ∼ 0
13.5 855 3.6
19.5 90 89.8
22.5 50 94.6
23.5 35 96.2
24.5 45 95.0
27.5 75 91.7
33.5 880 ∼ 0
38.5 885 ∼ 0
the normal one as:
Efficiency (%) = 100− Sensing time with bubbles actuation
Sensing time without bubbles actuation× 100 (3.3)
In literature it was observed that streaming is strong only if close to natural frequency, so the
peak in Figure 32 should be very sharp. Nevertheless, in these tests an important diminishing
in sensing period is shown even for frequencies not very close to the resonance one (± 1000 Hz);
it will obviously less important or not present for farther values. After these considerations,
quality factor is calculated as:
Q =fr∆f
(3.4)
65
fr is the resonance frequency, ∆f is defined as the full width at 1/√2 maximum; this means
that is the bandwidth over which percentage of time reduction is greater than half the time
reduction at resonant frequency. Q factor is a measure of quality of a particular resonance.
In this work quality factor has a relevant importance because resonance frequency was found
moving through a wide range, and it was necessary to estimate a bandwidth where expected
results are obtained.
3.3.2 Effects of Voltage
In this section, effects of microstreaming on sensing period are analyzed using different
driving voltages: in particular, even if frequency appears to be the most important parameter
in bubble oscillation, Chen et al. showed [90] that amplitude of acoustic wave (that means
peak-to-peak voltage of the electric signal) can affect micromixing in their device: in other
words, mixing efficiency was directly proportional to the voltage. In this work, signal was
increased by the power amplifier up to 120 V: this value was chosen because higher ones could
have been dangerous. Limiting the voltage magnification, sensing period should increase but
it is expected that working at natural frequency there will still be a significant time reduction,
meaning that changing voltage values is less relevant that changing frequency.
All the tests are carried out using just pH 4 buffer solution. As it is shown in Figure 33,
values of resistance are different from the one taken in previous experiments, since another
sensor is used: this is done both to check if sensors were working in the same way and to have
a proof for repeatability.
66
TABLE IX: EFFECTS OF VOLTAGE
Vpk−pk (V) Sensing time (s) Efficiency (%)
30 135 85.0
60 90 89.6
90 55 93.7
120 35 96.2
From data collected in Table IX, it is possible to state that decreasing voltage will increase
the sensing period, but its reduction will still be important even for low V if bubbles actuation
happens at resonance frequency.
67
0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 6 0 0 7 0 0 8 0 01 , 5 E + 0 4
2 , 0 E + 0 4
2 , 5 E + 0 4
3 , 0 E + 0 4
3 , 5 E + 0 4
4 , 0 E + 0 4
0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 6 0 0 7 0 0 8 0 01 , 5 E + 0 4
2 , 0 E + 0 4
2 , 5 E + 0 4
3 , 0 E + 0 4
3 , 5 E + 0 4
4 , 0 E + 0 4
B u b b l e s A c t u a t i o n
R (Ω
)
t ( s )
N o r m a l O p e r a t i n g C o n d i t i o n s
(a) pH 4
0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 6 0 0 7 0 0 8 0 0
2 , 0 E + 0 4
2 , 5 E + 0 4
3 , 0 E + 0 4
3 , 5 E + 0 4
0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 6 0 0 7 0 0 8 0 0
2 , 0 E + 0 4
2 , 5 E + 0 4
3 , 0 E + 0 4
3 , 5 E + 0 4
R (Ω
)
t ( s )
R (Ω
)
t ( s )(b) pH 5
68
0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 6 0 0 7 0 0 8 0 0
1 , 0 E + 0 4
1 , 5 E + 0 4
2 , 0 E + 0 4
2 , 5 E + 0 4
3 , 0 E + 0 4
0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 6 0 0 7 0 0 8 0 0
1 , 0 E + 0 4
1 , 5 E + 0 4
2 , 0 E + 0 4
2 , 5 E + 0 4
3 , 0 E + 0 4
R (Ω
)
t ( s )(c) pH 6
0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 05 , 0 E + 0 3
1 , 0 E + 0 4
1 , 5 E + 0 4
2 , 0 E + 0 4
2 , 5 E + 0 4
3 , 0 E + 0 4
0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 05 , 0 E + 0 3
1 , 0 E + 0 4
1 , 5 E + 0 4
2 , 0 E + 0 4
2 , 5 E + 0 4
3 , 0 E + 0 4
R (Ω
)
t ( s )(d) pH 7
69
0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0
1 , 0 E + 0 4
1 , 5 E + 0 4
2 , 0 E + 0 4
2 , 5 E + 0 4
3 , 0 E + 0 4
0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0
1 , 0 E + 0 4
1 , 5 E + 0 4
2 , 0 E + 0 4
2 , 5 E + 0 4
3 , 0 E + 0 4
R (Ω
)
t ( s )(e) pH 8
0 5 0 1 0 0 1 5 0 2 0 0 2 5 0 3 0 0
1 , 0 E + 0 4
1 , 5 E + 0 4
2 , 0 E + 0 4
2 , 5 E + 0 4
0 5 0 1 0 0 1 5 0 2 0 0 2 5 0 3 0 0
1 , 0 E + 0 4
1 , 5 E + 0 4
2 , 0 E + 0 4
2 , 5 E + 0 4
R (Ω
)
t ( s )
R (Ω
)
t ( s )(f) pH 9
70
0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0
5 , 0 E + 0 3
1 , 0 E + 0 4
1 , 5 E + 0 4
2 , 0 E + 0 4
0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0
5 , 0 E + 0 3
1 , 0 E + 0 4
1 , 5 E + 0 4
2 , 0 E + 0 4
R (Ω
)
t ( s )
R (Ω
)
t ( s )(g) pH 10
Figure 30: Analysis on sensing periods for each pH value from 4 to 10 ((a) to (g)): in black,Resistance as a function of time in the unmodified contidion; in red, Resistance as a functionof time once microbubbles are actuated.
71
0 2 0 0 4 0 0 6 0 0 8 0 0
2 , 0 E + 0 4
2 , 5 E + 0 4
3 , 0 E + 0 4
3 , 5 E + 0 4
R (Ω
)
t ( s )
1 3 5 0 0 H z
0 2 0 0 4 0 0 6 0 0 8 0 0
2 , 0 E + 0 4
2 , 5 E + 0 4
3 , 0 E + 0 4
3 , 5 E + 0 4
R (Ω
)
t ( s )
1 9 5 0 0 H z
0 2 0 0 4 0 0 6 0 0 8 0 0
2 , 0 E + 0 4
2 , 5 E + 0 4
3 , 0 E + 0 4
3 , 5 E + 0 4
R (Ω
)
t ( s )
2 2 5 0 0 H z
0 2 0 0 4 0 0 6 0 0 8 0 0
2 , 0 E + 0 4
2 , 5 E + 0 4
3 , 0 E + 0 4
3 , 5 E + 0 4R (
Ω)
t ( s )
2 3 5 0 0 H z
0 2 0 0 4 0 0 6 0 0 8 0 0
2 , 0 E + 0 4
2 , 5 E + 0 4
3 , 0 E + 0 4
3 , 5 E + 0 4
R (Ω
)
t ( s )
2 4 5 0 0 H z
0 2 0 0 4 0 0 6 0 0 8 0 0
2 , 0 E + 0 4
2 , 5 E + 0 4
3 , 0 E + 0 4
3 , 5 E + 0 4
R (Ω
)
t ( s )
2 7 5 0 0 H z
0 2 0 0 4 0 0 6 0 0 8 0 0
1 , 5 E + 0 4
2 , 0 E + 0 4
2 , 5 E + 0 4
3 , 0 E + 0 4
3 , 5 E + 0 4
R (Ω
)
t ( s )
3 3 5 0 0 H z
Figure 31: Resistance as a function of time for different frequency values
72
0 5 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 50
2 0
4 0
6 0
8 0
1 0 0
0 5 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 50
2 0
4 0
6 0
8 0
1 0 0
Efficie
ncy (
%)
f ( k H z )
Figure 32: Efficiency as a function of frequency. ∆f in dash in order to have a visual estimationof the quality factor Q.
73
0 2 0 4 0 6 0 8 0 1 0 0 1 2 0 1 4 03 E + 0 44 E + 0 45 E + 0 46 E + 0 47 E + 0 48 E + 0 49 E + 0 41 E + 0 5
0 2 0 4 0 6 0 8 0 1 0 0 1 2 0 1 4 03 E + 0 44 E + 0 45 E + 0 46 E + 0 47 E + 0 48 E + 0 49 E + 0 41 E + 0 5
0 2 0 4 0 6 0 8 0 1 0 0 1 2 0 1 4 03 E + 0 44 E + 0 45 E + 0 46 E + 0 47 E + 0 48 E + 0 49 E + 0 41 E + 0 5
R (Ω
)
t ( s )
3 0 V
R (Ω
)
t ( s )
6 0 V
R (Ω
)
t ( s )
9 0 V
Figure 33: Effects of Voltage on time reduction: sesning times decrease with increasing ampli-tude of voltage signal.
CHAPTER 4
CONCLUSION
The aim of this work was to demonstrate that performances of a surface-based graphene
nanosensor can be improved once that diffusion limits have been overcome. Even if graphene
is considered one of the best sensing materials available, detection can be rather slow when
target species have to move across the whole fluid sample. An additional microstreaming can
accelerate target movement toward graphene surface, eventually causing a reduction in sensing
time. This external streaming is created by oscillation of bubbles trapped in cavities which will
vibrate once an acoustic wave at a certain frequency is generated.
Since graphene is a relatively new sensing material, studies have been carried out on its
properties and sensing characteristics; contemporaneously, other research on oscillating bubbles
were performed to understand if they could actually improve sensor performances.
Results show that sensing time is drastically decreased when micro-streaming is added in the
fluid sample. This reduction means that target species (OH− or H3O+ ions in this experiment)
move toward graphene surface not only because of diffusion mechanisms, but they are carried by
an intense flow generated by the oscillation of bubbles. It is later assumed that time reduction
is only due to microstreaming, and graphene adsorbing mechanisms are the same in the two
conditions.
74
75
It is shown that time reduction is maximum when bubbles are actuated by an acoustic
wave with great amplitude and which has their resonant frequency. When these parameters are
changed, micro-streaming is less and less strong, and the designed device becomes inefficient.
76
4.1 Future Applications and New Designs
Now that it has been demonstrated that it is possible to overcome diffusion limits and reduce
the sensing period, this new technique can be applied to every kind of nano-scaled sensors; in
fact, as long as the quantity of fluid is small enough, oscillating bubbles can create a strong
microstreaming which accelerates target species movement.
This concept can be useful in a lot of biochemical applications: sensor performances can
be improved in detection of big targets such as glucose, DNA, cancer markers, proteins and
big cells. In fact, diffusion is a very slow phenomenon especially for big targets, and cavitation
microstreaming could be efficient in many applications. The possibility of remote actuation
makes acoustic streaming applicable in a high number of situations. As long as it is possible
to place a apparatus with cavities over a sensor and pour liquid in it, bubble actuation will
decrease sensing time in considered devices.
Moreover, now that the reliability and efficiency of this new concept have been demonstrated,
it is possible to improve it. For instance, if the quantity of fluid to be analyzed is known a
priori, it would be appropriate to design a device with the proper capacity in order to avoid
oversize tools. There is another improvement that regards the apparatus shape: a rectangular-
plan box is used to allocate PMMA drilled plates in this work; a better option consists in a
device with a hollow cylinder in the middle. In this configuration cavities would be present all
around the cylindrical internal surface (Figure 34). In order to build this kind of apparatus it
is necessary to use another building technique (such as lithography). This new device would
have the following advantages:
77
• Radial symmetry allows uniform streaming in the fluid sample;
• Cylindrical chamber guarantees absence of corners where turbulent vortexes where fluid
is stuck;
• Lithography allows creation of small undercuts, making cavities and bubbles trapped
inside them smaller, which is translated in stronger streaming.
If performances of this new device will be confirmed, a time reduction of ∼ 96 % in a
sensing test could lead to enormous advantages in the biomedical field: in fact, in this work pH
sensing has been improved even if the original time needed to obtain the measurement was not
excessively long (some minutes). For some particularly big proteins diffusion coefficient can be
of the order of some µm2/s: in the above shown design, it could take up to 7 hours for the
target specie to reach the surface of the sensor (in the limit case of just one detected element
in the solution). Introduction of oscillating bubbles can potentially decrease this time to 15
minutes, contributing to a significant cost and time reduction.
78
Figure 34: Alternative Design: ring with multiple cavities to be built with nanoscribe 3D printer
APPENDICES
79
80
Appendix A
TECHNICAL DRAWINGS
Figure 35: PMMA plate Type A: Technical drawing
81
Appendix A (continued)
Figure 36: PMMA plate Type B: Technical drawing
82
Appendix A (continued)
Figure 37: Box: Technical drawing
83
Appendix B
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VITA
NAME Andrea De Vellis
EDUCATION
Master of Science in Mechanical Engineering, University of Illinois atChicago, May 2016, USA
Specialization Degree in Mechanical Engineering , Jul 2016, Polytechnicof Turin, Italy
Bachelor’s Degree in Mechanical Engineering
Oct 2014, Polytechnic of Turin, Italy
LANGUAGE SKILLS
Italian Native speaker
English Full working proficiency
2014 - IELTS examination (7.0/9)
A.Y. 2015/16 One Year of study abroad in Chicago, Illinois
A.Y. 2014/15. Lessons and exams attended exclusively in English
Spanish Fluent
2010 - DELE examination (B1)
SCHOLARSHIPS
Spring 2016 Italian scholarship for final project (thesis) at UIC
Fall 2015 Italian scholarship for TOP-UIC students
105
