1 August 2011 Microfluidic sensing: state of the art fabrication and detection techniques
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Here we introduce the existing fabrication techniques, detection methods, and related techniques for microfluidic sensing, with an emphasis on the detection techniques. A general survey and comparison of the fabrication techniques were given, including prototyping (hot embossing, inject molding, and soft lithography) and direct fabrication (laser micromachining, photolithography, lithography, and x-ray lithography) techniques. This is followed by an in-depth look at detection techniques: optical, electrochemical, mass spectrometry, as well as nuclear magnetic resonance spectroscopy-based sensing approaches and related techniques. In the end, we highlight several of the most important issues for future work on microfluidic sensing. This article aims at providing a tutorial review with both introductory materials and inspiring information on microfluidic fabrication and sensing for nonspecialists.



With microfluidic/nanofluidic technology it is possible to operate on microscale or nanoscale liquids for controling or sensing purposes. With the microfabrication techniques initially rooted from the microelectromechanical systems (MEMS) technology, this field will gradually develop into a discipline itself.1, 2, 3 The fundamental techniques for microfluidic or optofluidic device fabrication originate from the semiconductor industry and are based on silicon or glass materials. With the development of polymer-based fabrication techniques, polymer-based microfluidic devices become more prevalent with the advantages of being economic and easy to fabricate, and having material versatility and good system compatibility.

The early designs of the microfluidic controling systems were mostly monolithic miniaturized components such as microvalves, micropumps, and micromixers.4, 5, 6 With further development, whole microfluidic systems were realized, which were made up of multiple elements to achieve certain functions. These parts comprise either of the monolithic microfluidic components7 or of the microfluidic components with the external components/devices.8 Designs of those microfluidic devices, such as geometries and scales, have been modified and improved according to the applications for better performance. 9, 10, 11, 12, 13, 14, 15, 16 Further development requires more components to be coupled with the microfluidic system for increased system functionality. Optical components seem ideal, with the benefits of noncontact, fast response, compactness, high sensitivity, multiplex operation possibility, and so on. Self-contained microfluidic devices have generated impact in the point-of-care and global health.17, 18 However, in order to achieve real self-contained miniature devices, it is ultimately required to have highly integrated systems. This means lowering or even eradicating the dependence on macro, bulky, external devices to perform control, detection, or analysis functions, by the development and integration of the necessary functional microcomponents. Examples recently demonstrated are the implementation of lensless microscopes of sub-pixel resolving ability on microfluidic platforms for on-chip imaging or diagnosis.12, 13, 19

The term optofluidics was coined in 2003 at the California Institute of Technology in Pasadena to describe systems that combine optics and microfluidics/nanofluidics (or to say, optical microfluidics).20, 21 The interaction between light and fluid provides possibilities of both versatile microsystems and a wide spectrum of applications.9, 22, 23, 24, 25, 26 In the past decade, there has been a growing interest and development of optical microfluidics (optofluidics) and an explosion of publications in the field. Actually, we can classify all microfluidic devices to either controlers or sensors. Here, we would like to emphasis on the microfluidic sensors. After the review of fabrication techniques in Sec. 2, we will have a brief introduction of the existing microfluidic detection methods and techniques in Secs. 3, 4. This is followed by a review of optofluidic sensing techniques in Sec. 5.


Fabrication Methods

In the early days, the fabrication of microfluidic devices mainly relied on techniques transferred from the conventional two-dimensional integrated circuit (IC) and silicon-based two- or three-dimensional MEMS processes. This includes photolithography, thin film metallization, and chemical etching. Later, glass based, glass-silicon, glass-polymer mixed microfluidic fabrication techniques, and devices started to garner more interest. 6, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39 The glass materials were preferred partly for the biocompatibility toward the biomedical related applications40, 41, 42, 43, 44 and the ideal surface characteristics where high temperature or strong solvents should appear 45, 46, 47, 48, 49, 50, 51, 52, 53 (e.g., on-chip capillary electrophoresis-based operations). However, lack of optical transparency at interested wavelengths (for silicon), micromachining difficulties, and comparably high expenses for both silicon and glass materials have hampered their wider applications in microfluidics. Tremendous effort has been made to find alternative materials that are more cost-effective and easier for micromachining. With the development of related fabrication techniques in recent years, the polymer/plastic-based microfluidic systems has garnered more interest than its conventional competitors.54 In spite of comparatively weak bonding and structure deformation during device packaging processes, polymer materials still seem attractive due to the facts that: they are more economic compared with silicon and glasses, easier to be fabricated in/on, avoidance of high-temperature annealing and stringent cleaning, more system integration friendly (e.g., interconnections), and there exists a wider range of materials to be chosen for characteristics that are required for each specific application, such as good optical transparency, biocompatibility, and chemical or mechanical properties. Another important reason for the interest from both academia and industry on polymer microfluidic devices is the possibility of disposable microfluidic chips toward biomedical and clinical applications. These devices usually require low cost of fabrication, high volume production, good reproducibility, and versatility in design for a wide spectrum of specific applications.

Current methods for fabrication of microfluidic devices include prototyping techniques (includes hot embossing,55, 56 injection molding,57, 58 and soft lithography59) and direct fabrication techniques such as laser photoablation or laser micromachining,60 photolithography/optical lithography61 and x-ray lithography62 (Figs. 1, 2). Table 1 presents the advantages and disadvantages of those techniques. Note that “photolithography” in this table refers to conventional photolithography that is mostly employed in IC industry for micrometer scale patterning. In fact, during the past decade photolithography techniques have progressed to achieve smaller feature patterning ability and have been coupled to various plastic/polymer-based techniques to better suit lab-on-a-chip applications. To date, most of the current soft lithography processes still rely on modern photolithography techniques for master template/mask fabrication. Consequently, the low resolution ability of soft lithography can be gradually improved with the high quality masks by modern photolithography. Sub-100-nm fabrication resolution can also be achieved by composite layers of stamps.63 Other techniques were also used to obtain the soft lithography masters with nanometer scale features below 5 nm: such as to replicate those features from single-walled carbon nanotubes64 or from crystal fractures65 as soft lithography masters. For photolithography made masters for the soft lithography process, the recently reported resolution limit has been pushed to around 20 nm by Li 66

Fig. 1

Illustrations of the typical fabrication procedures by the prototyping techniques (hot embossing, inject molding, and soft lithography).


Fig. 2

Illustrations of the typical fabrication procedures by the direct fabrication techniques: (a) laser micromachining, (b) photolithography/optical lithography, and (c) x-ray lithography. The “metal mask insertion” step in x-ray lithography is usually realized by electroplating.


Fig. 7

Density of active catalyst and flow map imaging by the hyperpolarization enhanced NMR spectroscopy reported by Pines’ group. MRI images [field of view (FOV) (x to z): 2.3 mm by 7.0 mm; pixel size: 20 μm by 60 μm] of a tightly packed catalyst bed (catalyst layer thickness is ∼5 mm) are shown. The picture shows the flow map in the xz plane with the use of polarized propane. The orientation of the arrows represents direction of the velocity, and their length represents its magnitude. The SNR of thermally polarized propylene was insufficient to generate a velocity map. The resolution of the flow map is intentionally decreased by retaining only one of every 16 arrows to avoid excessive overlap of the arrows (Ref. 116).


Table 1

Microfluidic fabrication techniques.

Hot embossingCost-effective, precise, and rapid replication of microstructures, mass productionRestricted to thermoplastics, difficult to fabricate complex 3D structures56
Injection moldingEasy to fabricate complex geometry, fine features, and 3D geometries, low cycle time, mass production, highly automatedRestricted to thermoplastics, high cost mold, difficult to form large undercut geometries58
Soft lithographyCost-effective, able to fabricate 3D geometries, high resolution (down to a few nm)Pattern deformation, vulnerable to defect59, 63, 64, 65, 66
Laser photoablationRapid, large format productionMultiple treatment sessions, limited materials60
Conventional photolithography/optical lithographyHigh wafer throughputs, ideal for microscale featuresUsually requires a flat surface to start with, chemical post-treatment needed61
X-ray lithographyHigh resolution to fabricate nano-patterns, absorption without spurious scattering, able to produce straight smooth wallsDifficulties in master fabrication process, time consuming, high cost62


Detection Methods

Integrated microfluidic devices involve the large-scale integration of various microfluidic components, such as microvalves, microchannels, micropumps, microfluidic mixers, and other elements to handle and control fluids at the microscale.67 They are frequently used for biological, chemical, and biomedical analysis. There has already been a considerable amount of insightful review articles on related topics.67, 68, 69, 70, 71, 72 Various detection methods exist in the field of chemical, biological diagnosis, or analysis on microfluidic platforms.

The detection methods in microfluidics can be classified into three major types: optical methods, 9, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89 electrochemical methods, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102 and mass spectrometry methods. 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113 Among these methods, optical and electrochemical methods are the most frequently utilized due to their selectivity and sensitivity. Other than the above major methods, approaches such as nuclear magnetic resonance (NMR) spectroscopy,114, 115, 116, 117, 118 magneto-resistive,119 and acoustical120, 121 are also coupled to microfluidics for sensing application.

As demonstrated in Fig. 3, typical optical detection methods comprise the direct detection by monitoring the light properties including fluorescence,74, 81, 82, 83 absorbance,84, 85, 86 and luminescence-based87, 88, 89 methods, and the light property modulation detections such as surface plasmon resonance (SPR) detection.76, 80, 122 These methods usually involve techniques such as evanescent waves,10 SPR,76, 80, 122, 123 interferometry,75, 124, 125, 126, 127, 128 Raman spectrometry,77, 129, 130, 131 fiber optics,78 and optical waveguides.79, 132 Photonic crystals, optical cavity structures, and several optical techniques have also been reported to be integrated with the microfluidic system for sensing purposes, using one- and two-dimensional surface PCs (guided mode resonance filters),133, 134, 135, 136, or three-dimensional photonic crystals,137, 138 optical cavities,139, 140 whispering gallery mode resonators, 141, 142, 143, 144, 145, 146, 147 and optical tweezers for cell related monitoring or fluidic rheological measurements148, 149, 150 (Fig. 4).

Fig. 3

Typical optical methods. (a) Fluorescence (in this case, fluorescent resonance energy transfer/FRET), (b) absorbance, (c) luminescence, and (d) surface plasmon resonance-based optical detection methods. GFP: green fluorescent protein; YFP: yellow fluorescent protein; GS: glass substrate.


Fig. 4

(a) Result of a three-dimensional photonic crystal optofluidic sensor for refractive index detection. The fluid refractive index in the microchannel above the photonic crystal was detected by the bandgap position shift. Transmittance spectrum of the whole system that reveals a bandgap around 4.3 μm (left inset). An illustration of the sensor (right inset and see Ref. 138). (b) Demonstration of the shear stress mapping inside a microfluidic device by optical tweezers (top sketch). Theoretical calculated results by the pure fluidic model and the experimental measured results of the fluid velocity and shear stress along y direction in the microfluidic device (bottom and see Ref. 150).


Electrochemical measurements are based on electrical property modulations of the analyte species that undergo redox reactions, and are usually employed for the detection of the electroactive species. They can be assigned to three categories: amperometries,90, 91, 92, 93, 94 potentiometries95, 96, 97 and conductometry98, 99, 100, 101, 102 measurements. The principles of these methods are demonstrated in Fig. 5. Amperometric detection is based on the fact that an applied voltammetric potential between a reference and a working electrode would cause the oxidation or reduction of the electroactive species in the vicinity, and an electrical current will be induced. Sensitive detection of the analyte(s) can be realized by the cyclic voltammogram(s) and current versus time curves of the electrode. In potentiometric detection, analyte detection is realized by monitoring the potential of an ion-selective electrode (usually a membrane) against a reference electrode. When selective ions pass through the membrane and a local equilibrium is established at the sensing interface, the resulting charge separation causes a potential between the working electrode and the reference electrode in relation to the species type and concentration. The principle of conductometric detection is that the conductivity of a zone is affected by the charged species in the zone. Different types of species would have their specific conductivity responses, which would also vary with different concentrations. It is the most commonly employed method in electrochemical measurements since it, in principle, can deal with all charged species of interest. The detection involves measuring the conductivity at a series of frequencies, both in conventional contacted conductivity detection101 and capacitively coupled contactless conductivity detection (C4D) methods such as potential gradient detection.102 Electrochemical detections are often used together with (capillary) electrophoresis operations (such as capillary electrophoresis separation) or in electrophoresis systems. Considering this, in this review the “electrochemical methods” actually include electrophoresis related work.92, 99, 101, 102

Fig. 5

Three types of electrochemical detection methods for microfluidics: (a) amperometric, (b) potentiometric, and (c) conductometic (capacitively coupled conductivity detector) detection.


Mass spectrometry103 (MS) is able to perform highly selective detection by monitoring the trajectory of ions in electric and/or magnetic fields, which elucidate the mass and charge of the ions. Its most important application is in proteomic studies for protein separation and further identification from the fragmentation pattern of proteins. Identification after separation can be carried out in two ways. One is direct detection by combing through the database using the individual types of obtained protein(s). The more sophisticated way is carrying out tandem MS (Ref. 151) to get protein fragments/ions for sequence tagging. To date, several MS configurations have already been developed to be integrated with microfluidic devices for this application, for instance, electrospray ionization (ESI)-MS (Refs. 104, 105, 106) and matrix-assisted laser desorption ionization (MALDI)-MS.107, 108, 109 In 2006, another paradigm is ion trap mass spectrometry integrated with microfluidics for protein identification by Hardouin 111 Other systems were also reported, such as a chip-liquid chromatography (LC)-MS system for label-free profiling of human serum113 and a LC-ESI-MS system for multiple proteins detection from breast cancer cellular extract.112 The resolving ability of MS has recently been pushed down to the detection of a single molecular by Roukes's group in Caltech using a nanoelectromechanical system-based MS (NEMS-MS) (Fig. 6).110 It can be expected that in the future when NEMS-MS meets microfluidics, a much more effective microfluidic-MS platform could be realized to analyze biological or chemical species (e.g., proteins or nanoparticles) at a single molecular level with the ability to operate in multiplexing and parallel modes.

Fig. 6

First generation NEMS-MS system developed by Roukes's group (a), the NEMS mass spectrometry for a gold nanoparticles dispersion (b), and the real-time records of single-molecule adsorption events from their experiments (Ref. 110).


Besides protein separation and identification, MS has also been applied to the quantitative detection in protein expression in various states (especially in disease states). However, the miniaturization and high sensitivity requirements have currently been one of the most significant technological hurdles. Yet, microfluidics seems to hold great promises for the related technological breakthrough: The micrometer scale geometries and smaller platform of microfluidic devices meet the enhanced sensitivity and system miniaturization need; the multi-channel geometries in microfluidics enable high throughput processing and multiplexing ability. Considering these, to couple with microfluidics could be the ultimate lab-on-a-chip solution for MS toward quantitative proteome applications. To our knowledge, there has not been any further report on MS-based microfluidic sensing and yet a lot of interesting research remains to be carried out.

Other than the three major categories, other methods such as the NMR spectroscopy115 have also been explored to be applied to microfluidic detection.43 It is a well-developed detection method in chemistry and life sciences, which employs the magnetic properties of nucleis or the chemical shift Zeeman effect and/or the Knight shift effect for detection purpose. NMR spectroscopy is able to detect biological and chemical analyte species such as proteins and nucleic acids. However, its application in microscale systems has been restricted by the low sensitivity of conventional NMR detection technique. Recently, this problem has been solved by hyperpolarization methods (e.g., to introduce the highly polarized para-hydrogen agent for signal enhancement). High resolution NMR for microfluidic systems was realized in 2007 by Pine's group in UC Berkley on the study of multi-phase flows and catalyst deactivation (Fig. 7).116 Besides direct detection, the Pines’ group also pioneered the remote monitor work of NMR-based microfluidic detections. In 2007, they reported the remote monitoring of spin coherence transfer in chemical transformations117 and a double-phase encoded remote detector of the fluid diffusion through membranes.118 This technique is readily applicable mostly in hydrogenation reaction-related detection and imaging, and might be extended for more applications in microfluidics. However, the limited reaction time scale/polarization lifetimes remains a key technological bottle-neck for NMR-based microfluidic analytical detection. Besides, similar to MS spectroscopy, another key hurdle is system miniaturization, in other words, to reduce the comparably large detector for better interface into microfluidics. In fact, not many related publications were reported afterward on NMR-based microfluidic detection. In spite of the technological challenges, NMR is still a competitive technique for microfluidic applications compared to optical or electrochemical methods: It does not have the optical accessibility issue for the region of interest (ROI) and the data acquisition time is much shorter, which makes time-resolved studies much easier; it has better detection pervasiveness than electrochemical methods that are limited to electroactive species. Hence, the solution to the weak NMR signal issue in microsystems, either by further signal enhancement or better detection instrumentations, will trigger a wider spectrum of lab-on-a-chip applications of NMR.


Sensing Techniques

In Sec. 3 we discussed general detection methods in microfluidics. Here, we would like to emphasize the microfluidics/optofluidics sensing techniques. A general review is presented in Table 2. From Table 2 we can see that the different methods have corresponding advantages and limitations. Some of them can be coupled with each other either to achieve certain phenomena for detection or to enhance sensor ability. For instance, evanescent waves are utilized with interferometers, optical fibers, fluorescence induction, and optical waveguides, in order to further enhance the detection sensitivity (e.g., in the form of a fiber-optic evanescent-wave approach152 or a fiber-optic localized plasmon resonance sensor153). They are also widely used to induce surface plasmon resonance, which is essential in surface-enhanced Raman scattering.154 Cavities structures are used in localized plasmon resonance detections to improve sensing performance.155 Other detection methods were also actively studied for microfluidics, such as integrated optics components that can accommodate large arrays of compact optical channels and devices. One example is the laser induced fluorescence (LIF) detection, which is extensively used in microchip separations.156

Table 2

Optofluidic sensing techniques.

FluorescenceTemperature, cell function, flow velocity, polymer dynamicsHigh selectivity, sensitivityHigh cost, extensive calibration and mathematical corrections, lack of appropriate fluorophoresDown to single DNA level74, 81, 82, 83, 157, 158
Mach-Zehnder interferometersRefractive index, fluorescein concentrationHigh resolution, label freeCompromise between interaction lengths and sensitivity, multiplexing difficultiesDown to a few nano-molar concentration75, 124, 125, 126, 159
Dual polarization interferometryRefractive index, conformational change, layer thickness, average densityLabel free, simultaneous multiple parameters detectionHigh cost, alignment difficulties, unsuitable for detection of large numbers of mutationsDown to sub-pico-molar concentration127, 128, 160
Surface enhanced plasmon resonanceRefractive index, molecular and chemical reactions, polymer dynamicsSuperior sensitivity and selectivity, label freeLow throughput, system alignment difficulties, small penetration depth, large sensing area required, small molecular weight analytes sensing difficulties, specific and nonspecific interactions differentiate difficulties, surface sensitiveDown to nano-molar level, single molecules (e.g., DNA, RNA, proteins)76, 80, 122, 123
Localized (surface) plasmon resonanceRefractive index, binding eventsLabel free, highly localized, real-time monitoring, simple and cost-efficient detection equipmentsInstability of the metal nanostructures’ morphology and optical propertiesDown to pico-molar concentration, single DNA level153, 154, 155, 161
Surface enhanced Raman spectroscopyMolecular detection, investigation of the structure and function of large bimolecules, analysis of chemical processesSuperior sensitivity and selectivity, label freeSmall penetration depth, surface quality dependence, denaturation problem for biomoleculars, overlapping peaksDown to single molecule level, sub-pico molar concentration77, 129, 130, 131, 154, 162
Fiber opticsRotation, acceleration, electric and magnetic field measurement, temperature, pressure, acoustics, vibration, linear and angular position, strain, humidity, viscositySuperior sensitivity, simultaneous multiple parameters detection, easy for integration, refractive index, chemical measurements, label free, environmental ruggedness, multiplexing ability, dynamic range and resolutionHigh cost, end-user unfamiliarityDown to tens of nanometers, pico-molar concentration78, 153, 163, 164
Planar waveguidesRefractive index detection, study and detection of particlesHigh sensitivity, label free, compact configurationSmall penetration depth, limited for processes with diffusing particlesSingle viruses and liposomes resolution79, 132
photonic crystalsParticle interactions (e.g., protein-protein, antibody–antigen and small molecule–protein interactions), cell-based assays, refractive index, concentration, absorption and conformation of biomolecules on a surfacePotentially high sensitivity, localized confinement, flexibility in sensor structures and related propertiesFabrication difficulties for higher order photonic crystals, related high cost, difficulties in high-throughput screeningDown to single molecule level (e.g., protein), nano-molar concentration133, 134, 135, 136, 137, 138
Micro-ring and microsphere resonators, including those using whisper gallery modes (WGM)Detection of virus, protein, DNA, or bacteria, detection of concentration, refractive index, binding events of moleculesMultiplexing feasibility for micro-ring resonators, high Q (microsphere resonators: Q >109 micro-ring using WGMs: Q >108)Mass produce difficulties, multiplexing difficulties for microsphere resonators, lack robustnessDown to single molecule level146, 147, 165



The past decade has witnessed the progresses in microfluidics: more microfluidic system prototypes, increased device complexity, and more fabrication and sensing techniques have been developed or improved. However, microfluidics sensors are still in a formative stage and hold tremendous opportunities to be applied to a wider spectrum of fields and applications. We could expect the next drive engine to microfluidics sensors development would be based on:

  1. Complete integration for compactness and self-contained microsystems

    While most of the current microfluidic systems are still based on microfluidic devices that are coupled with external macroscopic detectors or preliminary external detection platforms, it is of great significance to push the microfluidic systems down to a complete microscale level. The development of specific detection components for microfluidics and complete integration techniques would enable real compact and self-contained microfluidic systems.

  2. New and existing sensing principles and related technological advances

    It is essential to explore for new sensing principles, or possible sensing components to be integrated with microfluidics while improving the sophistication of the microfluidic sensing systems. Ideal candidates should be both localized and sensitive (with minimized negative system perturbance), easy to fabricate and integrate, easy to assemble or even without post-fabrication assembly. More materials could also be considered, for instance, functionalized nanoscale particles, such as specialty nanocomposites (e.g., nanomaterials, nanocrystals, nanoparticles, nanocolloids, liquid crystals, quantum dots) and bio-/chemical-functionalized nanoscale materials or particles, could be incorporated with a microfluidic environment for flexible reconfiguration and system tuning for various sensing purposes.

    Continuous research investments on optical, electrical, chemical, as well as mechanical, thermal, magnetic, or biological phenomena would open up new possibilities as well. In addition, technological advances in related fields such as electrical/optical/chemical instrumentation, microfabrication techniques, new material development, and processing techniques, would all contribute to the development of microfluidic sensors. Once the major barriers of existing sensing methods are cleared, such as the short life time and low resolution issue in NMR microfluidic sensors, the progress would be rapidly sped up.

  3. Theoretical work and software development

    The study of integrated microfluidic sensors should be extended to more sophisticated simulation methods and elaborate algorithmic models for a deeper understanding at a theoretical level. For instance, a more complex model should be developed for the theoretical understanding of the shear stress acting on the particle in microflows, which includes the effect of the particle size and other parameters such as concentration and temperature. As in a real microfluidic suspension environment, considerable deviations have been observed in the experimental measurement results from the simulation with a pure fluidic system.150 Modeling of the fluidic dynamic characteristics, such as velocity, heat transfer, and shear stress inside microfluidic devices will also be beneficial.

    Microfluidic work from the very beginning has been mainly among physical or more specifically fluid mechanical and lab-on-a-chip communities. However, the most important end-users are usually biological or chemical specialists, to whom the theoretical understanding, numerical simulation skills, and lab-on-a-chip know-how could be a huge hurdle. The accessibility of more user friendly simulation software to nonspecialists could alleviate this problem and allow biologists and chemists to actually get actively involved in the early stage development of the sensors to better suit the actual demands.

    Besides, the simulation software provides a more economical and quicker research and development loop by the pre-fabrication numerical tests for various designs or fabrication procedure optimization. In this way, the cost and time frame will be sharply reduced with refined theoretical simulations and modeling work carried out beforehand.

  4. Standard integration interfaces

    Another important issue is that most of the current microfluidic sensing platforms are “one-design-one-application” types. It is not easy to modify or upgrade the systems or switch for multi-function operations. Usually the change of applications or the instruction of an additional task would simply mean redesigning a system. Thus, a standard microfluidic interface, that is friendly and flexible for various functional components to be easily integrated to, holds great promises for enhancing the adaptivity of microfluidic sensing systems. This will open up the possibility of dynamic microfluidic systems that support versatile modes of interfacing and operations.


1.  A. Berg, H. G. Craighead, and P.-D. Yang, “From microfluidic applications to nanofluidic phenomena,” Chem. Soc. Rev. 39, 899–900 (2010). 10.1039/C001349H Google Scholar

2.  W.-C. Tian and E. Finehout, Chapter 11 in Current and Future Trends in Microfluidics within Biotechnology Research, A. P. Lee and G. Lin, Eds., Springer, New York (2008). Google Scholar

3.  G. M. Whitesides, “The origins and the future of microfluidics,” Nature 442, 368–373 (2006). 10.1038/nature05058 Google Scholar

4.  A. D. Stroock, S. K. W. Dertinger, A. Ajdari, I. Mezic, H. A. Stone, and G. M. Whitesides, “Chaotic mixer for microchannels,” Science 295, 647–651 (2002). 10.1126/science.1066238 Google Scholar

5.  B. Husband, M. Bu, A. G. R. Evans, and T. Melvin, “Investigation for the operation of an integrated peristaltic micropump,” J. Micromech. Microeng. 14, S64–S69 (2004). 10.1088/0960-1317/14/9/011 Google Scholar

6.  M. A. Unger, H. P. Chou, T. Thorsen, A. Scherer, and S. R. Quake, “Monolithic microfabricated valves and pumps by multilayer soft lithography,” Science 288, 113–116 (2000). 10.1126/science.288.5463.113 Google Scholar

7.  T. Thorsen, S. J. Maerkl, and S. R. Quake, “Microfluidic large-scale integration,” Science 298, 580–584 (2002). 10.1126/science.1076996 Google Scholar

8.  S. Balslev, B. Bilenberg, O. Geschke, A. M. Jorgensen, A. Kristensen, J. P. Kutter, K. B. Mogensen, and D. Snakenborg, “Fully integrated optical system for lab-on-a-chip applications,” in Proc. IEEE Int. Conf. on Micro Electro Mechanical Systems, MEMS, 25–29 Jan. 2004, pp. 89–92, Maastrict, the Netherlands (2004). Google Scholar

9.  A. M. Armani, R. P. Kulkarni, S. E. Fraser, R. C. Flagan, and K. J. Vahala, “Label-free, single-molecule detection with optical microcavities,” Science 317, 783–787 (2007). 10.1126/science.1145002 Google Scholar

10.  D. J. Sirbuly, A. Tao, M. Law, R. Fan, and P.-D. Yang, “Multifunctional nanowire evanescent wave optical sensors,” Adv. Mater. 19, 61–66 (2007). 10.1002/adma.200601995 Google Scholar

11.  M. Krishnan, N. Mojarad, P. Kukura, and V. Sandoghdar, “Geometry-induced electrostatic trapping of nanometric objects in a fluid,” Nature 467, 692–695 (2010). 10.1038/nature09404 Google Scholar

12.  X.-Q. Cui, L. M. Lee, X. Heng, W.-W. Zhong, P. W. Sternberg, D. Psaltis, and C.-H. Yang, “Lensless high-resolution on-chip optofluidic microscopes for Caenorhabditis elegans and cell imaging,” Proc. Natl. Acad. Sci. U.S.A. 105, 10670–10675 (2008). 10.1073/pnas.0804612105 Google Scholar

13.  G. Zheng, S. A. Lee, S. Yang, and C.-H. Yang, “Sub-pixel resolving optofluidic microscope for on-chip cell imaging,” Lab Chip 10, 3125–3129 (2010). 10.1039/c0lc00213e Google Scholar

14.  S. Mandal and D. Erickson, “Nanoscale optofluidic sensor arrays,” Opt. Express 16, 1623–1631 (2008). 10.1364/OE.16.001623 Google Scholar

15.  S.-M. Park, Y. S. Huh, K. Szeto, D. J. Joe, J. Kameoka, G. W. Coates, J. B. Edel, D. Erickson, and H. G. Craighead, “Rapid prototyping of nanofluidic systems using size-reduced electrospun nanofibers for biomolecular analysis,” Small 6, 2420–2426 (2011). 10.1002/smll.201000884 Google Scholar

16.  J.-L. Li, D. Day, and M. Gu, “Design of a compact microfludic device for controllable cell distribution,” Lab Chip 10, 3054–3057 (2010). 10.1039/c0lc00090f Google Scholar

17.  P. Yager, T. Edwards, E. Fu, K. Helton, K. Nelson, M. R. Tam, and B. H. Weigl, “Microfluidic diagnostic technologies for global public health,” Nature 442, 412–418 (2006). 10.1038/nature05064 Google Scholar

18.  S. J. Moon, H. O. Keles, A. Ozcan, A. Khademhosseini, E. Haeggstrom, D. Kuritzkes, and U. Demirci, “Integrating microfluidics and lensless imaging for point-of-care testing,” Biosens. Bioelectron. 24, 3208–3214 (2009). 10.1016/j.bios.2009.03.037 Google Scholar

19.  S. Seo, T.-W. Su, D. K. Tseng, A. Erlinger, and A. Ozcan, “Lensfree holographic imaging for on-chip cytometry and diagnostics,” Lab Chip 9, 777–787 (2009). 10.1039/b813943a Google Scholar

20.  V. R. Horowitz, D. D. Awschalom, and S. Pennathur, “Optofluidics: field or technique?” Lab Chip 8, 1856–1863 (2008). 10.1039/B816416A Google Scholar

21.  Y. Fainman, L. Lee, D. Psaltis, and C.-H. Yang, Optofluidics: Fundamentals, Devices, and Applications, McGraw-Hill, New York (2009). Google Scholar

22.  A. Groisman, M. Enzelberger, and S. R. Quake, “Microfluidic memory and control devices,” Science 300, 955–958 (2003). 10.1126/science.1083694 Google Scholar

23.  J. W. Hong, V. Studer, G. Hang, W. F. Anderson, and S. R. Quake, “A nanoliter scale nucleic acid processor with parallel architecture,” Nat. Biotech. 22, 435–439 (2004). 10.1038/nbt951 Google Scholar

24.  B. Tian, T. Cohen-Karni, Q. Qing, X.-J. Duan, P. Xie, and C. M. Lieber, “Three-dimensional, flexible nanoscale field-effect transistors as localized bioprobes,” Science 319, 830–834 (2010). 10.1126/science.1192033 Google Scholar

25.  X. Tao, A. Lee, W. Limapichat, D. A. Dougherty, and R. MacKinnon, “A gating charge transfer center in voltage sensors,” Science 328, 67–73 (2010). 10.1126/science.1185954 Google Scholar

26.  M. Yang, C.-W. Li, and J. Yang, “Cell docking and on-chip monitoring of cellular reactions with a controlled concentration gradient on a microfluidic device,” Anal. Chem. 74, 3991–4001 (2002). 10.1021/ac025536c Google Scholar

27.  S. C. Terry, J. H. Jerman, and J. B. Angell, “A gas chromatographic air analyzer fabricated on a silicon wafer,” IEEE Trans. Electron Devices 26, 1880–1886 (1979). 10.1109/T-ED.1979.19791 Google Scholar

28.  S. J. Harrison, K. Fluri, K. Seiler, Z.-H. Fan, C. S. Effenhauser, and A. Manz, “Micromachining a miniaturized capillary electrophoresis-based chemical analysis system on a chip,” Science 261, 895–897 (1993). 10.1126/science.261.5123.895 Google Scholar

29.  N. F. Raley, J. C. Davidson, and J. W. Balch, “Examination of glass-silicon and glass-glass bonding techniques for microfluidic systems,” Proc. SPIE 2639, 41–45 (1995). 10.1117/12.221298 Google Scholar

30.  M. U. Kopp, A. J. D. Mello, and A. Manz, “Chemical amplification: continuous-flow PCR on a chip,” Science 280, 1046–1048 (1998). 10.1126/science.280.5366.1046 Google Scholar

31.  M. Stjernstrom and J. Roeraade, “Method for fabrication of microfluidic systems in glass,” J. Micromech. Microeng. 8, 33–38 (1998). 10.1088/0960-1317/8/1/006 Google Scholar

32.  N. Bings, C. Wang, C. Skinner, K. Colyer, D. Harrison, J. Li, and P. Thibault, “Microfluidic devices connected to glass capillaries with minimal dead volume,” Anal. Chem. 71, 3292–3296 (1999). 10.1021/ac981419z Google Scholar

33.  J. M. Ruano, V. Benoit, J. S. Aitchison, and J. M. Cooper, “Flame hydrolysis deposition of glass on silicon for the integration of optical and microfluidic devices,” Anal. Chem. 72, 1093–1097 (2000). 10.1021/ac9906983 Google Scholar

34.  W. H. Grover, A. M. Skelley, C. N. Liu, E. T. Lagally, and R. A. Mathies, “Monolithic membrane valves and diaphragm pumps for practical large-scale integration into glass microfluidic devices,” Sens. Actuators B 89, 315–323 (2003). 10.1016/S0925-4005(02)00468-9 Google Scholar

35.  Z.-J. Jia, Q. Fang, and Z.-L. Fang, “Bonding of glass microfluidic chips at room temperatures,” Anal. Chem. 76, 5597–5602 (2004). 10.1021/ac0494477 Google Scholar

36.  Y. Cheng, K. Sugioka, and K. Midorikawa, “Microfluidic laser embedded in glass by three-dimensional femtosecond laser microprocessing,” Opt. Lett. 29, 2007–2009 (2004). 10.1364/OL.29.002007 Google Scholar

37.  M.-Q. Bu, T. Melvin, G. J. Ensell, J. S. Wilkinson, and A. G. R. Evans, “A new masking technology for deep glass etching and its microfluidic application,” Sens. Actuators B 115, 476–482 (2004). 10.1016/j.sna.2003.12.013 Google Scholar

38.  P. B. Allen and D. T. Chiu, “Calcium-assisted glass-to-glass bonding for fabrication of glass microfluidic devices,” Anal. Chem. 80, 7153–7157 (2008). 10.1021/ac801059h Google Scholar

39.  P. Vulto, T. Huesgen, B. Albrecht, and G. A. Urban, “A full-wafer fabrication process for glass microfluidic chips with integrated electroplated electrodes by direct bonding of dry film resist,” J. Micromech. Microeng. 19, 077001 (2009). 10.1088/0960-1317/19/7/077001 Google Scholar

40.  P. C. H. Li and D. J. Harrison, “Transport, manipulation, and reaction of biological cells on-chip using electrokinetic effects,” Anal. Chem. 69, 1564–1568 (1997). 10.1021/ac9606564 Google Scholar

41.  L. C. Waters, S. C. Jacobson, N. Kroutchinina, J. Khandurina, R. S. Foote, and J. M. Ramsey, “Microchip device for cell lysis, multiplex PCR amplification, and electrophoretic sizing,” Anal. Chem. 70, 158–162 (1998). 10.1021/ac970642d Google Scholar

42.  T. Ichiki, T. Ujiie, S. Shinbashi, T. Okuda, and Y. Horiike, “Immunoelectrophoresis of red blood cells performed on microcapillary chips,” Electrophoresis 23, 2029–2034 (2002). 10.1002/1522-2683(200207)23:13<2029::AID-ELPS2029>3.0.CO;2-R Google Scholar

43.  H. Lee, E. Sun, D. Ham, and R. Weissleder, “Chip-NMR biosensor for detection and molecular analysis of cells,” Nat. Med. 14, 869–874 (2008). 10.1038/nm.1711 Google Scholar

44.  B.-Y. Qu, Z.-Y. Wu, F. Fang, Z.-M. Bai, D.-Z. Yang, and S.-K. Xu, “A glass microfluidic chip for continuous blood cell sorting by a magnetic gradient without labeling,” Anal. Bioanal. Chem. 392, 1317–1324 (2008). 10.1007/s00216-008-2382-4 Google Scholar

45.  S. C. Jacobson, L. B. Koutny, R. Hergenroder, A. W. Moore, and J. M. Ramsey, “Microchip capillary electrophoresis with an integrated postcolumn reactor,” Anal. Chem. 66, 3472–3476 (1994). 10.1021/ac00092a027 Google Scholar

46.  Z.-H. Liang, N. Chiem, G. Ocvirk, T. Tang, K. Fluri, and D. J. Harrison, “Microfabrication of a planar absorbance and fluorescence cell for integrated capillary electrophoresis devices,” Anal. Chem. 68, 1040–1046 (1996). 10.1021/ac950768f Google Scholar

47.  K. Fluri, G. Fitzpatrick, N. Chiem, and D. J. Harrison, “Integrated capillary electrophoresis devices with an efficient postcolumn teactor in planar quartz and glass chips,” Anal. Chem. 68, 4285–4290 (1996). 10.1021/ac9604090 Google Scholar

48.  S. C. Jacobson, C. T. Culbertson, J. E. Daler, and J. M. Ramsey, “Microchip structures for submillisecond electrophoresis,” Anal. Chem. 70, 3476–3480 (1998). 10.1021/ac980349t Google Scholar

49.  T. Ujiie, T. K. Ichiki, and Y. Horiike, “Fabrication of quartz microcapillary electrophoresis chips using plasma etching,” Jpn. J. Appl. Phys. 39, 3677–3682 (2000). 10.1143/JJAP.39.3677 Google Scholar

50.  T. M. H. Lee, I.-M. Hsing, A. I. K. Lao, and M. C. Carles, “A miniaturized DNA amplifier: its application in traditional chinese medicine,” Anal. Chem. 72, 4242–4247 (2000). 10.1021/ac000384b Google Scholar

51.  Y.-Z. Deng, H.-W. Zhang, and J. Henion, “Chip-based quantitative capillary electrophoresis/mass spectrometry determination of drugs in human plasma,” Anal. Chem. 73, 1432–1439 (2001). 10.1021/ac0010328 Google Scholar

52.  N. Gottschlich, S. C. Jacobson, C. T. Culbertson, and J. M. Ramsey, “Two-dimensional electrochromatography/capillary electrophoresis on a microchip,” Anal. Chem. 73, 2669–2674 (2001). 10.1021/ac001019n Google Scholar

53.  F. Omasu, Y. Nakano, and T. Ichiki, “Measurement of the electrophoretic mobility of sheep erythrocytes using microcapillary chips,” Electrophoresis 26, 1163–1167 (2005). 10.1002/elps.200410182 Google Scholar

54.  R. Mukhopadhyay, “When PDMS isn't the best,” Anal. Chem. 79, 3248–3253 (2007). 10.1021/ac071903e Google Scholar

55.  H. Becker and U. Heim, “Hot embossing as a method for the fabrication of polymer high aspect ratio structures,” Sens. Actuators, A 83, 130–135 (2000). 10.1016/S0924-4247(00)00296-X Google Scholar

56.  S.-Z. Qi, X.-Z. Liu, S. Ford, J. Barrows, G. Thomas, K. Kelly, A. McCandless, K. Lian, J. Goettert, and S. A. Soper, “Microfluidic devices fabricated in poly(methyl methacrylate) using hot-embossing with integrated sampling capillary and fiber optics for fluorescence detection,” Lab Chip 2, 88–95 (2002). 10.1039/b200370h Google Scholar

57.  R.-D. Chien, “Micromolding of biochip devices designed with microchannels,” Sens. Actuators, A 128, 238–247 (2006). 10.1016/j.sna.2006.02.029 Google Scholar

58.  U. M. Attia, S. Marson, and J. R. Alcock, “Micro-injection moulding of polymer microfluidic devices,” Microfluid. Nanofluid. 7, 1–28 (2009). 10.1007/s10404-009-0421-x Google Scholar

59.  J. C. McDonald, D. C. Duffy, J. R. Anderson, D. T. Chiu, H.-K. Wu, O. J. A. Schueller, and G. M. Whitesides, “Fabrication of microfluidic systems in poly(dimethylsiloxane),” Electrophoresis 21, 27–40 (1999). 10.1002/(SICI)1522-2683(20000101)21:1<27::AID-ELPS27>3.0.CO;2-C Google Scholar

60.  J. Rossier, F. Reymond, and P. E. Michel, “Polymer microfluidic chips for electrochemical and biochemical analyses,” Electrophoresis 23, 858–867 (2002). 10.1002/1522-2683(200203)23:6<858::AID-ELPS858>3.0.CO;2-3 Google Scholar

61.  H. Cao, J. O. Tegenfeldt, R. H. Austin, and S. Y. Chou, “Gradient nanostructures for interfacing microfluidics and nanofluidics,” Appl. Phys. Lett. 81, 3058–3060 (2002). 10.1063/1.1515115 Google Scholar

62.  T. Mappes, S. Achenbach, and J. Mohr, “X-ray lithography for devices with high aspect ratio polymer submicron structures,” Microelectron. Eng. 84, 1235–1239 (2007). 10.1016/j.mee.2007.01.154 Google Scholar

63.  T. W. Odom, J. C. Love, D. B. Wolfe, K. E. Paul, and G. M. Whitesides, “Improved pattern transfer in soft lithography using composite stamps,” Langmuir 18, 5314–5320 (2002). 10.1021/la020169l Google Scholar

64.  F. Hua, Y.-G. Sun, A. Gaur, M. A. Meitl, L. Bilhaut, L. Rotkina, J.-F. Wang, P. Geil, M. Shim, and J. A. Rogers, “Polymer imprint lithography with molecular-scale resolution,” Nano Lett. 4, 2467–2471 (2004). 10.1021/nl048355u Google Scholar

65.  Q.-B. Xu, B. T. Mayers, M. Lahav, D. V. Vezenov, and G. M. Whitesides, “Approaching zero: using fractured crystals in metrology for replica molding,” J. Am. Chem. Soc. 127, 854–855 (2005). 10.1021/ja043436d Google Scholar

66.  Z.-W. Li, Y.-N. Gu, L. Wang, H.-X. Ge, W. Wu, Q.-F. Xia, C.-S. Yuan, Y.-F. Cheng, B. Cui, and R. S. Williams, “Hybrid nanoimprint-soft lithography with sub-15 nm resolution,” Nano Lett. 9, 2306–2310 (2009). 10.1021/nl9004892 Google Scholar

67.  D. J. Beebe, G. A. Mensing, and G. M. Walker: “Physics and applications of microfluids in biology,” Annu. Rev. Biomed. Eng. 4, 261–286 (2002). 10.1146/annurev.bioeng.4.112601.125916 Google Scholar

68.  H. A. Stone, A. D. Stroock, and A. Ajdari, “Engineering flows in small devices: microfluidics toward a lab-on-a-chip,” Annu. Rev. Fluid Mech. 36, 381–411 (2004). 10.1146/annurev.fluid.36.050802.122124 Google Scholar

69.  L. Baharudin, “Microfluidics: fabrications and applications,” Instru. Sci. Tech. 36, 222–230 (2008). 10.1080/10739140701850993 Google Scholar

70.  K. B. Mogensen, H. Klank, and J. P. Kutter, “Recent developments in detection for microfluidic systems,” Electrophoresis 25, 3498–3512 (2004). 10.1002/elps.200406108 Google Scholar

71.  A. Q. Liu, H. J. Huang, L. K. Chin, Y. F. Yu, and X. C. Li, “Label-free detection with micro optical fluidic systems (MOFS): a review,” Anal. Bioanal. Chem. 391, 2243–2452 (2008). 10.1007/s00216-008-1878-2 Google Scholar

72.  A. C. Siegel, S. K. Y. Tang, C. A. Nijhuis, M. Hashimoto, S. T. Phillips, M. D. Dickey, and G. M. Whitesides, “Co-fabrication: a strategy for building multi-component microsystems,” Acc. Chem. Res. 43, 518–528 (2010). 10.1021/ar900178k Google Scholar

73.  D. J. Bornhop and K. Swinney, “Detection in capillary electrophoresis: a review,” Electrophoresis 21, 1239–1250 (2000). 10.1002/(SICI)1522-2683(20000401)21:7<1239::AID-ELPS1239>3.0.CO;2-6 Google Scholar

74.  D. Ross, M. Gaitan, and L. E. Locascio, “Temperature measurement in microfluidic systems using a temperature-dependent fluorescent dye,” Anal. Chem. 73, 4117–4123 (2001). 10.1021/ac010370l Google Scholar

75.  P. Dumais, C. L. Callender, J. P. Noad, and C. J. Ledderhof, “Integrated optical sensor using a liquid-core waveguide in a Mach-Zehnder interferometer,” Opt. Express 16, 18164–18172 (2008). 10.1364/OE.16.018164 Google Scholar

76.  I. T. Kim and K. D. Kihm, “Label-free visualization of microfluidic mixture concentration fields using SPR reflectance imaging,” Exp. Fluids 41, 905–916 (2006). 10.1007/s00348-006-0210-1 Google Scholar

77.  T. Park, S. Lee, G. H. Seong, J. Choo, E. K. Lee, Y. S. Kim, W. H. Ji, S. Y. Hwang, D. G. Gweon, and S. Lee, “Highly sensitive signal detection of duplex dye-labelled DNA oligonucleotides in a PDMS microfluidic chip: confocal surface-enhanced Raman spectroscopic study,” Lab Chip 5, 437–442 (2005). 10.1039/b414457k Google Scholar

78.  V. Lien and F. Vollmer, “Microfluidic flow rate detection based on integrated optical fiber cantilever,” Lab Chip 7, 1352–1356 (2007). 10.1039/b706944h Google Scholar

79.  D. A. Chang-Yen and B. K. Gale, “An integrated optical oxygen sensor fabricated using rapid-prototyping techniques,” Lab Chip 3, 297–301 (2003). 10.1039/b305358j Google Scholar

80.  D. Sinton, R. Gordon, and A. G. Brolo, “Nanohole arrays in metal films as optofluidic elements: progress and potential,” Microfluid. Nanofluid. 4, 107–116 (2008). 10.1007/s10404-007-0221-0 Google Scholar

81.  W. K. Ridgeway, E. Seitaridou, R. Phillips, and J. R. Williamson, “RNA-protein binding kinetics in an automated microfluidic reactor,” Nucleic Acids Res. 37, e142 (2009). 10.1093/nar/gkp733 Google Scholar

82.  J. G. Santiago, S. Wereley, C. D. Meinhart, D. J. Beebe, and R. J. Adrian, “A micro-particle image velocimetry system,” Exp. Fluids 25, 316–319 (1998). 10.1007/s003480050235 Google Scholar

83.  M. G. Olsen, J. M. Bauer, and D. J. Beebe, “Particle imaging technique for measuring the deformation rate of hydrogel microstructures,” Appl. Phys. Lett. 76, 3310–3312 (2000). 10.1063/1.126635 Google Scholar

84.  G. Minas, J. S. Martins, J. C. Ribeiro, R. F. Wolffenbuttel, and J. H. Correia, “Biological microsystem for measuring uric acid in biological fluids,” Sens. Actuators, A 110, 33–38 (2004). 10.1016/j.sna.2003.10.049 Google Scholar

85.  M. P. Duggan, T. McCreedy, and J. W. Aylott, “A non-invasive analysis method for on-chip spectrophotometric detection using liquid-core waveguiding within a 3D architecture,” Analyst (Cambridge, U.K.) 128, 1336–1340 (2003). 10.1039/b309869a Google Scholar

86.  N. J. Petersen, K. B. Mogensen, and J. P. Kutter, “Performance of an in-plane detection cell with integrated waveguides for UV/Vis absorbance measurements on microfluidic separation devices,” Electrophoresis 23, 3528–3536 (2002). 10.1002/1522-2683(200210)23:20<3528::AID-ELPS3528>3.0.CO;2-5 Google Scholar

87.  B. Filanoski, S. K. Rastogi, E. Cameron, N. N. Mishra, W. Maki, and G. Maki, “A novel homogeneous bioluminescence resonance energy transfer element for biomolecular detection with CCD camera or CMOS device,” Luminescence 23, 22–27 (2008). 10.1002/bio.1011 Google Scholar

88.  O. Hofmann, P. Miller, P. Sullivan, S. T. Jones, J. C. deMello, D. D. C. Bradley, and A. J. deMello, “Thin-film organic photodiodes as inte- grated detectors for microscale chemiluminescence assays,” Sens. Actuators B 106, 878–884 (2005). 10.1016/j.snb.2004.10.005 Google Scholar

89.  A. M. Jorgensen, K. B. Mogensen, J. P. Kutter, and O. Geschke, “A biochemical microdevice with an integrated chemiluminescence detector,” Sens. Actuators B 90, 1–3 (2003). 10.1016/S0925-4005(03)00016-9 Google Scholar

90.  J.-Z. Zhu, Z.-Q. Zhu, Z.-S. Lai, R. Wang, X.-M. Guo, X.-Q. Wu, G.-X. Zhang, Z.-R. Zhang, Y.-T. Wang, Z.-Y. Chen, “Planar amperometric glucose sensor based on glucose oxidase immobilized by chitosan film on prussian blue layer,” Sensors 2, 127–136 (2002). 10.3390/s20400127 Google Scholar

91.  W. Cha, Y.-C. Tung, M. E. Meyerhoff, and S. Takayama, “Patterned electrode-based amperometric gas sensor for direct nitric oxide detection within microfluidic devices,” Anal. Chem. 82, 3300–3305 (2010). 10.1021/ac100085w Google Scholar

92.  J. C. Fanguy and C. S. Henry, “The analysis of uric acid in urine using microchip capillary electrophoresis with electrochemical detection,” Electrophoresis 23, 767–773 (2002). 10.1002/1522-2683(200203)23:5<767::AID-ELPS767>3.0.CO;2-8 Google Scholar

93.  X. X. Cai, N. Klauke, A. Glidle, P. H. Cobbold, G. L. Smith, and J. M. Cooper, “Ultra-low-volume, real-time measurements of lactate from the single heart cell using microsystems technology,” Anal. Chem. 74, 908–914 (2002). 10.1021/ac010941+ Google Scholar

94.  N. Ohgami, S. Upadhyay, A. Kabata, K. Morimoto, H. Kusakabe, and H. Suzuki, “Determination of the activities of glutamic oxaloacetic transaminase and glutamic pyruvic transaminase in a microfluidic system,” Biosens. Bioelectron. 22, 1330–1336 (2007). 10.1016/j.bios.2006.06.007 Google Scholar

95.  H. Suzuki and Y. Matsugi, “Microfabricated flow system for ammonia and creatinine with an air-gap structure,” Sens. Actuators B 98, 101–111 (2004). 10.1016/j.snb.2003.08.018 Google Scholar

96.  R. H. Liu, J.-N. Yang, R. Lenigk, J. Bonanno, and P. Grodzinski, “Self-contained, fully integrated biochip for sample preparation, polymerase chain reaction amplification, and DNA microarray detection,” Anal. Chem. 76, 1824–1831 (2004). 10.1021/ac0353029 Google Scholar

97.  I. Grabowska, M. Sajnoga, M. Juchniewicz, M. Chudy, A. Dybko, and Z. Brzozka, “Microfluidic system with electrochemical and optical detection,” Microelectron. Eng. 84, 1741–1743 (2007). 10.1016/j.mee.2007.01.248 Google Scholar

98.  M. Galloway, W. Stryjewski, A. Henry, S. M. Ford, S. Llopis, R. L. McCarley, and S. A. Soper, “Contact conductivity detection in poly(methyl methacylate)-based microfluidic devices for analysis of mono- and polyanionic molecules,” Anal. Chem. 74, 2407–2415 (2002). 10.1021/ac011058e Google Scholar

99.  M. Zuborova, Z. Demianova, D. Kaniansky, M. Masar, and B. Stanislawski, “Zone electrophoresis of proteins on a poly(methyl methacrylate) chip with conductivity detection,” J. Chromatogr. A 990, 179–188 (2003). 10.1016/S0021-9673(02)01805-8 Google Scholar

100.  C. L. Lago, H. D. T. Silva, C. A. Neves, J. G. A. Brito-Neto, and J. A. F. Silva, “A dry process for production of microfluidic devices based on the lamination of laser-printed polyester films,” Anal. Chem. 75, 3853–3858 (2003). 10.1021/ac034437b Google Scholar

101.  X.-H. Huang, R. N. Zare, S. Sloss, and A. G. Ewing, “End-column detection for capillary zone electrophoresis,” Anal. Chem. 63, 189–192 (1991). 10.1021/ac00002a020 Google Scholar

102.  Z.-Y. Wu, F. Fang, J. Josserand, and H. H. Girault, “On-column conductivity detection in capillary-chip electrophoresis,” Electrophoresis 28, 4612–4619 (2007). 10.1002/elps.200700456 Google Scholar

103.  E. Hoffmann and V. Stroobant, Mass Spectrometry: Principles and Application, 3rd ed., Wiley, New York (2007). Google Scholar

104.  G. A. Schultz, T. N. Corso, S. J. Prosser, and S. Zhang, “A fully integrated monolithic microchip electrospray device for mass spectrometry,” Anal. Chem. 72, 4058–4063 (2000). 10.1021/ac000325y Google Scholar

105.  L. Licklider, X. Q. Wang, A. Desai, Y. C. Tai, and T. D. Lee, “A micromachined chip-based electrospray source for mass spectrometry,” Anal. Chem. 72, 367–375 (2000). 10.1021/ac990967p Google Scholar

106.  J. Kameoka, R. Orth, B. Ilic, D. Czaplewski, T. Wachs, and H. G. Craighead, “An electrospray ionization source for integration with microfluidics,” Anal. Chem. 74, 5897–5901 (2002). 10.1021/ac020396s Google Scholar

107.  T. Miliotis, S. Kjellstrom, J. Nilsson, T. Laurell, L. E. Edholm, and G. Marko-Varga, “Capillary liquid chromatography interfaced to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry using an on-line coupled piezoelectric flow-through microdispenser,” J. Mass Spectrom. 35, 369–377 (2000). 10.1002/(SICI)1096-9888(200003)35:3<369::AID-JMS944>3.0.CO;2-N Google Scholar

108.  J. Liu, K. Tseng, B. Garcia, C. B. Lebrilla, E. Mukerjee, S. Collins, and R. Smith, “Electrophoresis separation in open microchannels. A method for coupling electrophoresis with MALDI-MS,” Anal. Chem. 73, 2147–2151 (2001). 10.1021/ac001326t Google Scholar

109.  M. L. Mok, L. Hua, J. B. Phua, M. K. Wee, and N. S. Sze, “Capillary isoelectric focusing in pseudo-closed channel coupled to matrix assisted laser desorption/ioization mass spectrometry for protein analysis,” Analyst (Cambridge, U.K.) 129, 109–110 (2004). 10.1039/b309610f Google Scholar

110.  A. K. Naik, M. S. Hanay, W. K. Hiebert, X. L. Feng, and M. L. Roukes, “Towards single-molecule nanomechanical mass spectrometry,” Nat. Nanotechnol. 4, 445–450 (2009). 10.1038/nnano.2009.152 Google Scholar

111.  J. Hardouin, M. Duchateau, R. Joubert-Caron, and M. Caron, “Usefulness of an integrated microfluidic device (HPLC-Chip-MS) to enhance confidence in protein identification by proteomics,” Rapid Commun. Mass Spectrom. 20, 3236–3244 (2006). 10.1002/rcm.2725 Google Scholar

112.  J. M. Armenta, A. A. Dawoud, and L. M. Lazar, “Microfluidic chips for protein differential expression profiling,” Electrophoresis 30, 1145–1156 (2009). 10.1002/elps.200800653 Google Scholar

113.  P. Horvatovich, N. I. Govorukhina, T. H. Reijmers, A. G. J. van der Zee, F. Suits, and R. Bischoff, “Chip-LC-MS for label-free profiling of human serum,” Electrophoresis 28, 4493–4505 (2007). 10.1002/elps.200600719 Google Scholar

114.  A. Webb, “Nuclear magnetic resonance of mass-limited samples using small RF coils,” Anal. Bioanal. Chem. 388, 525–528 (2007). 10.1007/s00216-007-1178-2 Google Scholar

115.  G. A. Webb, Nuclear Magnetic Resonance, The Royal Society of Chemistry, Cambridge (2003). Google Scholar

116.  L.-S. Bouchard, S. R. Burt, M. S. Anwar, K. V. Kovtunov, I. V. Koptyug, and A. Pines, “NMR imaging of catalytic hydrogenation in microreactors with the use of para-hydrogen,” Science 319, 442–445 (2008). 10.1126/science.1151787 Google Scholar

117.  M. S. Anwar, C. Hilty, C. Chu, L.-S. Bouchard, K. L. Pierce, and A. Pines, “Spin Coherence Transfer in Chemical Transformations Monitored by Remote Detection NMR,” Anal. Chem. 79, 2806–2811 (2007). 10.1021/ac062327+ Google Scholar

118.  V.-V. Telkki, C. Hilty, S. Garcia, E. Harel, and A. Pines, “Quantifying the diffusion of a fluid through membranes by double phase encoded remote detection magnetic resonance imaging,” J. Phys. Chem. B 111, 13929–13936 (2007). 10.1021/jp076760e Google Scholar

119.  M. Mujika, S. Arana, E. Castano, M. Tijero, R. Vilares, and J. M. Ruano-Lopez, “Magnetoresisitve immunosensor for the detection of escherichia coli O157:H7,” Biosens. Bioelectron. 24, 1253–1258 (2009). 10.1016/j.bios.2008.07.024 Google Scholar

120.  O. Tamarin, S. Comeau, C. Dejous, D. Moynet, D. Riebre, and J. Beziam, “Design of a bacteriophage model using love acoustic waves,” Biosens. Bioelectron. 18, 755–763 (2003). 10.1016/S0956-5663(03)00022-8 Google Scholar

121.  B. Godber, S. J. Kevin, K. S. J. Thompson, M. Rehak, Y. Uludag, S. Kelling, M. Sleptsov, M. Frogley, K. Wiehler, C. Whalen, and J. M. Cooper, “Direct quantification of analyte concentration by resonant acoustic profiling,” Clin. Chem. 51, 1962–1972 (2005). 10.1373/clinchem.2005.053249 Google Scholar

122.  A. D. Leebeeck, L. K. S. Kumar, V. D. Lange, D. Sinton, R. Gordon, and A. G. Frolo, “On-chip surface-based detection with nanohole arrays,” Anal. Chem. 79, 4094–4100 (2007). 10.1021/ac070001a Google Scholar

123.  E. Ouellet, C. Lausted, T. Lin, C. W. T. Yang, L. Hood, and E. T. Lagally, “Parallel microfluidic surface plasmon resonance imaging arrays,” Lab Chip 10, 581–588 (2010). 10.1039/b920589f Google Scholar

124.  R. G. Heideman and P. V. Lambeck, “Remote opto-chemical sensing with extreme sensitivity: design, fabrication and performance of a pigtailed integrated optical phase-modulated Mach-Zehnder interferometer system,” Sens. Actuators B 61, 100–127 (1999). 10.1016/S0925-4005(99)00283-X Google Scholar

125.  J. A. Chediak, Z. S. Lou, J. Seo, N. Cheung, L. P. Lee, and T. D. Sands, “Heterogeneous integration of CdS filters with GaN LEDs for fluorescence detection microsystems,” Sens. Actuators, A 111, 1–7 (2004). 10.1016/j.sna.2003.10.015 Google Scholar

126.  S. H. Hsu and Y. T. Huang, “A novel Mach-Zehnder interferometer based on dual-ARROW structures for sensing applications,” J. Lightwave Technol. 23, 4200–4206 (2005). 10.1109/JLT.2005.859435 Google Scholar

127.  H. Berney and K. Oliver, “Dual polarization interferometry size and density characterization of DNA immobilization and hybridization,” Biosens. Bioelectron. 21, 618–626 (2005). 10.1016/j.bios.2004.12.024 Google Scholar

128.  B. Lillis, M. Manning, H. Berney, E. Hurley, A. Mathewson, and M. M. Sheehan, “Dual polarisation interferometry characterisation of DNA immobilisation and hybridisation detection on a silanised support,” Biosens. Bioelectron. 21, 1459–1467 (2006). 10.1016/j.bios.2005.06.009 Google Scholar

129.  K. R. Strehle, D. Cialla, P. Rosch, T. Henkel, M. Kohler, and J. Popp, “A reproducible surface-enhanced Raman spectroscopy approach. Online SERS measurements in a segmented microfluidic system,” Anal. Chem. 79, 1542–1547 (2007). 10.1021/ac0615246 Google Scholar

130.  B. D. Piorek, S. J. Lee, J. G. Santiago, M. Moskovits, S. Banerjee, and C. D. Meinhart, “Free-surface microfluidic control of surface-enhanced Raman spectroscopy for the optimized detection of airborne molecules,” Proc. Natl. Acad. Sci. U.S.A 104, 18898–18901 (2007). 10.1073/pnas.0708596104 Google Scholar

131.  L. Tong, M. Righini, M. U. Gonzalez, R. Quidant, and M. Kall, “Optical aggregation of metal nanoparticles in a microfluidic channel for surface-enhanced Raman scattering analysis,” Lab Chip 9, 193–195 (2008). 10.1039/b813204f Google Scholar

132.  M. I. Rudenko, M. R. Holmes, P. Measor, D. W. Deamer, A. R. Hawkins, and H. Schmidt, “Planar electro-optofluidic chip: integration of nanopore with optofluidics,” in Conf. on Lasers and Electro-Optics (CLEO), San Jose, California, article CTuJJ3, Optical Society of America (2010). Google Scholar

133.  D. Erickson, T. Rockwood, T. Emery, A. Scherer, and D. Psaltis, “Nanofluidic tuning of photonic crystal circuitry,” Opt. Lett. 31, 59–61 (2006). 10.1364/OL.31.000059 Google Scholar

134.  C. J. Choi and B. T. Cunningham, “A 96-well microplate incorporating a replica molded microfluidic network integrated with photonic crystal biosensors for high throughput kinetic biomolecular interaction analysis,” Lab Chip 7, 550–556 (2007). 10.1039/b618584c Google Scholar

135.  L. L. Chan, S. L. Gosangari, K. L. Watkin, and B. T. Cunningham, “Label-free imaging of cancer cells using photonic crystal biosensors and application to cytotoxicity screening of a natural compound library,” Sens. Actuators B 132, 418–425 (2007). 10.1016/j.snb.2007.10.027 Google Scholar

136.  B. R. Schudel, C. J. Choi, B. T. Cunningham, and P. J. A. Kenis, “Microfluidic chip for combinatorial mixing and screening of assays,” Lab Chip 9, 1676–1680 (2009). 10.1039/b901999e Google Scholar

137.  H. J. Kim, S. Kim, H. Jeon, J. Ma, S. H. Choi, S. Lee, C. Ko, and W. Park, “Fluorescence amplification using colloidal photonic crystal platform in sensing dye-labeled deoxyribonucleic acids,” Sens. Actuators B 124, 147–152 (2007). 10.1016/j.snb.2006.12.024 Google Scholar

138.  J. Wu, D. Day, and M. Gu, “A microfluidic refractive index sensor based on an integrated three-dimensional photonic crystal,” Appl. Phys. Lett. 92, 071108 (2008). 10.1063/1.2840700 Google Scholar

139.  M. Loncar, A. Scherer, and Y. M. Qiu, “Photonic crystal laser sources for chemical detection,” Appl. Phys. Lett. 82, 4648–4650 (2003). 10.1063/1.1586781 Google Scholar

140.  M. L. Adams, M. Loncar, A. Scherer, and Y. M. Qiu, “Microfluidic integration of porous photonic crystal nanolasers for chemical sensing,” IEEE J. Sel. Areas Commun. 23, 1348–1354 (2005). 10.1109/JSAC.2005.851192 Google Scholar

141.  N. M. Hanumegowda, I. M. White, H. Oveys, and X. Fan, “Label-free protease sensors based on optical microsphere resonators,” Sens. Lett. 3, 315–319 (2005). 10.1166/sl.2005.044 Google Scholar

142.  M. Noto, M. Koshsima, D. Keng, I. Teraoka, V. Kolchenko, and S. Arnold, “Molecular weight dependence of a whispering gallery mode biosensor,” Appl. Phys. Lett. 87, 223901 (2005). 10.1063/1.2137902 Google Scholar

143.  N. M. Hanumegowda, C. J. Stica, B. C. Patel, I. M. White, and X. Fan, “Refractometric sensors based on microsphere resonators,” Appl. Phys. Lett. 87, 201107 (2005). 10.1063/1.2132076 Google Scholar

144.  Y. Lin, V. S. Ilchenko, J. Nadeau, and L. Maleki, “Biochemical detection with optical whispering-gallery resonators,” Proc. SPIE 6452, 64520U (2007). 10.1117/12.716591 Google Scholar

145.  S. L. Westcott, J. Zhang, R. K. Shelton, N. M. K. Bruce, S. Gupta, S. L. Keen, J. W. Tillman, L. B. Wald, B. N. Strecker, A. T. Rosenberger, R. R. Davidson, W. Chen, K. G. Donovan, and J. V. Hryniewicz, “Broadband optical absorbance spectroscopy using a whispering gallery mode microsphere resonator,” Rev. Sci. Instrum. 79, 033106 (2008). 10.1063/1.2894307 Google Scholar

146.  S. Arnold, R. Ramjit, D. Keng, V. Kolchenko, and I. Teraoka, “Microparticle photophysics illuminates viral bio-sensing,” Faraday Discuss 137, 65–83 (2008). 10.1039/b702920a Google Scholar

147.  D. Keng, S. R. McAnanama, I. Teraoka, and S. Arnold, “Resonance fluctuations of a whispering gallery mode biosensor by particles undergoing Brownian motion,” Appl. Phys. Lett. 91, 103902 (2007). 10.1063/1.2778351 Google Scholar

148.  E. Eriksson, J. Scrimgeour, J. Enger, and M. Goksor, “Holographic optical tweezers combined with a microfluidic device for exposing cells to fast environmental changes,” Proc. SPIE 6592, 65920P (2007). 10.1117/12.721859 Google Scholar

149.  H. Mushfique, J. Leach, H. Yin, R. D. Leonardo, M. J. Padgett, and J. M. Cooper, “3D mapping of microfluidic flow in laboratory-on-a-chip structures using optical tweezers,” Anal. Chem. 80, 4237–4240 (2008). 10.1021/ac8002006 Google Scholar

150.  J. Wu, D. Day, and M. Gu, “Shear stress mapping in microfluidic devices by optical tweezers,” Opt. Express 18, 7611–7616 (2010). 10.1364/OE.18.007611 Google Scholar

151.  D. F. Hunt, J. R. Yates III, J. Shabanowitz, S. Winston, and C. R. Hauer, “Protein sequencing by tandem mass spectrometry,” Proc. Natl. Acad. Sci. U.S.A 83, 6233–6237 (1986). 10.1073/pnas.83.17.6233 Google Scholar

152.  S.-F. Cheng and L.-K. Chau, “Colloidal gold-modified optical fiber for chemical and biochemical sensing,” Anal. Chem. 75, 16–21 (2003). 10.1021/ac020310v Google Scholar

153.  Y. Chuang, C.-Y. Lee, S.-H. Lu, S.-C. Wang, L.-K. Chau, and W.-H. Hsieh, “Using ac-field-induced electro-osmosis to accelerate biomolecular binding in fiber-optic sensing chips with microstructures,” Anal. Chem. 82, 1123–1127 (2010). 10.1021/ac902682k Google Scholar

154.  D. Hou, S. Maheshwari, and H.-C. Chang, “Rapid bioparticle concentration and detection by combining a discharge driven vortex with surface enhanced Raman scattering,” Biomicrofluidics 1, 014106 (2007). 10.1063/1.2710191 Google Scholar

155.  R. Ameling, L. Langguth, M. Hentschel, M. Mesch, P. V. Braun, and H. Giessen, “Cavity-enhanced localized plasmon resonance sensing,” Appl. Phys. Lett. 97, 253116 (2010). 10.1063/1.3530795 Google Scholar

156.  K. Uchiyama, H. Nakajima, and T. Hobo, “Detection methods for microchip separations,” Anal. Bioanal. Chem. 379, 375–382 (2004). 10.1007/s00216-004-2616-z Google Scholar

157.  S. H. I. Yeung, T. S. Seo, C. A. Crouse, S. A. Greenspoon, T. N. Chiesl, J. D. Ban, and R. A. Mathies, “Fluorescence energy transfer-labeled primers for high-performance forensic DNA profiling,” Electrophoresis 29, 2251–2259 (2008). 10.1002/elps.200700772 Google Scholar

158.  R. T. Ranasinghe and T. Brown, “Ultrasensitive fluorescence-based methods for nucleic acid detection: towards amplification-free genetic analysis,” Chem. Commun. (Cambridge) 47, 3717–3735 (2011). 10.1039/c0cc04215c Google Scholar

159.  R. Bruck, E. Melnik, P. Muellner, R. Hainberger, and M. Lammerhofer, “Integrated polymer-based Mach-Zehnder interferometer label-free streptavidin biosensor compatible with injection molding,” Biosens. Bioelectron. 26, 3832–3837 (2011). 10.1016/j.bios.2011.02.042 Google Scholar

160.  P. Estrela, D. Paul, Q.-F. Song, L. K. J. Stadler, L. Wang, E. Huq, J. J. Davis, P. K. Ferrigno, and P. Migliorato, “Label-free sub-picomolar protein detection with field-effect transistors,” Anal. Chem. 82, 3531–3536 (2010). 10.1021/ac902554v Google Scholar

161.  T. Endo, D. Ikeda, Y. Yawakami, Y. Yanagida, and T. Hatsuzawa, “Fabrication of core-shell structured nanoparticle layer substrate for excitation of localized surface plasmon resonance and its optical response for DNA in aqueous conditions,” Anal. Chim. Acta 661, 200–205 (2010). 10.1016/j.aca.2009.12.022 Google Scholar

162.  D. Choi, T. Kang, H. Cho, Y. Choi, and L. P. Lee, “Additional amplifications of SERS via an optofluidic CD-based platform,” Lab Chip 9, 239–243 (2009). 10.1039/B812067F Google Scholar

163.  W. Liang, Y. Huang, Y. Xu, R. K. Lee, and A. Yariv, “Highly sensitive fiber Bragg grating refractive index sensors,” Appl. Phys. Lett. 86, 151122 (2009). 10.1063/1.1904716 Google Scholar

164.  C. Markos, W. Yuan, K. Vlachos, G. E. Town, and O. Bang, “Label-free biosensing with high sensitivity in dual-core microstructured polymer optical fibers,” Opt. Express 19, 7790–7798 (2010). 10.1364/OE.19.007790 Google Scholar

165.  I. M. White, H. Oveys, and X.-D. Fan, “Liquid-core optical ring-resonator sensors,” Opt. Lett. 31, 1319–1321 (2006). 10.1364/OL.31.001319 Google Scholar

© (2011) Society of Photo-Optical Instrumentation Engineers (SPIE)
Jing Wu, Jing Wu, Min Gu, Min Gu, } "Microfluidic sensing: state of the art fabrication and detection techniques," Journal of Biomedical Optics 16(8), 080901 (1 August 2011). https://doi.org/10.1117/1.3607430 . Submission:

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