Transcript
Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in vitro
Master Thesis presented to the
Department of Microelectronics at the
Technische Universiteit Delft
In partial fulfillment of the requirements to obtain the degree of
Master of Biomedical Engineering (M.Sc.)
Director: Dr. Ronald Dekker Supervisor: Dr. Chris van Heesch
Submitted in June 8th , 2015 by:
Armando Galicia Naranjo Student Number: 4262484
Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
Table of contents 1 Introduction ........................................................................................................................................................ 2 1.1 Acoustic transduction in microfluidics ................................................................................. 2 1.2 Capacitive Micro machined Ultrasonic Transducers (CMUTs) ................................... 3 1.3 Acoustic streaming ........................................................................................................................ 4 1.4 Engineering microenvironments for living tissue: The Liver...................................... 5 2. Methodology ...................................................................................................................................................... 8 2.1 Experimental Setup....................................................................................................................... 8 2.1.1 Electronic System ....................................................................................................... 8 2.1.2 Acoustic Cell ................................................................................................................ 11 2.1.3 Camera setup & visualization .............................................................................. 12 2.2 Functionalities............................................................................................................................... 12 2.2.1 Particle trapping ....................................................................................................... 12 2.2.2 Mixing ............................................................................................................................ 13 2.2.3 Gradient generator. .................................................................................................. 14 3. Results ................................................................................................................................................................ 17 3.1 Pattern formation ........................................................................................................................ 19 3.2 Mixing, and dragging .................................................................................................................. 20 3.3 Concentration gradients ........................................................................................................... 21 4. Discussion ......................................................................................................................................................... 23 5. Conclusions ....................................................................................................................................................... 24 6. Acknowledgements ....................................................................................................................................... 25 7. References ......................................................................................................................................................... 26
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Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
1 Introduction
The goals of this graduation project are to introduce and prove the concept of an Acoustically Induced Microenvironment (AIM), and feature the application of Capacitive Micro machined Ultrasonic Transducers (CMUTs) in microfluidics. The practical approach for this work consists on implementing CMUTs to generate Acoustic Streaming and Standing Waves. The reach of these effects is assayed and discussed towards the development of building blocks that perform basic operations for microfluidics. The physical arrangement of the CMUTs in this project entails linear arrays of individual CMUTs. Moreover the transducers were integrated with a series of microfluidic elements (Acoustic Cells) to operate over the frequency range from 3 to 10 MHz For this project biological samples were not used. However some analogous properties are discussed over solid particles of a suspension in such a way that a given microenvironment considers features that are found in actual living tissue, e.g. the lobular structure of the liver. The functionalities to be explored using the linear array are: stirring, particle trapping, mixing and gradient formation. AIMs are conceived as a series of building blocks for more complex systems where the driving technology is reconfigurable without major hardware changes and easily embedded with current CMOS and Microfluidic technologies. In the biological context, the development of organ models such as a Liver on a Chip for Drug Screening is a leading example.
1.1 Acoustic transduction in microfluidics
The field of microfluidics deals with the study and manipulation of fluids at the micro scale.2 Therefore this field has been greatly influenced with the technologies that have driven the microelectronic industry. For instance lithography can be used to develop structures at the micro scale which can be used to host, circulate and manipulate small volumes of fluid. Given the scale of most microfluidic constructs compared to the wavelength, the study and implementation of acoustic elements is limited to the spectrum of ultrasound (in the order of MHz)2. A diversity of applications have been studied and implemented for several aims.2,5 Acoustic transduction is the transformation of certain types of energy from or towards mechanical motion occurring over certain frequencies in the sonic domain. Depending on the frequency, the sonic domain can be divided into the infrasound (f < 40 Hz), audio (40 Hz < f < 20 kHz) and ultrasound (f > 20 kHz)1. Sonic frequencies are denoted here as the vibration within a certain medium that can be represented by pressure waves. Transduction from electromechanical interactions is a starting point for the practical generation and detection of Ultrasonic Pressure Waves (UPW). To this end, applications can be implemented with piezoelectric or electrostatic transducers in microfluidics.9 2
Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
In addition to the classical8-11, 16-19 electro-mechanical references for ultrasound in microfluidics, interactions from and towards other domains of energy create conditions for useful technology. To illustrate these interactions, three categories are introduced: mechanic-acoustic, chemical-acoustic, and thermal-acoustic. Mechanic-acoustic interactions are those where the effects on fluid dynamics due to ultrasound lead to the implementation of functions such as the following: Noninvasive assembling of microstructures, streaming, particle trapping, particle sorting, and blending3. Surface Acoust Wave (SAW) transducers are commonly used for this means3,4,5. Chemical-acoustic interactions have been practical for sensors that are based on mass resonators5,7. For example, a CMUT device was reported7 to perform as a resonant mass sensor. This is achieved by coating (functionalizing) the capacitive membrane with a chemically selective polymer. The sensor was able to detect DMMP, with a detection limit of 56 ppb (3sigma). Thermal-acoustic interactions have led to the implementation of micro heating, and conversely as thermal sensing. The underlying principle of heating is based on absorption of ultrasound. Temperature measurements are determined by measuring a shift in speed of sound.6 An ultrasonic micro heater is reported in6, this device integrates Piezoelectric elements (400 MHz) and Biomedical (1-5 MHz) CMUT transducers, with micro channels. CMUT’s were placed inside the channel as they are not very efficient to couple ultrasound through the substrate. The devices are used to heat up liquids within the micro channel and also to measure the temperature by acoustic Time Of Flight (TOF). The measurement error is reported to be 0.1 °C 6. Only ZnO transducers were used for heating & measuring, CMUT’s are used only to measure. The method is reported to be insensitive to the temperature on the substrate.
1.2 Capacitive Micro machined Ultrasonic Transducers (CMUTs)
A Capacitive Micromachined Ultrasonic Transducer (CMUT) is a technology driven by the vibration of a thin membrane of a biased micro machined capacitor (Figure 1.1). It’s has advantages over piezoelectric elements. Contrary to the SAW transducers, there is for instance the flexibility of designing devices for specific frequencies keeping a wide bandwidth5, and the fact that CMUTs are CMOS compatible. These features make these devices very practical for IC integration5. In terms of acoustics, CMUTs are advantageous for the small impedance of the thin membrane that vibrates to generate or detect ultrasonic waves. Therefore integrating additional matching layers is not needed5. Additionally, the bandwidth of such material is significantly higher; therefore a wider range of frequencies can be employed over a surface that may be locally addressed5.
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Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
Figure 1.1- CMUT crossectional view, a basic configuration is depicted with its constitutive layers. Taken from Khuri Yakub Ultrasonics Group21.
1.3 Acoustic streaming
Acoustic streaming is defined as the implementation of a sustained flow within a fluid body after an acoustic wave has been propagated8,16. Three types of acoustic streaming are considered and reviewed. Although all of them are driven by viscous dissipation of mechanical energy through a medium and/or boundaries, specific features can be differentiated. Therefore each gives room to implement different applications3. The first type is the Inner and outer boundary layer acoustic streaming3: Namely boundary layer driven acoustic streaming. It’s produced due to viscous dissipation of acoustic energy into the boundary layer of a fluid. The effect takes place along any solid boundary in the direction of acoustic propagation; the length must be comparable or greater than a quarter of the acoustic wavelength. (λ>>h>>δv). Secondly the Eckart streaming, also known as quartz wind, happens due to viscous dissipation of the acoustic energy into the bulk of a fluid body3. A model for this phenomenon can be built upon the Stokes’ law of sound attenuation. It states that the amplitude of a plane wave decreases exponentially to a given travelled distance. The rate α at which it happens is given by the equation 1.1. In the equation η is the dynamic viscosity coefficient of the fluid, ω is the sound's frequency, ρ is the fluid density, and V is the speed of sound in the medium.
α
(1.1)
The wave’s energy is generally absorbed at rate that is generally proportional to the square of its frequency; therefore a fluid jet is ensued as the result of a sustained momentum flux. When this is applied to a confined body, vortices often follow.
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Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
Finally a third type of streaming is the Cavitation micro streaming.3,17,18 It occurs after a bubble is stably resonated thereof micro streaming is driven by viscous dissipation on its boundary layer. When it’s done on the vicinity of its resonance frequency, the first order velocity gets locally amplified. Therefore it differs from other forms of boundary driven layer streaming. 1.4 Engineering microenvironments for living tissue: The Liver
The liver has many metabolic and regulatory roles in human physiology. Its function in the digestive system is the production of bile that breaks down fats in order to make them more digestible. In addition, the liver also exerts major metabolic roles on the assimilation of drug compounds. Despite the amount of research conducted by the pharmaceutical industry, many drugs have still to be withdrawn from the market due to side effects that couldn´t be predicted during pre-marketing testing. Hepatotoxicity is one of those effects, causing the liver to shut down in the most severe cases. Having the technology to predict the effects of new drug candidates is a continuous work at a multidisciplinary arena. Thereby disciplines such as molecular biology, pharmacology, and microtechnology converge with a common goal: gain valuable knowledge to implement adequate disease and organ models. Drug assessments in-vivo (with either animal or human subjects), ex vivo, or in vitro models are done at different stages for market safety approval. Whereas living subjects have the disadvantage of offering a limited set of screening data, in vitro tests can be performed in high batches that yield a good volume of data. Drug screening in vitro is performed with cell cultures. Cultured liver cells degrade relatively fast. Therefore emulating a comparable concentration of soluble factors plays an important role as chemical gradients are well documented to be quite unique within liver tissue. Three metabolic areas are particularly differentiated which are the result of different diffusion distances (Figure 1.2) from the portal tract and the central vein. A semi-circular profile is formed from the richest region of oxygen and hormones.
Central vein
Portal triad
Figure 1.2- This crossectional diagram illustrates the structure of a liver lobule22. The green area is the richest on oxygen and soluble nutrients.
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Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
Metabolic zonation in the liver is controlled by a distribution of enzymes responsible for different types of metabolism. A recent study analyzing RNA of pericentral and periportal hepatocytes confirmed the long-standing hypothesis that the zonation of glucose, ammonia, and drug metabolism is correlated with RNA transcription. These distinct RNA leading to the emergence of either a periportal or a pericentral hepatocyte can be dictated by different mechanisms, being the presence of the aforementioned one of them.
Figure 1.3 – Microscopic Anatomy of the liver24.
Means to replicate the complex microfluidic environment of liver cells and its physicochemical properties is of prime importance in order to perform more accurate and conclusive drug assays as they will depend on how close the transcription routes are to actual cell phenotypes. The gradient of concentration of biomolecules that occurs in the liver units has been mimicked by means of microfluidic constructs. On such devices gradient properties can be adjusted. For instance, a device described in22 consists of a PDMS structure that was patterned by means of soft lithography. PDMS is a commonly used material due to its biocompatibility, optical clarity, and easy to manufacture process.
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Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
Cell to cell contact is also of prime importance for achieving correct cytokine signals (relevant cell differentiation). Thereby an appropriate phenotype and good cell survival has to be sustained for a reliable assessment of a new drug metabolism. Cell survival has been found to be affected by the shear stress caused by a continuous flow that is often used to modulate a concentration gradient22. Computational Fluid Dynamics (CFD) CFD is commonly performed in microfluidics as it helps to predict relevant flow22properties. Staining can be used to verify cell survival, thus it is possible to do mapping of the shear stress experienced by cells. In Ref 22 a test showed that viable cells grow denser in low shear stress regions than in areas with high shear stress.
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Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
2. Methodology In this chapter, the experimental design for this research project and its parts are listed and explained. In consequence insight about the methods and experimentation is thereby provided for the reader. The methods herein presented were performed to gain insight on the ultrasonic techniques for the creation and control of sub-millimeter environments within an aqueous medium. In addition these experiments seek to deliver a proof of concept for the building blocks that are proposed in this work. 2.1 Experimental Setup An experimental setup was prepared to perform a series of experiments with the objective of generating data upon the interactions between acoustic waves and solid particles that are suspended in a medium. This setup is divided in three parts: An Electronic System, a coupled Acoustic Cell, and an Image Acquisition set. 2.1.1 Electronic System The electronic system was designed and assembled with the objective of generating ultrasonic waves onto a CMUT array by means of an electrical signal. The system consists of four components: a generic electronic board, an exchangeable board containing a CMUT array on chip, function generators, and a DC biasing module (Figure 2.1). The generic electronic board (Figure 2.2 top) was prepared in such a way it connected an exchangeable board containing a CMUT chip to a series of SMB jacks. These jacks are thereafter connected to the signals that the CMUTs require to vibrate. This board is also a sufficiently stable mechanical element to anchor the several elements that compose the electronic system to a fixed position relative to the Image Acquisition set (Figure 2.3c). An electronic chip was wire bonded to each of the exchangeable boards in such a way it yields an array of 8 addressable elements, each element is a linear row of 80 ultrasonic transducers. In this way, the addressable rows were physically wired to be driven by a 4 channel function generator. Two exchangeable boards were made available (Figure 2.2), they differ on the way they were adapted to host one of the available Acoustics Cells that were implemented for this research (See 2.1.2). The CMUTs are biased on a DC level by the DC coupling module. This means that next to the AC signals provided by the function generators, a DC voltage needs to be added. This voltage is typically 90V for this family of CMUTs. The electronic device used is also depicted in Figure 2.3c, together with the DC power supply. The frequency range used in these experiments and at which the CMUTs operate is between 3 MHz up to 10 MHz.
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Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
This electronic system is therefore capable of driving 4 independent rows of adjacent CMUTs which cover a total area of 4mm2.
Function Generators 10VAC-20VAC 1-10 MHz 4 Ch DC coupling module DC Power Source 90-100 VDC
+
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4 Ch Generic Electronic Board Up to 8 addressable Channels Exchangeable board CMUT array on chip
Ultrasound
Figure 2.1. Electronic System
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Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
Figure 2.2. TOP: Wire bonding for the exchangeable CMUT board with the function generator and DC bias voltage. BOTTOM: Exchangeable boards containing the CMUT arrays.
b
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c Figure 2.3. Full electronic setup. (a) Function Generators, (b) DC coupling block, (c) Generic board & exchangeable board are set within a camera’s field of vision.
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Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
2.1.2 Acoustic Cell An acoustic cell is an assembly that allows the interaction between ultrasonic transducers, and an aqueous sample that is contained in a confined space. For the purposes of this work, the aqueous sample is constituted by a suspension of solid particles within a water-soap recipe. The aqueous sample is hereafter referred as medium. Three types of acoustic cell were implemented; they can be classified according to an exclusive type of interphase they hold between the acoustic speakers and the medium: Transducer-Medium, Glass-Medium, and PDMS-Medium. Transducer-medium: This acoustic cell hosts the medium directly on top of the ultrasonic transducers; a cross section is depicted in Figure 2.4a. Confinement is achieved by placing a 100um thick glass plate on top of the medium. Glass-medium: A glass that hosts the medium is acoustically coupled to the CMUTs with commercial ultrasonic gel. Confinement is conferred by placing a 100um thick glass plate on top of the medium. It creates a sandwich like structure whose crosssection is depicted in Figure 2.4b. The separation between the pair of glasses is approximately 1mm. PDMS-medium: A PDMS plate is coupled on top of the CMUT surface. Commercial gel is used to acoustically couple this plate (Figure 2.4c). Confinement of the medium is achieved in the normal direction by placing a 100um thick glass and in the radial direction by the features given during the process of PDMS casting and patterning. A depiction of the different pattern templates that were used are offered in Figure 2.5. For details on these templates, refer to Appendix A (Design).
x,y,z z z
PCB
CMUT array
Medium
Glass
Ultrasonic Gel
PDMS
Figure 2.4. Acoustic cells. (a) Transducer-medium: There is direct contact between the CMUTs and the medium that is confined with a glass that is on top. (b) GlassMedium: The medium is confined between two glass plates. (c) The medium is confined inside the features of a casted PDMS plate.
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Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
2.1.3 Camera setup & visualization In order to gather data and analyze the behavior of the medium after ultrasonic excitation, an image acquisition system was adapted. This system comprises a camera that is embedded to a 10x microscope (Figure 2.3c), a personal computer, and image acquisition software. The camera, along with the software that is provided by the manufacturer, allows capturing images on a maximum rate of 20 frames per second. On each experiment the assembly between one of the acoustic cells and the electronic system is anchored in such a way that the top view of the CMUTs fall within the camera’s field of vision. Consequently a 2D map with the distribution on the suspended particles within the medium is made available on each frame. MATLAB scripts were prepared to be used on the processing of the output imagery. 2.2 Functionalities This research was inspired and designed onto the premise of being able to implement several buildings blocks for microfluidics. In all the cases the degree of novelty is mainly given by the fact that CMUTs had been reportedly used mainly for biomedical imaging. To that end, three different functions were attempted and tested: Particle trapping, mixing, and gradient formation. Each functionality is the result of a set of conditions that are given to both the electrical and therefore acoustical point of view, and to the geometrical properties of each acoustic cell that had been tested for this project. 2.2.1 Particle trapping The design of a building block for particle trapping is based on the implementation of standing waves. These standing waves are intended to create an interference pattern thereof a footprint is expected to be followed by the particles contained in the medium. A series of interference patterns are created by the superposition of waves: the acoustic wave that is continuously propagated from the CMUTs, and the waves that are partly reflected by each interphase of the acoustic cell. Therefore, the variables that are available to design a specific trapping device are firstly the properties of the waves created by the CMUTs resonation such as frequency (wavelength), wave shape (e.g. sinusoid) and pressure (amplitude); and secondly the geometrical properties of the acoustic cell which is going to yield a series of reflected waves. Figure 2.9 depicts the influence of the geometrical properties of PDMS acoustic cells, which are expected to come in handy to visualize and amplify the distance between pressure nodes by the optical system. Projections of the pressure planes are generated in the form of lines at the surface of the PDMS; these features are essentially a form of inclination. Thereby visualization of the normal interference pattern is made possible from a top view.
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Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
Figure 2.5. Top view of the templates that were used for the PDMS-medium acoustic cells. In these images colour lightness is a direct indication of depth when PDMS is casted on them. An example of how these acoustic patterns are created is depicted in figure 2.6. The localization of pressure nodes is going to determine the regions at which particles can be dragged within a given acoustic cell. Depending on the acoustic impedence difference between the medium and the particle (which is defined by the density and speed of sound of each), the particles will have the tendency to move to the nodes or anti'nodes of the acoustic interference pattern. In either way, the particles will give the same shape and pattern. Since the desirable result is the generation of a spatial aggregation of the particles that are suspended within the medium, factors that effect on dragging the particles are of interest. The factors that were expected to play a major role are: Particle buoyancy- The inherent capacity of the suspension to keep particles in the bulk of the body, and the time they require to be deposited on the bottom of the fluid container (Acoustic cell). This condition affects the availability of particles that can be dragged to a pressure node. Fluid viscosity- This is a property that plays a role on the minimum force that is required to drag particles and aggregates to a desirable location. Medium homogeneity- A perception on particle size and their localization can trigger artifacts due to the formation of aggregates between these particles. The amounts of effective reflectors- The effects of reflection from the top plane due to the medium-glass-air interface are expected. However this is only an abstraction of a wave whose components travel on a three dimensional space. Therefore reflections from the lateral interphases may be also visible. 2.2.2 Mixing Mixing blocks are designed to perform as the result of the stirring effect of acoustic streaming (Figure 2.7), or by spreading aggregates over a wider region within the acoustic cell. A series of experiments were prepared in order to test for aggregates that get diffused over ultrasonic excitation. The shape and size of these aggregates were not controlled variables.
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Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
Figure 2.6. Interference pattern generated along the direction of wave propagation for each acoustic cell. This pattern is visible only from cross-sectional views like the ones here depicted. Pressure waves that propagate from the CMUTs (green) are reflected to create pressure nodes.
Figure 2.7. Flow profile created due to the Eckhart flow (Acoustic Streaming). The design of a mixing block is based on this principle.
2.2.3 Gradient generator. The design of a block that generates a gradient of suspended particles is inherently created when an aggregate with a smoothly diffused contour is formed around a trapping node. The design a-priori considers the amount of energy transmitted by ultrasound that can be used as a control variable for the steepness of such gradients. 14
Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
Two ways of affecting the energy of ultrasound were considered: Handling the time of ultrasonic excitation referred hereafter as Time Modulation, and varying the amplitude of the ultrasonic waves (Amplitude Modulation).
Figure 2.8. . A green ultrasonic wave of given amplitude is propagated through a given medium (light green), this wave is reflected (red wave)and causes an interference pattern. Particles (black) suspended in the medium will be dragged to pressure nodes. The higher ultrasound amplitude is, the interference pattern will create sharper particle concentrations.
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Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
Top
Cross-section
120 µm
Figure 2.9 – Top view and cross section of a PDMS well for an acoustic cell. This specific PDMS part is featured with a cavity of elliptical profile. All green dashed lines locate the position of pressure nodes given that ultrasonic waves propagate from the bottom of the PDMS well. Due to the geometrical profile of the cross section, projections are created at more distant points over the surface.
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Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
3. Results A series of experiments were performed in order to gain insight on the performance of different configurations, these configurations aim to create microenvironments by means of ultrasonic waves. All the findings that came out of those experiments are presented in this section. Details about the design and rationales for each experimental component of this research are broadly described in the section 2 of this work. A total of 23 sets of experiments were designed, assembled and performed. Each set followed a specific group of variables and configurations thereof. Table 3.1 summarizes all the effects that were observed. Without bias voltage
With bias voltage
Figure 3.1- Both images are of the same area of the used CMUT array on chip, the area surrounded in red corresponds to the active area (elements electrically connected to a function generator). The image of the left was taken when the chip was off whereas the image on the right depicts a change on reflection due to the bias voltage.
The selected CMUT array-on-chip for this research yields an area that was not completely used due to the fact that only a limited number of elements were electrically connected to a function generator. Therefore a CMUT ‘active region’ (Figure 3.1) has been defined for the purposes of this work as the physical area on top of actively vibrating CMUTs. The active region contains four addressable rows, meaning that they were in some cases driven by different electrical settings. The active region was electrically configured in six different settings: 1. Single Spatial Frequency - All four rows in the active region were driven at the same frequency and phase for an indefinite period of time. Meaning the time so long that no changes occur in the acoustic cell. 2. Multiple Spatial Frequencies- Every row is assigned a specific frequency and amplitude but all of the signals are generated with the same phase (sync). 3. Single Spatial Frequency Sweeps- All four row in the active region were driven to the same phase and frequency, however the frequency value was evenly swept within a range of frequencies at a certain periodicity. 4. Single Frequency Time Modulation-All the rows were driven at the same frequency, however it was done repeatedly during finite periods of time. 17
Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
5. Single Frequency Amplitude Modulation-All the rows were driven at the same frequency and a voltage level was used as a control variable for foreseeable changes. 6. Frequency Modulation- All the rows were driven at the same frequency, however frequency was switched just after the acoustic cell had reached an steady/stable configuration (as in Single Spatial Frequency).
Every CMUT can be considered as a point source emitting ultrasound. The transmitted pressure wave by the CMUTs is a result of the summation of the point sources of every active CMUT. Due to the short distance towards the CMUTs, the pressure wave is considered to be in the near-field, which means it will have a considerable degree of inhomogeneity, and the pressure pattern will likely have a periodicity corresponding to the distances between the CMUTs. The effects that were observed during this research are accordingly classified and reported in six categories that apply for each type of acoustic cell (Section 2.1.2).
Configuration
Type of Acoustic cell TransducerMedium
Glass-Medium
Single spatial frequency
Pattern Formation
Pattern Formation
Multiple spatial frequency
Pattern formation
PDMS-Medium Pattern Formation. Mixing.
Not Available
Not Available
Gradient Single spatial frequency sweep
Mixing*
Aggregate dragging.
Aggregate dragging.
Single Frequency Time Modulation
Not Available
Gradient Formation
Gradient Formation
Single frequency Amplitude Modulation
Not Available
Not Available
Gradient Formation
Frequency Modulation
Mixing*
Gradient Formation
Gradient Formation. Mixing.
Table 3.1- Correlated phenomena found during experimentation 18
Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
3.1 Pattern formation Pattern formation was obtained by applying the following configurations: Single Spatial Frequency (Figure 3.2), and with Multiple Spatial Frequency (Figure 3.3). All the patterns herein reported were observed to be consistent on every performed experiment for a given acoustic cell.
a
b
c
d
Figure 3.2- Top view of the patterns that resulted over single spatial frequency exerted on several acoustic cells .a. for a transducer-medium interface .b. for a glassmedium interphase .c. into a PDMS channel of a PDMS-medium interphase .d. for a PDMS elliptical well of a PDMS-medium solution. Obtaining a specific pattern is related by the electric driving conditions and type of acoustic cell. The main parameter that can be measured for this functionality is the pitch or characteristic length as in general the resulting particle sorting are periodic patterns. A set of experiments was run for determining the influence of the inclination angle between a PDMS-medium acoustic cell and the chip’s surface. It was found that a slight inclination is required to produce powder sorting over an interference pattern.
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Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
However the pitch of such patterns was not found to be correlated to its angle within a range of 15° to 30°.
a
b
Figure 3.3- Top view of the patterns that resulted over multiple spatial frequencies exerted on several acoustic cells .a. for a transducer-medium interface .b. for a glassmedium interphase .c. into a PDMS channel of a PDMS-medium interphase .d. for a PDMS elliptical well of a PDMS-medium solution.
3.2 Mixing, and dragging Mixing and dragging are functionalities that have in common the need for moving relatively big volumes of medium. Mixing is possible by means of inducing circulation of the fluid that is contained within certain space. It was found that stirring is possible by means of applying a Single Spatial Frequency configuration over a PDMS-medium acoustic cell. In the figure 3.4, a top view of a PDMS well is depicted before and after ultrasound is turned on. When ultrasound is not being exerted, the particles are kept suspended over the medium with limited random motion due to surface tension. As soon as ultrasound starts to be radiated over the active area, the former random motion is turned into a well-defined circulation over two vortices. This is potentially the result of acoustic streaming. The direction of the flow and location of the vortices is determined by the acoustic cell. The flow speed depends on frequency and voltage.
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Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
Figure 3.4 – Top view snapshots of an ultrasonic driven stirring chamber.
Dragging of particles was achieved by first collecting them using a Single Spatial Frequency configuration. After obtaining clusters of particles the frequency was swept repeatedly e.g. 5 to 7 MHz in a time span of 1 second. The clusters responded by moving along the changing interference pattern, based on the frequency effectively dragging the clusters through the medium (Figure 3.5).
Figure 3.5- Top view snapshots while dragging of particle aggregates within a PDMSmedium acoustic cell was performed by a configuration of a Single Spatial Frequency Sweep.
3.3 Concentration gradients An attempt was done in order to find a control variable for tuning a concentration gradient. To this end a Single Frequency Amplitude Modulation was used and an image processing script was written in MATLAB in order to trace a concentration profile along a predefined route.
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In Figure 3.6 the route for sampling is marked in red. The script for measuring concentration was run for six different voltage levels, and it was found that a greater voltage produces a sharper interference pattern. The steepness at which concentration of aggregates are set is thereby related to the narrowness of the peaks. Conversely, on lower voltages, the resulting pulling force is not strong enough to keep tightly packed accumulation regions. Therefore a set of more fuzzy lines are formed. The tracer yields in this case a curve with less narrow peaks (Figure 3.7).
a.
b.
c.
Figure 3.6- Top view of the patterns that are induced on different driving voltages. In all cases signals are sinusoids of 6.5 Mhz. Voltages peak to peak are from left to right: 6Volts, 10 Volts and 15 Volts. The red line depicts the trajectory followed by a script that measures the concentration of particles.
Voltage influence on the radial profile for particle aggregation
Proportional aggregation of particles
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Figure 3.7- Influence of the voltage level on the steepness of particle aggregation of the ring pattern induced on elliptical PDMS wells.
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A series of interference patterns were induced in PDMS-medium acoustic cells. They were driven with a configuration of Single Spatial Frequency. The coupling between the CMUTs and the acoustic cell was comparable in all the cases. The goal of this particular series of tests was to get insight on how much the relative positioning of an interference pattern varies from one sample to another. The figure 3.8 depicts in yellow the deviation limits for position. Spatial deviation of the aggregation pattern Proportional aggregation of particles
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Linear position (pixels)
Figure 3.8- Spatial deviation of the aggregation patterned lines in a rectangular PDMS well. 4. Discussion
During this research the use of CMUTs has been explored for microfluidic devices. A wide set of practical acoustic functionalities were observed during the experiments, such as flow, concentration, dragging and transportation of particles by making use of the unique properties of the CMUTs, which allows to change the frequency over a large frequency range. CMUTs have been integrated with various acoustic cells to demonstrate these acoustic functionalities. It is worth to mention that most acoustical effects, such as flow and pattern generation have been produced repeatedly for a wide range of acoustical parameters, no exact control over direction and the location of these particles has been obtained. For a better control, not only a better defined acoustic cell needs to be made with precise geometry, but also the characterization needs to be improved. The current optical analytical microscope with camera only allows a limited magnification and illumination to analyze the patterns parallel to the CMUT surface. However, most acoustical interference patterns (planes) are expected to be also parallel to the CMUT surface, making them not visible by the current setup. A strong relationship between the topographic features of a well (which hosts a medium with suspended particles) and the patterns that are sorted by the suspended particles was observed. These particles of about 5 micron are known to be hydrophobic, which means they have a tendency to aggregate and stick to the PDMS surface. The relationship between topography and particle patterns is induced by a balance between two effects: first the fact that pressure nodes are likely to be localized in planar regions that are parallel to the plane that is observed from the top, and secondly that the pressure differences that are created are not strong and stable enough to indeed concentrate particles on those planes. 23
Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
A hypothesis is that these particles tend to deposit at the bottom of a containing well since present buoyant forces are not strong enough to keep them evenly suspended. While these particles sink following a path to the bottom, eventually some of them reach a pressure node and get aggregated. In consequence particles are trapped by a normal force (due to gravity), surface tension (due to chemistry) and a trapping/pulling force (due to acoustic interference). This could explain why a configuration of rings is consistently followed on the set of experiments with a non-flat topography of their acoustic cells. Another fact that can be mentioned is the fact that particles contained within a medium are also part of the fluid, therefore some characteristics of the fluid shall be considered inhomogeneous and variable during particle sorting. In other words, by creating a cluster of particles, the cluster starts to have its own acoustical properties such as speed of sound, reflectivity, and absorption when a critical size (of a few wavelengths) is reached. This will also have an impact of the overall interference pattern in the medium. The driving motivation for this project is to explore available possibilities to enhance the potential of cell cultures by means of implementing ultrasonic technologies. In biology is not always easy to determine an accurate and quantitative guideline for the physical variables playing a role in cell cultures. One example is the process of trypsination, were centrifugal forces are not accurately measured since the desired effect can be observable in a qualitative way thus accepted as long as enough dissociating of cells is produced. For acoustical induced flow and induced concentration gradients this qualitative way of determining the effect will also be required. However, using biological samples was outside the scope of this research.
5. Conclusions
As a result of this research, a proof of principle could be delivered for the feasibility of implementing AIMs as building blocks for cell cultures. The functionalities that were proven are Pattern Formation (Sorting), Mixing (Stirring), Dragging, and Gradient Tuning. An acoustic flow was observed by using a PDMS-medium acoustic cell; these flows are capable to drive formation of patterns of semi-suspended particles on three distinct types of acoustic cell. The properties of the bottom surface of PDMS-medium acoustic cells define the geometry of an interference pattern by possibly creating projections of the otherwise pressure planes located in the normal direction of the chip’s surface. Tuning the profile of concentration gradients was proved by changing the voltage within a range of 4 to 15 Vac using a PDMS-medium acoustic cell featured with a rectangular well. The result is shown as a change on the fuzziness at which an interference pattern is formed. Particle aggregates were dragged inside acoustic cell by sweeping the frequency from former interference driven patterns, in all three types of acoustic cells.
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Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
6. Acknowledgements
I acknowledge the support from the National Council for Science and Technology (CONACYT), the Schuurman-Schimmel-Van Outeren Foundation, Philips Research Eindhoven, and Delft University of Technology on funding this project and my MSc education.
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7. References
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14. Turnbull, D. H., & Foster, F. S. (1992). Fabrication and characterization of transducer elements in twodimensional arrays for medical ultrasound imaging. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 39, 464 -475. 15. von Ramm, O. T. (2000). 2D arrays. Ultrasound in Medicine and Biology, 26(Suppl. 1), S10S12. Wang, H., Ritter, T., Cao, W., & Shung, K. K. (1999). Passive Materials for High Frequency Ultrasound Transducers. SPIE Proceedings, 3664, 3541. 16. A. Lenshof, C.Magnusson, T. Laurell, Acoustofluidics 8: applications of acoustophoresis in continuous flow microsystems, Lab Chip 12 (2012) 1210–1223. 17. E.A. Neppiras, Acoustic cavitation, Phys. Rep. 61 (1980) 159–251. 18. R. Manasseh, P. Tho, A. Ooi, K. Petkovic-Duran, Y. Zhu, Cavitation microstreaming and material transport around microbubbles, in: L.G. Garreton (Ed.), International Congress on Ultrasonics, Proceedings, 2010, pp. 427–432. 19. M.A. Sobanski, C.R. Tucker, N.E. Thomas,W.T. Coakley, Sub-micron particle manipulation in an ultrasonic standing wave: applications in detection of clinically important biomolecules, Bioseparation 9 (2000) 351–357. 20. J.P. Kilroy, A.L. Klibanov, B.R. Wamhoff, J.A. Hossack, Intravascular ultrasound catheter to enhance microbubble-based drug delivery via acoustic radiation force, IEEE Trans. Ultrason. Ferroelectr. Freq. Control 59 (2012) 2156–2166. 21. Khuri Jakub Ultrasonics Group, ‘General Description on CMUT Research’. http://www-kyg.stanford.edu/khuriyakub/opencms/en/home/ 22. Shih MC, Tseng SH, Weng YS, Chu IM, Liu CH. A microfluidic device mimicking acinar concentration gradients across the liver acinus. Biomed Microdevices. 2013 Oct;15(5):767-80. 23. Cyril Torre, Christine Perret, and Sabine Colnot. Progress in Molecular Biology and Translational Science: Molecular Determinants of Liver Zonation. Copyright 2010, Elsevier Inc., Vol. 97 All rights reserved. DOI: 10.1016/S1877-1173(10)97005-1 24. Human anatomy & physiology, Elaine N. Marieb, Katja Hoehn, 9th ed, p. 880. ISBN13: 978-0-321-74326-8
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Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
Appendix A – ´PDMS-medium´ type Acoustic Cells Disclaimer: Scale in the following projections is not kept to hold a friendlier depiction of the relevant features on each acoustic cell. For an actual view please refer to each size annotation herein added.
2 cm
1 cm
0.25 cm
PDMS - Stirring Well
1 cm 2 cm 0.25 cm
0.5 cm
0.005 cm
0.005 cm
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Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
PDMS – Curved Bottom Ovular Well
0.35 cm 1 cm 2 cm
0.5 cm
0.125 cm
0.100 cm
2
2 cm
0.25 cm
0.125 cm
Acoustically Induced Microenvironments (AIMs) Building blocks for organ models in-vitro A. Galicia Naranjo
PDMS basic Channel
2 cm
0.125 cm
1 cm 2 cm
0.5 cm
0.125 cm
3
