Development of Phage/Antibody Immobilized Magnetostrictive Biosensors by Liling Fu A dissertation submitted to the Graduate Faculty of Auburn University in partial fulfillment of the requirements for the Degree of Doctor of Philosophy Auburn, Alabama May 14, 2010 Keywords: magnetostrictive milli/micro cantilever, resonance behavior, biosensors, bio-detection, phage/antibody immobilization, nonspecific adsorption Copyright 2010 by Liling Fu Approved by Zhongyang Cheng, Chair, Associate Professor of Materials Engineering Jeffrey W. Fergus, Professor of Materials Engineering Barton C. Prorok, Associate Professor of Materials Engineering Curtis G. Shannon, Professor of Chemistry and Biochemistry ii Abstract There is an urgent need for biosensors that are able to detect and quantify the presence of a small amount of pathogens in a real-time manner accurately and quickly to guide prevention efforts and assay food and water quality. Acoustic wave (AW) devices, whose performance is defined by mass sensitivity (S m ) and quality factor (Q value), have been extensively studied as high performance biosensor platforms. However, current AW devices still face some challenges such as the difficulty to be employed in liquid and low Q value in practical applications. The objective of this research is to develop magnetostrictive sensors which include milli/microcantilever type (MSMC) and particle type (MSP). Compared to other AW devices, MSMC exhibits the following advantages: 1) wireless/remote driving and sensing; 2) easy to fabricate; 3) works well in liquid; 4) exhibits a high Q value (> 500 in air). The fundamental study of the damping effect on MSMCs from the surrounding media including air and liquids were conducted to improve the Q value of MSMCs. The experiment results show that the Q value is dependent on the properties of surrounding media (e.g. viscosity, density), the geometry of the MSMCs, and the harmonic mode on the resonance behavior of MSMCs, etc. The phage-coated MSMC has high specificity and sensitivity even while used in water with a low concentration of targeted bacteria. Two currently developed phages, JRB7 and E2, respectively respond to Bacillus anthracis spores and Salmonella iii typhimurium, were employed as bio-recognition elements in this research. The phage-immobilized MSMC biosensors exhibited high performance and detection of limit was 5 x 10 4 cfu/ml for the MSMC in size of 1.4 x 0.8 x 0.035 mm. The MSMC-based biosensors were indicated as a very potential method for in-situ monitoring of the biological quality in water. The MSP combine antibody was used to detect Staphylococcus aureus in this experiment. The interface between MSPs and antibody was modified using Traut?s Reagent by introducing the sulfhydryl group. To improve the mass sensitivity of magnetostrictive biosensors, several blocking agents were used to resist the nonspecific adsorption of S. aureus on the surface of the magnetostrictive biosensors and the blocking effects were studied by using ELISA and SEM. The results showed casein was one of the best blocking agents to resist the nonspecific binding in this experiment. Casein blocked antibody immobilized MSP biosensors exhibited high sensitivity and the limit of detection is 10 2 cfu/ml. iv Acknowledgements I would like to express my sincere gratitude to Dr. Z. -Y. Cheng for his expert guidance, support and persistent encouragement during my graduate studies at Auburn University. I would like to emphasize that his influence on me was not only in acquiring scientific knowledge but also as a person. I would like to give my appreciation and sincere thanks to Dr. Barton C. Prorok, Dr. Curtis G. Shannon, Dr. Jeffrey W. Fergus for serving on my committee and for their generous guidance and kind support, to Dr. Byran A. Chin for providing the bio-safety laboratory, and to Dr. Tung-shi Huang for his helpful discussions and insightful suggestions. Thanks are also due to Ms. I-Hsuan Chen for her help in the biological sample preparations; Mr. L.C. Mathison and Mr. Roy Howard for the general technical support; and Ms. Alison Mitchell for the writing/formatting corrections of the papers and dissertation. Thanks also go to my colleague and friends, Dr. Suiqiong Li, Dr. Xiaobing Shan, Levar Odum, Kewei Zhang, Peixuan Wu, Lin Zhang, Xu Lu, Dr. Anxue Zhang, Dr. Jing Hu, Yuhong Wang, Dr. Yuming Hzou, Shichu Huang, Shin Horikawa, Wen Shen, Michael L. Johnson, Dr. Liwei Wang, and Dr. Dongna Shen for all their help and suggestions. The author would also like to thank her parents and her family for their love, constant emotional support and encouragement during her studies. v Table of Contents Abstract..........................................................................................................................ii Acknolegements............................................................................................................iv List of Figures...............................................................................................................iv List of Tables.................................................................................................................iv Chapter 1 Introduction....................................................................................................................1 1.1 Background ..........................................................................................................1 1.2 Bacteria.................................................................................................................2 1.2.1 Salmonella......................................................................................................2 1.2.2 Bacillus anthracis spores ...............................................................................3 1.2.3 Staphylococcus aureus ...................................................................................5 1.3 Research objectives ..............................................................................................5 1.4 Dissertation organization......................................................................................6 References ..................................................................................................................7 Chapter 2 Literature review............................................................................................................9 2.1 Conventional culture methods..............................................................................9 2.2 Molecular recognition methods..........................................................................10 2.2.1 Nucleic acid-based detection (PCR) ............................................................10 2.2.2 Immunological-based detection (ELISA)....................................................11 2.3 Biosensors ..........................................................................................................14 iv 2.3.1 Electrochemical sensors...............................................................................15 2.3.2 Optical sensors.............................................................................................16 2.3.3 Acoustic wave devices .................................................................................20 2.3.3.1 Classification of AW devices.................................................................20 2.3.3.2 Operation principle................................................................................24 2.3.3.3 A typical AW device - QCM..................................................................25 2.3.4 Microcantilever based biosensors................................................................26 2.3.4.1 Operation mode .....................................................................................26 2.3.4.2 Cantilever arrays....................................................................................27 2.3.4.3 Surface functionalization.......................................................................28 2.3.4.4 Biological applications ..........................................................................29 2.4 MSMC-based biosensors....................................................................................30 References ................................................................................................................31 Chapter 3 Sensor platform - MSMC.............................................................................................40 3.1 Configuration of MSMC ....................................................................................40 3.2 Operation principle.............................................................................................42 3.3 Theory.................................................................................................................45 3.4 Determination of several important parameters .................................................50 3.4.1 Characteristic frequency ..............................................................................50 3.4.2 Quality factor ...............................................................................................55 3.4.3 Mass sensitivity............................................................................................57 3.5 Experimental flow chart .....................................................................................60 3.6 Measurement setup.............................................................................................62 References ................................................................................................................66 v Chapter 4 Fundamental study.......................................................................................................68 4.1 Introduction ........................................................................................................68 4.2 Theoretical model...............................................................................................69 4.3 Materials and methods........................................................................................74 4.3.1 Measurement set-up.....................................................................................74 4.3.1.1 In vacuum..............................................................................................74 4.3.1.2 In liquids................................................................................................74 4.3.2 Design of MSMC sensor dimensions ..........................................................75 4.3.3 Selection of liquid reagents..........................................................................76 4.3.3.1 Glycerol/water mixture system .............................................................76 4.3.3.2 Several organic solvents........................................................................77 4.4 Results and discussions ......................................................................................78 4.4.1 Resonance behavior in vacuum ...................................................................78 4.4.2 Resonance behavior in liquids .....................................................................86 4.4.2.1 Glycerol/water mixture system .............................................................86 4.4.2.2 Several organic solvents........................................................................90 4.5 Conclusions ......................................................................................................100 References ..............................................................................................................101 Chapter 5 Phage immobilized magetostrictive biosensors.........................................................105 5.1 Introduction ......................................................................................................105 5.2 Materials and methods......................................................................................108 5.2.1 Fabrication of MSMC................................................................................108 5.2.2 Measurement set-up...................................................................................109 vii Antibody modification...............................................................................................139 6.1 Introduction ......................................................................................................139 6.1.1 Antibody structure......................................................................................140 6.1.2 Polyclonal antibody vs. monoclonal antibody...........................................140 6.1.3 The oriented attachments of Antibody on solid surface.............................142 6.2 Experimental ....................................................................................................148 6.2.1 Reagents.....................................................................................................148 6.2.2 Antibody thiolation and separation ............................................................148 6.2.3 Measurement of thiolated antibody ? Bradford Dye Assay.......................150 6.2.4 Measurement of -SH group........................................................................152 6.3 Results and discussion......................................................................................152 6.3.1 The collection of the thiolated antibody after separation...........................152 6.3.2 The concentration of thiolated antibody ....................................................153 6.3.3 Quantification of the sulfhydryls ...............................................................154 6.4 Conclusions ......................................................................................................156 References ..............................................................................................................156 Chapter 7 Aantibody-immobilized magnetostrictive biosensors - Blocking nonspecific adsorption...................................................................................................................161 7.1 Introduction ......................................................................................................162 7.2 Materials and methods......................................................................................164 7.2.1 Sensor platform-Magnetostrictive particle ................................................164 7.2.2 Microorganisms .........................................................................................165 7.2.3 Reagents.....................................................................................................165 7.2.4 Protocol for evaluating the ability of blocking agents...............................166 7.2.4.1 Microscopic analysis ...........................................................................167 vi 5.2.2.1 Static system........................................................................................110 5.2.2.2 Dynamic system ..................................................................................110 5.2.3 Phage and its immobilization..................................................................... 111 5.2.3.1 Phage JRB7 ......................................................................................... 111 5.2.3.2 Phage E2..............................................................................................112 5.2.4 Bacteria ......................................................................................................112 5.2.4.1 Bacillus anthracis spores.....................................................................112 5.2.4.2 Salmonella typhimurium......................................................................113 5.2.5 Bacteria binding measurement...................................................................113 5.2.6 SEM images...............................................................................................113 5.2.7 Specificity ..................................................................................................114 5.3 Results and discussion......................................................................................114 5.3.1 Sensor platform..........................................................................................114 5.3.2 Phage immobilization ................................................................................117 5.3.3 Static system ..............................................................................................119 5.3.3.1 Bacillus anthracis spores.....................................................................119 5.3.3.2 Salmonella typhimurium......................................................................124 5.3.4 Dynamic system.........................................................................................127 5.3.4.1 Stability of dynamic system under various flow rates.........................127 5.3.4.2 The sensor response under various flow conditions............................128 5.3.4.3 Real detection of MSMC.....................................................................130 5.3.4.4 Binding equations and Hill plot...........................................................133 5.4 Conclusions ......................................................................................................134 References ..............................................................................................................135 Chapter 6 viii 7.2.4.2 ELISA..................................................................................................168 7.2.5 Real time bacteria binding measurement...................................................169 7.2.5.1 MSP sensor fabrication........................................................................169 7.2.5.2 Theory and principle............................................................................170 7.2.5.3 Measurement set-up ............................................................................171 7.2.5.4 Antibody immobilization.....................................................................172 7.2.5.5 Real time measurement .......................................................................173 7.3 Results and discussion......................................................................................173 7.3.1 Blocking efficiency of nonspecific binding from SEM analysis...............173 7.3.2 Blocking efficiency of nonspecific binding from ELISA test ...................179 7.3.3 Dose response of reference sensors ...........................................................182 7.4 Conclusions ......................................................................................................183 References ..............................................................................................................184 Chapter 8 Future recommendations............................................................................................188 iv List of Figures Figure 2-1. The schematic of biological agent detection: targeting at molecular level. ......................................................................................................................................10 Figure 2-2. The schematics of three types of ELISA assays. (a) Sandwich assays; (b) Indirect assays; and (c) Competitive assays.................................................................13 Figure 2-3. Schematic diagram of a typical biosensor.................................................15 Figure 2-4. Schematic of SPR based biosensors..........................................................19 Figure 2-5. The schematics of several important AW devices: (a) SH-APW; (b) TSM; (c) SAW, and (d) FPW. ...............................................................................................21 Figure 2-6. Construction of a QCM biosensor and its principle..................................25 Figure 2-7. Cantilever sensor modes of operation: (a) static mode, where Asymmetric molecular binding to the cantilever?s top surface leads to an overall cantilever bending, (b) heat mode detecting temperature Changes by a static bending due to different thermal expansion of the Metal layer and silicon cantilever, and (c) dynamic mode detecting Mass changes on the cantilever by changes in resonance frequency. ........26 Figure 2-8. Scanning electron micrograph of a cantilever sensor array. (Courtesy of Viola Barwich, University of Basel, Switzerland.)......................................................28 Figure 3-1. The schematic of Magnetostrictive cantilever...........................................40 Figure 3-2. Schematic illustration of the principle of MSMC as a transducer for biosensors.....................................................................................................................42 Figure 3-3 The magnetostriction response of a magnetostrictive material under the external magnetic field (H). .........................................................................................43 Figure 3-4. The schematic illustration of the operation principle of MSMC based biosensors for detecting bacteria. The binding of bacteria on both sides of the MSMC. ......................................................................................................................................44 Figure 3-5. The deflection schematic of cantilever beam............................................46 iv Figure 3-6. Curves of ?cos , and ?cosh 1 ? . The eigenvalues for a cantilever with one end free and the other end fixed can be graphically obtained from the intersections of these two curves...........................................................................................................47 Figure 3-7. The natural vibration motion at 0 th -3 rd harmonic modes and the nodal points (violet triangles) 0-3 at the 0 th , 1 st , 2 nd , and 3 rd resonance oscillation modes of the clamped cantilever which were obtained from Eq. (3-7).......................................49 Figure 3-8. Measured resonance spectrum, amplitude and phase signals versus frequency from Lock-in amplifier for the fundamental mode of an MSMC in the size of 3.0 mm x 1.0 mm x 35 ?m in air. ............................................................................51 Figure 3-9. Characteristic frequency dependent phase spectrum for the fundamental mode of an MSMC in size of 3.0 mm x 1.0 mm x 35 ?m. The dashed black line is the detected/measured signal, while the red solid line is the generated signal from the Lorentz fitting. .............................................................................................................52 Figure 3-10. The first five harmonic peaks from (a) amplitude output and (b) phase output for the MSMC with the size of 4.4 mm x 0.8 mm x 35 ?m. ............................54 Figure 3-11. The schematic of the point mass loaded at the free end of cantilever beam. ......................................................................................................................................58 Figure 3-12. The mass sensitivity (uniform and at the free end) vs. length of the MSMC based sensors with the fundamental mode. Two widths with 0.8 mm and 1.0 mm were used. .............................................................................................................60 Figure 3-13. The experimental flow chart in this research. .........................................61 Figure 3-14. Measurement set-up in laboratory for this research................................63 Figure 3-15. The experiment design of test chamber (a), MSMC (b), and pick-up coil (c). ................................................................................................................................63 Figure 4-1. The damping mechanism of Q value of a cantilever.................................68 Figure 4-2. The schematic of a damped string of oscillating spheres. R is the effect radius of an oscillating sphere......................................................................................70 Figure 4-3. The scheme of measurement set-up in vacuum. .......................................74 Figure 4-4. The schematic of measurement set-up in liquids. .....................................75 Figure 4-5. The density vs. the percentage of glycerol in glycerol/water mixture system. The black squares represent the value from the calculation which based on no volume change after mixture. The red dots represent the experiment data which measured by Tensiometer.............................................................................................77 Figure 4-6. (a) The resonance behaviors of an MSMC in size of 3.0mm x 1.0mm x v 35?m at room temperature in air at different pressures: 1). 1.0 x 10 5 Pa; 2). 8.0 x 10 4 Pa; 3). 4.0 x 10 4 Pa; 4). 1.0 x 10 3 Pa; 5). 1.0 x 10 2 Pa; 6). 1.0 x 10 1 Pa; 7). 1.0 x 10 0 Pa. (b) The normalized Q value (Q/Q 0 ) (Solid Circle) and normalized resonant frequency (f/f 0 ) (Solid Triangle) as a function of air pressure. The Q 0 and f 0 represent the Q value and characteristic frequency of the MSMC at one atmosphere pressure.....................80 Figure 4-7. Measured and theoretical calculated Q values of the MSMC under various pressures. The theoretical prediction of the dependence of Q value on pressure when the air damping in the molecular region by using Eq. (4-16). .....................................82 Figure 4-8. The first three harmonic peaks and their characteristic frequencies for the MSMC with the size of 3.0 mm x 1.0 mm x 35 ?m. ...................................................84 Figure 4-9. The Q value vs. pressure (a) and the Q/Q atm vs. pressure (b) of the MSMC with the size of 3.0 x 1.0 x 0.035 mm for the first three harmonic peaks....................85 Figure 4-10. The phase spectrum vs. the percentage of glycerol in the glycerol/water mixture system. (a) the raw data; (b) the fitting data by using PeakFit software. .......87 Figure 4-11. The density and viscosity dependence of characteristic frequency and Q value in the glycerol/water mixture system: (a) 0d f and Q vs. ? and (b). Q vs. dn f??/1 . The solid line is the linear fitting results of the original experimental data. ......................................................................................................................................88 Figure 4-12. The dependence of Q value on the viscosity of the liquid media (a) Q vs. dn f??/1 for the different mixture systems. The dependence of resonance frequency on the density of the liquid media (b) dn fvs.? for several liquid media......................89 Figure 4-13. The dependence of the 0d f and Q value of three MSMCs with the same width (1.0 mm) and different length (4.0, 3.0, and 2.0 mm): (a) the 0d f vs. the density of the liquid media, (b) Lff ?? )/( vs. the density of the liquid media, (c) the Q value vs. f L ??/1 , and (d) the Q value vs. the viscosity of the liquid media.............93 Figure 4-14. The dependence of the 0d f and Q value of three MSMCs with the same length (3.0 mm) and different width (1.5, 1.0 and 0.5 mm): (a) the 0d f vs. the density of the liquid media, (b) Wff ?? )/( vs. the density of the liquid media, (c) the Q value vs. f L ??/1 , and (d) the Q value vs. the viscosity of the liquid media...96 Figure 4-15. The dependence of the 0d f and Q value of three MSMCs with the same cross-section area (2.0 mm x 1.5 mm, 3.0 mm x 1.0 mm and 4.0 mm x 0.75 mm): (a) the 0d f vs. the density of the liquid media, (b) the Q value vs. f L ??/1 . The thickness for all the MSMCs is 35 ?m. .......................................................................98 Figure 5-1. Scheme of the set-up of (a) the static system and (b) dynamic system based on MSMC biosensor. .......................................................................................110 vi Figure 5-2. The typical resonant behavior of the MSMCs in size of 2.8 mm x 1.0 mm x 35 ?m and in size of 1.4 mm x 0.8 mm x 35 ?m in air and in water, respectively. 116 Figure 5-3. (a) The resonance peak of the MSMC in air before and after phage immobilization. (b) A typical SEM image of the phages binding on the surface of an MSMC sensor. The black fiber-like materials are phage bundles. ............................117 Figure 5-4. A typical curve of the characteristic frequency vs. time of an MSMC biosensor that was exposed to B. anthracis spore solutions with various concentrations. The concentration was increased from 5 x 10 4 cfu/ml to 5 x 10 8 cfu/ml. The dimensions of the MSMCs are 1.4 mm x 0.8 mm x 35 ?m................................120 Figure 5-5. Dose response curve of MSMC biosensors for detecting B. anthracis spores in water. Each point is the average value of the three sensors. The response curves were plotted by using the sigmoid fit. (a) Two typical sizes of MSMC sensors: 2.8 mm x 1.0 mm x 35 ?m (? 2 = 0.01, R 2 = 0.99) and 1.4 mm x 0.8 mm x 35 ?m (? 2 = 3.18, R 2 = 0.99). (b) The comparison of the MSMC sensor and the reference sensor (? 2 = 0.84, R 2 = 0.99) with the same size of 2.8 mm x 1.0 mm x 35 ?m. .......................121 Figure 5-6. Typical SEM images of the surface of the MSMC biosensors exposed to the B. anthracis spore suspension with the concentration of 5 x 10 8 cfu/ml for 2 hours: (a) at the middle of the cantilever beam; (b) at the tip of the cantilever beam; and (c) the whole beam of the reference sensor (devoid of phage immobilization)..............123 Figure 5-7. The specificity of MSMC sensor to several Bacillus species. The size of MSMC sensor was 1.4 mm x 0.8 mm x 35 ?m. Identical phage-coated MSMC sensors were exposed to different Bacillus species under the identical condition. ................124 Figure 5-8. The shift in a characteristic frequency due to the various concentrations of S. typhimurium with (a) 5 x 10 5 cfu/ml and (b) 5 x 10 7 cfu/ml. The corresponding SEM images of S. typhimurium with the concentrations of (c) 5 x 10 5 cfu/ml and (d) 5 x 10 7 cfu/ml. The size of MSMC used here was 2.8 x 1.0 x 0.035 mm. The duration was two hours. ...........................................................................................................126 Figure 5-9. Dose response curve of MSMC biosensors for detecting S. typhimurium in water. Each point is the average value of the three sensors. The response curves were plotted by using the sigmoid fit. Two typical sizes of MSMC sensors: 2.8 mm x 1.0 mm x 35 ?m (? 2 = 0.42, R 2 = 0.99) and 1.4 mm x 0.8 mm x 35 ?m (? 2 = 1.54, R 2 = 0.99). ..........................................................................................................................127 Figure 5-10. Flow rate dependence of characteristic frequency of MSMC based biosensor at 0.1 ml/min, 1.0 ml/min, and 5.0 ml/min.................................................128 Figure 5-11. The effects of flow rate on sensor response. The binding of B. anthracis spores, 5 x 10 7 cfu/ml, to MSMC sensor at flow rate of (b) 0 ml/min, (c) 0.3 ml/min, and (d) 1.0 ml/min. The control (a) shown is the response of an MSMC sensor without phage immobilization.................................................................................................129 Figure 5-12. (a) The typical dose responses of MSMC sensors (? 2 = 1.02, R 2 = 0.99) and reference sensor via dynamic system with the flow rate of 0.3 ml/min for 30 min. vii Each point is the average value of the three sensors. The response curves were plotted by using the sigmoid fit. The size of MSMC is 2.8 x 1.0 x 0.035 mm. (b) Hill plots of binding isotherms for the MSMC sensors. The ratio of occupied and free phages is shown as a function of B. anthracis spores concentrations measured by a phage-coated MSMC sensor. The straight line is the linear least squares fit to the sensor data (R=0.99, slope = 0.309). .........................................................................132 Figure 6-1. The schematic of antibody crystal structure: Fc (fragment crystallizable) and Fab (fragment antigen binding) regions, carbohydrates, and antigen binding sites. ....................................................................................................................................140 Figure 6-2. Schematic of the antibody immobilization on the gold-coated surface of the sensors with (a) random orientation, (b) ideal orientation, and (c) protein A binding-mediated orientation.....................................................................................143 Figure 6-3. The scheme of Langmuir-Budegett thin film. (a) A schematic illustration showed components of an amphiphile (left), and the orientation of an amphiphile adopted at an interface (right). (b) Deposition of a floating monolayer on a solid surface. [13] ...............................................................................................................145 Figure 6-4. The schematic reaction of antibody and Traut?s Reagent. ......................147 Figure 6-5. The schematic of desalting column used to separate thiolated antibody and extra Traut?s Reagent. ................................................................................................150 Figure 6-6. The UV absorbance of antibody at 280nm for the continuous thiolated antibody samples after separation..............................................................................153 Figure 6-7. The standard curve of the antibody concentration with the absorbance at 595 nm. ......................................................................................................................154 Figure 7-1. The typical SEM images of the reference magnetostrictive biosensors with different magnification of (a) x2000, and (b) x5000. The reference biosensors were absent of antibody immobilization and nonspecific blocking. The biosensors were exposed to the 5 x 10 8 cfu/ml of S. aureus culture for one hour................................164 Figure 7-2. The schematic of microtiter plate (12 Columns x 8 Rows) and sensor in each well. ...................................................................................................................167 Figure 7-3. Schematic of the experiment design for evaluating the effectiveness of the blocking agents on the nonspecific adsorption in microscopic analysis without antibody (a) and with antibody (b).The symbols ?, ?, ?, ?, and ? in the SEM images mean that these five regions (c) were taken SEM images in this experiment. ....................................................................................................................................168 Figure 7-4. Schematic of the experiment design for evaluating the effectiveness of the blocking agents on the nonspecific adsorption in ELISA test without antibody (a) and with antibody (b)........................................................................................................169 Figure 7-5. The schematic of measurement set-up and operation principle. .............171 viii Figure 7-6. SEM images of bacterial adsorption on magnetostrictive biosensors. Negative control (devoid of antibody immobilization): (a) S. aureus adsorption directly to non-blocking gold surface, (b) 5% BSA blocking surface, (c) 5% casein blocking surface. (d) Antibody-immobilized biosensor: S. aureus adsorption to 5% casein blocking surface..............................................................................................176 Figure 7-7. Efficiency of six blocking agents with three different concentrations evaluated by SEM. (a). Number of bacterial cells means the average number adsorbed on various surfaces in a 48 ?m x 60 ?m (2880 ?m 2 ) area of magnetostrictive sensor treated only with blocking agent (devoid of antibody). Each sensor was taken five pictures. Each blocking agent with various concentrations was repeated 4 times. Control means the sensor devoid of blocking agent. .................................................178 Figure 7-8. The absorbances (O.D. 405 ) in ELISA for the magnetostrictive biosensor immobilized without antibody (a) and with antibody (b). Each data were the average values of 5 samples. The concentration of each blocking agent was listed in the X-axis. ....................................................................................................................................180 Figure 7-9. The result was combined the absorbance from the sensor treated with antibody and without antibody in ELISA test. The solid column represents the absorbance obtained from the sensor devoid of antibody immobilization. The blank columns represent the absorbance obtained from the antibody-coated sensors. .......181 Figure 7-10. The dose response of (a) the reference sensor without and with casein blocking and (b) of the antibody-immobilized MSP sensor via dynamic system. The size of MSP sensor was 1.0 x 0.3 x 0.015 mm. The flow rate was 30 ?l/min...........183 Figure 8-1. The microfabrication process of MSMC.................................................190 Figure 8-2. The schematic of the microfabricated pick-up coil.................................191 iv List of Tables Table 2-1. Review of AW devices................................................................................23 Table 2-2. Comparison MSMC with Current MCs......................................................30 Table 3-1. The effective material properties of Metglas TM 2826, Cu thin film, and cantilever beam. ...........................................................................................................41 Table 3-2. Graphically obtained Eigenvalues for the flexural resonance modes of MSMC..........................................................................................................................48 Table 3-3. The constants A, B, C, and D for the first four harmonic modes. ..............48 Table 3-4. The resonance frequencies for the first five modes obtained from Eqs. (3-11) and (3-12) and measurement for the MSMC with the size of 4.4 mm x 0.8 mm x 35 ?m. .......................................................................................................................55 Table 3-5. Q values for the first five modes of the MSMC in size of 4.4 mm x 0.8 mm x 35 ?m. .......................................................................................................................57 Table 4-1. MSMCs were used to measure the resonance behavior in vacuum and in liquids...........................................................................................................................75 Table 4-2. The viscosity and density of glycerol/water mixture system was measured by Viscometer and Tensiometer at 20 o C. ....................................................................76 Table 4-3. Density and viscosity of liquids at 20 o C from the literature.......................78 Table 4-4. The characteristic frequencies and Q values of MSMCs were used in the liquids measurement. ...................................................................................................91 Table 4-5. The effective radius obtained from the experiment (Eq. (4-18)) and the cross-section approximation (Eq. (4-19)). ...................................................................99 iv Table 6-1. Traut?s Reagent: 14mM stock solution. ....................................................148 Table 6-2. The experiment design of the standards. ..................................................152 Table 6-3. The results of the standards. .....................................................................153 Table 6-4. Results of polyclonal anti-aureus antibody modification by using Traut?s Reagent. The concentrations of antibody and sulfhydryl group, the -SH number for each antibody molecular under different Traut?s Reagent molar excess. ..................155 Table 6-5. The concentrations of antibodies, and their sulfhydryls, and the -SH group per antibody molecular of several antibodies which modified by Traut?s Reagent with the 20-fold molar excess. ...........................................................................................156 Table 7-1. The blocking agents and its concentrations were used in this experiment. ....................................................................................................................................166 Table 8-1. The design of MSMC dimension using micro-fabrication technique.......189 1 CHAPTER 1 INTRODUCTION 1.1 Background Bacteria are unicellular microorganisms and thousands of types of bacteria are naturally present in our environment. Some types of bacteria are used beneficially in making foods such as cheese and yogurt. Other bacteria, pathogens, cause disease in humans, animals, and plants. In food industry, when certain pathogens enter the food supply, they can cause food-borne illness. Only a few types (i.e. Salmonella and Escherichia coli) cause millions of cases of food-borne illness each year. Most of the bacteria cause the foodborne illness undetectably since they cause the flu-like symptoms and have no odor and do not change the color or texture of the food. Therefore, it would be fairly easy to result in an epidemic in a fairly large population by using a bacteria infection. It has been suggested that 1.5 billion people around the world are infected by bacteria each year, and that 70% of these infections are food-borne [1]. Furthermore, the number of illness caused by food-borne bacteria in the United States is 33 million annually, with the mortality rate being approximately 10, 000 people [1]. Illnesses caused by these organisms cost the U.S. economy $9.3-12.8 billion every year. Bacteria present in animals at slaughter can also lead to human illness. 2 In the U.S., it is estimated that 1% of the beef carcasses, 8.7% of the swine carcasses, and 20% of poultry carcasses are contaminated with Salmonella (U.S. Food and Drug Administration 2002). Another type of bacteria, caused human diseases or death, is biological threat agent. There are a number of different types of biological agents that could be used in an attack. Some cause diseases that can be spread by infected people, such as smallpox, while others are only dangerous when a person comes into direct contact with the biological agent, such as anthrax. Since the biological terrorism attack on September 2001, the anthrax bacillus, Bacillus anthracis has come into insight and attracted the attention of biological researchers. Prevention of microbial diseases depends on an effective and rapid detection of various pathogenic micro-organisms in food, clinic medicine and the environment. Therefore, analytical technologies for detecting and quantifying the presence of a small amount of biological threat agents in a real-time manner are urgently needed in food safety, medical diagnostics, environmental monitoring, and in public safety/security areas. 1.2 Bacteria 1.2.1 Salmonella Salmonella species are a leading cause of foodborne bacterial illnesses in humans. Salmonella species are common, naturally occurring bacteria found in the intestinal tracts of many animals and birds. Human salmonellosis is generally increasing worldwide. Most people infected will develop diarrhea, fever and abdominal cramps within a few days of infection, and their illness can last up to a week. Poultry, beef and eggs are the predominant reservoirs of Salmonella species with other foods (fruits and vegetables) as potential vehicles for infection. 3 The recent Salmonella outbreak in Sept. 2008 was caused at least 388 people infection and cover 42 states in United States [2]. Additionally, various strains of Salmonella have been linked to previous outbreaks, caused by contaminated eggs, meat, poultry, vegetables, pet food and even peanut butter. For example, from August 2006 to May 2007, 628 cases of salmonellosis linked to peanut butter were occurred at the plant. Fall 2006, Salmonella outbreak related to contaminated tomatoes cause at least 183 people?s sickness (e.g. diarrhea, and fever) in 21 states of United States. In April 2005, USDA linked cases of Salmonella infections in people to stuffed frozen chicken products sold in Minnesota and Michigan. In 2004, several outbreaks of Salmonella were linked to consumption of uncooked Roma tomatoes. These outbreaks resulted in over 500 cases of illness. It is believed that the implicated tomatoes were contaminated in either the field or the packing house. 1.2.2 Bacillus anthracis spores Biological warfare is the use of viruses, bacteria, other microorganisms, or toxins derived from living organism to cause death or disease in humans, animals or plants [3]. Biological warfare agents are more problematic to use as a weapon of mass destruction and could kill more people than a nuclear or chemical attack. It poses a serious global threat to military and civilian populations. Biological warfare aerosols are usually invisible, odor- and taste-free and are difficult to detect due to condensation of liquids droplets on the skin or uniform. Unlike a chemical agent attack, a biological attack does not cause an immediate reaction. Research and development of technologies for detecting weapons of mass destruction have intensified since 1991 when chemical and biological weapons were discovered in Iraq?s arsenal. Currently, 17 countries are suspected of having an offensive biological weapons program. In 1992, 20 people were administered 4 chemoprophylaxis after a Virginia man sprayed his roommates with a substance that he claimed was anthrax. In 1994, a Japanese sect of the Aum Shinrikyo cult attempted an aerosolized release of anthrax from the top of building in Tokyo [4]. In 1995, 2 members of a Minnesota militia group were convicted of possession of ricin, which they had produced themselves for use in retaliation against local government officials. In 1996, Ohio man was able to obtain bubonic plague cultures through the mail. In 1997, the Defense Against Weapons of Mass Destruction Act directed the Department of National Head of the Home Security Office and Defense to establish a domestic preparedness program to improve the ability of local, state, and federal agencies to respond to biological incidents. During 1998 and 1999, multiple hoaxes occurred involving the threatened release of anthrax in the United States that resulted in decontamination and antibiotic prophylaxis for the intended victims. Nearly 6000 persons across the United States have been affected by these threats. According to a study by the Centers for Disease Control and Prevention (CDC), an intentional release of anthrax by a bioterrorist in a major US city would result in an economic impact of $ 477.8 million to $ 26.2 billion per 100, 000 persons exposed. Concentrated anthrax spores, used for bioterrorism in the 2001 anthrax attacks in the United States, were delivered by mailing postal letters containing a few grams of spores. From then to November 2001, a total of 23 confirmed or suspected cases of bioterrorism-related anthrax (10 inhalation, 13 cutaneous) occurred in the United States [5]. Most cases involved postal workers in New Jersey and Washington DC, and the rest occurred at media companies in New York and Florida, where letters contaminated with anthrax were handled or opened. As a result of these cases, approximately 32,000 persons with potential exposures initiated antibiotic prophylaxis to prevent anthrax infections. 5 1.2.3 Staphylococcus aureus Staphylococcus aureus is a common cause of foodborne illness which is excluded in some epidemiologic surveillance programs [6]. By producing the heat-stable staphylococcal toxins, some strains of S. aureus can result in staphylococcal food poisoning. The common symptoms include nausea, vomiting, abdominal cramps, prostration and diarrhea. This kind of symptoms can last 30 minutes to seven hours after consumption of foods contained staphylococcal toxins. S. aureus also would cause skin abscesses, pneumonia, bacteremia, endocarditis and toxic shock syndrome, which is not from the foodborne source. Thus, it requires the treatment with antibiotics and hospitalization. The spread of S. aureus could be through human-human contact, domesticated animals (e.g. pets) [7]. Another important source of S. aureus is the nosocomial infection, especially nosocomial pheumonia, surgical wound infection, and bloodstream infection [8]. For example, Methicillin-resistant S. aureus (MRSA) was recognized in the United States in 60s? the last century [9-12]. 1.3 Research objectives The goal of this research is to develop a methodology to in-situ detect the target bacteria using phage/antibody immobilized magnetostrictive sensors. The objectives are: 1) The fundamental study of resonance behavior of magnetostrictive milli/micro cantilevers (MSMC) including the resonant frequency and Q value in various surrounding media such as air and liquids. Study the damping effect from surrounding media, and investigate size effect of MSMC device such as the scale and harmonic mode, on the Q value and resonance frequency of MSMC in surrounding media. 6 2) Establish bacteria binding test system in real-time manner. 3) Demonstration of the in-situ detection of several targeted bacteria including B. anthracis spores, and S. typhimurium via static system and dynamic system using phage-immobilized MSMC biosensors; study the size effect on the mass sensitivity and limit of detection. 4) Antibody modification by using Traut?s reagent. Study the effect of the molar extra fold of Traut?s reagent on the thiolation of antibody (e.g. sulfhydryls per antibody). 5) Characterization of blocking agent to resist the nonspecific adsorption of S. aureus on the magnetostrictive biosensors. Study the influence of blocking agents on the mass sensitivity of magnetostrictive biosensors. 1.4 Dissertation organization The first chapter introduces the background and the research objective. The second chapter reviews the current microbial detection techniques including the conventional methods, molecular methods and biosensors. A new biosensor combined the magnetostrictive micro/milli cantilever (MSMC) with phage is introduced. The third chapter gives the operation principle of MSMC based biosensors and the determination of several important parameters. The fourth chapter discusses the damping effect from the surrounding media and size effect on the resonance behaviors of the MSMCs including the resonance frequency and the Q value. The fifth chapter demonstrates the performance of phage-coated MSMCs to in-situ detect the targeted bacteria including B. anthracis spores and S. typhimurium in water via static system and dynamic system. The sixth chapter studies the interface between antibody and gold coated magnetostrictive biosensors by using Traut?s reagent. The resistance of the nonspecific adsorption of S. aureus on the sensor?s surface by using various 7 blocking agents with different concentrations is studied in Chapter 7. Chapter 8 gives the prospect of MSMCs with smaller size by the microfabrication techniques and antibody immobilization by difference methods. References 1. Envirotainer. 2001. Available from http://www.envirotainer.com 2. http://www.cnn.com/2009/HEALTH/01/08/salmonella.outbreak.cdc/index.htm l 3. North Atlantic Treaty Organization, NATO Handbook on the Medical Aspects of NBC Defensive Operations, Part II, Biological NATO Amed P-6(B), 1996. 4. G.W. Christopher, T.J. Cieslak, J.A. Pavlin, E.M. Eitzen, Jr., Biological warfare. A historical perspective, J. Am. Med. Assoc. 278 (1997) 412-417. 5. http://www.themoldsource.com/archives/bw.html 6. http://www.ecolab.com/PublicHealth/Saureus.asp 7. J.C. Seguin, R.D. Walker, J.P. Caron, W.E. Kloos, C.G. George, R.J. Hollis, R.N. Jones, M.A. Pfaller, Methicillin-resistant Staphylococcus aureus outbreak in a veterinary teaching hospital: potential human-to animal transmission, J. Clin. Microbio. 37 (5) (1999) 1459-1463. 8. D.S. Schaberg, D. Culver, R. Gaynes, Major trends in the microbial etiology of nosocomial infection, Am. J. Med. 91 (3B) (1991) 72s-75s. 9. F.E. Barrett, R.P. McGehee, M. Finland, Methicillin-resitant Staphylococcus aureus at Boston City Hospital, N. Engl. J. Med. 279 (1968) 441- 448. 10. R.W. Haley, A.W. Hightower, R.F. Khabbaz, The emergence of methicilin-resistant Staphylococcus aureus infections in United States hospitals: possible role of the house staff-patient transfer circuit, Ann. Intern. Med. 97 (1982) 297-308. 8 11. F.H. Kavser, T.M. Mak, Methicillin-resistant staphylococci, Am. J. Med. Sci. 264 (1972) 197-205. 12. 12. R.D. O?Toole, I. Drew, B.J. Dahlgren, H.N. Beatv, An outbreak of methicillin-resistant Staphylococcus aureus infection, JAMA 213 (1970) 257-263. 9 CHAPTER 2 LITERATURE REVIEW In this chapter, the current microbial techniques for detecting the bio-threaten agents and food-borne pathogens were reviewed. The current microbial detection methods include conventional culture methods, molecular recognition techniques including nucleic acid-based and immunological based detection, and biosensors. The biosensors are divided into three types according to the detection transductions: electrochemical biosensors, optical biosensors, and acoustic wave devices. Several important acoustic wave sensors especially microcantilevers and their operating principle were described. 2.1 Conventional culture methods The conventional culture method for bacterial detection is by putting bacteria sample onto agar culture plates and incubating these plates at optimal temperatures (e.g. 37 o C) for 1-2 days; then the bacteria are counted based on formation of colonies on the agar surface. Some bacteria require a variety of agar media to detect them. Culture methods are the most reliable tools for detection and identification of bacteria, viruses and the like, however, they are laborious and time-consuming, which is not suitable for the in-field test [1]. 10 2.2 Molecular recognition methods Molecular recognition systems that can be used for rapid identification can improve response time and thus avert or reduce the number of casualties associated with food contamination, a potential bioterrorism or biowarfare event [2]. Biological agents Bacterial cells Viruses Bacterial spores Nucleic acid Antigens Figure 2-1. The schematic of biological agent detection: targeting at molecular level. According to the molecular level of biological agents (see Figure 2-1), molecular recognition methods can be divided into two types: nucleic acid-based detection and immunological-based detection. Molecular recognition methods have been widely applied in food testing, clinical diagnostics and environmental monitoring by the identification of bacteria, viruses and their products (e.g. antigens and toxins). Generally, immunological detection is faster, more reliable and more robust than nucleic acid-based detection, but the latter is more specific and sensitive. 2.2.1 Nucleic acid-based detection (PCR) By definition, virtually any self-replicating biological entity can be separated based on the nucleic acid sequences unique to the particular organism except prions because of the absence of nucleic acid in these protein particles. Nucleic acid-based detection can be broadly classified into two categories: direct target probing with signal 11 amplification and target amplification. Polymerase Chain Reaction (PCR) is a typical assay based on target amplification. Direct DNA hybridization is better than PCR to quantify target, however, the latter is more sensitive. As a typical molecular based method, PCR is a technique widely used in molecular biology, microbiology, genetics, diagnostics, clinical laboratories, environmental science, and many other applications [3-5]. PCR so called comes from the DNA polymerase used to amplify a targeted DNA or DNA region by in vitro enzymatic replication. The ?chain reaction? means the original DNA template such as a single piece of DNA, or a very small number of pieces of DNA exponentially amplified. The PCR is one of the most sensitive existing rapid methods to detect microbial pathogens in clinical specimens, especially for those specific pathogens that are difficult to culture in vitro or require a long cultivation period. However, the application of PCR to clinical specimens still has many potential problems due to the susceptibility of PCR to inhibitors, contamination and experimental conditions. For example, the sensitivity and specificity of a PCR assay is dependent on target genes, primer sequences, PCR techniques, DNA extraction procedures, and PCR product detection methods. Even though the basic protocols of a PCR assay have been well-established, which include DNA extraction and preparation as well as the amplification and detection of amplicons, PCR detection of bacteria in clinical samples (e.g. cerebrospinal fluid) has not yet been reviewed. 2.2.2 Immunological-based detection (ELISA) Immunological-based assay is a laboratory technique that makes use of the immunological binding between an antigen and its homologous antibody to identify and 12 quantify the specific antigen or antibody in a blood or body fluid sample. Antibody-based immunoassay is one of the most successful techniques which are employed to detect bacterial cells, spores and viruses. An antibody is a protein (immunoglobulin) which produced by B-lymphocytes in response to stimulation by an antigen. Quantitative detection of antibody/antigen can be obtained by a variety of methods. Labeling the antigen/antibody is one of the most common methods. The label may be an enzyme, radioisotope, magnetic label or fluorescence. Recently, immunological detection has been extensively developed for the bacterial detection. One is Enzyme-Linked ImmunoSorbent Assay (ELISA). ELISA is an excellent method which was used to detect bacteria in food successfully [6-7]. The ELISA test is based on the concept that a molecule (e.g. antibody or antigen) is immobilized to a plate. There are three frequently-used forms of ELISA test: sandwich assays, indirect assays, and competitive assays as shown in Figure 2-2. The form selected is case-dependent, which means the availability of reagents and the dynamic range required for a certain assay should be considered. Usually, sandwich assays are more sensitive and robust and therefore are used frequently. In sandwich assays, the primary antibody, which is highly specific to the antigen, is firstly immobilized onto a plate (shown in Figure 2-2(a)). Then, the antigen and the secondary antibody as the detection antibody are added consequently to form ?sandwich? structure between the two antibodies. Usually, an enzyme is attached to the detection antibody to generate a different epitope. Finally, the substrate is added to react under the enzyme and produce a colorimetric readout as the detection signal, which is proportional to the amount of target antigen. The indirect assays involve the antigen attached to a plate firstly, as shown in 13 Figure 2-2(b). Then the primary antibody specific to the antigen is added into the plate. A species-specific antibody (secondary antibody) labeled with enzyme is added next. The same as the sandwich assay, the substrate is added to produce the signal. The signal is directly indicate the amount of an antibody to a specific antigen. (a) (b) (c) Figure 2-2. The schematics of three types of ELISA assays. (a) Sandwich assays; (b) Indirect assays; and (c) Competitive assays. Competitive assays (Figure 2-2(c)) are based on the competition of labeled and unlabeled ligand for a limited number of antibody/antigen binding sites. This method usually is used to measure small analytes, or while the primary antibodies and secondary antibodies to the antigen do not exist. Only one antibody is used in this assay due to the steric hindrance from two antibodies binding to a very small analyte. The steps for competitive ELISA assay are somewhat different with the above two assays. To quantify the small analytes, a fixed amount of labeled antigen and variable amount of unlabeled 14 antigen are added into the antibody-coated plate. The more unlabeled antigen, the less labeled antigen bound to the antibody. Then the secondary antibody specific to labeled antigen is added to generate the signal. For competitive ELISA, the more the unlabeled antigen in the sample, the weaker the eventual signal. However, most of these molecular methods are laborious and require the well-skilled personnel. It still needed to develop robust molecular based in-field test. 2.3 Biosensors A biosensor is an analytical device incorporating a biological sensing element (probe/receptor) to a transducer (platform) system. The schematic of a typical biosensor is shown in Figure 2-3. The bio-recognition element, such as antibody, is highly specific to the target species [9-10]. The reaction between the target species and the bio-recognition unit would result in some changes in the physical/chemical properties of the recognition unit. These changes are measured by using a transducer. According to the transduction methods, the biosensors can be classified into three main types: electrochemical biosensors [11], optical biosensors [12], acoustic wave (AW) devices [13-15]. The first biosensor, the ?enzyme-electrode? was demonstrated by Clark and Lyons in 1962 [8], which was used to measure glucose concentration in solution. The novel discoveries in optics (e.g. the evanescent wave phenomenon) and the use of piezoelectric-based acoustic wave devices were contributed to the development of biosensors. AW sensors attracted a great deal of attentions since it can offer many advantages such as real-time detection, simplicity of structure, ease to be miniaturize and cost effectiveness. 15 E Ab Nucleic Acid Signal Transducer Sample Enzyme reaction Immuno-reaction DNA hybrid S P Etc. Figure 2-3. Schematic diagram of a typical biosensor. E and Ab represent enzyme and antibody respectively. 2.3.1 Electrochemical sensors Electrochemical biosensors are the most common type of biosensors which coupled a biological recognition element to an electrode transducer. In this process, an electrochemical species (e.g. electrons) are consumed or generated to produce a useful electrochemical signal, which can be measured by an electrochemical detector. According to the electrochemical property measured by a detector, electrochemical biosensors may be classified into conductometric, potentiometric, and amperometric biosensors. Conductometric biosensors measure the changes in the conductance of the biological component arising between a pair of metal electrodes [16-18]. Potentiometric and amperometric biosensors are the most commonly used in conjunction with electrochemical biosensors. In potentiometric biosensors, the analytical signal is obtained by converting the biorecognition process into a potential signal and the potential difference between an indicator and a reference electrode was measured. They function under equilibrium conditions and monitor the accumulation of charge at zero current, created by selecting binding at the electrode surface [19-20]. Amperometric biosensors monitor the current resulted from the electrochemical oxidation/reduction of an electroactive species which involved in the recognition process at a constant applied potential. It usually performed by maintaining a constant-potential at a Pt, Au or C based 16 working electrode or an array of electrodes with respect to a reference electrode. Amperometric biosensors are more attractive because of its high sensitivity, rapid response, wide linear range and low cost [21]. The advantage of linear concentration dependence of amperometry makes it well suited for bacterial assay. Amperometric sensors aimed at microbial analysis have been reported [22-24]. It was reported that the detect limit is 10 4 ~10 5 cfu/ml of Staphylococcus aureus by using amperometric biosensors [22]. The limitation of this method was the variation in the signal produced by different strains of bacteria. Despite of the large number of published reports on electrochemical biosensors capable of detecting microorganisms, it is still a challenge to create electrochemical biosensors with the necessary properties for reliable and effective determination of microorganism in real samples. A biosensor must be able to provide a lower detection limit with a rapid analysis time at a relatively low cost. Biosensor development facing some technical problems that include the interaction of matrix components, methods of sensor calibration, the requirements for reliable and low maintenance functioning over extended periods of time, sterilization, reproducible fabrication of numerous sensors, the ability to manufacture the biosensor at a competitive cost, disposable format, and a clearly identified market. The next generation of battlefield detection devices will most likely be stand-alone, multi-analyte, remote sensing, fully automated devices with integrated sample preparation and biosensing elements. 2.3.2 Optical sensors Optical sensor is based on the measurement of photons, rather than the electrons in electrochemical sensors, especially measurement of absorbance, reflectance, or 17 fluorescence emissions occurred in the ultraviolet (UV), visible, or near-infrared (NIR). So far fluorescence is the detection method most often applied and comes into a variety of schemes. In fluorescence biosensing, the detection parameters include the intensity, decay time, anisotropy, quenching efficiency, luminescence energy transfer, and so on. According to the detection parameter, the fluorescence biosensing can be divided into three types: direct sensing, which the molecule being detected before and after a change/reaction; indirect biosensing, where a dye is added to optically transduce in the presence of an analyte [25]; and fluorescence energy transfer (FRET), which an energy transfer during the reaction. Optical layouts include plain sensor foils and also waveguide optical systems, capillary sensors, and arrays. The advantage of optical biosensors is that their results are either real time or close to real time. As the molecule being detected comes into contact with the biologic or biological sensing element an optical change occurs that the biorecognition element detects. The only limitation is the rate at which the instrument processes the data and therein displays the information to its operator. Optical sensors based on the excitation of surface plasmons are called surface plasmon resonance (SPR). SPR biosensors were well developed by different companies in the last more than 15 years. The geometrical setup of SPR biosensors is mostly in the easy-to-build Kretschmann configuration as shown in Figure 2-4. In general, an SPR is comprised of an optical system, a medium and an electronic system. SPR detects a change in the propagation constant (e.g. coupling angle, coupling wavelength, intensity, and phase) of the surface plasmon caused by a change in the refractive index of the dielectric through coupling condition. Accordingly to the measured characteristics of the light wave modulated by a surface plasmon, SPR sensors can be classified as sensors 18 with angular, wavelength, intensity, or phase modulation [26]. In SPR sensors with angular modulation, a surface plasmon was excited by a monochromatic light wave. The strength of coupling between the incident wave and the surface plasmon is observed at multiple angles of incidence, typically by employing a convergent light beam. The excitation of surface plasmons is found as a dip in the angular spectrum of reflected light. The angle of incidence yielding the strongest coupling is detected and used a sensor output [27]. In SPR sensors with wavelength modulation, a collimated light wave containing multiple wavelengths was used to excite a surface plasmon, typically a beam of polychromatic light. The excitation of surface plasmons is observed as a dip in the wavelength spectrum of reflected light. The wavelength yielding the strongest coupling is acted as a sensor output [28]. Intensity modulation is based on the measurement of the strength of the coupling between the light wave and the surface plasmon at a single angle of incidence and wavelength, and the intensity of light wave used as a sensor output [29]. In SPR sensors with phase modulation the shift in phase of the light wave coupled to the surface plasmon is measured at a single angle of incidence and wavelength of the light wave and served as a sensor output [30]. In the last decades, various pathogens in food including Escherichia coli O157:H7, Salmonella typhimurium, and the like have been studied by SPR biosensors. By using SPR, Escherichia coli O157:H7 was first detected by Fratamico et al. in 1998 [31]. After that, numerous SPR biosensors for detecting of Escherichia coli O157:H7 have been reported. Choi?s group combined Multiskop (Optrel GBR, Germany), a commercial SPR sensor, with monoclonal antibodies immobilized on a protein G-coated sensor surface. The sensor was capable to directly detect Escherichia coli O157:H7 and the limit of 19 detection (LOD) was at 10 4 cells/ml [32]. To improve the sensor performance, by conjunction with the immobilization of antibodies via a mixed SAM of alkanethiolates, they used the same SPR instrument which can detect Escherichia coli O157:H7 down to 10 2 cells/ml [33]. Additionally, Choi?s group also demonstrated the detection of Salmonella typhimurium in buffer by using the same instrument and monoclonal antibodies immobilized via protein G attached to an alkanethiolate SAM on the sensor surface. The LOD was found at the concentration of 10 2 cells/ml [34]. It was reported that the LOD for Salmonella typhimurium in milk was at 10 5 cells/ml [35]. Light source Detector Prism Glass slide Gold Flow channel Figure 2-4. Schematic of SPR based biosensors. In the past 5 years, the performance of SPR biosensors has been improved in terms of sensor hardware and biospecific coatings. However, SPR sensors still face some challenges regarding certain measurements: (1) refractive index is the only signal measured by SPR; (2) surface chemistry is limited by the obligatory noble surface (e.g. gold); (3) the SPR signal (e.g. the refractive index) is influenced by physical side effects, which means the instruments should be calibrated in different buffers. Thus, advanced SPR sensor platforms in combination with novel biospecific surface is still urgently 20 needed for rapid, sensitive and specific detection of bacteria in food and environment. 2.3.3 Acoustic wave devices Acoustic wave (AW) devices are operated based on acoustics ? the use of elastic/mechanical waves at frequencies well above the audible range propagating in specially designed solid sensing structures. AW devices have been commercially used for more than 60 years. For example, the surface acoustic wave devices acted as bandpass filters are successfully used in transceiver electronics. Additionally, AW devices are also used as torque and tire pressure sensors in automotive industry, chemical sensors in medical applications, and the sensors to measure vapor, humidity, temperature and mass in environment. AW devices are low cost, inherently rugged, very sensitive, and intrinsically reliable. Some are also capable of being passively and wirelessly interrogated (no sensor power source required). 2.3.3.1 Classification of AW devices Usually AW devices use a piezoelectric material to generate the acoustic wave. When the acoustic wave propagates through or on the surface of the piezoelectric material, a change of the characteristics of the propagation path gets rise to a change of the velocity/amplitude of the wave, which can be monitored by measuring the frequency/phase characteristics of the device. A wave propagating through the substrate is called a bulk wave which including the Thickness-Shear Mode (TSM) resonator and Shear-Horizontal Acoustic-Plate-Mode (SH-APM). If the wave propagates on the surface of the substrate, it is called a surface wave. The most commonly used surface wave devices are Surface-Acoustic-Wave (SAW) sensor and Shear-Horizontal Surface Acoustic Wave (SH-SAW) sensor. One of the other AW devices is base on 21 Flexural-Plate-Wave (FPW). The schematics of these several main AW devices were shown in Figure 2-5 and their advantages and disadvantages were listed in Table 2-1. TSM (Figure 2-5(b)) typically consists of a thin disk of AT-cut quartz with circular electrodes patterned on both sides. Usually TSM resonator uses a piezoelectric substrate material in which the electric field generated between electrodes couples to mechanical resonances. Therefore, in a practical sensor, changes in resonance frequency of the device are measured electrically (e.g. electrical admittance). SAW generated and moving either directions of wafer Electrode (Transducers) Piezoelectric Substrate Membrane Amplifier Output frequency Piezoelectric film Silicon substrate (a) Output Transducer Cross-section Displacement Input Transducer Quartz Plate Wave Propagation Surface Displacement (b) (c) (d) Figure 2-5. The schematics of several important AW devices: (a) SH-APW; (b) TSM; (c) SAW, and (d) FPW. [36-39] SAW devices (Figure 2-5(c)) are based on stress-free boundary imposed by the surface of a crystal gives rises to a unique acoustic mode whose propagation is confined to the surface and therefore known as a surface acoustic wave. SAW is most conveniently 22 excited on a piezoelectric crystal using an interdigitated electrode pattern, or interdigital transducer (IDT). For an IDT, the transducer operates most efficiently when the SAW wavelength matches the transducer periodicity. This occurs when the transducer is excited at the synchronous frequency, defined by the product of the SAW propagation velocity over the transducer periodicity. When SAW devices are used for sensors or thin-film characterization, the interactions between surface waves and a perturbation give rise to wave velocity and attenuation response. This surface wave is very sensitive to the surface perturbation. Therefore, SAW sensors exhibit a much higher sensitivity than TSM. However, the presence of the surface-normal displacement component makes the SAW poorly suited for liquid sensing application. SH-APW sensors use a thin piezoelectric substrate/plate which is functionalized as an acoustic waveguide confining the energy between the upper and lower surfaces of the plate (shown in Figure 2-5(a)). Therefore, both faces of the crystal undergo displacement, so that detection can occur on either surface of the device. SH mode has particle displacements predominantly parallel to the device surfaces and normal to the direction of propagation. The absence of a surface-normal component of displacement allows SH plate mode to propagate in contact with a liquid without coupling excessive amounts of acoustic energy into the liquid, which makes it suit for liquid sensing application. The sensitivity of the SH-APM depends on the thickness of the substrate. SH-APM sensors are more sensitive than TSM resonator, but less sensitive than SAW sensors. There are two reasons: one is the sensitivity to mass loading and other perturbations is substrate thickness reversal dependent, which means sensitivity increasing as the device is thinned and the minimum thickness is constrained by 23 manufacturing processes. The other one is that in SH-APM sensor, the wave energy is not maximized at the surface, which reduces sensitivity since the sensitivity is proportional to the amount of energy in the propagation path. Table 2-1. Review of AW devices. Techniques Advantages Disadvantages TSM resonator Thickness Shear Mode QCM (quartz crystal microbalance)[13-14] High sensitivity; Easy to use; Cost effectiveness. The sensitive material has to be brought onto one of these electrodes; Need an external voltage source to generate the signal. SAW device [40] (Surface Acoustic wave) more sensitive, low cost and better reliability than TSM Restricted to crystal surface; Not work well in liquid since the acoustic wave got damped severely. FPW device [14] (Flexural Plate Wave) Higher sensitivity in low frequency range than SAW Difficult to fabricate MC [15, 41] (Microcantilever) Compact size; Easy integration with analysis circuit; Higher sensitivity than other AW devices The amplitude of the resonant peak and Q value reduce significantly in a viscous environment such as air or liquid MSMC[42] Magnetostrictive microcantilever Rapid response; Easy to operate; Wireless sensed Low-cost production Q value and amplitude need to be increased when exposed to liquid system In a FPW device (Figure 2-5(d)), an acoustic wave is excited in a thin plate, whose thickness is a fraction of the acoustic wavelength. FPW can be dimensioned so that its phase velocity is lower than that of most liquids, when the FPW device contacts or is immersed in such a liquid, a slow mode of propagation exists in which there is no radiation from the plate. FPW device works well in a liquid environment. FPW device has a very high sensitivity due to its very small thickness. 24 2.3.3.2 Operation principle An AW device is an acoustic resonator and mostly works as a mass sensor. That is, the reaction between the bio-recognition component and the target species results in a change in the mass load of the transducer/resonator, which shifts the resonance frequency. Thus, by monitoring the resonance frequency of an AW device, the reaction between the bio-recognition unit and the target species, such as captured bacterium cells by antibody/phage, can be determined. An AW device as a transducer used in biosensors is characterized using two critical parameters: mass sensitivity ( dm df S m ?= ) and quality merit factor (or Q value). The mass sensitivity is defined as the shift in resonance frequency due to the attachment of a unit mass, while the Q value reflects the mechanical loss of the devices and characterizes the sharpness of the resonance peak in the amplitude/phase versus frequency plot. A higher S m means a more sensitive device, while a higher Q value represents a capability to determine a smaller change in resonance frequency (i.e. a higher resolution in determining resonance frequency). Therefore, it is highly desirable for an AW device to have a higher S m and a larger Q value. Among all AW devices, micro/nano-cantilever exhibits extremely high sensitivity primarily due to its small mass [41, 43-44]. For example, the detection of a mass as small as 10 -18 g using cantilever has been demonstrated. Therefore, a great deal of efforts has been spent on the development of micro/nano-cantilever based biosensors. However, the current cantilever used in liquid exhibits a small Q value, which makes the cantilevers work poorly in liquid. For example, the Q value of these cantilevers in liquid is barely more than 10 [15, 45]. This is really a challenge for cantilever-based biosensors since most of the samples to be tested are liquids. 25 2.3.3.3 A typical AW device - QCM A quartz crystal microbalance (QCM), a type of TSM resonator, is a piezoelectric based mass sensor which can be used in different environments (e.g. vacuum and liquid). A QCM is a gold-coated quartz crystal as shown in Figure 2-6. As a sensitive surface mass sensor, QCM has been also extensively studied as transducer for biosensors due to its simplicity, convenience and real time response [48-49]. The schematic of QCM as biosensor is shown in Figure 2-6. The QCM sensors generally measure the immune reactions in liquid between immobilized and target molecules (e.g. antibody and antigen) [50-51]. It is also effective at determining the affinity of molecules (e.g. protein) to surfaces functionalized with recognition sites. The detection limit and response time for QCM reported by Hao et al., on 2009 is about 10 3 cfu/ml and less than 30 min respectively for detecting of Bacillus anthracis spores and vegetative cells [52]. Au electrode Crystal substrate Au electrode Antibody Antigen Due to bacteria binding Figure 2-6. Construction of a QCM biosensor and its principle. 26 2.3.4 Microcantilever based biosensors 2.3.4.1 Operation mode Recently, micro- and nanometer scale cantilevers have been studied as sensor platforms using physical principles that are similar to those found in atomic force microscopy. In terms of actuating and sensing technologies, Microcantilevers (MCs) can be operated based on three different principles: static, heat, and dynamic modes [53-55]. The static deflection mode [56-58] is based on that the binding on one side of a cantilever causes unbalanced surface stress resulting in a measurable deflection up or down (shown in Figure 2-7(a)). In this mode, the target molecules should be only bound on one side of the cantilever, otherwise the additional stress from the opposing surface would cancel and the cantilever will not bend. The deflections of about 10nm for the cantilever sensors were caused by surface stresses of several 10 -3 N/m [59]. (a) (b) (c) Figure 2-7. Cantilever sensor modes of operation: (a) static mode, where asymmetric molecular binding to the cantilever?s top surface leads to an overall cantilever bending, (b) heat mode detecting temperature changes by a static bending due to different thermal expansion of the metal layer and silicon cantilever, and (c) dynamic mode detecting mass changes on the cantilever by changes in resonance frequency. [60] In heat (bimetallic) mode [53, 55], the cantilevers are coated by a thin metal layer. Thus, heating up or cooling down metal-silicon cantilever structure will result in the 27 difference in the thermal expansions of these two materials and thus bending of the cantilever as shown in Figure 2-7(b). It can be measured the cantilever deflections of several nanometers while the temperature changes of 10 -5 K. In dynamic mode [61-62] the cantilever is an oscillator as shown in Figure 2-7(c); the binding on the cantilever increases mass and thus lowers the resonant frequency, much like quartz crystal microbalances. It can be detected that a change of 1 Hz in resonance frequency roughly corresponds to a mass change of 1 pg for the cantilever [62]. MCs based on the dynamic mode have many advantages over those based on the static mode, such that both surfaces of the device can be used for sensing and no preferable orientation of cantilever beam (in static mode, the cantilever beam has to be horizontal). Dynamic MCs investigated so far can be classified into two types [15, 45]: passive and active. The passive MCs, e.g. silicon-based MCs [46], require a mechanical system to actuate the device oscillation and an optical system to measure the vibration of the device. On the other side, the active MCs, e.g. piezoelectric MCs [63], can be actuated by simply applying an electric field, and the vibration of active MCs can be easily monitored (e.g. impedance for piezoelectric MCs). 2.3.4.2 Cantilever arrays Disregarding of the operating mode of MCs, it is always of advantage to use several cantilevers in parallel, so called array, as indicated in Figure 2-8. It is evident that more information from a single experiment can be obtained by using sensor arrays. A lot of concerns in biological detection have risen since the biological systems are normally more complex and more unique than physical systems and their properties are actual environment dependent. We have already known that cantilevers are 28 temperature-sensitive sensors and might also respond to changes in buffer composition. In addition, not only the target molecules, also several other molecules in the sample might interact with the sensor. To eliminate the noise signal for measurement environment, the cantilever array, which was composed several physically identical cantilevers only covered with different surface coatings is as a substitute alternative of single cantilever. The physical identity should be checked before an experiment by either recording the thermal responses of the cantilevers by a well defined heat pulse or by measuring the resonance frequencies. Up to now, cantilever arrays of up to eight cantilevers in parallel were preformed in complex biological samples. Figure 2-8. Scanning electron micrograph of a cantilever sensor array. [64] 2.3.4.3 Surface functionalization In order to recognize and identify the complex biological systems, the surface of cantilevers should be changed to an intelligent sensor surface. Therefore, it is an important issue for sensor applications to coat or functionalize the sensor surface with the recognition layer which can define the application and performance of a sensor. One of the major challenges in sensor application is how to tailor biosensor coatings so that the biological recognition elements are tightly bound to the sensor surface but are still functional as in their natural environment [65]. 29 Cantilever biosensors in the surface stress mode, only one side of a cantilever need coat biological receptors for the target molecules, whereas the other side should prevent any specific or non-specific adsorption of sample molecules. Surface coatings have to be reliable, and they should be robust against changes in buffer and temperature and ideally withstand repetitive detection and cleaning cycles. Cantilever sensors, interactions on top of the sensing layer should be fully transferred to the underlying substrate favoring a dense and covalent surface functionalization with receptor molecules close the surface. Up to date, usually cantilevers show two distinct surfaces including silicon based and gold based surface. Therefore, silane and thiol chemistry can be used to respectively modify the silicon and gold surface with different receptor layer or inert coatings. Based on the high affinity between gold and sulfur groups, the gold surface can be modified by thio-labeled nucleic acids/proteins exposing cysteines at the surface [66]. Additionally, thiolated poly(ethylene glycol)s can act as inert layers which prevent molecular adsorption on the cantilever surface. For the silicon based surface, it can be modified by amino- or mercapto-silane monolayers since its end groups can be further cross-linked to receptor molecules [67]. On the other hand, the negatively charged silicon dioxide can electrostatically absorb the highly positively charged molecules. But there are different sophisticated methods for surface modification for different biosensing applications. 2.3.4.4 Biological applications Cantilever-based devices as highly versatile sensors have already shown an impressive performance by using mechanical, optical, electrostatic, and electromagnetic methods to actuate/sense cantilever motion and a move to more advanced applications 30 (e.g. gases, chemicals, or biological organisms). Cantilever sensors can be operated in various environments including vacuum, air, or liquids. The major advantages are the wide field of applications, that they are small size and label-free, and provide fast response time, high sensitivity, can be microfabricated, and need only small sample volumes for their operation. The response of cantilever is, to date, comparable with other established label-free biosensing methods and a general setup can be easily modified to detect a variety of different parameters and substances such as temperature, mass, gases, biomolecules or cells. 2.4 MSMC-based biosensors Silicon-based MCs have been much more widely investigated than active MCs because of the availability of microfabrication techniques for silicon-based materials and devices. Additionally, silicon-based MCs exhibit a larger Q value and a higher S m than piezoelectric-based MCs [42]. However, it is still a big challenge for current MC-based biosensors operating in liquids. For example, the Q value of these cantilevers in liquid is barely more than 10 [15, 45]. Table 2-2. Comparison MSMC with Current MCs. Characteristics Silicon based MCs Piezo based MCs MSMCs Transduction Optical (separated bulk system) Electrical (on broad circuit) Magnetically (wireless, no connection) Operate in air Yes Yes Yes Operate in liquid Difficult Very difficult Works well Q value High (>100 in air) Low (<100 in air) Very high (>200 in air) Structure Simplest Complicated Simpler Fabrication Easy Difficult Easy Overall sensitivity High Low High 31 Magnetostrictive materials have been widely used in the development of actuators and sensors due to their low cost and robustness [68-74]. By using magnetostrictive materials, a new type of active cantilever, magnetostrictive cantilever, was introduced recently as a biosensor platform. Magnetostrictive milli/micro cantilevers (MSMCs) can be easily actuated and sensed. More importantly, they exhibit a high Q value, ~500 in air and ~30 in water, respectively [42]. The comparison of three cantilevers was reviewed in Table 2-2. 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The active layer used here is an amorphous magnetostrictive alloy, Metglas TM 2826 ribbon (Honeywell, Morristown, NJ); the inactive layer is Cu thin film sputtered on the Metglas using magnetron DC sputtering system. Figure 3-1. The schematic of Magnetostrictive cantilever. The properties of cantilever beam such as density, Young?s modulus, and Poisson?s ratio are listed in Table 3-1. The thickness is 20 ?m and 15 ?m for the active layer and the inactive layer, respectively. Since these two layers have the same length and L Magnetic field W h Magnetostrictive materials (actuating layer) Copper (inactive layer) 41 width, the volume of these two layers is only thickness dependent. Thus, the average density calculated from the Metglas TM 2826 alloy and Cu can be used as the density of the MSMC. In fabrication of MSMCs, firstly the Metglas TM 2826MB ribbon was polished to about 20?m of the thickness by using 2000# polish paper and then cleaned with acetone in a Cole Parmer 8891 ultrasonic cleaner for ten minutes. The copper layer (~15 ?m in thickness) was sputtered on the polished Metglas thin film. Prior to the deposition of copper layer, a chromium thin film of 100 nm in thickness was deposited on the Metglas to enhance the bonding between Metglas layer and copper layer. The copper/Metglas bilayer was then cut into rectangles (strips) in different sizes. The bilayer strip was clamped at one end using a PMMA plastic holder to form the cantilever or MSMC. The cantilever was then coated with a gold layer (~ 130 nm in thickness) by magnetron sputtering. The gold layer is employed to prevent the corrosion of the cantilever and to promote the immobilization of the bio-recognition element. Prior to the gold deposition, a thin layer of chromium with a thickness of 100 nm was sputtered on the cantilever as the adhesion layer. The Denton Sputtering System was employed in all the sputtering steps. Table 3-1. The effective material properties of Metglas TM 2826, Cu thin film, and cantilever beam. Materials Density g/cm 3 Young?s Modulus GPa Thickness ?m Poisson?s Ratio Metglas TM 2826 [1] 7.9 100-110 20 0.5 or 0.33 [3] Copper thin film [2] 8.9 110 15 0.36 Metglas TM /Cu bilayer 8.32 110 35 0.5 42 3.2 Operation principle The operation principle of all acoustic wave devices based sensor platforms are the same: a change in the mass load on the sensor shifts the resonance frequency, which can be measured and recorded by using computer-based output system. The sensing principle of the MSMC platform is shown in Figure 3-2. An MSMC consists of two layers: magnetostrictive/active layer and inactive layer as shown in Figure 3-2 (a). Due to the magnetostrictive effect, the length of the active layer would change under magnetic field. Meanwhile, the inactive layer, bonded together with the active layer, restricts the length change, which would result in the bending of the MSMC. If a time-varying (ac) magnetic field (see Figure 3-2 (b)) is applied, a bending/flexural oscillation of the MSMC would be induced. Due to the magnetic nature, the bending/flexural oscillation of the MSMC results in an emission of a magnetic flux, which can be detected using a pick-up coil (see Figure 3-2 (c)). The output oscillating signal (e.g. phase signal) of the pick-up coil is shown in Figure 3-2 (d). (c) Pick-up Coil Time-Varying Magnetic Field (a) MSMC Frequency Pha s e (b) ac magnetic field Frequency Am plitu d e (d) Figure 3-2. Schematic illustration of the principle of MSMC as a transducer for biosensors. 43 If the time-varying magnetic field is a sine wave, the bending vibration of an MSMC would also be a sine function of time. Since the magnetostrictive strain response (?) is an even function of the driving magnetic field (H), as shown in Figure 3-3, the MSMC is usually actuated using a small ac signal imposing on a large dc bias. As revealed in Figure 3-3, if only a small ac magnetic signal is applied, the strain response in the material is in a quadratic function of the driving magnetic field. As a result, the strain response is small and at a frequency that is the double of the frequency of the driving ac field. On the other hand, if the small ac field is imposed on a dc bias, a larger ac stain response is observed at the same frequency as, and is proportional to, the ac driving field. Therefore, an MSMC is usually operated by imposing a small ac magnetic field on a dc bias. H H DC ? AC AC ? Figure 3-3. The magnetostriction response of a magnetostrictive material under the external magnetic field (H). 44 Wireless driving/sensing is the principal advantage of the MSMC over current MCs. Additionally, if the inactive layer is a magnetic material, the signal from the pick-up coil can be enhanced and the dc field may not be needed. This is another advantage offered by MSMC, which would be important for small-size MSMCs. That is, for MSMCs with the same size, the signal strength can be enhanced over some range, which is a desired feature for real-time detection since the distance between the sensor and the interrogation system may change over a range due to the different requirements. Phage Gold layer MSMC Bacteria MSMC Ph a s e Frequency (f 0 ) H dc H ac H dc H ac Ph as e Frequency (f 0 ) Figure 3-4. The schematic illustration of the operation principle of MSMC based biosensors for detecting bacteria. The binding of bacteria on both sides of the MSMC. The principle of the MSMC as the biosensor platform was shown in Figure 3-4. The MSMC platform coated with the biological recognition element (e.g. phage or antibody for antigen) will lower the resonance frequency due to the bacteria/antigen binding on the sensor surface. The shift of resonance frequency caused by the mass load can be expressed as the mass sensitivity and will be discussed in Section 4.2. The binding bacteria can be obtained by analysis the frequency shift based on the mass sensitivity. 45 3.3 Theory The wave equation for the bending/flexural wave motion of a rectangular cantilever beam (in the length of L, width of W, and thickness of h) without damping can be expressed as [4]: 0' 4 4 2 2 = ? ? + ? ? x y IE t y M C (3-1) where y is the bending deformation of the beam at the point x (x-direction is along the length of the cantilever, as shown in Figure 3-1. Under the assumption of a beam structure withW >> h , the effective Young?s modulus is given by 2 1 ' ?? = E E (3-2) where ? and E are Poisson?s ratio and Young?s modulus of the cantilever beam, respectively. The moment of inertia for a rectangular beam can be given 3 2/ 2/ 2 0 12 1 WhdzdyzI h h W ?? ? == (3-3) WhM C ?= is the effective mass of cantilever beam, where ? is the effective mass density of the beam material. For harmonic oscillations, we can substitute ti eyy ? 0 = in Eq. (3-1) and obtain 0' 4 0 4 0 2 = ? ? +? x y IEyM C ? (3-4) which we can write as 0 4 4 0 4 )( y Lx y ? = ? ? (3-5) where 46 IEM L C '/)( 24 ? ? = (3-6) x y x=0 x=L Figure 3-5. The deflection schematic of cantilever beam. The general solution of a homogeneous fourth-order differential wave equation is the sum of four linear independent solutions x L Dx L Cx L Bx L Ay ???? sincossinhcosh 0 +++= (3-7) where A, B, C, and D are the constants. For a cantilever beam rigidly fixed at one end (x=0) and free at the other end (x=L) (see Figure 3-5), considering the boundary conditions for various types of attachment of the beam, 0)0( 0 ==xy , 0 0 0 = ? ? =x x y , for 0=x , 0 2 0 2 = ? ? =Lx x y , and 0 3 0 3 = ? ? =Lx x y , for Lx = (3-8) where the first two boundary conditions are due to the fact that one end of the cantilever 47 beam is clamped. The third one and the fourth one are due to no bending moment and shear force at the free end of the cantilever beam. We put Eq. (3-8) into Eq. (3-7), the detailed calculation steps were listed in Appendix 1, and a characteristic relationship can be obtained [4] 1coshcos ?=?? (3-9) 0 5 10 15 20 25 -1 0 1 n=6 n=5 n=4 n=2 n=3 n=1 n=0 -1/cosh? cos? f( ? ) ? Figure 3-6. Curves of ?cos , and ?cosh 1 ? . The eigenvalues for a cantilever with one end free and the other end fixed can be graphically obtained from the intersections of these two curves. The eigenvalue ? can be obtained either graphically or by approximate methods, or even using tables of functions. For example, the eigenvalue ? of different modes can be determined by graphically solved Eq. (3-9) (see Figure 3-6) and the first seven eigenvalues were given in Table 3-2. For the higher harmonic mode, the eigenvalues might be estimated by using ?)5.0( +n [6]. 48 Table 3-2. Graphically obtained Eigenvalues for the flexural resonance modes of MSMC. Resonance mode i ? 2 i ? 1 / ?ii ff Theoretical i=0 1.8751 3.5160 - i=1 4.6941 22.035 6.267 i=2 7.8548 61.697 2.800 i=3 10.996 120.90 1.960 i=4 14.137 199.86 1.653 i=5 17.279 298.56 1.494 i=6 20.420 416.99 1.397 ? ? ? ? i=n ?)5.0( +n [34] [ ] 2 )5.0( ?+n 2 5.0 5.0 ? ? ? ? ? ? ? + n n Based on the eigenvalues for the resonance harmonic modes at 0-3, we can calculate the constants A, B, C, and D for Eq. (3-7) and the results were listed in Table 3-3. Actually, A is the values of B times. For example, for the fundamental mode, BCA 3622.1?=?= . Since B is related to the amplitude of wave Eq. (3-7), but not the shape of the oscillating motion. Thus, we just use B=1 in the plot of the harmonic motion of the cantilever beam. Table 3-3. The constants A, B, C, and D for the first four harmonic modes. Mode ? Sinh ? Cosh ? Sin ? Cos ? A B C D 0 1.8751 3.1841 3.3374 0.95415 -0.29963 -1.3622 1 1.3622 -1 1 4.6941 54.646 54.658 -0.99983 -0.01829 -0.9819 1 0.9818 -1 2 7.8548 1289.0 1289.0 1.0000 -1.0008 -1.0008 1 1.0008 -1 3 10.996 29818 29818 -1.0000 -1.0000 -1.0000 1 1.0000 -1 Note: if B is 1, the data in Table 3-3 is exact value; otherwise, the constants should be B times. The natural resonance motions of the first four harmonic modes of vibration are shown in Figure 3-7. It showed that certain regions of the cantilever (e.g. the Nodal point) do not take part in the vibration displacements and the positions of these parts are not 49 changing with the mode of vibration. For example, for the 0 th harmonic mode, the Nodal point is sitting on the clamped end of the cantilever. Therefore, the sensitivity of a cantilever to the added mass and mass responsivity is different along the cantilever at different vibration modes. The simulation by using Eq. (3-7) showed that the largest responsivity to the additional mass was achieved at its application close to the cantilever?s free end for the 0 th mode [7], and the mass sensitivity was described and calculated in Section 4.3. 01 0 3 rd mode 2 nd mode 1 st mode 0 th mode : Nodal point Figure 3-7. The natural vibration motion at 0 th -3 rd harmonic modes and the nodal points (violet triangles) 0-3 at the 0 th , 1 st , 2 nd , and 3 rd resonance oscillation modes of the clamped cantilever which were obtained from Eq. (3-7). By combining Eq. (3-2), Eq. (3-3), with Eq. (3-6), the angular frequency of a rectangular cantilever can be obtained 50 22 2 )1(12 2 L hE f nnn ?? ??? ? == (n = 0, 1, 2, ?) (3-10) Thus, the natural resonance frequency of the n th -mode without damping for a rectangular cantilever is [4, 8-9]: )1( 122 22 2 ?? ? ? ? = E L h f n n (n = 0, 1, 2, ?) (3-11) where 5.0=? . Liang et al. [3] modified Eq. (3-11) by using the plane-stress or biaxial modulus as, )1(122 2 2 ??? ? ? = E L h f n n (n = 0, 1, 2, ?) (3-12) where 33.0=? . 3.4 Determination of several important parameters 3.4.1 Characteristic frequency Figure 3-8 gives a typical resonance spectrum of an MSMC obtained from the output signals (the amplitude signal and the phase signal) of the pick-up coil. The amplitude signal reflects the amplitude of the bending oscillation of the MSMC, while the phase signal represents the phase difference between the ac magnetic field and the bending oscillation. For the plot of the oscillation amplitude versus frequency, the amplitude reaches the maximum at the resonance frequency (f r ) and the minimum at the anti-resonance frequency (f ar ), respectively. The phase signal reaches its peak at a frequency (f 0 ) (f r < f 0 < f ar ). In the characterization of the MSMC-based sensors, the phase signal was used to determine the resonance behavior, which means f 0 is considered as the characteristic 51 frequency of the MSMC. Based on the results shown in Figure 3-8, the f r , f ar , and f 0 are 2585, 2602, and 2594 Hz, respectively, for an MSMC with a size of 3.0 mm x 1.0 mm x 35 ?m. Thus, the characteristic frequency is 2594 Hz for the MSMC in the size of 3.0 mm x 1.0 mm x 35 ?m. Clearly, the characteristic frequency determined in this way is higher than the real resonance frequency and smaller than the antiresonance frequency of the device. This method is also used in the characterization of piezoelectric-based cantilevers [10]. 2500 2600 2700 0.0 5.0x10 -6 f 0 =2594Hz f ar =2602Hz f r =2585Hz Phase (De g r ee) A m plit ud e ( a .u.) Frequency (Hz) -2 -1 0 Figure 3-8. Measured resonance spectrum, amplitude and phase signals versus frequency from Lock-in amplifier for the fundamental mode of an MSMC in the size of 3.0 mm x 1.0 mm x 35 ?m in air. 52 2400 2600 2800 84 85 86 (a) Original peak Baseline P h as e an g l e Frequency (Hz) 2550 2600 2650 -2 0 (b) a 0 /2 a 2 a 1 a 0 P h as e (degr ee) Frequency (Hz) Normalized peak Generated peak Figure 3-9. (a). The original spectrum of phase vs. frequency from the output signal. (b). The normalized spectrum (dashed black line) and generated spectrum (red solid line). The MSMC used here is in size of 3.0 mm x 1.0 mm x 35 ?m for the fundamental mode. The red solid line is fitted by using the Lorentz fitting. 53 To precisely determine the value of characteristic frequency ( 0 f ) from the experimental results, the phase peak of the MSMC was fitted using different functions. Before fitting, the original peak shown in Figure 3-9 (a) should subtract the background (baseline) which is from the phase delay of the system. It is found that the phase peak can be fitted well using the Lorentz function. The spectroscopy function of Lorentzian amplitude can be expressed as [])/)(1/( 2 210 aafa ?+=? (3-13) where ? is the phase signal at the frequency 0 a , 1 a , and 2 a are the resultant fitting constants. From the above equation, we can obtain the characteristic frequency 10 af = . The curves from the experiment data and fitting data were shown in Figure 3- 9 (b). To determine the repeatability of the fitting, the same set of experimental data was fitted over different frequency ranges. For the data shown in Figure 3- 9 (b), the fitting results indicate that the error in the 0 f is smaller than 0.1 Hz. As we discussed Section 3.3, the resonance frequency can be theoretically calculated by using Eq. (3-11). The eigenvales for the n th harmonic mode can be graphically obtained and listed in Table 3-2. To confirm the theoretical analysis, the first five harmonics for the MSMC in size of 4.4 mm x 0.8 mm x 35 ?m were measured in this experiment. The phase signals and the characteristic frequencies for first five harmonic peaks are shown in Figure 3-10. The resonance frequencies from Eqs. (3-11) and (3-12) (theoretical analysis) and experimental measurement from Figure 3-9 were listed in Table 3-4. It is obvious that the theoretical frequencies are very close to the experimental data. The analytical error is no more than 3.2 % from Eq. (3-11). Also, the ratio of 1 / ?ii ff 54 were given in Table 3-3 and the values are very close to the ratios from the experiment. Therefore, this theory is reasonable to be used to estimate the frequency in this study. 0.0 5.0x10 3 2.2x10 4 -8.0x10 -6 -4.0x10 -6 0.0 4.0x10 -6 8.0x10 -6 (a) f 4,r =68200 Hz f 4,ar =68420 Hz f 3,r =41130 Hz f 3,ar =41310 Hz f 2,r =20820 Hz f 2,ar =20940 Hz f 0,r =1230.8 Hz f 0,ar =1242.1 Hz f 1,r =7440 Hz f 1,ar =7496 Hz 5# peak 4# peak3# peak 2# peak 1# peak 4.0x10 4 6.5x10 4 7.0x10 4 -8.0x10 -6 -4.0x10 -6 0.0 4.0x10 -6 8.0x10 -6 Am p litude (a.u.) Frequency (Hz) 1100 1200 1300 7000 7500 0 1 2 3 f 1 =7468.4 Hz f 0 =1235.9 Hz #2 peak #1 peak No rma l i z ed p h ase an g l e Frquency (Hz) 20000 21000 f 2 =20878 Hz #4 peak #3 peak 40000 42000 68000 69000 (b) f 4 =68311 Hz f 3 =41219 Hz #5 peak Figure 3-10. The first five harmonic peaks from (a) amplitude output and (b) phase output for the MSMC with the size of 4.4 mm x 0.8 mm x 35 ?m. 55 Table 3-4. The resonance frequencies for the first five modes obtained from Eqs. (3-11) and (3-12) and measurement for the MSMC with the size of 4.4 mm x 0.8 mm x 35 ?m. Harmonic 0 th mode 1 st mode 2 nd mode 3 rd mode 4 th mode rtheo f , (Hz) from Eq. (3-11) 1226.0 7683.3 21513 42166 69701 rtheo f , (Hz) From Eq. (3-12) 1297.1 8128.9 22761 44612 73743 r f (Hz) 1230.8 7444.3 20825 41136 68216 ar f (Hz) 1242.1 7492.3 20928 41306 68403 f (Hz) 1235.9 7468.4 20878 41219 68311 1- r f / rtheo f , From Eq. (3-11) -0.3% 3.1% 3.2% 2.4% 2.1% 1- f / rtheo f , From Eq. (3-12) 5.1% 8.4% 8.5% 7.8% 7.5% 1- f / rtheo f , From Eq. (3-11) -0.8% 2.8% 3.0% 2.2% 2.0% 1- f / rtheo f , From Eq. (3-12) 4.7% 8.1% 8.3% 7.6% 7.4% 2 ,Expn ? - 6.043 2.796 1.974 1.657 2 ,Theon ? - 6.267 2.800 1.960 1.653 1- 2 ,Expn ? / 2 ,Theon ? - 3.6% 0.2% -0.7% -0.2% 3.4.2 Quality factor Usually, the improvement of sensor performance can be obtained by reducing the noise while the physical signals (e.g. mechanical signal) were converted to electrical signals/magnetic signals, or by controlling other error sources (e.g. uncompensated 56 thermal drift). In this process, energy dissipation in the cantilever causes the stored vibration energy to convert into heat. A higher Q value indicates a lower rate of energy dissipation relative to the oscillation frequency, so the oscillations die out more slowly. Generally Q is defined to be [11] d i U U periodperenergydissipated energyvibrationstored Q ?? 2)(2 == (3-14) In this research, we provide the magnetic energy to resist the decay of oscillations of cantilever. Q value is used to characterize the sharpness of the resonance peak, and can be defined as the resonance peak/frequency over the width at half the peak height, as shown in Figure 3-8. Here, the resonance frequency might be substituted by characteristic frequency obtained from the phase signal. It also can be calculated by using Eq. (3-13) and given by 21 2/ aaQ = (3-15) The Q values of the first five modes of the MSMC were measured in this experiment. The experiment data (see Figure 3-9) were fitted by Eq. (3-13) and the Q values were calculated by Eq. (3-15). The results for the MSMC in size of 4.4 mm x 0.8 mm x 35 ?m were listed in Table 3-5. Clearly, the higher harmonic mode increases Q value. Meanwhile, the signal of the harmonic peak is weaker for the higher mode. In this research, the fundamental harmonic mode would be used for fundamental study (Chapter 4) and biosensing application (Chapter 5) of MSMC. 57 Table 3-5. Q values for the first five modes of the MSMC in size of 4.4 mm x 0.8 mm x 35 ?m. Harmonic mode 0 th 1 st 2 nd 3 rd 4 th Q value 126.4 132.6 195.5 227.3 324.3 In resonant detection systems, the frequency width of the resonant response is the fundamental instrumental limit, so Q value can be influenced by many factors (e.g. support loss, internal friction, and surrounding media). For example, the damping in the viscous fluids is the primary dissipation mechanism that limits the Q value and broadens the resonance. This factor motivates the device designs that optimize the ratio of mass to Q value of the cantilever. In the low pressure (vacuum) regime, viscous damping is eliminated but clamping loss, and internal structure (e.g. chemical coatings) can also contribute to mechanical losses and degrade Q value. The detailed influence of the viscous damping will be examined in Chapter 4. 3.4.3 Mass sensitivity A small change in mass (mass sensitivity) is one type of device sensitivity, which can be used when detecting single small entities such as bacteria, viruses, nanoparticles, or single molecules. Sensors with a very high absolute mass sensitivity could detect single cell and enumerate analytes. Resonant MEMS and NEMS devices actuated in vacuum have demonstrated mass sensitivity in the order of attograms or less [12-15]. Usually, sensors measure changes in mass uniformly distributed over the sensor. For example, for quartz crystal microbalance with large-scale dimension, since the bacteria number in the whole surface of sensor is a huge number, the mass sensitivity is in terms 58 of mass per unit area, which value can be translated into a value for total mass measured. If a small mass load (?m) is uniformly distributed on the surface of a cantilever beam, the mass sensitivity (S m ) of the cantilever can be written as [10, 16-17]: Wh f M f m f S n C nn unim ?22 , =? ? ? ?= (?m << M) (3-16) where n f? is the shift in the resonant frequency due to the mass load ( m? ). Figure 3-11. The schematic of the point mass loaded at the free end of cantilever beam. To examine the resonance frequency change due to a point mass loaded at the tip of the cantilever (see Figure 3-11), the effect mass of the cantilever beam should be modified as [4] WhM C ?236.0= (3-17) Therefore, by combined Eq. (3-16) and Eq. (3-17), we can obtain Wh f M f m f S n C nn tipm ?472.02 , =? ? ? ?= (?m << M) (3-18) Substituting Eq. (3-11) into Eqs. (3-16) and (3-18), the m S of a rectangular cantilever is: )1( 1 12 4 1 233 2 , ?? ? ? ? = E WL S n unim (?m << M) (3-19) )1( 1 12 944.0 1 233 2 , ?? ? ? ? = E WL S n tipm (?m << M) (3-20) Equations (3-19) and (3-20) indicates that the S m of a cantilever is determined by 59 four factors: 1) the location of the mass load, 2) resonance mode (? n ), 3) geometry (L and W), and 4) materials properties of the cantilever beam: )1( 23 ?? ? E . The values of )1( 23 ?? ? E for materials used in typical active MCs are given in Table 3-4, where a magnetostrictive alloy (Metglas TM 2826 MB used in this study) and PZT5A (a widely used and commercially available piezoelectric ceramic) are included [1, 6, 17]. The results indicate that for cantilevers with the same dimensions, an MSMC would exhibit a m S of about 36% higher than a piezoelectric MC. More importantly, as will be demonstrated below, the MSMC also exhibits a higher Q value. The length dependent mass sensitivity is shown in Figure 3-12. Two widths with 1.0 mm and 0.8 mm were used in this experiment for biosensing application. We also can find the mass sensitivity which the addition mass is attached at the tip of cantilever beam is higher than that which the addition mass is uniform distributed on the same cantilever beam. In Figure 3-12, two violet-color regions represent the mass sensitivities for the MSMC sensors which will be used in the biosensing application (Chapter 5). 60 1234 10 6 10 7 10 8 10 9 L= 2.8~3.0 mm h = 0.035 mm W = 0.8 mm W = 1 mm S m (H z/g) Length (mm) Uniform additional mass At the free ending Uniform additional mass At the free ending L= 1.4~1.5 mm Figure 3-12. The mass sensitivity (uniform and at the free end) vs. length of the MSMC based sensors with the fundamental mode. Two widths with 0.8 mm and 1.0 mm were used. 3.5 Experimental flow chart The experimental flow chart of this research is shown in Figure 3-13. It is mainly divided into three parts: fabrication of sensor?s platform, fundamental study, and biosensing application. 61 Figure 3-13. The experimental flow chart in this research. METGLAS 2826MB Ribbon Polishing (~20?m) using 2000# Polish Paper Ultrasonic Cleaning with Acetone Cutting into Strips Depositing a Cu layer (15?m) on Metglas layer by Denton Sputtering System Immersed into the test chamber containing targeted bacteria Detection limit One end of the strip was fixed by PMMA holder MSMC Yes Coating Cr/Au layer (125nm/130nm) Immobilize Phage/antibody (Static) Recording frequency shifts under different concentration Exposure time MSMC exposed OsO 4 Coating Au layer Taking SEM picture Measure resonance behavior in water High Q value Strong signal Test chamber Static system Flow system No 62 3.6 Measurement setup The photograph of measurement setup in this experiment is given in Figure 3-14. The setup used here to characterize the resonance behavior of the MSMC consists of a custom-designed Helmholtz coil and a pair of homemade pick-up coils. The Helmholtz coil consists of two pairs of coils: one pair can generate an ac magnetic field at frequency up to 500 kHz and the other pair can create a strong dc magnetic field which was connected to a dc power supply. The Helmholtz coil is linked to a lock-in amplifier (SRS830, Stanford Research Systems, Sunnyvale, CA) which provides a sine wave signal with constant RMS (root-mean-square). In this study, a dc magnetic field of 20 Oe was employed to offset the magnetic anisotropy of the magnetostrictive layer, while an ac magnetic field with the amplitude of 3.2 Oe was used to actuate the oscillation of the MSMC. An MSMC (see Figure 3-15 (b)) was put into a test chamber (see Figure 3-15 (a)) that was sited in the middle of the Helmholtz coil (see Figure 3-14). The pick-up coil was wound on the outside of the sample chamber to measure the magnetic signal emitted from the MSMC. To eliminate the background signal, the pick-up coil was made of two identical coils that were wound in opposite directions and connected in a series, as shown in Figure 3-15 (c). Therefore, the output signal of the pick-up coil only reflects the magnetic signal emitted from the bending vibration of the MSMC. The signal was measured using a lock-in amplifier, which had two outputs: amplitude and phase. The amplitude represents the oscillating amplitude of the magnetostrictive cantilever, while the phase represents the phase difference between the ac driving magnetic field and the MSMC?s bending vibration. 63 Test Chamber Figure 3-14. Measurement set-up in laboratory for this research. (a) (b) (c) Figure 3-15. The experiment design of test chamber (a), MSMC (b), and pick-up coil (c). 64 The pick-up coil was used to measure the magnetic signal from the oscillation of cantilever beam. Thus, the design of the pick-up coil is very important in order to receive the magnetic signals and to further amplify the output signals. The diameter of the pick-up coil is dependent on the dimension of MSMC used in this experiment. Usually the smaller width of the MSMC used in this experiment is 1.5 mm. Thus, the diameter of the pick-up coil should be larger than 1.5 mm to contain the cantilever beam. In this experiment, the internal diameter of the tube to make pick-up coil is 2.0 mm, and the external diameter is 3 mm. The configuration of the pick-up coil was also restricted by the inductance of the pick-up coil. The inductance of the pick-up coil is proportional to the wound turns of pick-up coil, the cross section area of coil, and reversibly to the length of the coil. As we know, the stronger signal of the pick-up coil is more preferable for the experiment, which comes from the larger inductance. Thus, several layers of pick-up coil were used to get the strong signal in order to increase cross section area, and shorten the length of coil. The magnet (copper) wire used here is relative thin with the diameter of 1.37 mm. 65 Appedix 1. The calculation steps while Eq. (3-8) was put into Eq. (3-7). 0sin0cos0sinh0cosh0 DCBA +++= CA+=? 0 (a) 0cos0sin0cosh0sinh0 DCBA +?+= DB+=? 0 (b) ???? sincossinhcosh0 DCBA ??+= ???? sincossinhcosh0 BABA +++=? (c) ???? cossincoshsinh0 DCBA ?++= ???? cossincoshsinh0 BABA +?+=? (d) Eq. (c) + Eq. (d), ???? sin)()cossinh)(cosh(0 ABBA ?++++= ??? ? cossinhcosh sin )( )( ++ ? = ? + ? AB BA Eq. (c) ? Eq. (d), ???? sin)()cossinh)(cosh(0 BABA +++??= ? ??? sin cossinhcosh )( )( +? = ? + ? AB BA Thus, we can obtained ? ??? ??? ? sin cossinhcosh cossinhcosh sin +? = ++ ? (e) ??++= ?+= +?++=? ????? ??? ??????? 222 22 2 sinhcoscoscosh2cosh sinh)cos(cosh )cossinh)(coshcossinh(coshsin 02coscosh2 0sinhcoscoscosh2coshsin 2222 =+? =?+++? ?? ?????? 1coscosh ?=? ?? (f) 66 References 1. http://metglas.com/downloads/2826mb.pdf 2. D.T. Read, Young?s modulus of thin films by speckle interferometry, Measurement Science & Technology 9 (1998) 676-685. 3. C. Liang, S. Morshe, B.C. Prorok, Correction for longitudinal mode vibration in thin slender beams, Applied Physics Letters 90 (2007) 221912. 4. J. Merhaut, Theory of electroacoustics, New York; London: McGraw-Hill International Book Co., 1981. 5. D.A. Mendels, M. Lowe, A. Cuenat, M.G. Cain, E. Vallejo, D. Ellis, F. Mendels, Dynamic properties of AFM cantilevers and the calibration of their spring constants, Journal of Micromechanics and Microengineering 16 (2006) 1720-1733. 6. A.K. 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Gray, American Institute of Physics Handbook, 3rd ed., chapter 3, McGraw hill, New York, 1973. 68 CHAPTER 4 FUNDAMENTAL STUDY of MSMC 4.1 Introduction As we discussed in Chapter 3, all AW devices including MCs suffer the damping effect in a viscous medium, such as air or liquid. The damping effect reflects the influence of different factors on the sensor device. The vibration damping may be caused by internal friction (e.g. the beam materials), support loss (e.g. the cantilever holder), and the flow force from the surrounding media such as air and viscous liquids as shown in Figure 4-1. The internal friction and support loss, which are dominant damping factors in ordinary size machines, have been extensively studied by using structural damping theory, slip damping theory and wave propagation theory [1-4]. The internal damping is inherent from the cantilever devices. Therefore, the internal damping study is not covered in this research. Support loss Internal friction Oscillation Flow of surrounding media Figure 4-1. The damping mechanism of Q value of a cantilever. 69 The damping effect of a medium on an AW device depends on the medium (density and viscosity) and the AW device (structure, dimension, and vibration mode) [5-7]. The damping effect is experimentally observed by a shift in the resonance frequency to a lower frequency and a reduction in the Q value. That is, the influence of the damping effect on the resonance behavior has some similarity with the mass influence on the resonance behavior. The damping plays an important role in various cantilever?s applications. For examples, cantilevers have been widely explored in biosensors, and chemical sensors. The sensitivity and resolution of the cantilever devices strongly depend on its Q value which is related to the damping. Therefore, it is important to predict the Q value for the cantilever design. The apparent Q value of a cantilever can be expressed as [53] exti i QQQQQ 11111 supint ++== ? (4-1) where int Q and sup Q represent the dissipation effects due to the internal friction of the cantilever and the support loss, whereas ext Q include the external effects (e.g. viscous media) that act on the cantilever. 4.2 Theoretical model The Q value of a vibrating cantilever in a viscous fluid has been studied theoretically using several models. The simplest method is based on the harmonic oscillating sphere theory. In this theory, an MSMC in liquid behaves as the oscillation of a damped string of spheres [8-11]. To consider the effect of the surrounding viscous media on the MSMC beam, there are several assumptions and approximations implemented in this theoretical model: 70 (1) The cross section of the beam is uniform over its entire length; (2) The length of the beam L greatly exceeds its nominal width W (L>>W); (3) The beam is an isotropic linearly elastic solid and internal frictional effects are negligible; (4) The vibration amplitude of the beam is far smaller than any length scale in the beam geometry; (5) The drag force of the beam is the sum of drag force from the individual sphere. This model has been widely applied to many areas: the development of micro power generator; study of air viscous damping effects by a Farby-Perot micro-opto-mechanical device; absolute pressure measurement; mass sensing resonators; measurement of liquid?s viscosity and density; and design of atomic force microscopy probes [12]. R Figure 4-2. The schematic of a damped string of oscillating spheres. R is the effect radius of an oscillating sphere. When an oscillator is immersed into a liquid and driven by an external harmonic force ti fe ? , the motion of an initially flat, thin, homogeneous cantilever can be described by using the one - dimensional Euler-Bernoulli differential equation, which can be written as [8] 71 ti IC fe x y IE t y b t y MM ? = ? ? + ? ? + ? ? + 4 4 2 2 ')( (4-2) In this equation, the term ( 2 2 t y M I ? ? ) represents the inertial force in potential flow past the cantilever, and t y b ? ? is the dissipative force due to the viscous drag. Where y , x , and f represent beam deflection, longitudinal position, and force amplitude; b is the damping coefficient due to the viscous liquid and intrinsic structure of the cantilever. The intrinsic damping coefficient may come in part from the epoxy/glue between the active layer and inactive layer (e.g. PZT and stainless steel for piezoelectric MC) and other internal dissipation mechanisms. Here, we just consider the influence of viscous liquid on the cantilever and ignore the damping from the internal structure. Under the assumption of a beam structure withW >> h , the apparent Young?s modulus is given by 2 1 ' ?? = E E , where ? and E are Poisson?s ratio and Young?s modulus of the beam material, respectively. 3 2/ 2/ 2 0 12 1 WhdzdyzI h h W ?? ? == , is the moment of inertia for a rectangular beam. WhM C ?= and I M represent the effective mass of cantilever beam and the induced mass respectively, where ? is the specific mass density of the beam material. The induced mass I M can either exist due to absorbing molecules on the surface or it describes the mass of molecules of the surrounding media that are accelerated by the vibration of the beam. This leads to a dependency of the resonance frequency on the resonance behavior in general from the surrounding media. Solving Eq. (4-2) under the condition of resonance yields the eigenvalues for the damped angular resonance frequencies 72 2/1 2 4 )(4 1 )( ' ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? + ? + = ICIC n dn MM b MM IE? ? (4-3) ? ? ? ? ? ? ? ? ?? ? ? ? ? ? ? ? ? + ? C I n IC n dn M M MM IE 2 1 1 )( ' 2/1 4 ? ? ? (4-4) where n ? is the n th order undamped angular resonance frequency, given by )1(12 22 2 2 2 ?? ? ??? ? == E L h f n nn (3-10) For an oscillating sphere of an effective radius R in a liquid of density L ? and viscosity ? both I M and b have analytic expressions [8] ? ? ? ? ? ? += R R M I ? ? ? 2 9 1 3 2 3 (4-5) ? ? ? ? ? ? += ? ? ? ? ? ? += ? ?? ? ? ?? R R R R b 161 6 2 (4-6) Where dn dn L f??????? //2 == (? is the viscosity of the surrounding liquid media, and dn f is the resonance frequency in the medium) is the decay length in the liquid, which means the thickness of liquid molecules sticking on the cantilever. For the relative frequency shift of the first-order resonance frequency we derive, combining Eqs. (3-10), (4-4), and (4-5) 0 3 ) 2 9 1( 3 f RLWh R f LL ? ? ?? +?=? (4-7) Where 0 f is the first-order resonance frequency of the cantilever without damping, as given by )( 2 CI C n I nn MM M f M f m f S <> I M , we ignore the contribution of the induced mass to the Q value, Eq. (4-4) can be simplified to ndn ?? ? . Based on this, we can combine Eqs. (4-6) and (4-9), and finally obtain the Q value of a vibrating beam in the viscous region, approximated by an oscillating sphere with radius R )/1(6 )1(12/ 222 L n RRL EWh Q ??? ??? + ? = (4-10) This result indicates an increasing Q value with decreasing length or increasing resonance frequency. For relatively low viscosity or high frequency (? L /R<<1), the effect of the second term on the right-hand of Eq. (4-10) is negligible so that Eq. (4-11) is obtained, dn LLn f RRL EWh Q ?? ? ?? ?? ??? /1 6 )1(12/ 222 ?? ? ? (4-11) Q value is an important parameter in the resonance characteristics of a cantilever. A higher Q value indicates a smaller minimum detectable frequency change and therefore a better resolution (sensitivity) of the sensor system. 74 4.3 Materials and methods 4.3.1 Measurement set-up 4.3.1.1 In vacuum The resonant behavior of MSMCs in air at different pressures was investigated at room temperature. In this experiment, the pressure of the test chamber was obtained by a Varian SD-300 mechanical pump and monitored using a Varian multi-Gauge. As shown in Figure 4-3, a three-way control valve, which connected the mechanical pump, thermal couple sensor, and the test chamber containing the MSMC, was employed to maintain a given pressure. After the pressure reached the designated pressure and was maintained about 10 minutes, then the resonance behavior of the MSMC was measured. Mechanical pump Test chamber MSMC Pick-up coil Multi-gauge 3-way glass valve Thermocouple transducer Figure 4-3. The scheme of measurement set-up in vacuum. 4.3.1.2 In liquids As shown in Figure 4-4, the experimental setup consisted of a Helmholtz coil, lock-in amplifier, a computer-based output system, and a test chamber maintained at about 20 o C. A cleaned MSMC sensor was put into the test chamber containing the test liquid. The lock-in amplifier was connected to the pick-up coil interfaced to a data 75 acquisition PC for obtaining amplitude and phase angle measurements. H AC H DC Helmholtz coil Test chamber MSMC Pick-up coil Lock-in amplifier DC power supply PC Viscous liquid Figure 4-4. The schematic of measurement set-up in liquids. 4.3.2 Design of MSMC sensor dimensions Table 4-1. MSMCs were used to measure the resonance behavior in vacuum and in liquids. Sample Length mm Width mm Thickness ?m Theoretical frequency (0 th harmonic) Hz 1 4 1 35 1293 2 3 1 35 2298 3 2 1 35 5171 4 1 1 35 10342 5 3 0.3 35 2298 6 3 0.6 35 2298 7 2 1.5 35 5171 8 4 0.75 35 1293 To characterize the effect of MSMC geometry on the resonant behavior, MSMC having different length with same width, different width with same length and the same area (length x width) were designed in this research. The size dimensions and the theoretical resonant frequencies from Eq. (3-11) of these samples were listed in Table 4-1. 76 4.3.3 Selection of liquid reagents 4.3.3.1 Glycerol/water mixture system The glycerol/water mixture system was frequently employed to determine the density or viscosity of liquids by using cantilevers [14-16]. The reason why we choose glycerol/water mixture is that glycerol and water can dissolve each other completely to obtain uniform solution. Table 4-2. The viscosity and density of glycerol/water mixture system was measured by Viscometer and Tensiometer at 20 o C. Sample Ratio of water : glycerol vol% Density x Viscosity (cp ? g/cm 3 ) Density (g/cm 3 ) ( at 20 o C) Viscosity (cP) ( at 20 o C) 1 100:0 1.011 0.9982 1.012 2 95:5 1.225 1.014 1.208 3 90:10 1.718 1.030 1.669 4 85:15 2.029 1.046 1.940 5 80:20 2.690 1.067 2.520 6 75:25 2.963 1.074 2.760 7 70:30 3.890 1.094 3.556 8 60:40 5.513 1.113 4.950 9 50:50 10.90 1.147 9.502 The test samples were deionized water and various concentration of glycerol solutions prepared in deionized water as shown in Table 4-2. The percentages of glycerol in water/glycerol mixture system used here are 5 vol%, 10 vol%, 15 vol%, 20 vol%, 25 vol%, 30 vol%, 40 vol%, and 50 vol% respectively. The viscosities and densities of various glycerol concentration solutions were also listed in Table 4-2. The density of each test sample was measured by using Sigma 702 Tensiometer, while the product of viscosity and density was measured by using Viscoliner 1710 Series Viscometer. Thus, we can obtain the viscosity for each test sample solution. Figure 4-5 gives the densities of various glycerol/water solutions from the measurement and calculation which based on 77 the assumption of no volume change before and after mixture of water and glycerol. In Figure 4-5, there is very small deviation of the experiment data from the calculation data, which means not obvious volume change before and after mixing. We can simply use the densities from the calculation (assuming no volume change). 02040608010 1.00 1.05 1.10 1.15 1.20 1.25 Density (g/cm 3 ) Glycerol vol% Calculation Experiment (Sigma 702) Figure 4-5. The density vs. the percentage of glycerol in glycerol/water mixture system. The black squares represent the value from the calculation which based on no volume change after mixture. The red dots represent the experiment data which measured by Tensiometer. 4.3.3.2 Several organic solvents To determine the influence of the surrounding liquid media on the resonance behavior of an MSMC, the device was characterized in six different solvents including water, ethanol, methanol, 2-propanol, hexane and ethylene glycol. The densities and viscosities of these liquid media at room temperature (20 o C) were listed in Table 4-3. In all these experiments, the MSMCs were completely immersed in liquid. 78 Table 4-3. Density and viscosity of liquids at 20 o C from the literature [17]. Density (g/cm 3 ) ( at 20 o C) Viscosity (cP) ( at 20 o C) Water 1.000 1.0 Ethanol 0.7893 1.22 Methanol 0.7914 0.59 2-propanol 0.7855 2.27 Hexane 0.6548 0.31 Ethylene glycol 1.1088 21.0 4.4 Results and discussions 4.4.1 Resonance behavior in vacuum The damping in air is profound due to the complicated dynamics between the coupling of structure and airflow; it is still a challenge to establish the analytical model to predict the Q value of MSMC. Some simplified analytical approaches have been reported to estimate Q value instead. For example, Newell [18] has applied Stoke?s law to yield the Q value for the first harmonic peak, as given in 2 2 24 1 L EWh Q Newell ? ? = (4-12) Furthermore, Hosaka and Itao have also employed the string of oscillating spheres model and the equation is presented as follows [19] 2 2 22.0 L EWh Q Hosakal ? ? ? (4-13) which is the similar as Newell Q . Therefore, for cantilever in air, Q value changes with the geometry of the cantilever, harmonic mode and the viscosity is given by 2 22 L Wh Q n ? ? ? (4-14) While it is the same as the behavior of cantilever in the viscous liquid media, as shown in Eq. (4-11). Eq. (4-14) shows that the Q value is linearly dependent on the reciprocal of 79 the viscosity. It is also indicated that the Q value is strongly dependent on the geometry of the cantilever. That is, the Q value increases with decreasing length, while it increases with increasing thickness and width. Therefore, if an MSMC with smaller length is used, the Q value would be higher than what is reported here. For a damped cantilever, the oscillation reaches a maximum at a frequency, apparent resonance frequency (f r ), lower than the real resonance frequency (f n ) as [20] () nnr fQff