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Advancements in on-chip and free-space optical sensing technologies Nichols, Jacqueline 2013

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ADVANCEMENTS IN ON-CHIP AND FREE-SPACE OPTICAL SENSING TECHNOLOGIES  by  Jacqueline Nichols  B.A.Sc., The University of British Columbia, 2011  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF APPLIED SCIENCE  in  THE COLLEGE OF GRADUATE STUDIES  (Electrical Engineering)   THE UNIVERSITY OF BRITISH COLUMBIA   (Okanagan)  September 2013   ? Jacqueline Nichols, 2013  ii Abstract  Optical detection technologies for on-chip and free-space applications have numerous benefits. When appropriately designed, these systems offer heightened sensitivity for numerous research fields?especially those based upon biochemical technologies. An on-chip sensing system is first presented in this work as an integrated microfluidic architecture for measuring the refractive index of a given sample. The optical sensing capabilities are dictated by an overhead microlens that is fabricated by way of a new electro-dispensing technique. The microlens contact angle can be tuned to allow for sampling of fluid refractive indices with variable ranges and resolutions. A free-space optical sensing system is then presented. The system utilizes retroreflective elements to detect microscopic particles in macroscopic volumes. System refinements are made to the geometry, shape, and materials. Imaging refinements are then made to further increase the overall sensitivity of the system.       iii Preface  Chapter 2 is based on work conducted in the Integrated Optics Laboratory in partnership with numerous researchers at the University of British Columbia. This chapter includes published works from J. Nichols, A. Ahmadi, M. Hoorfar, H. Najjaran, and J. F. Holzman, ?In situ digital microfluidic conductance sampling,? Sens. Act. A-Phys, Sensor Actuat. A-Phys., vol. 152, pp. 13-20, 2012 as well as parts of J. Nichols, C. M. Collier, E. L. Landry, M. Wiltshire, B. Born, and J. F. Holzman, ?On-chip digital microfluidic architectures for enhanced actuation and sensing,? J. Biomed. Opt., vol. 17, no. 6, pp. 067005(1-7), 2012. For the former article, I fabricated the devices, conducted all experiments, and wrote the first draft. For the latter article, work for the ?Actuation? section was carried out and drafted within the article by C. M. Collier, while work for the ?Sensing? section was carried out by E. L. Landry and myself, and drafted within the article by myself. Excerpts from J. Nichols (2012) are presented in Appendix A. Chapter 3 is based on work conducted in the Integrated Optics Laboratory by Dr. J. F. Holzman, M. Bergen, J. Taylor, and myself. I was responsible for supervising/conducting the majority of the experiments.   iv Table of Contents  Abstract .................................................................................................................................... ii!Preface ..................................................................................................................................... iii!Table of Contents ................................................................................................................... iv!List of Figures ......................................................................................................................... vi!List of Symbols ..................................................................................................................... viii!List of Abbreviations .............................................................................................................. x!Acknowledgements ................................................................................................................ xi!Dedication .............................................................................................................................. xii!Chapter 1 Introduction ........................................................................................................... 1!1.1! Background and Motivation ..................................................................................................... 1!1.1.1! On-Chip Optical Sensing ................................................................................................... 2!1.1.2! Free-Space Optical Sensing ............................................................................................... 3!1.2! Scope of this Thesis .................................................................................................................. 4!Chapter 2 On-Chip Optical Sensing ..................................................................................... 6!2.1! Electrical Sensing ..................................................................................................................... 7!2.1.1! Conductance Sensing ........................................................................................................ 8!2.1.2! Capacitance Sensing .......................................................................................................... 9!2.2! Standard Optical Sensing ........................................................................................................ 10!2.3! Optical Cavity Sensing ........................................................................................................... 13!Chapter 3 Free-Space Optical Sensing ............................................................................... 25!3.1! Optical Sensing Challenges .................................................................................................... 25!3.2! Back-Reflection Detection System ......................................................................................... 28!3.2.1! Geometry Refinement ..................................................................................................... 30!3.2.2! Shape Refinement ............................................................................................................ 32!3.2.3! Material Refinement ........................................................................................................ 35!3.2.4! Imaging Refinement ........................................................................................................ 37!! Macroscopic Investigation ....................................................................................... 41! v! Microscopic Investigation ........................................................................................ 42!! Differential Imaging Technique ............................................................................... 43!Chapter 4 Conclusions and Future Work .......................................................................... 45!References .............................................................................................................................. 47!Appendices ............................................................................................................................. 53!Appendix A: Conductance Sensing ................................................................................................. 53!Appendix B: On-chip Digital Microfluidic Architectures for Enhanced Actuation and Sensing .... 57!Appendix C: Additional Experimental Images ................................................................................ 66!!   vi List of Figures  Figure 2.1    The digital microfluidic multiplexer shown as a representative photograph with a conceptual diagram as the inset to this photograph. ................................. 8!Figure 2.2    Normalized reflected OA intensity, IOA, versus fluid refractive index, nf, of a sample fluid on a glass surface with ng = 1.5. .................................................... 12!Figure 2.3    The Optical Cavity Sensor, for the digital microfluidic multiplexer, with (a) ray-tracing model results for a fluid with refractive index nf = 1.52, (b) ray-tracing model results for an air fluid with refractive index nf = 1.000, and (c) the applied electro-dispensing process for fabrication of a microlens with a contact angle of ! = 45? and radius of 900 !m. ................................................. 17!Figure 2.4    Normalized reflected OA intensity, IOA, on the image sensor for a sample fluid refractive index nf inside the Optical Cavity Sensor. ................................ 20!Figure 2.5    Optical Cavity Sensor refractive index range !nf and resolution "nf are shown as a function of microlens contact angle ! ......................................................... 21!Figure 2.6    Photograph of the electro-dispensing set-up. ..................................................... 24!Figure 3.1    Retroreflection for (a) a corner-cube retroreflector and (b) a spherical retroreflector. ..................................................................................................... 29!Figure 3.2    Normalized reflected OA intensity, IOA, for retroreflection from a corner-cube retroreflector and a spherical retroreflector. ...................................................... 32!Figure 3.3    Diameters, d, of the dispensed polymer sphere as a function of the dispensing pressure, Pdisp. Dispensing time for all results is 5 seconds. .............................. 34!Figure 3.4    The refractive index n as a function of wavelength, ", for four NOA polymers (61, 63, 68, and 1625) and two glasses (LaSFN9 and BaTiO3). ........................ 36!Figure 3.5    The free-space optical sensing configuration as an optical system (a) model, (b) schematic, and (c) photo. .............................................................................. 38!Figure 3.6    Normalized first lens optical power, D1 = 1/f1, displayed as a function of refractive index, n, for the optical model with macroscopic results in red and microscopic results in blue. ................................................................................ 40! vii Figure 3.7    The differential imaging technique is presented with unitless intensities on the OA displayed for the signals and the resulting photographs are shown as insets. ................................................................................................................. 44!Figure A.1    A flowchart of the conductance sampling algorithm. ........................................ 55!Figure A.2    Results for two microdrops within the digital microfluidic multiplexer as (a) experimental results of the conductance across the device, (b) the extracted microdrop model from the Matlab simulation, and (c) the extracted microdrop model from the Matlab simulation as viewed from overhead. ......... 56!Figure B.1    The digital microfluidic multiplexer is shown as an orthogonal grid of lower row electrodes and upper column electrodes driven by a centre-tap transformer with a single primary input, Vin(0?), and two out-of-phase secondary outputs, V0(0?) and V0(180?). For Vth = 0, the modified fluid surface tension "# in the left figure inset can allow microdrop motion along all activated row and column electrodes. ........................................................... 63!Figure B.2    Digital microfluidic multiplexer operation is shown for a structure with a high threshold voltage, Vth = 620 Vrms. .............................................................. 64!Figure B.3    Digital microfluidic multiplexer operation is shown for a structure with low threshold voltage, Vth = 48 Vrms. ........................................................................ 65!Figure C.1    A polymer macrosphere fabricated with a defect. ............................................. 66!Figure C.2    Polymer microspheres being dispensed into a filler fluid using the modified electro-dispensing technique. ............................................................................. 66!Figure C.3    A polymer macrosphere and the corresponding back-reflected signal. ............. 67!Figure C.4    A glass macrosphere and the corresponding back-reflected signal. .................. 67!Figure C.5    One single corner-cube retroreflector on a sampling slide. ............................... 67!Figure C.6    Four corner-cube retroreflectors detected on a sampling slide. ......................... 68!  viii List of Symbols  Symbol Description  At total microdrop area covering overlapped electrodes  c capacitance d sphere diameter D1 lens optical power  d1a distance from sample surface to first lens in optical schematic d1b distance from sample surface to second lens in optical schematic dg central gap between multiplexer plates dsens2  area of hypothetical image sensor  f1 focal length of first lens in optical model  f2  focal length of second lens in optical model  f1a representative focal length for first lens in optical schematic  f1b representative focal length for first lens in optical schematic gt normalized summed total conductances  gx normalized summed x-channel conductances gy normalized summed y-channel conductances Gmax maximum possible conductance  Gt total summed conductances  Gx x-channel summed conductances Gy y-channel summed conductances  Gxy discrete conductance distribution  IOA intensity on the optical axis l3 volume of microscopic particle  L3 volume of macroscopic cube  Lx length of electrode in the x-direction  Ly length of electrode in the y-direction  m number of x-electrodes n number of y-electrodes nf fluid refractive index  ix ng glass refractive index n0 refractive index of air p centre-to-centre pitch of DMM electrodes  P0 nominal power  Pdisp dispensing pressure  Pi incident power  Pr reflected power  R reflectivity r0 radius of microdrop  tdisp dispensing time  Vdisp dispensing tip voltage  w width of electrode  x0 microdrop centre on the x-channel y0 microdrop centre on the y-channel   Greek Symbols "nf fluid refractive index resolution !nf  fluid refractive index range #LV liquid-vapor surface tension #SV solid-vapor surface tension  #SL solid-liquid surface tension  $ drop conductivity  % azimuthal angle of corner-cube  !  polar angle of corner-cube  !f fluid transmitted angle  !g glass incident angle  "  wavelength     x List of Abbreviations  Abbreviations Definitions 2-D Two-dimensional 3-D Three-dimensional CMOS Complementary Metal Oxide Semiconductor DC Direct Current  DI Deionized DNA Deoxyribonucleic Acid EWOD Electrowetting-on-dielectric IR Infrared LED Light-Emitting Diode MEMS Microelectromechanical Systems NOA Norland Optical Adhesive OA Optical Axis OCT Optical Coherence Tomography PDMS Polydimethylsiloxane PTFE Polytetrafluorethylene UV Ultraviolet VGA Video Graphics Array    xi Acknowledgements  I am deeply grateful to my supervisor, Prof. Jonathan Holzman, for his enthusiasm, encouragement, patience, and support. He has taught me many skills around the lab for research while encouraging me to further work on technical communications through writing papers and presenting research at conferences. His guidance and feedback has made such a positive impact on my overall time at the University of British Columbia.  I would also like to extend my thanks to my committee members Dr. Deborah Roberts, Dr. Kenneth Chau, and Dr. Sunny Li for their valuable advice, time, and effort.  I owe many people thanks for their support and generosity during my time of study at The University of British Columbia. I would like to thank all my colleagues in the Integrated Optics Laboratory for our discussions and sharing their viewpoints on research. In particular, I would like to extend my thanks to Xian Jin, Chris Collier, Emily Landry, and Mark Bergen for their help and generosity through out my time in the research group. A heartfelt thank you goes out to everyone in Alpha Omega Epsilon for making the times working and studying on campus a far more enjoyable experience. For all the rest of my friends I?ve met in Kelowna, especially my old housemates, thank you for always being fantastic.   Finally, I would like to thank my family for their understanding all these years. My achievements would not have been possible without their support and encouragement.      xii Dedication        This thesis is dedicated to Ryan Nichols.  1 Chapter 1 Introduction  There are a wide variety of optical detection methods utilized in contemporary research. These detection methods are the result of a long developmental history in optical research. A review of some of the more critical developments in optical technology can reveal the benefits and challenges for contemporary light-based systems, and the following section carries out this review.  1.1 Background and Motivation Optics has been an important topic of study for millennia. The first recorded document on optics was by Euclid in approximately 300 BC. His work, Optics, treated optics in a geometrical fashion with light rays as lines. Euclid?s ray approach failed to reveal the physical nature of the light waves, but it did give this early researcher insight into simple principles of geometry, such as the law of reflection. The work Optics is now available as an English translation by Harry Edwin Burton [1].  Approximately 200 years after Euclid?s study, Hero of Alexandria extended the basic principles of optics. Hero?s analysis of reflection, light, and mirrors was chronicled in Catoptrica. The work described the physical nature of visual rays and included emission theory (light trapping on unpolished surfaces vs. reflection from smooth surfaces). At the same historical point in time, Ptolemy began to study refracted light for waves traveling between media of different density (or refractive index). The values obtained from his experiments have laid the groundwork for modern theory, and it was at this point in time that optics began to be considered as a means to control light. The work of Alhazen investigated spherical and parabolic mirrors and included important discussions on the focusing characteristics of mirrors. The modern concepts of spherical aberration and magnification were even introduced.  Efforts to understand and control light rays continued on into the Renaissance period through the work of many European scholars. Roger Bacon described light as propagating through a medium in a fashion that is similar to that of sound. He suggested that the speed of light is   2 finite and that convex lenses could be utilized to correct defective eyesight. In 1621, Willebrord Snellius established a critical rule in optics, being Snell?s Law. This law defines the relationship between the incident and refracted light angles and the refractive indices of the respective incident and refracted sides. Both refraction and reflection were then thoroughly investigated by Isaac Newton in the 1600s. It was demonstrated that white light could be decomposed into a colour spectrum (or even recombined back into white light). Newton went on further to construct the first reflecting telescope, having no chromatic aberration due to its use of mirrors. In the 1800s, Maxwell studied the equations of electric and magnetic fields, and it was ultimately concluded that light is a transverse electromagnetic wave that travels at the speed of light.  Beyond the time of Maxwell, optics began to progress into a highly technological area. In 1958, Schawlow and Townes [2] proposed that the principle of a microwave emitter (maser) could be extended for use as a light emitter (laser). The laser was later described by Theodore Maiman in 1960 and built at the Hughes Research Laboratories using a ruby lasing medium [3]. The introduction of this laser led to the creation of various lasers, with both gaseous and solid forms, and this allowed for optical measurements across many wavelengths. Ultraviolet, visible, and infrared sources could now be made and applied for intricate micron-scale analyses with broad spectral information. This has opened the door to optical sensing as an effective analytical tool.  There are a great many optical sensing techniques that have been introduced over the past few decades. For the purposes of this thesis, these techniques can be categorized as follows: on-chip optical sensing and free-space optical sensing. These two techniques will be defined and explained in the following two subsections.  1.1.1 On-Chip Optical Sensing On-chip optical sensing refers to light-based measurement techniques carried out on an integrated (typically small) platform. This can be a device where the actuation and movement occurs inside the chip with the sensing located above, or on a monolithic platform with the actuation and sensing existing in one small area. On-chip optical sensing is often used in   3 continuous-flow microfluidic devices or the newer digital microfluidic devices.  On-chip optical sensing has been demonstrated by Srinivasan et al. in 2004 by way of a photodiode-LED set up. This is set up as a monolithic sensing system to a digital microfluidic device where a sample is dispensed, mixed, and then detected. The purpose of this system is to detect the concentration of glucose in a sample. The sensitivity of the system is dependent on the time of detection as well as the dilution factor of the overall sample. Taking these into account, the sensitivity ranges from 16.6 ? 27.2 uAU dl/s mg, with AU standing for absorbance unit.  Lien et al. have also shown on-chip optical sensing in 2007 by way a continuous flow microfluidic device and an optical fiber cantilever. A single-mode fiber is placed across the continuous flow microfluidic channel in line with multi-mode fiber. The flow rate of the system can be measured as the laminar flow creates a drag force and displaces the fiber tip, which in turn reduces the intensity of light transmitted through the multi-mode fiber. A resolution, which is dependent on the viscosity of the sample, of ~0.022 is obtained in these measurements, and the single-mode fiber recovers its response after large flow rates.  On-chip optical sensing is now prevalent in biomedical and pharmaceutical fields. Direct applications include integrated optical hollow waveguides for refractometry [4], integrated fiber-optic cantilevers for flow rate detection [5], and optofluidic lasers for detection on-chip [6]. In digital microfluidics, for example, on-chip optical sensing has been achieved by way of light emitting diodes (LEDs) with photodiodes [7], thin-film photodetectors [8], and optical ring resonators [9].  1.1.2 Free-Space Optical Sensing Free-space optical sensing refers to light-based measurement techniques carried out with minimal optical beam guiding on an open (typically large) platform. It is now widely utilized for analyzing samples in labs and is beginning to be used in analyzing tumors or lesions inside of the body.    4 A prime example of free-space optical sensing, Optical Coherence Tomography (OCT), was introduced in 1991 [10]. This method is ideal for medical applications requiring high resolution in vivo sensing. This method allows for imaging reflections within tissues or opaque mediums and provides cross-sectional images. The utilization of optical waves allows for higher resolution than that of sound or radio frequencies. An ultrahigh-resolution version of OCT, which utilizes a pulse laser and a detection element for in vivo sensing, was developed in 2001 by Hartl et al. [11]. This method is ideal when a tomographic map of an area is required, such as observing tumors or other lesions inside the body.  Fluorescence detection, demonstrated by Garcia et al. in 1987 and Ahmed et al. in 2013, is a commonly used free-space optical sensing technique for detecting pathogens such as cryptosporidium. US EPA Method 1622 and1623 describe standardized methods for detecting cryptosporidium and giardia in bulk systems of water, including elution and separation followed by enumeration via fluorescence. The samples are stained with fluorescently labeled antibodies, and light is shone on the slides, causing the oocysts to fluoresce with uncollimated light towards a detector. Fluorescence detection at a magnification of !250 was shown by Garcia for organism confirmation of cryptosporidium oocysts [12].    As more research moves towards optical sensing technologies, it is apparent that optical sensing offers heightened levels of sensitivity for operation on especially small scales, compared to examples of imaging or spectroscopy with longer radio wavelengths. These attributes are particularly important for the emergence of micro- and nano-technologies, and optical sensors will undoubtedly play an important role in these future optical sensing applications.  1.2 Scope of this Thesis An introduction is given in chapter 1 of this thesis. My own research work on optical sensing techniques for on-chip two-dimensional (2-D) architectures and free-space three-dimensional (3-D) architectures are then presented in chapters 2 and 3, respectively. Final conclusions are given in chapter 4.   5  Chapter 2 focuses on on-chip (2-D) optical sensing. A literature review is provided to outline state-of-the-art integrated optical detection methods and demonstrate the need for improved sensitivity for lab-on-a-chip systems. The standard on-chip optical sensing technique, that makes use of simple light reflection on the chip, is adapted in my work to improve the detection capabilities. An optical cavity is employed by way of an overhead polymer microlens to create an especially sensitive relationship between the internal fluid refractive index and the reflected optical intensity. Theory, fabrication, and experimental results are presented. Details on the refractive index sensing range and resolution are given. This on-chip optical sensing work is supported by an on-chip microdroplet actuation system, with relevant details on the microdroplet actuation system shown in Appendix A.  Chapter 3 focuses on free-space (3-D) optical detection. The challenges of optical detection in a multi-directional large-scale architecture are witnessed here. Enhanced retroreflection is employed to improve the back-reflected optical signal levels, and this is done with micron-scale retroreflectors. Spherical retroreflectors are developed for this application. The required refractive indices to establish the desired retroreflection are formed as polymer macrosphere retroreflectors. The results are compared to glass microsphere retroreflectors and corner-cube retroreflectors. It is shown that improved back-reflection can be established for these spherical retroreflectors with the appropriate selection of materials and dimensions. This ultimately leads to improved measurement sensitivities and more practical sensing systems with larger working areas. Ultimate improvements are made by the introduction of a differential imaging technique to further resolve the micron-scale retroreflective elements.  Chapter 4 summarizes the contributions of this thesis then lays the groundwork for future developments.    6 Chapter 2 On-Chip Optical Sensing  On-chip devices are monolithic structures that are miniaturized for operation as planar (2-D) integrated chips. Such on-chip devices are often referred to as lab-on-a-chip-systems. On-chip devices began with the introduction of microtechnology in 1954. The devices evolved throughout the 1960?s by way of technological developments in microelectromechanical systems (MEMS). In 1979, the first laboratory micro-sensing system was introduced [13].  Many research disciplines are now interested in these micron-scale laboratory devices. Recent on-chip applications include Deoxyribonucleic Acid (DNA) pyrosequencing [14], DNA ligations [15], and immunoassays [16]. The small device scales are ideal for applications seeking reagent economy and high measurement sensitivities.  The advantages of on-chip devices come from their reduced size. The compact nature of the devices allow for process parallelization and high-throughput analyses. This allows for reduced fluid consumption volumes during testing resulting in less waste. As the transport distances are scaled-down, the analysis times are also reduced. Reduced analysis times yield faster system responses and overall improvements in process control.  It is important to note that difficulties can arise as on-chip sensing devices are scaled to smaller dimensions. Process control becomes more complex with reduced sample volumes, as the reagents of interest become increasingly susceptible to surface forces. Capillary surface forces begin to dominate over volume forces that typically dominate in the macroscopic domain [17]. Further challenges relate to on-chip sensing. The majority of detection methods (electrical, optical, etc.) have signal levels that scale-down with diminishing device areas. This can lead to unacceptably low signal levels and reduced sensitivity. These considerations must be taken into account for improved sensing when developing the next generation of on-chip sensing devices.  The following subsections will investigate current architectures for fluid sensing in a 2-D plane. Electrical sensing is introduced first by way of conductance and capacitance sampling.   7 The benefits and drawbacks of these electrical techniques are discussed. A standard optical sensing technique is then presented. It is shown that optical sensing can become especially challenging for micron-scale device dimensions, and a new Optical Cavity Sensor is introduced to overcome the sensitivity limitations of operation on small scales. The Optical Cavity Sensor is created with a new electro-dispensing process. The relevant fabrication considerations are presented for this process. Theoretical and experimental sensing results are then shown for the Optical Cavity Sensor.  2.1 Electrical Sensing Many current on-chip sensing methods are based upon electrical measurements. From a fundamental standpoint, these measurements can characterize their environment by way of two distinct quantities: conductance and capacitance. Conductance sensing quantifies the ability for free charges to flow through the material. Capacitance sensing quantifies the ability for bound charges in the material to polarize in an external electric field. Conductance and capacitance sensing both have benefits and drawbacks that will be examined here.  The principle of electrical sensing is introduced here by way of a digital microfluidic multiplexer. The multiplexer, as analyzed for localization in bi-layer digital microfluidics by Abolhasani et al. [18], has an upper plate of row electrodes that is orthogonal to a lower plate of column electrodes. The space between the upper and lower plates is the fluid actuation layer. This structure is shown in Fig. 2.1. Microdrop fluid samples are located between the upper and lower plates and can be actuated by applying voltages to the appropriate rows and columns. The microdrop of interest is attracted to the high-field region between the activated row and column electrodes. Details of microdrop actuation are given in Collier et al. [19], and the references therein.    8  Figure 2.1    The digital microfluidic multiplexer shown as a representative photograph with a conceptual diagram as the inset to this photograph.   2.1.1 Conductance Sensing Conductance sensing quantifies the ability for a material to allow free charge transport and pass conduction current. Conductance sensing is particularly useful for discerning on-chip locations of high conductivity fluid (such as electrolytic solutions [20]) versus low   9 conductivity fluid (such as oil or air). Conductance probing can therefore be effective in determining the spatial distributions of conductive fluids in sensing structures?to ultimately support fluid control and actuation.  There are benefits to conductance sampling, and this technique has proven to be especially successful when characterizing electrolytic solutions. Electrolytic solutions can have a wide range of ionic concentrations that can be effectively probed by way of fluid conductivity. The ionic concentrations and conductivity measurement ranges can be over six orders of magnitude [21]. As ionic conduction avoids dielectric saturation, this dynamic range of conductance values dominates over that of other sampling processes such as capacitance sampling [22].  There are some important drawbacks that must be considered for conductance sampling, however. The surface area of the sensing electrode will dictate the absolute value of the conductance. When smaller on-chip device dimensions are sought, this surface area will be reduced and the measurement sensitivity worsens. Furthermore, the fluid of interest must be in direct contact with the metal electrodes. This can lead to electrolysis when direct current (DC) currents are applied. The highly effective microdrop actuation techniques based upon electrowetting-on-dielectric (EWOD) [23] are therefore not possible with conductance sensing, as the internal dielectric layers needed for EWOD cannot be introduced (as they would block the conductance sensing current). Given these disadvantages, there are ongoing studies for electrical measurements based upon capacitance sensing.  2.1.2 Capacitance Sensing Capacitance sensing can be used to characterize the dielectric properties of fluids. The process makes use of the intimate relationship between applied external electric fields and the polarization of internal dielectrics (i.e., fluids). The capacitance sensing technique is especially useful for digital microfluidic actuation architectures as the electrodes used for actuation can also be used for sensing [24]. Furthermore, the dielectric layers required for EWOD that block the aforementioned conduction sensing currents can now remain?and can even be optimized to accentuate displacement current flow. It is this displacement current   10 that is measured in capacitance sensing techniques. The capacitance sensing technique can be readily applied to the digital microfluidic multiplexer described in Appendix A.  Capacitance sampling is a well-established method for sampling on-chip fluid characteristics. The presence (or lack) of a fluid is recorded through a change in the local dielectric properties, and this maps itself onto the measured displacement current. Capacitance sensors can now be found in a wide array of devices that measure liquid levels [25], humidity [26], and even touch-pressure [27].  While capacitance sensing has practical benefits for easy merging with on-chip fluid actuation architectures, it has the same device-area-scaling drawback as conductance sensing. The measured capacitance values will be proportional to the electrode area of interest, and the scaling down of the dimensions in such a device will result in diminished signal levels. This can lead to unacceptably low signal levels for capacitance measurements. Furthermore, the low-frequency dielectric properties that are probed by capacitance sensing have limited spectroscopic information. There is little frequency-dependence for material absorption lines below a frequency of one gigahertz, so it becomes difficult to observe distinct material characteristics.  With the above disadvantages of capacitance sensing in mind, there has been growing interest in optical sensing techniques. The broadband nature of optical sources, with wavelengths of 200 nm to 400 nm in the ultraviolet (UV) spectrum, 400 nm to 800 nm in the visible spectrum, and 750 nm to 1 mm in the infrared (IR) spectrum, can open the door to a wide range of on-chip optical sensing techniques for spectroscopic material analyses. The following subsection will elaborate on the standard optical sensing technique.  2.2 Standard Optical Sensing Standard optical sensing makes use of fluid detection with an overhead (typically) illumination source and integrated camera/sensor. Many device architectures have been presented for such sensing. Chatterjee et al. [28] have shown the motion of droplets through applying AC or DC potentials in an open system with an above imaging camera. Watson et   11 al. [29] implemented a digital microfluidic device and viewed their mixing and motion results via standard optical sensing.  For standard optical sensing, the source and sensor can be chosen for the appropriate spectral range of interest?UV, visible or IR. Furthermore, the spectral information made available by the optical source should ideally be tracked in real-time as a digital image. Such results are shown in the Fig. 2.2 inset of the photograph for the digital microfluidic multiplexer.  To quantify spectroscopic detail in a digital image for an internal fluid, it is necessary to establish a refractive index contrast between the overhead glass superstrate, with refractive index ng, and the fluid of interest, with refractive index, nf. The refractive index contrast creates a reflection in proportion to the incident intensity, Iinc. The reflected optical axis (OA) intensity, IOA, can then be defined for normal incidence by the Fresnel equation [30] for the reflectivity   R= IOAIinc = ng ! nfng + nf"#$$ %&''2 . (1)  It is apparent from equation (1) that an appreciable OA intensity, IOA = RIinc, comes about when there is a significant difference in the refractive indices, ng - nf. This constraint for standard optical sensing can make reflected power monitoring difficult for images of fluids with high refractive indices. The challenges of standard optical sensing are clearly seen in Fig. 2.2. The reflected OA intensity, IOA, is shown as a function of the fluid refractive index nf. When the fluid reactive index is close to that of glass, ng " 1.5, there is minimal refractive index contrast and negligible reflected power.   A further challenge of standard optical sensing relates to its use of reflected power measurements. Reflected optical powers will scale proportionally with the fluid sampling area. Small sampling areas will have small back reflective powers. This can become a   12 problem for technologies with small device dimensions, as the reflected optical signal power can become diminishingly small.  Given the spectroscopic benefits of optical sensing and the scalability issues of standard optical sensing, the following subsection will introduce the Optical Cavity Sensor for improved measurement sensitivity with on-chip systems.     Figure 2.2    Normalized reflected OA intensity, IOA, versus fluid refractive index, nf, of a sample fluid on a glass surface with ng = 1.5. An overhead image of two microdrops in a digital microfluidic multiplexer is shown in the inset. The outline of the microdrops can be seen, although the reflected OA intensity contrast between the inside of the microdrop and the regions of surrounding air within the multiplexer is minimal.       13 2.3 Optical Cavity Sensing Optical sensing methods are desirable for broadband detection sensitivity, as optical material characteristics can be ascertained on appreciably small scales (down to the sub-micrometer level) with broad spectral signatures (spanning 200 nm to 1 mm). The on-chip integration of such optical sensing systems will therefore have the potential for improved sensitivity in practical and noninvasive devices. However, the use of optical sensing techniques on increasingly smaller scales leads to a fundamental reduction in optical signal power?as a finite optical intensity acquired over a smaller sensing area leads to reduced optical power. This device scalability issue must be resolved for appreciable optical signal levels. Given the advantages of optical sensing for material characterization, and the sensitivity challenges associated with small-scale on-chip sensing, the work in this section introduces a multilayered optical cavity to accentuate refraction through the on-chip fluid. This Optical Cavity Sensor employs a microlens on the superstrate and reflective plane on the substrate. Microdrop samples of interest are actuated into this sensing region for interrogation by an overhead optical beam. The name of the Optical Cavity Sensor is given to the device to describe the fact that the optical beam is folded within a volume (i.e., cavity) containing the fluid to be sampled. The term ?cavity? is not meant to suggest that multi-reflection optical resonance is used within the device. Light refraction through the fluid is especially sensitive to the fluid refractive index, thus the back-reflected optical intensity can be used to gauge the fluid refractive index. The particular microlens focal characteristics and device dimensions will ultimately determine the refractive index measurement range and resolution according to the following analyses.  The Optical Cavity Sensor of interest to this investigation is implemented as a sensing station at the edge of the aforementioned digital microfluidic multiplexer (described in Appendix A). The multiplexer is designed with a 1 mm thick glass superstrate and 1 mm thick glass substrate. The superstrate and substrate are copper-coated and patterned via UV photolithography into the digital microfluidic multiplexer architecture. An electrode width of w = 500 ?m and pitch of p = 600 ?m are used. The superstrate and substrate copper patterns are then spin-coated with a 7-?m-thick polydimethylsiloxane (PDMS) film as an insulative layer and a 7-?m-thick Teflon-AF film as a hydrophobic layer. The completed superstrate   14 and substrate are aligned in a bi-layered structure, with a dg = 650 ?m central air gap as the fluid actuation region. The device architecture is capable of intricate microdrop actuation across the 2-D grid [19]. Voltages are applied to the linear upper row and lower column electrodes to draw the microdrop of interest to the fluid sensing station, where the Optical Cavity Sensor can be used to probe the fluid refractive index.  The Optical Cavity Sensor operates by way of ray refraction and reflection through the configuration shown in Figs. 2.3(a) and (b). Collimated light rays from a broadband optical source travel through an overhead microlens and begin to converge as they pass through the on-chip system. The converging light rays pass through the glass superstrate and into the microdrop fluid of interest. The light rays refract at the upper glass-fluid interface and subsequently reflect at the lower fluid-copper interface.  The rays shown in red in Fig. 2.3 were obtained through a ray-tracing simulation in MatLab. Ray-tracing, or geometrical optics, can be used to describe the wave propagation direction through the use of vectors. This technique uses Snell?s law to calculate the change of angles in rays for systems with ray refraction and bending. Ray-tracing is ideal for structures of this size, but begins to break down for structures on the same order of the wavelength of light used (in which cases finite-difference time-domain analyses can be employed). For the present ray-tracing analysis, all individual rays are traced through the setup, with the Law of Reflection used at reflective surfaces and Snell?s Law used at all dielectric interfaces. The rays are traced all the way back to the image sensor, where they are analyzed to compute the optical intensity The optical intensity is inversely proportional to the separation between the light rays: light rays that are densely packed with small separations would describe a high intensity; and light rays that are disbursed with large separations would describe a low intensity. This ray-tracing analysis can be carried out for a variety of different dimensions in the setup and for a variety of different fluid refractive indices.  The process of light ray refraction and reflection through the Optical Cavity Sensor is especially sensitive to the internal refractive indices. The collimated light rays having passed   15 through the overhead microlens will be converging as they reach the upper glass-fluid interface. At this point, they will undergo refraction according to Snell's Law,    , (2)  where nf is the fluid refractive index, ng is the (typically higher) glass refractive index, !g is the glass incident angle, and !f is the fluid transmitted angle.  The light rays propagate through the fluid and strike the lower fluid-copper interface where they reflect according to the Law of Reflection, stating that the incident light ray angle is equal to the reflected light ray angle. Thus, the reflected light rays continue to converge at the fluid transmitted angle !f?albeit in an upward direction toward the overhead microlens. The upward-traveling light rays in the fluid will eventually reach the upper glass-fluid interface and undergo refraction according to Snell's Law in equation (2). The refraction at this interface reverses the light bending induced by the original incident trajectory, and the light rays will travel toward the overhead microlens with an angle that is equal to the original glass incident angle !g.  It is important to note that the above refraction and reflection process will change according to the fluid refractive index nf and its effect on the effective focal length of the overall microlens-cavity system. A lower nf establishes a larger !f for more rapid light ray converging and a reduced effective focal length in the microlens-cavity system. A higher nf establishes a lower !f for slower light ray converging and a longer effective focal length in the microlens-cavity system. The fluid?s refractive-index-induced perturbations to the optical characteristics can therefore act as an effective fluid probe.  Light rays that have passed through the microlens-cavity and exit the overhead microlens are imaged by a bulk lens as a beam profile on a 2-D image sensor. The size of the beam profile on this image sensor, and conversely the beam intensity IOA on this image sensor optical axis nf = ng !sin! gsin! f  16 (OA), can be used to characterize the microlens-cavity system. Short or long effective focal lengths for the microlens-cavity system will result in differing beam profiles and OA intensities. For any given test, the fluid with the highest allowable refractive index for the scan is inserted into the optical cavity sensor, and the overhead bulk lens is adjusted to bring the back-reflected image to a focus on the image sensor. From this point, a reduction in the refractive index will be seen as a broadening of the beam on the image sensor and a resulting decrease in the OA intensity. The bulk lens exists in the system to give one additional degree of freedom. By having two degrees of freedom in the system (the other being the separation distance between the plates), the OA intensity can be calibrated to the refractive index of the initial sample.  For the configuration shown in Fig. 2.3(a), a fluid refractive index of nf = 1.52 is used to pre-align the microlens-cavity system with a sharp focus on the image sensor. Ray-tracing model results are shown in this figure. One can see from the rays in this configuration that the incident collimated rays pass through the overhead microlens and begin to converge. Subsequently, the rays undergo a small change in their convergence angle at the upper glass-fluid interface, reflect off the lower fluid-copper interface, and have their original convergence angle restored as they return upward through the upper glass-fluid interface. The rays then reach a focal point near the microlens. The light rays exiting the microlens are then imaged to a sharp point on the image sensor. This condition is characterized by high OA beam intensity IOA.  For the configuration shown in Fig. 2.3(b), having air as the fluid with a refractive index of nf = 1.00, the ray-tracing model results exhibit a differing response to that of the aforementioned fluid. The incident collimated rays pass through the overhead microlens and reach the upper glass-fluid interface, then undergo a larger change in convergence angle, compared to that of the prior fluid with nf = 1.52. The rays then propagate through the fluid and reflect off the lower fluid-copper interface. The rays have their original convergence   17             (a)      (b)                   (c)  Figure 2.3    The Optical Cavity Sensor, for the digital microfluidic multiplexer, with (a) ray-tracing model results for a fluid with refractive index nf = 1.52, (b) ray-tracing model results for an air fluid with refractive index nf = 1.000, and (c) the applied electro-dispensing process for fabrication of a microlens with a contact angle of !  = 45? and radius of 900 !m.  18 angle restored as they return upward through the upper glass-fluid interface. Notice, in this case, that the light rays exhibit a shorter effective focal length in the microlens-cavity system, compared to that of the prior fluid with nf = 1.52, and reach a focal point well inside the glass superstrate. The light rays then exit the overhead microlens and are imaged on the image sensor. The beam profile seen on the image sensor will have a larger diameter and reduced OA beam intensity IOA, compared to that of the prior fluid with nf = 1.52.  From the descriptions above, it is apparent that a microlens-cavity system can be implemented to establish a relationship between the fluid refractive index and OA intensity on the image sensor. The Optical Cavity Sensor is such a system. The Optical Cavity Sensor is designed to provide the required refractive index sensing capabilities, in terms of sensing range and resolution. This is done by prescribing a customized microlens contact angle. The relationship between the back-reflected beam?s OA intensity on the image sensor, IOA, and the internal fluid refractive index, nf, is precisely set by the contact angle of the microlens.   To demonstrate the dependence between refractive index sensing characteristics and microlens contact angle, ray-tracing model results from a Matlab model are collected for IOA as a function of nf for multiple microlens contact angles. It is found from these model results that there is a dependency between IOA and nf, and this dependency can be appropriately segmented to define an acceptable linear range for refractive index measurements. This linear range for refractive index measurements is defined here as the refractive index operational range, !nf. It is understood that the model results will have some level of deviation from the linear trend, across the refractive index operational range, and a design decision is made to accept a tolerance of 1% for this deviation from linearity. In this way, a resolution is defined for the refractive index measurements, and this refractive index resolution is defined here as a hundredth of the refractive index of the operational range, i.e., !nf = 100 "nf.   With the above definitions in mind for the refractive index operational range and refractive index resolution, ray-tracing model results are collected for a microlens having a relatively small contact angle of ! = 45?. The model results are shown as green triangles in Fig. 2.4 with a corresponding linear trend line shown through these markers. The linear trend line is   19  IOA(nf) = 0.8145 nf - 0.2396 (R2 = 0.9999), (3)  for fluid refractive indices spanning from nf = 1.28 to 1.52. This refractive index operational range, !nf = 0.24, is particularly wide, although it comes at the cost of a coarse measurement resolution, "nf = 0.0024.  The resolution can be improved (i.e., reduced) by using sharper focusing with a higher microlens contact angle. This modified relationship between IOA and nf can be seen for the case of a moderate microlens contact angle of ! = 60?, whose theoretical model results are shown by blue diamonds in Fig. 2.4. Note the increased slope in the linear trend  IOA(nf)= 2.9398nf - 3.4741 (R2 = 0.9973), (4)  with its resulting improvement to (i.e., reduction of) the refractive index resolution, "nf = 0.0007. The fluid refractive indices span from nf = 1.45 to 1.52, so the refractive index operational range, !nf = 0.07, does diminish compared to that of the small contact angle.   Even higher microlens contact angles can be used if one wishes to further improve the refractive index resolution. This can be seen for the case for a large microlens contact angle with ! = 70?, denoted by red squares in Fig. 2.4. The IOA versus nf trend is now  IOA(nf) = 24.13nf - 35.202 (R2 = 0.9965), (5)  and the increased slope dramatically improves (i.e., reduces) the refractive index resolution, "nf = 0.0001. In this case, the fluid refractive indices span from nf = 1.49 to 1.50, so the refractive index operational range reduces to !nf = 0.01. The improved resolutions made available by this technique can be particularly useful for sensitive measurements of chemical kinetics [31] and temperature characteristics where refractive index perturbations of the 0.0005 must be resolved [32].    20   Figure 2.4    Normalized reflected  OA  intensity, IOA , on the image sensor for a sample fluid refractive index nf inside the Optical Cavity Sensor. Microlens contact angles are  !  = 45?, 60?, and 75 ?. Experimental results are shown for the !  = 43? microlens as crosses.   The overall relationship between the microlens contact angle !  and the refractive index range, !nf, and resolution, "nf, is fully characterized by the employed ray-tracing model and the results are summarized by the curve in Fig. 2.5. The refractive index range !nf is shown on the left vertical axis and the refractive index resolution "nf is shown on the right vertical axis, for microlens contact angles spanning 45? to 80? along the horizontal axis. A polynomial trendline   !nf = 2!10-6 !  2 ? 3!10-4 !  + 1.24!10-2 ( R 2 = 0.99687),   (6)    21 is found for this relationship. Note how an increased contact angle offers a finer (i.e., smaller) refractive index resolution, but this comes at the cost of a lower refractive index range.    Figure 2.5    Optical Cavity Sensor refractive index range !nf and resolution "nf are shown as a function of microlens contact angle ! . For large ! , the system has a fine resolution with a small refractive index range. For small ! , the system has a course resolution with a large refractive index range.   It becomes necessary to gauge the level of resolution and range needed for a set of refractive index measurements, and design the microlens system accordingly. For example, high-sensitivity ("nf < 0.0002) measurements of refractive indices can be made with microlens contact angles above !  = 65?, but the refractive index range will be limited (!nf < 0.02). In contrast, low-sensitivity ("nf < 0.0016) measurements of refractive indices can be made with   22 microlens contact angles below 50?, and the refractive index range for these measurements will be especially large (! nf < 0.16).   It is obvious from the prior microlens analyses that customized microlenses are needed to implement the Optical Cavity Sensor. Microlenses are not readily available for purchase, especially when a customized contact angle is required. For this application, both a customized size and contact angle are needed to provide for operation over a user-defined range of refractive indices. This can be provided by a tunable mechanism for the microlens contact angle and resulting optical characteristics. It is necessary to fabricate the microlens in the appropriate location on the digital microfluidic multiplexer. The microlens electro-dispensing system shown in Fig. 2.3(c) can offer this in situ tunable fabrication.   The electro-dispensing technique is used to form the microlens above the on-chip sampling station by dispensing a UV-curable polymer droplet with a metal dispensing tip. The dispensing process is carried out with a pneumatic pressure-based system. Electronic control of the pressure and dispensing times is used to create microlenses with volumes on the scale of nanolitres (limited mainly by the dispensing tip?s inner diameter). After the appropriate polymer volume is dispensed, the shape of the microlens can be adapted by real-time adjustments to the metal dispensing tip voltage, V disp. The dispensed microlens droplet profile is defined by V disp, with respect to a lower grounded copper plate. The electrocapillary response of the microlens droplet is dictated by way of the Lippmann-Young equation,  , (7)  where c  is the capacitance per unit area. Initial conditions with V disp = 0 define the nominal contact angle !0, with "sf, "sl and "lf as solid-filler, solid-liquid, and liquid-filler surface tensions, respectively. Voltage-activated conditions with V disp ! 0 define the user-modified contact angle !( V disp). With a surrounding air filler and glass substrate, the nominal polymer microlens contact angle is especially low and is only reduced further by further by V disp. If cos! V( )  = cos!0 + cVdisp22"lf   = "sf ! "sl"lf + cVdisp22"lf  23 necessary, an appropriate liquid filler (i.e., glycerol) and substrate can be used to increase the nominal contact angle by a careful balancing of the surface tensions.  One can ultimately apply V disp to reduce the contact angle to the desired !( V disp) value. When the desired contact angle is formed, UV-curing is carried out with a 405 nm 10 mW laser over 20 minutes.  To demonstrate electro-dispensing and Optical Cavity Sensor operation, a configuration is prepared for sensing over a wide-range of refractive index measurements. A microlens profile with a contact angle of ! = 45? is chosen for this. A UV-curable polymer Norland Optical Adhesive (NOA) 68 droplet of 1.5 nL volume is dispensed in an air filler onto a polytetrafluorethylene (PTFE) coated glass substrate to form the microlens. The pneumatic electro-dispensing apparatus shown in Fig. 2.6 is used for this process. The dispensing tip voltage is tuned over the range V disp = 300 to 1500 VDC to form the desired microlens contact angle (with real-time viewing on a side-camera). UV-curing is applied when the desired microlens is created with a radius of 900 !m and contact angle of 45?.  The fabricated microlens is part of the Optical Cavity Sensor that is incorporated as a sampling station adjacent to the digital microfluidic multiplexer. This element provides the desired localized optical sensing of fluid refractive indices between the two plates. To determine the fluid refractive index for a broad range of wavelengths, a collimated white LED is used to illuminate the structure. The back-reflected optical beam is then sampled by a beamsplitter and overhead image sensor. An appropriate sequence of multiplexer electrode activations is used to pull the fluid samples into the sampling station where images are captured and refractive indices are calculated.  Tests with well-known refractive indices are used to validate and calibrate the operation of the Optical Cavity Sensor. The OA intensities for this calibration are recorded for water (nf  = 1.33), ethanol (nf = 1.36), and silicone oil (nf = 1.52). Results are displayed as crosses in Fig. 2.4 and are seen to follow the theoretical linear trend for the ! = 45? microlens. Only three experimental results are displayed as limited materials with known refractive indices were   24 available. Experimental results were not done with the other microlenses as the environmental conditions, which would affect the refractive index of the samples while sensing, would be difficult to control. Ultimately, the Optical Cavity Sensor can be used to characterize a wide variety of fluids within the on-chip microdrop motion/sensing system.  The presented Optical Cavity Sensor has potential for refractometry in many biomedical applications. The scalable nature of the multiplexer makes it ideal for operations incorporating bioassays and clinical diagnostics on human urine, saliva, tears, and sweat [33]. The combined multiplexer and refractometry system can be used for biomedical applications such as determining the concentration of hemoglobin in red blood cells [34], determining protein and lipid concentrations with refractometry [35], and measuring concentrations of solutions for cases ranging from distilled to saturated [36].     Figure 2.6    Photograph of the electro-dispensing set-up.     25 Chapter 3 Free-Space Optical Sensing  In the previous section, an on-chip optical detection system was introduced to localize and analyze microscopic samples at desired locations in the 2-D plane of a chip.  In this section, a free-space optical detection system is introduced. With free-space operation over large macroscopic volumes, it is especially challenging to localize microscopic samples for detection. These challenges are addressed.  3.1 Optical Sensing Challenges There are many applications for which one wishes to detect the presence of microscopic elements in large (i.e., macroscopic) 3-D volumes. Consider, for example, the detection of dispersed and microscopic waterborne pathogens within a large volume of water. The challenge can be seen by simple system scaling arguments for a hypothetical macroscopic cube with a volume of L3 = (10 cm)3, where L is the side length. Within this macroscopic cube there exists a microscopic particle, in the form of a cube, that one wishes to detect. This microscopic particle has a volume of l3 = (10 ? m)3, where l is the side length. Optical detection is carried out by illuminating one entrance face of the macroscopic cube with an incident optical power of P0. The optical power striking the microscopic particle is a small fraction of the incident optical power on the entrance face, and this fraction is set approximately by the ratio of face areas of the microscopic to macroscopic cubes. One would expect that a small fraction of the incident optical power, of only P0 ?  l2/L2 = P0 ?  10-8, would illuminate the microscopic particle. The absolute optical power illuminating the microscopic particle would be alarmingly low, as it is only the illuminating power on the microscopic particle that must ultimately be detected. The situation worsens when one considers that the illuminating power on the microscopic particle is further reduced during the reflected light propagation and detection processes.  A hypothetical image sensor, with a representative cross-sectional area of dsens2 = (1 cm)2, would be placed on the entrance face of the macroscopic cube to capture reflected optical power scattered off the microscopic particle. The light that scatters backward off the microscopic particle towards the entrance face and detector will radiate uniformly   26  (approximately) over a hemispherical solid -angle of 2! . Thus, the back-reflected intensity will diminish as the reciprocal of the back-reflected propagation distance squared. In the worst-case scenario, when the microscopic particle is on the macroscopic cube?s face opposite to the entrance face, the back-reflected optical beam must propagate a distance of L . The optical power incident on the detector will be P 0 ?  l 2/ L 2 ?  d 2/(2 ! L 2)  ! P 0 ?  10-8 ?  10-3  ! P 0 ?  10-11. One could imagine that high incident optical powers on the order of Watts would be needed, or even sophisticated phase-sensitive detection schemes [ 37 ] , to bring the signal on the detector to an acceptable level of nanoWatts or higher.  The prior hypothetical analysis accentuates the difficulty of detecting microscopic particles in macroscopic volumes. It is, however, possible to introduce a more sophisticated free-space optical measurement system to minimize the scattered optical power loss during back-reflection. The back-reflected optical power in the previous hypothetical analysis is uncollimated and is radiated over a wide hemispherical solid-angle. Thus, it would be important to detect the back-reflected optical power over a very short propagation distance, by using a microscope for example, but this is not possible with macroscopic systems. Instead, one can incorporate a back-reflection process that maintains the phase of a collimated incident laser beam. Such a process is facilitated by retroreflection if a retroreflector redirects incident light directly back to its source. In this way, the incident collimated optical power that strikes the microscopic retroreflective particle can be made to travel directly back to its source as a collimated beam that is well-confined in the transverse dimensions. Backscattered losses are therefore minimal. One can visualize this retroreflective process for the previous hypothetical analysis by incorporating a laser for the incident optical beam and a large image sensor over the entrance face of the macroscopic cube. The microscopic retroreflective particles will show up as bright points of light on the image sensor. The detected optical power associated with a microscopic particle for this retroreflection scenario can be as high as P 0 ?  l 2/ L 2 ?  1 ! P 0 ?  10-8. This result is 1000 times higher power, compared to that of the original scattered back-reflection scenario.  Given the improved optical signal levels that can be obtained by incorporating retroreflection, such a process will be incorporated into the free-space optical sensing system   27 of this section. Retroreflection has proven to be a useful tool in highly sensitive photodetection applications [38], and the primary motivation for this free-space optical detection work relates to the detection of waterborne pathogens. Certain waterborne pathogens, such as Cryptosporidium, can bring about infection from minute (even single-pathogen, or 1-10 oocysts) concentrations in water [39]. Current tests are required to be run multiple times in order to receive an accurate measure of the pathogens present in the system [40]. It is critical, therefore, to develop a detection system that can resolve microscopic particles/pathogens in macroscopic systems. This detection can be carried out through two discrete steps.  The first step in pathogen detection involves tagging, where a recognition element is used to bond an optical tagging structure to the pathogen of interest. Recognition elements include peptides [41], carbohydrates [42], or aptamers [43], but a particularly effective recognition element is the antibody [44]. An antibody, or immunoglobulin, is a protein that is able to precisely lock onto antigens. The specificity of antigens is an especially effective capability for targeting specific pathogens in the detection process [45]. A retroreflector is an effective optical tagging structure, and it can be readily coated with an antibody. The antibody-activated retroreflector is introduced to a sample to adhere to any targeted pathogens. The overall process is described in detail by Das [46] and the references therein.  The second step in pathogen detection involves free-space optical sensing. The free-space optical sensing process makes use of the retroreflective process described at the start of this section. The macroscopic system is illuminated by a collimated laser source, and the back-reflection from the macroscopic system is monitored by way of an image sensor. The presence of a pathogen, with its antibody-activated retroreflector, will then be seen as a bright pinpoint of light on the image sensor. Such a process can be used to acknowledge the presence of pathogens and/or quantify the level of pathogen contamination. The following sections in this chapter will analyze and improve upon the retroreflective optical sensing process needed for technologies such as pathogen detection.      28 3.2 Back-Reflection Detection System The retroreflector is the key element for the desired free-space optical sensing of microscopic pathogens/particles. The two main structures that can establish retroreflection are the corner-cube retroreflector and the spherical retroreflector. Both of these forms are considered here.   The simplest form of retroreflector is the corner-cube retroreflector shown in Fig. 3.1(a). The corner-cube retroreflector has three reflective orthogonal mirrors lying in the x , y , and z  planes. A ray of light entering this corner-cube along the vector !i = - r x!- r y! - r z!, will have the three orthogonal mirrors flip the respective signs of the x , y , and z  components. The resulting ray vector for the retroreflected beam will be !r = + r x! + r y! + r z!. This retroreflected beam can then travel directly back to the optical source. The corner-cube retroreflector is a practical element for retroreflection applications operating over a broad wavelength range, as reflective mirror surfaces can be made to have little wavelength dependence. The corner-cube retroreflector is a simple solution for large-scale retroreflecting, such as surveying, where a user can easily control the corner-cube orientation. One could imagine, however, that intricate applications such as microscopic back-reflection monitoring, which do not easily allow the user to reorient the corner-cube toward the incident illumination direction, may fail to retroreflect if the corner-cube is not facing the incident light direction. The angular directionality of the corner-cube retroreflector must be carefully considered.   A different form of retroreflector, the spherical retroreflector, can be used for improved directionality. A spherical retroreflector is shown in Fig. 3.1(b). The refractive index of the sphere is n and its diameter is d  = 2r , where r  is the radius. The circular profile of the sphere in the displayed x - z  plane is defined by x 2 + z 2 = r 2. The coordinate z -axis is aligned along the OA, and a light ray is incident on the sphere at a distance x  off the OA. The sphere can be made to retroreflect if it can transform the incident ray vector  !i = + ! into the desired retroreflected ray vector !r = - ! .  This retroreflection can be accomplished through an appropriate sequence of refraction and reflection at the sphere?s perimeter. The incident light ray first undergoes refraction at the front surface of the sphere and is bent towards the OA. The internal light ray then propagates through the sphere and strikes the rear surface exactly at the OA. At this point, the light ray is reflected and follows a mirrored traject ory, with   29 respect to the OA, back through the sphere. When the internal light ray strikes the front surface of the sphere, it undergoes refraction and exits antiparallel to the incident light ray. The retroreflected beam is then prepared for its ultimate return to the source.    (a)  (b)  Figure 3.1    Retroreflection for (a) a corner-cube retroreflector and (b) a spherical retroreflector.     30  The critical design variable for this spherical retroreflection is the sphere?s refractive index n . The refractive index must be carefully chosen to have the incident light ray refract at the front surface of the sphere and precisely strike the rear surface at the OA. Consider this condition for the case of a sphere surrounded by air with a refractive index of n 0 = 1. The incident light ray refraction at the front surface of the sphere is characterized by Snell's Law with n 0sin! n = n sin! t, where the incident angle ! n and transmitted angle ! t are both defined with respect to the surface normal at the ( z , x ) point of incidence. For a light ray being close to the OA, according to the so-called small-angle paraxial approximation, Snell's Law can be cast as ! n ! n ! t. An implicit derivative can then be taken of the x 2 + z 2 = r 2 expression describing the perimeter of the sphere and evaluated at the point of incidence to yield a tangential slope of d x /d z  = - z / x  and a normal slope of -dz /d x  = x / z  = tan! n ! ! n. The paraxial Snell's Law result, ! t ! ! n/ n , can then be used with the normal slope result, ! n ! x / z , to define an internal slope for the ray of tan( ! n-! t) ! ! n-! t ! x / z  - x /( nz ) = (1 -1/ n ) x / z ! (1 -1/ n ) x / r . If one wishes to have the internal ray strike the rear surface at the OA, this internal slope should have a rise of x  over a run of approximately 2 r , giving the final condition for spherical retroreflection:    . (8 )   Thus, it is possible to achieve spherical retroreflection by having a sphere with a refractive index of n  = 2. It should be mentioned, however, that this is an especially high refractive index and can be challenging to obtain.  The retroreflection characteristics are analyzed and improved in the following subsections through a series of geometry, shape, material and imaging refinements.  3.2.1 Geometry Refinement The corner-cube and spherical retroreflectors will be characterized in this subsection according to their geometrical forms. Corner-cube retroreflectors are the most common 2and,211 ==!"#$%&' nrxrxn  31 retroreflector and have even been recently applied by Rony Das [46] as antibody-activated retroreflectors in a water quality monitoring system.   The greatest concern for a corner-cube retroreflector is its limited directionality. It is possible for incident light rays to illuminate a corner-cube along one of its non-reflective surfaces (i.e., not enter the three-sided reflective corner). This angular directionality is shown in the ray-tracing model results of Fig. 3.2, by way of the reflected OA intensity [47]. The corner-cube retroreflector has mirrored surfaces in the x, y, and z planes. Incident light is directed into the corner-cube along a polar angle ! = acos(1/!3) " 54.7? defined off the z-axis, while the azimuthal angle is varied from " = 0 to 90?. The azimuthal angle is defined off the x-axis in the x-y plane. Note how the reflected OA intensity, IOA, is at a maximum for " = 45? and ! " 54.7?. It is at this point that the incident light rays enter the corner-cube structure along the vector !i = -rx!-ry! -rz! = -!-! -! and retroreflect along the vector !r = +rx!+ry!+rz!! = +!+!+!. This balance point is the alignment for maximum retroreflection. Small deviations of the alignment off this balanced point reduce the reflected OA intensity. Large deviations of the alignment off this balanced point, outside of the range of 0? < " < 90? and 0? < ! < 90?, offer no retroreflection. Clearly, the directionality of the corner-cube is a concern if reliable single-retroreflector/pathogen detection is desired.  The ideal solution to the retroreflection directionality problem of the corner-cube can be found by introducing spherical geometry. The sphere, by its very definition, has complete symmetry over its 4!  steradians solid-angle. This perfect directionality is apparent by way of the normalized retroreflective OA intensity, IOA, shown in Fig. 3.2. The spherical geometry can retroreflect for all incident angles, 0? < " < 360? and 0? < ! < 180?. There are, however, challenges for introducing spherical retroreflectors, in terms of their shape and material. The necessary shape refinements and material refinements are addressed in the following two subsections.     32   Figure 3.2    Normalized reflected OA intensity, IOA, for retroreflection from a corner-cube retroreflector and a spherical retroreflector. The polar angle is kept constant at ! = acos(1/!3) " 54.7? The azimuthal angle "  is varied. Adapted from Collier et al. [47].   3.2.2 Shape Refinement In the previous section, it was determined that a spherical structure is an ideal geometry to offer complete and uniform directionality. However, it can be difficult to fabricate microscopic retroreflectors that have sufficiently spherical shapes [48]. This shape refinement is addressed here. A new method is examined for creating polymer spheres.  Polymer spheres are created using a modified version of the electro-dispensing technique introduced in section 2.3. Instead of dispensing the polymer volume onto a flat surface, the polymer is dispensed within a glycerol filler fluid. The surface tension of the filler allows the polymer to form a spherical shape while staying suspended in the middle of the container. The dispensing tip is raised during the dispensing process to allow the polymer to form a   33 freely-floating polymer sphere in the middle of the filler fluid. (The glycerol is kept at a well-controlled temperature below room temperature until it is poured into the container for dispensing the polymer, as this gives an optimal and reproducible surface tension to keep the spheres suspended.) Once the dispensing tip is removed from the fluid, the container is exposed with UV light to solidify the polyme r. A 365 nm UV exposure is used for 25 minutes. The contents of the container are then poured over a filter to separate the spheres from the filler fluid. The polymer spheres are rinsed with deionized (DI) water to remove glycerol and baked in an oven for one hour to bake off excess water.  The modified electro-dispensing technique offers control of the sphere?s shape through careful selection of the dispensing tip gauge (size) and material. If a high gauge tip is chosen, with smaller inner diameter, the dispensed volume is decreased. If a low gauge tip is chosen, with larger inner diameter, the dispensed volume is increased. Further control is added by preferential selection of the dispensing tip material. The most common dispensing tip is made out of a stainless steel, but PTFE lined dispensing tips are chosen here for creating the polymer spheres. This is due to the surface tension of the polymer adhering to metallic tips. A PTFE needle tip with a gauge of 22 is chosen for the following analysis.   Further control of the modified electro-dispensing technique can be achieved through the dispensing pressure and time. These two variables can be used to dispense the desired sphere volume. The dispensing time, t disp, is set as 5 seconds for all of the following experiments, allowing for the diameters to be controlled only through changes in the pressure. A complete characterization of the polymer sphere diameter versus pressure is carried out and the results are shown in Fig. 3.3. The polymer sphere diameters are measured using a Zeiss stereoscope with negligible measurement error. For each pressure value, a minimum of five spheres are created and the diameters are displayed with the minimum, maximum, and average values shown in Fig. 3.3. As the pressure is increased from P disp = 2.5 PSI up to P disp = 15 PSI, polymer spheres are created with diameters ranging from d  = 1.5 mm up to d  = 3.6 mm. Representative spheres are shown as photos in the insets. A linear trend is immediately apparent for the results, with the diameter d  following the trendline equation,    34  d  = 0.163  P disp + 1.0877 ( R2 = 0.97498).  (9 )   The modified electro-dispensing technique demonstrates excellent precision, with a percent error of less than 5% over the course of fabricating a set of polymer spheres.   Reproducibility and accuracy acco rding to the linear equation (9 ) can be maintained over time by minimizing dispensing tip clogging (by rinsing the tip) and keeping the unit covered from UV light while not in use. An automated actuation m echanism, to routinely withdraw the dispensing tip after dispensing the volume, would also assist the reproducibility.     Figure 3.3    Diameters, d , of the dispensed polymer sphere as a function of the dispensing pressure, P disp. Dispensing time for all results is 5 seconds. The PTFE needle tip has a gauge of 22. The corresponding linear trendline curve fit is shown. Representative photos of polymer spheres are shown as insets.     35  3.2.3 Material Refinement An effective spherical retroreflector must be fabricated with control over both its shape (as in the previous section) and its material (as shown here). Equation (8) showed that a spherical retroreflector must have a refractive index that is sufficiently close to n = 2. Unfortunately, it is very difficult to find a UV-curable polymer with this high of a refractive index. (Polymers would be an ideal material for tagging as they can be doped for enhanced signal extraction via spectral filtering.)  One way to increase the refractive index of these polymers is to select an appropriate wavelength for the illumination. As a general rule, given normal dispersion, the refractive index increases as the wavelength decreases. With this in mind, a series of UV-curable polymers from Norland Optical Adhesives (NOA) are considered and characterized. The refractive indices for NOA 61, 63, and 68 are shown in Fig. 3.4. NOA 68 is the standard high refractive index UV-curable polymer, but its refractive indices are still unacceptably low across the entire wavelength range. To proceed with the retroreflection study, the NOA vendor was contacted to request a polymer with as high of a refractive index as possible. NOA 1625, with a refractive index of n = 1.625, was developed and supplied for testing. Although this refractive index is not at the ideal value, it is used further in this study to determine the degree to which it can be used for retroreflection in this free-space optical sensing system.  To provide an analysis of free-space optical sensing with higher refractive indices, it is necessary to move to a different material system. The refractive indices made available by polymers are simply too low. Instead, glasses are chosen as high refractive index materials. The glasses LaSFN9 and BaTiO3 are chosen as suitable materials for microspheres. LaSFN9 has a refractive index of n = 1.85 [49] and BaTiO3 has a refractive index of n = 2.04 [50], at a wavelength of !  = 405nm. These glass microspheres are available for purchase in bulk quantities with diameters ranging from 5 ? m ? 1000 ? m, and the refractive indices for these materials are shown with in Fig. 3.4. Both glasses are viable materials for the spherical retroreflection and will be used and compared with the NOA 1625 polymer for the free-space optical detection system.    36  To obtain the desired high refractive index of n = 2, it is possible to select an appropriate wavelength to increase the refractive index. As the wavelength in the system is decreased towards the UV range, the refractive index of a material increases. For this reason, the wavelength of !  = 405nm is chosen for the detection system. This is shown for the previously mentioned NOA polymers and optical glasses in Fig. 3.4. The data for the NOA polymers was obtained directly from NOA [48], and the data for the glasses was obtained through online resources [49, 50].   Figure 3.4    The refractive index n as a function of wavelength, ! , for four NOA polymers (61, 63, 68, and 1625) and two glasses (LaSFN9 and BaTiO3). The refractive indices quoted in this graph are at a temperature of 25? C, [49-51].   Analyses are ultimately needed to determine the level at which a sphere?s refractive index can provide sufficient retroreflection. As the refractive index of a sphere decreases below n = 2, the retroreflected beam diverges away from the OA to give an increased beam area (and decreased intensity) on the image sensor. It then becomes necessary to incorporate corrective   37  lenses to collimate the retroreflected beam in the setup, which now resembles a hybrid between a free- space optical sensing system and a microscope. Sharp  images are only formed with a sufficiently high magnification? at the cost of a reduced sampling area. These analyses will be carried out in the following subsection, imaging refinement.  3.2.4  Imaging Refinement  Now that the geometry, shape, and material have been refined, it is important to examine imaging for the system. Fig. 3.5 shows such a system by way of an optical system model, schematic, and photo.  The optical system model is presented in Fig. 3.5(a) as a simplified version of the actual experiment schematic shown in Fig. 3.5(b). A mirror is used in the model to represent the sample. In the model, a lens with an effective focal length of f1 is positioned along the horizontal axis at  a distance of s, the working distance, from the mirror. This first lens has an effective focal length, as it characterizes the focal characteristics of two bulk lenses that lie in front of the image sensor in the schematic of Fig. 3.5(b). The second lens in the optical system model, with a focal length of f2, is positioned at a distance of d/2 from the mirror, where d is the diameter of the retroreflecting sphere. This second lens represents the focusing characteristics of the retroreflecting sphere. The focal length of this second lens is   f2 = d 4 n( n ! 1 ) . (10 )  Note that the ideal sphere with n = 2 will have f2 = d/2.  Under this condition, the first lens can be removed from the system, and incident light rays traveling parallel to the OA will focus at the intersection of the OA and mirror. This ideal focus will allow the back - reflected rays to return back through the optical system model anti - parallel to the incident rays and strike the image for optimal retroreflection .    38   (a)     (b)    (c)   Figure 3.5    The free-space optical sensing configuration as an optical system (a) model, (b) schematic, and (c) photo. The first lens with focal length f 1 in (a) is the effective focal length of the two combined lenses with focal lengths f 1a and f 1b shown in (b) and (c). The second lens, with the focal length f 2, models the focusing characteristics of the sphere on the sample surface. The mirror in (a) models the reflection at the sample.  39  This optical system model can be used to determine the focal length of the first lens that is needed to compensate for less than ideal sphere refractive indices (n < 2). When the refractive index is decreased below n = 2, the rays entering the sphere (i.e., second lens) do not focus on the OA at the mirror surface. Then when the back-reflected rays exit the sphere on their return path towards the image sensor, they will diverge at a finite angle away from the OA. The further below n = 2 the refractive index is, the greater this divergence will be.   Such divergence will require greater magnification by the first lens in the optical system, and this will require a greater optical power, D1 = 1/ f1, for the first lens. The resulting optical powers for the first lens, D1, are shown for refractive indices varying from n = 1.55 to n = 2.0 in Fig. 3.6. It is important to note that the highest refractive index, n = 2.0, requires an optical power of D1 = 0, corresponding to an infinite focal length for the first lens, and thus no magnification is needed for this ideal case.  As the refractive index is decreased, however, it becomes necessary to introduce higher optical powers and greater magnifications for the first lens. When the refractive index is reduced from n = 1.85 to n = 1.55, for example, the optical power of the first lens must increase by 2.3 times, and thus there would be a corresponding decrease in the sampling diameter of approximately 2.3 times.  The free-space optical sensing is implemented by way of the schematic shown in Fig. 3.5(b). The incident laser source has a wavelength of 405 nm. The incident beam first passes through a 50/50 cube beamsplitter. A plate beamsplitter was originally used but resulted in ghost, i.e., overlapped, images disrupting the actual retroreflected results. The cube beamsplitter is chosen with antireflective coatings on the four surfaces of the cube to minimize ghost images. A 50/50 ratio is chosen for the beamsplitter to result in the lowest amount of powerloss, considering both forward-propagating and back-reflected rays.  Two lenses are placed in the middle of the setup to act as the first lens, with an adjustable effective focal length, in the optical system model. The lens closer to the source has a focal length of f1a = 25 mm, and the lens closer to the sample has a focal length of f1b = 50 mm.   40 The use of these two lenses allows the back-reflected image on the image sensor to be brought into sharp focus, by adjusting the two lens positions, d 1a and d 1b. If the refractive index of the sphere is altered, the distances between the lenses can be adjusted to maintain focused beam intensities on the image sensor. In general, refractive indices closer to n = 2 will require weaker effective focusing by f 1a and f 1b, offering larger sampling diameters.    Figure 3.6    Normalized first lens optical power, D1 = 1/f1, displayed as a function of refractive index, n, for the optical model with macroscopic results in red and microscopic results in blue. The lens optical power is a measure of the magnification required in the optical system, where a larger magnification leads to a smaller sampling diameter. The photo insets show experimental results for the (a) polymer macrosphere, (b) glass macrosphere, (c) glass microspheres, and (d) corner-cube retroreflectors.   The complete optical system for the experimental setup is shown in the photo of Fig. 3.5(c). Images are taken by the image sensor and viewed on a laptop. The image sensor is a Lifecam VX-2000. The device uses Video Graphics Array (VGA) Complementary Metal Oxide Semiconductor (CMOS) sensor technology and has a resolution of 1.3 megapixels. The   41  dimensions of the image sensor are 3.24 x 4 mm2, although the entire area of the image sensor is not applied for each scan. The complete optical system is tested through a series of macroscopic and microscopic investigations.  The lens optical power, D 1 , is used to determine the approximate sampling diameter available on various samples. As the lens optical power is decreased, the magnification is similarly decreased in the system, resulting in a larger sampling diameter with less scanning times. Macroscopic Investigation A polymer macrosphere of diameter d = 3.0 mm, created with P disp = 12.5 PSI,  and refractive index of n = 1.625 is selected for the first experiment. A back - reflected image for this polymer macrosphere is shown in the inset of Fig. 3.6 . Although the retroreflection is easily seen for this one macrosphere, significant focusing is required by f1a  and f1b , resulting in a lens optical power of D 1  = 0.87 . This large optical power, corresponding to a high magnification, leads to a reduced field of view on the sample and ultimately an increased scanning time across the sample. At the same time, it is difficult to obtain a sharp image with an appreciable and well- defined intensity.  Next, a glass macrosphere with a diameter of d = 3.0 mm and a refractive index of n = 1.835 is chosen to match the size of the polymer macrosphere from the first experiment. The retroreflection image as seen on the detector is shown as an inset in Fig. 3.6 . The higher refractive index of the glass macrosphere reduces the divergence of the back - reflected rays and ultimately results in sharper images with higher signal intensities and a larger sampling diameter. The resulting lens optical power for this system is D 1  = 0.42, as shown in Fig. 3.6. The reduced optical power of this first lens increases the field of view for the glass macrosphere, compared to that of the polymer macrosphere, and ultimately results in reduced sample scanning times.     42 Microscopic Investigation Two micron-sized retroreflector forms are examined: corner-cube retroreflectors and glass microsphere retroreflectors.  Glass microspheres are tested to characterize the retroreflector response. The glass microspheres are a material similar to BaTiO3 and have refractive indices of approximately n = 1.9 [52] and diameters of d = 53 - 63 ? m, as introduced in subsection 3.2.3. The resulting back-reflection image for these elements is shown in the left inset in Fig. 3.6. The optical lens power is D1 = 0.30, which is lower than D1 = 0.87 for the polymer macrosphere and D1 = 0.42 for the glass macrosphere. This results in a much lower required magnification than for both of the polymer macrospheres.  Corner-cube retroreflectors are tested next. The corner-cube retroreflectors used in this experiment are made by Ruchhoeft et al. [38]. The resulting retroreflection from the corner-cube retroreflectors is displayed as an inset at n = 2.0 in Fig. 3.6. The lens optical power, D1, is approximately zero for this sample, resulting in minimal required magnification.  One difficulty that is not apparent when looking at the optical lens power is the ability to consistently detect all retroreflectors on a slide. The reliability of the observed intensity for the corner-cube retroreflectors is sacrificed by the directionality problem described in subsection 3.2.1. This problem became quite apparent while trying to image multiple retroreflectors, each of which had its own directionality dependence (and therefore different intensities on the image sensor). The exact amount of retroreflectors missed during imaging was indeterminable, as the location of retroreflectors was difficult to place. Imaging multiple retroreflectors on one slide became significantly easier with the glass microsphere retroreflector samples. As shown in subsection 3.2.2, the spherical retroreflector has no directionality associated with it, allowing for the detection of all of the retroreflectors present on the slide, independent of their orientation. Therefore, although the microspheres require slightly higher magnification than that of the corner-cubes, the glass microspheres are the ideal retroreflector for optical free-space imaging.   43  Differential Imaging Technique  Although the results for the micron-sized glass microspheres yield significant improvements for back-reflected signal intensity, it is important to note that the signal-to-background ratio is the real figure-of-merit for free-space optical sensing. Background intensity appears as diffuse light on the image sensor by way of scattering from non-retroreflective sources, such as mounts, defects, interfaces, and ambient lighting. These diffuse sources reduce the signal-to-background ratio.  To improve the signal-to-background ratio for free-space-optical sensing, a differential optical imaging technique is introduced. The differential imaging technique is illustrated through a series of intensity profiles and retroreflected signals in Fig. 3.7. The images in Fig. 3.7(a) show a single retroreflected signal (the original image) and a retroreflected signal upon shifting the sample (the shifted image). It is important to note that the retroreflected intensity patterns are collimated, thus the corresponding pattern on the image sensor coming from retroreflectors on the sample surface will shift on the image sensor as the sample is shifted. In contrast, uncollimated intensity on the image sensor, having scattered from objects other than retroreflectors, will not shift on the image sensor as the sample is shifted. Because of this distinction between retroreflected and non-retroreflected intensity patterns, it is possible to construct a differential image with the scattered intensity background removed, leaving the retroreflected intensity patterns. This is done by creating a differential image, shown in Fig. 3.7(b), as the absolute value of the difference between the original and shifted images. This process removes the unshifted background and creates a pair of retroreflected signal intensity patterns on the differential image. A full-scale example of this differential imaging technique is shown in the results of Fig. 3.7(c).   For the images shown, the original signal-to-background was 6 dB and increased to 12 dB for the differential imaging technique. With this technique, it becomes possible to reduce the background intensity and create pairs of retroreflected signal intensities that can be easily recognized by image/pattern recognition algorithms.     44    Figure 3.7    The differential imaging technique is presented with unitless intensities on the OA displayed for the signals and the resulting photographs are shown as insets. The original and shifted images are displayed, with a horizontal distance in between the two images in (a). These two signals are differenced in (b) to show the differential image. This is shown in a sample image processed in Matlab with glass microspheres in (c). This sample shows 11 different glass microspheres on a slide where the red/left dot is the original image and the green/right dot is the shifted image.     45  C hapter 4 Conclusion s and Future Work   An on-chip optical sensing system was introduced for localized on-chip operation. An Optical Cavity Sensing system was fabricated and demonstrated for the sampling of internal fluid refractive indices. The microlens system was designed and characterized to establish the desired relationship between the back-reflected intensity and fluid refractive index. It was found that user-defined refractive index ranges and resolutions could be obtained by tuning of the microlens contact angle. An electro-dispensing technique was used for this in situ tuning. The resulting system was able to offer practical advantages for fabrication and operation of on-chip optical sensing systems.  Future work for this project would involve complete system integration. It is necessary to integrate the actuation and sensing systems of the presented on-chip technology. Further testing could be done in a controlled environment for the high contact angle microlenses to obtain further experimental data.  A free-space optical sensing system was also introduced for sensing micron-sized particles. Refinements were made to the geometry, shape, material, and imaging characteristics for the free-space optical sensing system. A corner-cube retroreflector was initially examined, although the inherent directionality was not ideal for high-sensitivity imaging. A modified electro-dispensing technique was then used to create polymer macrospheres. These elements did not have a sufficiently high refractive index to create sharp and well-defined back-reflected intensities, so other materials were explored. A glass macrosphere and microsphere were examined. It was concluded that a glass microsphere made of BaTiO3 was ideal as it offered an exceptionally large sampling area with well-defined back-reflected images. An imaging refinement technique based on differential imaging was then applied to further increase the signal-to-background noise from 6 dB to 12 dB for the images. Overall, the work presented here effectively quantified the advantages and disadvantages of various retroreflector-based sensing systems, and this information was used to refine the overall operation of a free-space optical sensing system.    46  Similar to that of on-chip sensing, it is necessary to package the free-space optical system for reliable use by operators. This would require merging with other processes, such as pathogen capture and tagging. To improve the process by decreasing the time for analysis, a computer program could be developed for image processing to record and count the detected pathogens. Applications such as pathogen detection can see especially significant benefits from the presented work, as such applications often require a single-pathogen detection limit?a capability that is not always possible with contemporary technology.  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Kolusheva, ?Carbohydrate biosensors,? Chem. Rev., vol. 104, pp. 5987-6015, 2004.    52 [43] S. Tombelli, M. Minunni, and M. Mascini, ?Analytical applications of aptamers,? Biosens. Bioelectron., vol. 20, no. 12, pp. 2424-2434, 2005.  [44] P. J. Conroy, S. Hearty, P. Leonard, and R. J. O?Kennedy, ?Antibody production, design and use for biosensor-based applications,? Semin. Cell Dev. Biol., vol. 20, pp. 10-26, 2009.  [45] A. Wiseman, "Designer enzyme and cell applications in industry and in environmental monitoring," J. Chem. Tech. Biotech., vol. 56, no. 1, pp. 3-13, 1993.  [46] R. Das, ?Cryptosporidium detection through antibody immobilization on a solid surface,? M.A.Sc. Thesis, University of British Columbia, Kelowna, BC, Can., 2010.  [47] C. M. Collier, X. Jin, J. F. Holzman, and J. Cheng, ?Omni-directional characteristics of composite retroreflectors,? J. Opt. A-Pure Appl. Op., vol. 11, 085404(1-10), 2009.  [48] B. E. Bernacki, N. C. Anheier, K. Krishnaswami, B. D. Cannon, and K. B. Binkley, ?Design and fabrication of efficient miniature retroreflectors for the mid-infrared,? SPIE Defense & Security Conference 2008, Infrared Technology and Applications XXXIV, vol. 6940, paper 6940-30, 2008.  [49] SUMITA ?Optical Glass Data Book,? Version 8.01, 2011.  [50] M. Wohlecke, V. Marrello, and A. Onton, ?Refractive index of BaTiO3 and SrTiO3 films,? J. Appl. Phys., vol. 48, pp. 1748-1750, 1977.  [51] E. Norland, ?Re: Refractive index at different wavelengths,? Message to Jacqueline Nichols, 3 June 2011. Email.  [52] E. Titmus, ?Re: Inquiry about Cospheric products,? Message to Jacqueline Nichols, 18 February 2013. Email.    53 Appendices Appendix A: Conductance Sensing  Conductance sensing on the multiplexer was first demonstrated by Nichols et al., and the principle is demonstrated here. Conductance sensing is carried out by taking the appropriate measurements of differential conduction current flow between the M row electrodes and N column electrodes. The conductance sampling algorithm then follows the flowchart in Fig. A.1. In this flowchart, Gx is the sum of conductance values in the x-direction, Gy is the sum of conductance values in the y-direction, Gxy is the measured 2-D discrete conductance distribution, and Gt is the total conductance associated with the microdrop. The functional forms of these conductance values are as follows:   ,  ,  , (1)  where m and n are the number of electrodes in the x- and y- directions, !  is the finite conductance of the electrolyte, w is the width of the conductive electrodes, d is the distance of the fluid actuation layer, Lx and Ly are the lengths in the x- and y-directions, respectively, and At is the total area of the microdrop covering areas of overlapped electrodes. The maximum possible conductance, Gmax, is defined as  . (2) Gx = Gxy=y = 1n! ! wd "Lx = Gmax "LxwGy= Gxy=x = 1m! ! wd "Ly= Gmax "LywG t = G y =y = 1n! G x =x = 1m!  G m a x " A tw 2 G max = ! w 2d  54  The dimensionless and normalized summed conductance values are given by gx for the x-direction, gy for the y-direction, and gt for the total conductance, where  ,  ,  . (3)  The respective central x- and y-coordinates of the microdrop on the grid are denoted by   ,  , (4)  and the radius of the microdrop is denoted by   . (5)  Further details for the full conductance algorithm are given in Nichols et al..  Representative experimental results from utilizing this conductance sampling algorithm are shown in Fig. A.2. The device used for this analysis incorporated M = 40 linear row electrodes on the top plate and N = 40 linear column electrodes on the bottom plate, each with a width of w = 200 ? m and a centre-to-centre pitch of p = 400 ? m. A central gap gx = G xG m a xgy = G yG m a xg t = G x yG m a xx 0 = x !g xg tx = 1m"y 0 = y !g yg ty = 1n"r 0 = 1! ! gt  55 separates the upper and lower plates at a distance of d g  = 150 ? m. These electrodes are patterned utilizing ultraviolet (UV) photolithographic exposure followed by FeCl wet etching. Two microdrops are presented in the experiment of Fig. A.2(a) with the Matl ab algorithm results in Fig. A.2(b). The extracted overhead view from the M atlab model is shown in Fig. A.2(c). It can be seen that the spatial resolution is well-suited for the given size of electrodes and microdrops in the experiment.      Figure A.1    A flowchart of the conductance sampling algorithm. The digital microfluidic multiplexer prototype carries out this algorithm to extract the fluid conductance distribution.      56    Figure A.2    Results for two microdrops within the digital microfluidic multiplexer as (a) experimental results of the conductance across the device, (b) the extracted microdrop model from the Matlab simulation, and (c) the extracted microdrop model from the Matlab simulation as viewed from overhead.      57  Appendix B : On- chip Digital Microfluidic Architectures for Enhanced Actuation and S ensing   Selected content from J. Nichols, C. M. Collier, E. L. Landry, M. Wiltshire, B. Born, and J. F. Holzman, ?On -chip digital microfluidic architectures for enhanced actuation and sensing,? J. Biomed. Opt., vol. 17, no. 6, pp. 067005(1 -7), 2012.    On- chip digital microfluidic architectures for enhanced actuation and sensing  1. I NTRODUCTION  For many contemporary analytical technologies there exists a desire for reconfigurability or even real-time adaptive processing? features that are not compatible with permanently etched or micromachined fluid flow structures. In response, digital microfluidics has emerged to meet these adaptability requirements.6,7,8  Digital microfluidic systems employ programmable voltage-induced actuation of discrete fluid microdrops with independent control applied over a two-dimensional (2-D) electrode plane (ideally). The generalized nature of this digital architecture, along with the adaptability of the voltage-induced electrohydrodynamic actuation process,9 makes such a reconfigurable system highly advantageous. The 2-D layout can be programmed for user-defined analytical tasks, while adaptive control can be implemented to provide real-time fault detection, path planning, and process scheduling.10 Comprehensive details on digital microfluidics can be found in the work of Berthier 11 and a recent review by Jebrail and Wheeler 12.  A primary challenge for 2-D digital microfluidics relates to actuation scalability? defined here as the need for complete 2-D fluid actuation with fine spatial resolutions and numerous inputs. Generalized actuation is achieved with digital microfluidic stru ctures incorporating 2-D square-electrode grids with M rows and N columns. This becomes impractical in large grids, though, as M ! N input electrical address lines are needed to apply voltages to all M !   58 N  electrodes without overlapping, crossing or shorting address lines. Such 2-D grids have been restricted, therefore, to sizes on the order of 2 ! 4.13 (Multi-level topologies with electrical via holes14 are typically avoided due to their increased fabrication costs and photolithographic complexity.) Ideally, one must ease electrical addressability constraints and reduce system inputs to facilitate actuation in complex digital microfluidic architectures. Section 2 of this work builds upon our prior digital microfluidic multiplexer15 to ease these addressability constraints by way of a bi-layered linear electrode structure incorporating lower rows and upper columns. This system can actuate microdrops at all M ! N  = 14 ! 14 = 196 grid locations with only M + N  = 14 + 14 = 28 electrical inputs through differential voltage biasing with AC voltage waveforms on the upper and lower electrodes having opposite polarities. The design presented here is adapted for practical operation at a 0.64 Vrms level?being well below the 5 V limit for the ultimate application to transistor-transistor logic (TTL) and low-voltage CMOS technologies.16  2. ACTUATION Digital microfluidic devices employ distributed electrode structures to create spatial voltage distributions and actuate internal fluids. The generalized electrode geometry for accomplishing this is the 2-D square electrode grid structure.21,22 Such a system offers complete microdrop control at all M  ! N  grid locations but suffers from addressability issues when scaled to large M  and N  values. All M  ! N  electrical input lines must be routed from off-chip contact pads to internal electrodes, between electrode gaps in the 2-D plane, and such address lines can become unwieldy to implement without crossing, overlapping or shorting.  To enhance actuation and ease 2-D digital microfluidic addressability constraints, an innovative cross-referenced structure was introduced by Xiao et al.23 The cross-referenced structure uses orthogonal and separated upper and lower linear electrode arrays, thus 2-D horizontal and vertical microdrop motion can be induced between these upper and lower electrodes. This technique can be scaled for use with a large M  ! N  grid, as the linear   59 electrodes act as both the actuation electrodes and addressing lines, and only M  + N  inputs are needed. Unfortuna tely, the reduction of inputs can lead to the multi-microdrop interference phenomenon when multiple microdrops are present. The applied upper and lower electrode voltages needed to move one microdrop could inadvertently actuate other microdrops along the activated electrodes. Path planning, 10 routing,24 and graph theory scheduling25 have all been proposed to alleviate this multi-microdrop interference effect.  In this work, the cross-referenced layout is extended for use with low-voltage differential AC voltage biasing. The resulting digital microfluidic multiplexer gives complete M  ! N  addressability in the 2-D on -chip plane with only M  + N  inputs and no observable multi-microdrop interference. Positive and negative voltage polarities are applied via phase -shifts to lower and upper electrodes, respectively, establishing a trinary input state of differential voltage amplitudes between the upper and lower electrodes on the 2-D grid: i. grid locations along unactivated upper or lower electrodes are grounded; ii . grid locations along activated upper or lower electrodes, excluding activated electrode crosspoints, have a differential voltage equal to the applied voltage amplitude; iii. activated electrode crosspoints have a differential voltage equal to twice the applied voltage amplitude. This trinary state of differential voltages can then be used in tandem with the well-known threshold voltage phenomenon26 to initiate motion of a single microdrop in the 2-D plane at the activated electrode crosspoint. The applied voltage is selected to be less than the threshold voltage and greater than one-half the threshold voltage to allow only this doubled-voltage crosspoint to overcome the threshold.  Threshold-based differential actuation can be implemented in a practical design through the use of voltage-transformed AC waveforms. Microdrop motion occurs at lower voltages for AC waveforms, and the low current draw through insulating device layers allows for especially low input voltages, V in(0?), on the primary side of the vo ltage step-up transformer. To form out-of-phase AC voltage waveforms for the differential voltage actuation technique, a centre-tap transformer is used. The resulting AC -actuated digital microfluidic multiplexer is shown in Fig. B .1. Positive -polarity waveforms defined by V 0(0?) are directed from the   60 secondary side of the transformer to the desired ith lower electrode row with an i-phase-switch, while negative-polarity waveforms defined by V0(180?) are directed from the secondary side of the transformer to the j th upper electrode column with a j -phase-switch. The applied voltage amplitude V0 is linked to the threshold voltage Vth through the inequality Vth/2 < V0 < Vth. A V0  value in this range will initiate microdrop motion only at the one desired activated electrode crosspoint.  To quantify the microdrop motion with activation the ith lower row electrode and j th upper column electrode, it is necessary to link the differential voltage Vij  at the (i, j ) crosspoint to the local modified fluid surface tension ! !  with27            (1) where c is the capacitance per unit area. For a small differential voltage, Vij  ! Vth, there is insufficient electric field to induce microdrop motion; for a larger differential voltage, Vij  > Vth, the local electric field creates a non-zero modified surface tension, ! ! , inducing the desired microdrop motion. Such actuation localization is apparent from a comparison of the fluid?s modified surface tension distribution in a system with negligible th reshold voltage, Vth = 0 (Fig. B .1 left inset), and a system with finite threshold voltage, Vth " 0 (Fig. B .1 right inset). Note that there exists the possibility for motion along all activated electrodes in the left inset, while the possibility for motion is localized to the activated electrode crosspoint in the right inset. The enhanced localization brought about by this multiplexing technique can greatly enhance the scalability of the actuation process and will be used in this work for 2 -D microdrop control on a 14 # 14 grid.  Microdrop actuation is tested in the afore -mentioned bi-layer digital microfluidic multiplexer. The structure consists of two silica plates with 50 nm thick copper electrodes. Copper features are patterned onto the silica plates via UV photolithography to produce a digital microfluidic multiplexer with 14 linear electrodes having w  = 500 mm width and p = 600 mm centre-to-centre pitch. This pitch sets a fundamental lower limit on the microdrop !"!#$%>&='t hi jt hi jt hi jVVVVVVc ,0,21 22(  61 diameter and can be readily reduced in this linear electrode structure if operation is desired for smaller microdrop diameters. For operation wishing to avoid mixing between multiple microdrops, the relevant microdrops should be separated by a distance of at least this electrode pitch28. Each plate is spin-coated with a layer of polydimethylsiloxane (PDMS) followed by a layer of Teflon AF. After high-temperature curing, the electrode plates are aligned in the orthogonal form of Fig. B.1 with a separated plate distance of d = 650 mm. Fluid motion in the digital microfluidic multiplexer is tracked by an overhead high-resolution camera and apochromatic microscope (LEICA APOZ6).  Voltage biasing is applied to the digital microfluidic multiplexer at 470 Hz as two opposite-phase AC waveforms. The waveforms are generated by a centre-tap transformer (Hammond 117E4) having a voltage gain of 2 V 0/V in = 75 between the opposite-polarity secondary terminals and the input. The positive-polarity secondary-side waveform V 0(0?) is directed to the i th lower electrode row with a i -phase-switch; the negative-polarity secondary-side waveform V 0(180?) is directed to the j th upper electrode row with a j -phase-switch.  Initial digital microfluidic multiplexer tests are carried out for a device with thick (10 mm) PDMS layers and a correspondingly high threshold voltage, V th = 620 Vrms. For above-threshold motion in one desired location and stationary conditions elsewhere, the 2-D multiplexing inequality V th/2 < V 0 < V th must be obeyed for the applied voltage V 0. This gives V th/75 < V in < 2 V th/75 for the input voltage V in. An input voltage of V in = 8.3 Vrms is selected, giving an applied voltage of V 0 = 310 Vrms. Multiplexed actuation is shown in Figs. A2.2(a) and (b). Microdrop 1 is centred at i  = 6, j  = 5 and microdrop 2 is centred at i  = 6, j  = 10 to create a configuration for which standard cross-referenced actuation along the i  = 6 row would normally suffer from multi-microdrop interference. Here, the multiplexing with V 0(0?) on i  = 8 and 9 and V 0(180?) on j  = 11 and 12 leads to the enhanced electric field at the activated electrode crosspoint and preferential actuation of microdrop 2 to i  = 8.5, j  = 11.5. Microdrop 1 remains stationary. Complete 2-D actuation is ultimately achieved across all 14 ! 14 = 196 grid points in this multiplexed structure with only 14 + 14 = 28 inputs.    62 For practical application to on-chip systems, and primary relevance to biofluidic devices29,30,31, there exists a desire for low input voltages. The above input voltage of V = 8.3 V rms in particular, is too large for integration with TTL/CMOS 16,32 so a device redesign is applied to lower the input voltage. Such lower voltage operation must be considered carefully, though, as the threshold voltage must be pronounced for multiplexed operation. Threshold voltages have been rigorously characterized for voltages down to 50 V 26, although few analyses exist at lower voltages. With this in mind, a revised digital microfluidic multiplexer is created with identical dimensions to the prior multiplexer and a reduced PDMS layer thickness (1 micron). The new multiplexer is tested and found have a threshold voltage of V th = 48 V rms. The input voltage operational range of 0.64 V rms < V in < 1.28 V rms for this device is therefore well within the range needed for low-voltage TTL/CMOS operation.   Microdrop actuation is shown in Fig. B .3 for a selected input voltage of V in = 0.64 V rms. The initial configuration in Fig. B .3(a) has microdrop 1 centred at i  = 7.5, j  = 8 and microdrop 2 centred at i  = 4.5, j  = 12.5. A simple motion algorithm is tested first through voltage activation in two separate steps with the final result shown in Fig. B .3(b). In the first step, row i  = 11 and columns j  = 12 and 13 are activated to draw microdrop 1 to the i  = 10.5, j  = 12.5 crosspoint. In the second step, row i  = 2 and columns j  = 12 and 13 are activated to draw microdrop 2 to the i  = 2.5, j  = 12.5 crosspoint. A second and more complex algorithm is shown in Fig. B .3(c) for microdrop mixing. Microdrop 1 and 2 are first dra wn together with microdrop 1 pulled to the i  = 6.5, j  = 11.5 crosspoint and microdrop 2 pulled to the i  = 2.5, j  = 11.5 crosspoint (shown as dashed circles), then the voltage is applied to rows i  = 5 and 6 and columns j  = 12 and 13 to draw the microdrops together. A variety of sequences can be ultimately carried out for 2-D multiplexed actuation with this low input voltage, and the complete motion is shown in Fig. B .3(c). A final actuation step is used to draw the microdrop of interest to the sampling station in Fig. B. 3(d) for the optical fluid sensing process.     63  LIST OF FIGURES AND TABLES    Figure B .1    The digital microfluidic multiplexer is shown as an orthogonal grid of lower row electrodes and upper column electrodes driven by a centre - tap transformer with a single primary input, V in(0?), and two out- of- phase secondary outputs, V 0 (0?) and V 0 (180?). Fo r V th = 0, the modified fluid surface tension !" in the left figure inset can allow microdrop motion along all activated row and column electrodes. For V th # 0, the modified fluid surface tension in the right figure inset can allow microdrop motion at a si ngle desired activated electrode crosspoint.     64     Figure B.2    Digital microfluidic multiplexer operation is shown for a structure with a high threshold voltage, V th = 620 Vrms. Microdrop actuation is demonstrated by the (a) initial and (b) final states for motion of microdrop 2 while microdrop 1 is stationary.     65        Figure B .3    Digital microfluidic multiplexer operation is shown for a structure with low threshold voltage, V th = 48 V rms. Microdrop actuation is shown by (a) the initial step, (b) a simple motion algorithm, (c) a more complex mixing algorithm, and (d) moving the merged microdrop to the sampling station.     66  Appendix C: Additional Experimental Images      Figure C. 1   A polymer macrosphere fabricated with a defect. By introducing an automated actuation mechanism to remove the needle tip at precise times, these defects can be eliminated.     Figure C. 2    Polymer microspheres being dispensed into a filler  fluid using the modified electro-dispensing technique.     67    Figure C. 3    A polymer macrosphere and the corresponding back - reflected signal.    Figure C. 4     A glass macrosphere and the corresponding back - reflected signal.    Figure C. 5    One single corner- cube retroreflecto r on a sampling slide. Although the sample itself had a large amount of corner- cubes on it, only one was detected due to directionality difficulties.   68      Figure C.6    Four corner-cube retroreflectors detected on a sampling slide. The variation of intensities between the four back-reflected signals is due to the inherent directionality problem.  


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