Recent advances in gas phase microcantilever-based sensing
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Zhou Long
Dr. Zhou Long received a BS in Chemistry from Sichuan University of China under the supervision of Dr. Xiandeng Hou, and a PhD in Analytical Chemistry from The University of Tennessee, USA (advisor: Dr. Michael J. Sepaniak) in 2010 when he started working as a postdoctoral research fellow with Dr. Sepaniak and was also affiliated with Oak Ridge National Laboratory. Currently, he is an Assistant Professor of Analytical Chemistry at Sichuan University of China, and his research interests include miniature bio/chemical sensors, analytical atomic spectrometry, and bio/chemical separation.
Dr. Michael J. Sepaniak received a PhD in Analytical Chemistry from Iowa State University in 1980. He joined the faculty of the University of Tennessee in 1981 and has also been affiliated with Oak Ridge National Laboratory since that time. His research interest in Analytical Chemistry broadly spans chemical separations, laser spectroscopy, sensor development, and nanoscience and technology. He has directed the research of approximately 20 post docs, 70 graduate students, and has over 190 peer-reviewed publications.
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Xiandeng Hou
Dr. Xiandeng Hou received his PhD in Chemistry from University of Connecticut under the supervision of Dr. Robert G. Michel in 1999. After two periods of postdoctoral research experience with Dr. Bradley T. Jones at Wake Forest University, he joined the Faculty of Chemistry of Sichuan University, Chengdu, China. He is now a Professor of Analytical Chemistry, and the Director of the Analytical and Testing Center of Sichuan University. His main research interest lies in spectral analysis. He has authored and coauthored over 130 publications, and is on editorial boards of several international journals of analytical spectrometry.
Abstract
Microcantilever (MC) sensors have become a more attractive technique for gas phase sensing during recent years. The purpose of this review is to critically summarize the recent advances in terms of theory, detection and sensing scheme, sensor design, and applications of MC-based gas sensors, with most of the related work reported since 2005.
Introduction
Low-cost, highly selective, and sensitive gas sensors have always been pursued by researchers. Since the last decade, the capability to use the motions of microcantilevers (MCs) as an effective method for gas phase sensing has become a practical and intriguing option.
MCs are extremely sensitive to surface processes owing to their large surface area-to-mass ratios. The major principle of MC sensing is based on the analyte-induced MC surface stress, which leads to MC motions of mechanical movements and deformations. On the basis of that, various response characteristics of an MC, such as resonant frequency, deflection amplitude, phase and quality factor, etc., can be obtained through either optical or electrical detection techniques, with according results further employed for the determination, characterization, and identification of gaseous analytes (Lavrik et al. 2004, Goeders et al. 2008, Singamaneni et al. 2008). Moreover, during the past several years, it should be noted that besides the common deflection motion, some research attention has been paid to lateral and torsional motions of MC for further improvement of sensitivity (Goeders et al. 2008, Xie et al. 2008), and damping effects were also studied deeply to achieve better performance of MC gas sensors (Martin et al. 2008, Xia and Li 2008, Bidkar et al. 2009, Lee et al. 2009b).
Compared with other kinds of gas sensors, MC sensors have demonstrated several advantages, including fast response time, low cost, array format, small overall dimensions, and great potential for field application. During the past several years, MC sensors have been emerging as a more attractive device for real-time and label-free detection of various gaseous analytes compared with the earlier period of development, especially with the outstanding improvement of fabrication, modification, and functionalization techniques applied to MC gas sensors. MCs fabricated with materials other than the most commonly used silicon (Si)-based compounds, such as SU-8 (Nordstrom et al. 2008), polyimide (Zhu et al. 2011), and alumina (Lee et al. 2009a), are more frequently used for gas phase sensing. Varieties of coatings immobilized on MC surfaces have been reported, including organic/inorganic responsive phases, piezoelectric or piezoresistive layers, and self-assembled mono-/bilayers of sensing sites, which have made MC gas sensors applicable to the detection of a wider range of analytes than ever before. Although the current applications of MC gas sensors still lie in the analysis of laboratory samples, most of them highly illustrated realistic human concerns such as environmental (Kooser et al. 2004, Adams et al. 2005, Reddy et al. 2012), health-care (Zuo et al. 2006, Lang et al. 2007, Yang et al. 2010, Kelling et al. 2011, Mihara et al. 2011), security (Chen et al. 2010, Xu et al. 2010, Seena et al. 2011a), energy (Yen et al. 2008, Long et al. 2009), etc. Moreover, extra research efforts were made to take advantage of the MC array (MCA) format and prepare highly selective MC differential arrays. By using pattern recognition techniques and algorithms such as principal components analysis (PCA) or artificial neural network (ANN), binary or tertiary gaseous mixtures could be analyzed, with individual analyte in the mixture identified (Senesac et al. 2006, Loui et al. 2008). Gaseous mixture could also be analyzed by coupling gas chromatography (GC) with an MC gas sensor, with the former for mixture separation and the latter as a detector (Chapman et al. 2007b). However, only preliminary research work has been carried out in this newly developed approach. Moreover, analysis of breath samples of real patients has been accomplished by using MCA sensors recently, which is one of the few good examples of the real-world applications of MC gas sensors (Lang et al. 2007, Kelling et al. 2011).
Operation mode and sensing principle
The functionality of MC gas sensors is based on the mechanical movements and deformations of their micromachined components, such as single-clamped suspended cantilever beams or multiple-clamped suspended beams (bridges). In the absence of external gravitational, magnetic, and electrostatic forces, MC deformation is unambiguously related to a gradient of mechanical stress generated in the device. On the basis of measured parameters, cantilever bending, or resonance frequency, the operational mode of an MC can be defined as either static or dynamic, respectively. The static mode of deflection occurs when adsorbed species cause differential surface stresses on the opposing surfaces of the MC, while the dynamic mode of detection occurs when the frequency of vibration of the beam changes as species are adsorbed onto the MC surface and the mass changes. Setup and methods allowing the simultaneous detection of MC oscillation and bending in the gas phase has a long history (Battiston et al. 2001, Vidic et al. 2003). Recently, considering that the frequency stability and sensitivity of an MC sensor in dynamic mode in the gas phase are mainly determined by its mechanical quality factor, which exhibits a large reduction, Dufour et al. (2007) studied two different bending vibration modes, “weak-axis bending” and “strong-axis bending”, in order to minimize the loss for increasing the quality factor and sensitivity, with higher resonant frequency obtained in the strong-axis bending mode. The higher resonant modes of MC-based gas sensors, especially lateral and torsional motions of MCs, can be modeled in similar manners as static and dynamic modes, while promising enhanced sensitivity owing to higher quality factors. Although most of the previous research efforts have focused on the common flexure modes (vertical or bending), some research efforts were made on lateral or torsional mode MC gas sensing during the past several years. For instance, Xie et al. (2008) employed the first torsional mode for improving the resolution of mass detection, and presented a model based on the Rayleigh-Ritz method, which has been widely used to resolve natural frequencies of continuum systems. The potential (U) and kinetic (T) energies of the torsional system are considered to calculate the natural frequency of the system, and the maxima Umax and Tmax are defined by
where L, ρ, and z(x) are the length, density, and mode shape of the MC, respectively; G is the shear modulus; Ip is the polar area moment of inertia; J is the torsional constant; and ω is the nth torsional resonant frequency, which is defined by
Moreover, the experimental results showed that the mass sensitivity of this torsional mode was an order higher than that of the bending mode within the realm of existing commercial MCs.
For a multilayered MC with a “sandwich” structure, small temperature changes will cause MC deflection due to thermal expansion differences, which is usually called the “biomaterial effect” (Djuric et al. 2007b). In reference to the MC sensors, this mode of operation is frequently referred to as the “heat mode” (Lavrik et al. 2004). The temperature change can be either caused by external influences, such as change in environmental temperature (thermal detection) or occurring directly on the surface by virtue of an exothermic or endothermic process due to the adsorption of target analytes (Krause et al. 2008, Patton et al. 2010). Recently, Djuric et al. (2007b) proposed a new theoretical approach to the analysis of bimaterial infrared thermal detector performance. After identifying all of the relevant noise mechanisms (temperature fluctuations, Brownian motion), the authors solved the appropriate Langevin stochastic equation and obtained the mean square deflection of the bimaterial MC oscillator. This enabled the determination of all of the important parameters, which depend on the relevant thermal, mechanical, and geometrical properties of the constituent parts of the detector and the chosen materials, as well as on the gas type and pressure. It was demonstrated that detectivity could approach the ideal value with pressure decrease if other parameters were properly chosen.
If an MC is involved in a gaseous ambiance that influences its operation, damping effects need to be considered to improve the MC sensor performance. Martin et al. (2008) presented models for determining the damping and the quality factor of an MC in vertical, horizontal, and torsional motion, using a consistent model of gas-surface interaction, operating in the free-molecular-flow regime. The model incorporated effects such as wall temperature and accommodation coefficients, and high aspect ratios were valid until the peak velocity of the vibration reached one-fifth of the gas thermal velocity. Xia and Li (2008) investigated the air drag damping effect of micromachined MCs in different resonance modes on the quality factor, which were operated in ambient air. On the basis of a simplified dish-string model for an air drag force acting on the resonant cantilever, the air drag damping properties of the cantilevers vibrating in torsional and flexural modes were analyzed with theoretic vibration mechanics. It was seen that the damping characteristics of the torsional cantilever resonators were generally better than those of the flexural ones, and the quality factor of the cantilever resonator in a higher-frequency mode was always superior to that in a lower frequency. Lee et al. (2009b) proposed a theoretical approach to predict the dynamic behavior of long, slender, and flexible MCs affected by squeeze-film damping at low ambient pressures. It extended continuum gas damping models, which were originally derived for a rigid oscillating plate near a wall, to flexible MCs for calculating and predicting squeeze-film damping ratios of higher-order bending modes at reduced ambient pressures. Bidkar et al. (2009) solved the quasi-steady Boltzmann equation and computed a closed-form fit for gas damping of rectangular MCs, which was valid over four orders of magnitude of Knudsen numbers (Kn) spanning the free molecular, transition, and low-pressure slip flow regimes. The damping ratio (ζgas,n) and quality factor (Qgas,n) of an MC oscillating in an unbounded gaseous medium in its nth vibration mode were predicted as follows:
where ρc is the MC density and Ac is numerically equal to the MC width times the thickness. The gas damping coefficient, cf, was expressed in terms of two non-dimensional numbers, γ=log10 (κ) and τ=log10 (Kn κ/2), where κ is equal to the MC width divided by thickness in value.
The fundamental working principle for MC sensors is the transduction of analyte adsorption on the MC surface into the mechanical response change of the MC. Up to now, theoretical efforts have been made toward understanding the mechanisms and features of physisorption-induced or chemisorption-induced cantilever behavior (Muralidharan et al. 2003, Dareing and Thundat 2005, Djuric et al. 2007a, Raorane et al. 2008, Yi and Duan 2009, Zhang et al. 2012). In 2005, Dareing and Thundat (2005) proposed a model for adsorption-induced surface stress based on atomic or molecular interaction. The model was tested with Hg adsorption on Au-coated cantilevers, which gave insight into the interatomic forces that play a significant role in creating adsorption-induced surface stresses and resultant mechanical bending of MCs. Djuric et al. (2007a) recently presented the theory of the adsorption and desorption process of an arbitrary number of gases on the MC sensor surface, with the assumption that the sorption followed the Langmuir isotherm. Furthermore, investigation of the possibility of identification of gases in the mixture was carried out on the basis of the power spectral density of the adsorbed mass fluctuations. Also considered was the possibility of lowering the adsorbed mass fluctuations by adding a certain amount of a gas to the mixture. As an example of the application of the presented theory, the fluctuations of the mass adsorbed on the surface of the Si MC sensor surrounded by the atmosphere of two and three gases were calculated. Raorane et al. (2008) used five benzene thiols with different functional end groups as receptors to investigate multiple binding interactions of aromatic vapors, with a conceptual diagram of possible molecular interactions presented (Figure 1). Yi and Duan (2009) first obtained the relations between the adsorption-induced surface stress and the van der Waals and Coulomb interactions in terms of the physical and chemical interactions between adsorbates and solid surfaces. A theoretical framework was presented to predict the deflection and resonance frequencies of MCs with the simultaneous effects of the eigenstrain, surface stress, and adsorption mass. The adsorption-induced deflection and resonance frequency shift of MCs were numerically analyzed for the van der Waals and Coulomb interactions. The theoretical framework quantified the mechanisms of the adsorption-induced surface stress, and provided guidelines to the analysis of the sensitivities and the identification of the detected substances. Zhang et al. (2012) recently presented a theoretical model to investigate both the deflection change and resonance frequency shift of an MC due to covalent chemisorption, with the chemisorption of oxygen on an Si surface taken as a representative example. The connection between the cantilever responses and the molecular-level covalent bond interactions were established. The deflection at the MC free end is
Representative conceptual diagram of possible molecular interactions between aromatic vapors and benzene thiols as receptors. Reproduced with permission from Raorane et al. (2008).
where η is the adsorption density; b and l are the MC width and length, respectively; κ is the curvature of the beam; u is the Keating-type potential function for covalent bond interactions; and E*I donates the effective bending stiffness of the MC. By using Hamilton’s principle, the ith mode resonance frequency of the adsorbate-MC system can be derived as
where β1=1.875, β2=4.649, β3=7.855, β4=10.996, etc. The authors concluded that interatomic chemical interactions played an important role in the mechanical responses of the MCs.
Detection scheme
The detection schemes employed for MC gas sensors can be primarily categorized into optical and electrical schemes. The former includes optical lever and interferometry, and the latter includes piezoresistive, piezoelectric, and capacitance. During recent years, MC gas sensors employing electrical schemes have been reported much more often than optical schemes, while sometimes, both optical and electrical responses of MCs employed for the analysis of gaseous analytes were presented (Seena et al. 2011a).
Optical scheme
The optical lever technique derives from the readout scheme used in AFM systems, in which light is reflected from the back of the MC onto a segmented photodiode or position-sensitive photodetector. The optical lever is currently the most sensitive method for measuring deflection, while it is ineffective when the sample passing the cantilever absorbs or scatters light (Shekhawat et al. 2006). Voiculescu et al. (2006) characterized the surface motion of the MC beam oscillator with a previously developed scanning laser Doppler vibrometer system. The system illuminated the sample surface with light from an argon-ion laser. Scattered light for the sample surface was mixed on the surface of a photodetector, with the frequency-shifted reference light. The photodetector produced a frequency-modulated signal that, once demodulated, was proportional to the surface displacement at a single location. Krause et al. (2008) combined photothermal spectroscopy on an Au-Si bimaterial MC with the mass-induced change in the cantilever’s resonance frequency. The schematic of the experimental setup used for photothermal deflection spectroscopy is demonstrated in Figure 2. Detection using adsorption-induced resonant frequency shift together with photothermal deflection spectroscopy showed high selectivity with a subnanogram limit of detection (LOD) for vapor phase-adsorbed explosives.
Schematic of the experimental setup used for photothermal deflection spectroscopy. Reproduced with permission from Krause et al. (2008).
Since the middle of the last decade, the application of optical levers has been extended to MC sensor arrays by coupling multiple lasers into a layer array, through utilization of sequential reflection of a light beam off each cantilever in the array onto a single detector (Dutta et al. 2004, Senesac et al. 2006, Lang et al. 2007, Long et al. 2009). On the other hand, optical interferometry, which offers higher bandwidth measurement than a simple optical lever, has been introduced as a microelectro-mechanical system (MEMS)-based technique, which shows promise for the readout approach. For MC gas sensors, phase-shifting interferometric microscopy (PSIM) is not dependent on alignment and allows the monitoring of the entire displacement profiles of all MCs in the array, using just one light source. This technique is capable of measuring very small deflections but has a limited dynamic range. Recently, Kelling et al. (2009) and Paoloni et al. (2011) developed a sample cell that could hold multiple MCA chips and allowed for fast and reproducible sensor chip replacement as well as individual or common addressing of all chips in a low-volume sample cell. Eight cantilevers from four different sensor chips could be monitored simultaneously. The prototype bread-board system of the PSIM instrument for the simultaneous monitoring of the displacements of multiple MCAs is demonstrated in Figure 3. Later, with PSIM as the detection scheme, Kelling et al. (2011) built an exhaled breath analysis research instrument, which was used to test sensor surface coatings and develop sensor sets with response patterns suitable for clear correlation to patients’ health condition. At present, the optical (laser) system has been the most widely used detection manner for gas sensors involving MCA, which, however, prevents the MCA gas sensors from further miniaturization of the whole system.
Prototype bread-board system of a PSIM instrument for the simultaneous monitoring of the displacements of multiple MCAs. Reproduced with permission from Kelling et al. (2009).
Electrical scheme
Piezoelectric or piezoresistive materials are widely adopted in MC sensors for characterization of regimes, including pressure, acceleration, strain, or force, by converting them into electrical charge based on the piezoelectric effect. Wang et al. (2005) once studied the effect of direct current (DC) bias voltage on the resonant frequency of piezoelectric MC, with analytic equations suitable for the multilayer structure built, and the laser interference experiment confirmed the equations. A second-order relation between the DC bias and the resonant frequency shift could be reached from both the analytic equations and the experimental results. The resonant frequency measurement could be greatly simplified through DC voltage scanning.
Adams et al. (2005) used a self-sensing, self-actuating, piezoelectric MC to detect adsorption-induced bending. The bending was measured by bringing the resonating cantilever into intermittent contact with a surface, the elevation of which was maintained by a piezotube in feedback. When the cantilever bent, its oscillatory amplitude changes, and the piezotube was adjusted to compensate. For enlarging the bending of the cantilever under surface stress induced by a specific reaction, Li et al. (2006) developed an SiO2 MC sensor that featured much lower Young’s modulus than conventional Si or Si nitride MCs. Thin single-crystalline Si piezoresistors were integrated with the MCs for electric readout, with the piezoresistors fully encapsulated by SiO2 for improving resolution and showing lower leakage-related noise. Wang et al. (2009) reported an Si MC sensor with an embedded n-type metal oxide semiconductor field-effect transistor (nMOSFET) for observing the kinetics of chemical molecules interaction based on the surface stress sensing principle. Figure 4 shows the SEM images of the nMOSFET MC sensor and the common source stage circuit with resistive load used as the measurement circuit. In the sensors, the Si cantilevers with Au coating and the channels of the embedded nMOSFETs were configured along the crystal orientation. The kinetics of and the surface stress from the chemical interactions between acetone, ethanol, nitroethane, and thiol molecules were observed, which followed the Langmuir model. The output signals of the nMOSFET-embedded cantilever sensors induced by various targets were different, which implied that the devices might allow for gaining insights into the kinetics of intermolecular interactions. Zhu et al. (2008) examined the flexural resonance frequency shift of a piezoelectric MC sensor during humidity detection and showed that the flexural resonance frequency shift of the sensor during detection was a result of Young’s modulus change of its piezoelectric layer. Owing to this change, the sensor flexural resonance frequency shift was >300 times larger than could be accounted for by mass loading. Wang (2009) presented a detailed theoretical analysis of the frequency response of a piezoelectric MC immersed in air and excited by an arbitrary driving force, in which a couple stress theory was introduced to the dynamic deflection function of a piezoelectric MC sensor to explain the size effect. Numerical results showed a good agreement with the experiments. Methods for the prediction of the dynamic characteristics of long beam-like microcomponents could be easily derived on the basis of the presented theory, which is of value to users and designers of MEMS.
SEM image of an nMOSFET-embedded MC sensor. The inset displays the common-source stage circuit with resistive load, which was used as the measurement circuit in our experiments. Reproduced with permission from Wang et al. (2009).
The MC beams used for electrical detection are usually fabricated by involving the Wheatstone bridge circuit. In 2005, Voiculescu et al. (2005) presented the design, fabrication, and testing of a resonant cantilever beam in complementary metal oxide semiconductor technology. The design of the cantilever beam included interdigitated fingers for electrostatic actuation and a piezoresistive Wheatstone bridge design to read out the deflection signal. A polymer layer was applied to the surface of the MC beam to enhance its sorptivity to a chemical nerve agent. Gilda et al. (2012) recently presented a new sensitive bidirectional current excitation method for piezoresistive sensor measurements. The authors proposed a circuit that actuated two half bridges connected in the fashion with bidirectional constant current sources. The end points of two arms at one side were disconnected so that the bridge could be driven with two identical current sources, connected at one end of each half bridge. The proposed circuit was insensitive to thermoelectric and stray noise effects, as it measured the peak-to-peak value of the generated voltage. A variation of 40 ppb in gas concentration using piezoresistive SU-8 MCs was measured by the proposed circuit at room temperature. Yoshikawa et al. (2011) presented a membrane-type surface stress sensor based on the piezoresistive readout integrated in the sensor chip. The sensor consisted of an “adsorbate membrane” suspended by four piezoresistive beams, composing a full Wheatstone bridge. The whole analyte-induced isotropic surface stress on the membrane was efficiently transduced to the piezoresistive beams as an amplified uniaxial stress (Figure 5). Evaluation of a prototype membrane-type surface stress sensor used in the experiments demonstrated a high sensitivity with a factor of >20 higher than that obtained with a standard piezoresistive cantilever. Finite element analysis indicated that changing dimensions of the membrane and beams could substantially increase the sensitivity further.
Schematic illustration of the membrane-type surface stress sensor with p-type piezoresistors on n-type single crystal Si(100). Reproduced with permission from Yoshikawa et al. (2011).
Electrical detection schemes used for MCA gas sensors modified with piezoresistive or piezoelectrical materials were reported recently as well (Then et al. 2006, Yoshikawa et al. 2009), although not as popular as MCA gas sensors using optical detection schemes. For instance, Loui et al. (2008) employed readout electronics composed of stacked circuit boards. Each analog board integrated Wheatstone bridge circuits (one per sensor channel), analog-to-digital conversion, and amplification, while a common digital board performed data processing and readout. Zhao et al. (2008) measured the change in the piezoresistance of each coated MC in the array with respect to that of the “blank” reference MC using a Wheatstone bridge circuit. Recently, Kimura et al. (2012) described the detection of volatile organic compounds (VOCs) through analysis of more than one output signal obtained from integrated MC sensor arrays. The resonant frequency changed according to the sorption and desorption processes of VOC at the MC surface, and the resistance changes in the film were simultaneously monitored. The MC sensor produced response isotherms for the frequency and resistance changes that were qualitatively similar to other sensors and microelectrodes. Furthermore, MCA gas sensors employing an electrical detection scheme, despite not being widely used nowadays, will probably become popular in the future especially because of system miniaturization, which is very conducive to the development of portable sensing devices. It is well known that piezoresistive cantilever-based sensors are sensitive to ambient temperature changes due to the highly temperature-dependent piezoresistive effect and mismatch in thermal expansion of composite materials. Thermal drifting caused by the self-heating in piezoresistive MC sensors is a major source of inaccuracy. Recently, Loui et al. (2010a) developed a closed-form semiempirical model to understand the physical origins of thermal drifting. The two-component model described both the effects of temperature-related bending and heat dissipation on the piezoresistance. The temperature-related bending component was based on the Euler-Bernoulli theory of elastic deformation applied to a multilayer cantilever. The heat dissipation component was based on energy conservation per unit time for a piezoresistive cantilever in a Wheatstone bridge circuit, representing a balance between electrical power input and heat dissipation into the environment. Han et al. (2012) proposed a novel method of temperature drift compensation for MC-based sensors with a piezoresistive full Wheatstone bridge integrated at the clamped ends by subtracting the amplified output voltage of the reference cantilever from the output voltage of the sensing cantilever through a simple temperature compensating circuit. It was demonstrated that the temperature drift of MC sensors could be significantly reduced by the method. Ansari and Cho (2012) derived a simple and accurate conduction-convection model to predict the temperature distribution in p-doped piezoresistive MCs because of self-heating. The model was applied to a four-layer Au-coated piezoresistive SiO2 MC biosensor with a U-shaped Si piezoresistor. The analytical results were compared with the numerical results. The effect of the convective heat transfer coefficient on temperature profile was also studied. The comparison results showed that the analytical and numerical results were accurate within 4%. The sensitivity results showed that the resistance change produced by thermal drifting was about five to eight times that caused by the surface stress. Finally, the cantilever temperature profile was found to be strongly affected by the piezoresistor size and the convective heat transfer coefficient. Recent research work on the dynamic behavior of MCs also indicated that the flexural resonance frequencies of piezoelectric MC sensors could be influenced by air in which it immersed as a result of viscous damping effects.
The cantilever can also act as one of the parallel plates of a capacitor, which is also known as the capacitive detection mode, in which MC sensors with capacitive readout are fabricated with good characteristics as gas sensors. As the cantilever deflects, the distance between the two plates changes and this changes the capacitance of the system. Capacitive detection of cantilever deflection is usually employed for the static operation mode, as the MC fundamental resonance can be obscured. Amirola et al. (2005) reported the design and fabrication of a micromachined Si capacitive device and presented application to the VOC detection on the basis of the capacitive variations due to induced differential surface stress. The LODs for the measured gases were below 50 ppm for toluene and 10 ppm for octane. Elliott et al. (2011) reported a fully electrical MC device that used capacitance for both actuation and detection, and showed that it could characterize various gases with a bare Si MC. The motion of the cantilever as it ringed down when the oscillating force was removed, was detected by measuring the voltage induced by the oscillating capacitance in the MC/counter-electrode system. The ringdown waveform was analyzed using an iterative numerical algorithm to calculate the oscillator motion, modeling the cantilever/electrode capacitance to calculate the electrostatic force. After calibration, the viscosity and density of several gaseous mixtures were simultaneously measured.
Fabrication, modification, and functionalization of MC gas sensors
Fabrication
Fabrication of cantilevers is feasible for those researchers with access to proper micromachining facilities, with the employed techniques reported such as lithography (Lee et al. 2009a, Misiakos et al. 2009) and etching (Li et al. 2006). The shape of the cantilever, for most of the time, mainly depends on the mode of detection. At present, most of the MCs employed for MC gas sensors have been fabricated with Si-based materials, including Si, silicon nitride, SiO2, and silicon-on-insulator.
Other than Si-based materials, some organic materials were also employed for MC fabrication. Owing to its simple processing and low Young’s modulus, SU-8 has become a more attractive material used for MC fabrication (Nordstrom et al. 2008, Gilda et al. 2012). For the further development of SU-8 MC fabrication, Seena et al. (2011b) reported a piezoresistive SU-8 nanocomposite MC sensor, with a good dispersion of carbon black (CB) in the SU-8/CB nanocomposite piezoresistor achieved, and an optimal range of 8–9 vol.% CB concentration obtained for improved sensitivity, low device variability, and low noise level. Reddy et al. (2012) later also fabricated an SU-8/CB nanocomposite MC for CO sensing. Zhu et al. (2011) fabricated a polyimide MC for trinitrobenzene sensing. The MC was prepared using a three-mask process. An SiO2 layer was thermally grown on an Si substrate, with a polyimide layer then coated on top. The polyimide was patterned with reactive ion etching using oxygen to form the cantilever structure. A Cr/Au layer was evaporated on the polyimide and patterned using lift-off to form the sensing element. The Si substrate was etched from the back side using a standard deep reactive ion etching process, which ceased when the thermal oxide layer was reached. Finally, the cantilever was released by removing the thermal oxide layer using a buffered oxide etching process. Other inorganic materials were employed for MC fabrication as well. For instance, Lee et al. (2009a) fabricated a cantilever with hexagonally ordered nanowells from anodic alumina through photolithography and electrochemical etching, which was applied to trace moisture sensing.
Moreover, the monolithic integration of MC gas sensors can reduce the sensitivity to external interference and enables autonomous device operation. In 2005, Vancura et al. (2005) presented an electromagnetically actuated resonant cantilever gas sensor system that featured piezoresistive readout by means of stress-sensitive transistors. The monolithic gas sensor system included a polymer-coated resonant cantilever and the necessary oscillation feedback circuitry, both monolithically integrated on the same chip. The fully differential feedback circuit allowed for operating the device in self-oscillation with the cantilever constituting the frequency-determining element of a feedback loop. The combination of magnetic actuation and transistor-based readout entailed little power dissipation on the cantilever and reduced the temperature increase in the sensitive polymer layer. Recently, Zimmermann et al. (2008) presented a monolithic, integrated sensor system architecture that featured MCs operated in the deflection mode. The MCs were coated with polymer layers to detect VOCs, with the analyte-sorption-induced surface stress changes of the MCs detected by piezoresistive Wheatstone bridge configurations embedded in the MCs. The integrated readout circuitry included a chopper-stabilized amplifier, which performed a low-noise, low-offset amplification of the μV-range sensor signal. Misiakos et al. (2009) presented a monolithic photonic MC device comprising light sources and detectors self-aligned to suspended silicon nitride waveguides all integrated into the same Si chip. In this device, a silicon nitride waveguide optically linked an Si light-emitting diode to a detector. Then, the optocoupler released a localized formation of resist-silicon nitride cantilevers through e-beam lithography, dry etching, and precisely controlled wet etching through a special microfluidic setup. Pham et al. (2011b) presented results related to the fabrication of a sensitive mechano-optical MC-based sensor for H2 gas, provided with a selectively gas-absorbing Pd layer, suspended above an Si3N4 grated waveguide. Solutions to address several technical problems encountered during the preparation of the integrated devices, such as grating production, surface roughness, facet quality, etc., were given.
Modification
A few reports demonstrated that plain MCs could achieve some research goals for gas phase sensing. For instance, Tetin et al. (2010) applied the principle that MC resonance frequency shifts on the basis of the density and viscosity of the surrounding gas fluid for the detection of binary gas mixtures using plain MCA. Owing to lack of coating and modification, there were no absorption or desorption phenomena for the analyte-MC interaction, which led to short response time. Moreover, because of low surface area, plain MCs could not achieve high sensitivity for gas phase sensing. To overcome this issue, surface roughening of the MCs could be one solution. Shemesh et al. (2011) employed a method of “reaction-induced vapor phase stain etching” (Stolyarova et al. 2008) to make one plain Si side of MC become more porous. However, for most cases, creation of a film having high surface area (Chapman et al. 2007a, Kapa et al. 2008) or piezoelectric/piezoresistive properties on plain MC surfaces was the most commonly employed approach. Films for MC modification were usually prepared by coating corresponding materials onto MC surfaces through sputtering (Kadam et al. 2006, Li et al. 2006, Yen et al. 2008, Liu et al. 2012), e-beam evaporation (Baselt et al. 2003, Sanghun et al. 2005, Kapa et al. 2008, Krause et al. 2008, Shi et al. 2008), vapor deposition (Dutta et al. 2004, Chapman et al. 2007b, Long et al. 2009), microdropping (Urbiztondo et al. 2009), or dip coating (Yu et al. 2012).
Au film coated on MC surface was early applied to Hg vapor sensing in gas phase based on Au-Hg amalgamation (Rogers et al. 2003, Adams et al. 2005, Kadam et al. 2006), while in recent years it has been used for immobilizing self-assembled monolayers (SAMs) of thiol compounds through Au-thiol chemistry. These compounds either have the sensing sites that could interact with the target analytes (Adams et al. 2005, Raorane et al. 2008) or were used as a linkage to covalently bond other compounds (Paoloni et al. 2011, Hwang et al. 2011) or nanomaterials (Xu et al. 2010, Yang et al. 2011) that have the sensing sites for specific gaseous analytes. Early in the past decade, in order to obtain a higher sensitivity, Au films were first nanostructured into a more “porous” film before being functionalized for liquid phase sensing, with orders of magnitude of response signals increased (Tipple et al. 2002). Otherwise, for gas phase sensing, these nanostructured films were commonly coated with organic responsive phases (Dutta et al. 2004, Long et al. 2009) rather than SAM of sensing sties. It was demonstrated that the sensitivities increased with the thickness of the nanostructured phases or the organic phases within certain thickness ranges. Moreover, it should be noted that for better adhesion of Au films to MC surfaces, a thin layer of other metals such as Cr (Dutta et al. 2004, Li and Li 2006, Krause et al. 2008, Long et al. 2009, Hwang et al. 2011) and Ti (Seena et al. 2011a) were sometimes deposited beneath the Au films.
Oxides of various transition metals have become more attractive for MC modification. Kimura et al. (2012) developed a porous film of TiO2 nanoparticles on an MC surface. The film was subsequently coated with polymer layers, which worked as highly sensitive sensing interfaces to VOC vapor. Alumina recently started to be applied to MC gas phase sensing of ppm-level water moisture (Kapa et al. 2008, Shi et al. 2008). Alumina films coated on MC surfaces were obtained either by oxidizing the coated Al films through anodization methods (Kapa et al. 2008) or by reacting with oxygen at high temperature (Shi et al. 2008). Afterward, Long et al. (2010) developed nanostructured MC surfaces by modifying the active side of the MCs with alumina nanoparticles, with tetramethoxysilane as the cross-linker.
MC modification with other materials such as sol-gel or carbon nanotubes was reported lately as well. Yu et al. (2012) reported a novel top-down/bottom-up combined resonant MC chemical sensor, where the nanosensing sol-gel-based material of a mesoporous thin film was directly self-assembled on the sensing region of the MC. The terminals of sensing sites (-NH2 group) could be simultaneously constructed at the pore inner surface when the mesoporous thin film was grown on the cantilever. The sensor showed quick response and sensitive detection of CO2 through acid-to-base specific reaction. Xu et al. (2010) reported multiwall carbon nanotube (MWCNT)-modified resonant MC chemical sensors for the detection of trinitrotoluene (TNT) vapor. The MWCNTs featuring a high specific surface area were premodified and then self-assembled on the thiol-functionalized Au pad on an MC in which a resonance-exciting heater and a signal-readout piezoresistive Wheatstone bridge were integrated. The MWCNTs were further functionalized with TNT-sensitive groups by grafting onto the sidewalls of the MWCNTs (Figure 6).
The entire process of the MWCNTs for material modification, immobilization on Au surface at the cantilever end, and TNT-sensitive functionalization. Reproduced with permission from Xu et al. (2010).
Functionalization
MCs for gas phase sensing are usually functionalized by either immobilizing a self-assembled mono-/bilayer of receptors or coating a responsive organic/inorganic phase on MC surfaces. Selection of the receptors or phases is highly related to the target analytes. With more kinds of analytes involved in the application scope of MC gas sensors recently, various sensing layers were developed accordingly. For instance, Kooser et al. (2004) used a composite phase of poly(ethylene oxide) (PEO) blended with nickel atoms or clusters to modify MC sensors for CO sensing. The authors believed that the nickel components acted as a catalyst for the carboxylation of PEO by the CO during the sensing process, which also retained much of the physical characteristics of PEO. Zuo et al. (2006) selected a self-assembled bilayer of Cu2+/11-mercaptoundecanoic acid (11-MUA) as a coating to capture organophosphorus molecules. This composite layer could specifically recognize P=O-containing compounds with the formation of a P=O–Cu2+ coordination structure. Seo et al. (2007) coated MCs with three isomers of mercaptophenol SAMs to detect formaldehyde vapor, and found that 3-mercaptophenol-coated MCs showed the largest deflection owing to high reactivity with formaldehyde. When the functionalized cantilever was exposed to interferents, the deflection direction of the cantilever was the opposite of that induced by the chemical reaction with formaldehyde. Yang et al. (2010) functionalized the MC surfaces with an SAM of 11-MUA, which adsorbed trimethylamine (TMA) through hydrogen bonding between the SAM and TMA molecules, and the MC was deflected by the changes in the surface stress as a result of the hydrogen bonding-based chemisorption. Zhu et al. (2011) coated tetrathiafulvalene-functionalized calix[4]pyrrole (TTF-C4P) as a receptor on the MC surface to bind nitroaromatic trinitrobenzene through a combination of π-electron-rich surfaces provided by the TTF subunits and hydrogen bonding interactions provided by the pyrrole NH protons.
Self-assembled mono-/bilayer
Immobilization of an SAM of thiol compounds on Au-coated MC surfaces is most commonly reported for the functionalization of MC gas sensors, with those compounds such as 11-MUA (Li and Li 2006, Zuo et al. 2006, Yang et al. 2010, Yang et al. 2011), benzene thiol derivatives (Seo et al. 2007, Raorane et al. 2008), 4-mercaptopyridine (Yang et al. 2011), and 4-mercaptobenzoic acid (4-MBA) (Pinnaduwage et al. 2003) ever reported. However, unlike MC liquid phase sensing, those thiols were rarely employed as sensing sites but more of a linkage to bind the “real” receptors for target analytes on MC surfaces.
Immobilization of thiol compounds on the surface of Au-coated MCs for functionalization was mostly accomplished in liquid phase, by using dilute solutions. Recently, the interaction between thiol vapor and Au surface in gas phase was investigated. Tabard-Cossa et al. (2007) studied the surface stress response of MC-based sensors as a function of the morphology, with the model of the adsorption of alkanethiol SAMs at the gas-solid interface investigated. It was demonstrated that the average grain size of the Au sensing surface strongly influenced the magnitude of the surface stress change induced by the adsorption of octanethiol. A 25-fold amplification of the change in surface stress was observed on increasing the average Au grain size of the sensing surface. Chapman et al. (2007a) carried out surface thiolation studies by measuring the response of three different MCs coated with 35 nm smooth Au, 50 nm dealloyed Au, and 150 nm dealloyed Au, respectively, to an in situ functionalization with 1 mm propane thiol. Oxidative desorption of the propane thiol from the Au surface through cyclic voltammetry made it possible to quantify the amount of thiol on each surface. It was demonstrated that the greater the degree of roughness and surface crevices, the greater the available surface for thiol immobilization. It was observed that the 50 nm dealloyed Au had greater roughness than the smooth Au, while the thicker 150 nm dealloyed Au seemed to have transitioned from a roughened surface to a more porous one.
Paoloni et al. (2011) prepared receptor-coated MC chips by the “click” reaction. Bis(11-azidoundecanyl)disulfide was used for the formation of azide monolayers on Au surfaces. Individual chips were functionalized by reactions with different alkynes using efficient “click” chemistry, as shown in Figure 7. The surface “click” reaction reduced the effort that would be required to synthesize and purify the corresponding functional thiols. A proof-of-concept sensor composed of four individual MC chips presenting different headgroups could unambiguously discriminate the fingerprint response of a nerve gas simulant from other solvent vapors. Hwang et al. (2011) reported that a peptide could be utilized as a receptor molecule in the gas phase for application in micro-/nanosensors, by using a specific peptide that recognizes 2,4-dinitrotoluene (DNT) at room temperature and in an atmospheric environment. Figure 8 shows the structure of the monolayer and the chemical reactions that took place on the surface to prepare the peptide-presenting monolayer. SAM of a carboxylic acid-presenting monolayer was first formed on the Au-coated MC surface, which was then treated with EDC and aminoethyl maleimide. Cysteine-containing peptides were then covalently anchored on the resulting maleimide-presenting monolayer through Michael addition. Surrounding tri(ethylene glycol) groups prevented non-specific adsorption, ensuring that only specific interactions between DNT and the DNT specific peptide occurred on the surface.
Cartoon representation of the functionalization of surface using “click” chemistry. Reproduced with permission from Paoloni et al. (2011).
Schematic diagram of the surface functionalization process used to immobilize the DNT-specific peptides for gas phase DNT detection. Reproduced with permission from Hwang et al. (2011).
Zuo et al. (2006) presented a chemical sensor for trace organophosphorus vapor detection. A self-assembled composite bilayer of Cu2+/11-MUA was modified on the surface of the sensing cantilever, by immersing an 11-MUA-modified MC surface in CuSO4 aqueous solutions. Experimental results indicated that the sensor could be quite sensitive to dimethylmethylphosphonate (DMMP) vapor, with adsorption of DMMP on the self-assembled composite layer well fit to a Langmuir isotherm model. Chen et al. (2010) proposed a method of directly modifying a siloxane sensing bilayer on an SiO2 surface. A siloxane-head bottom layer was self-assembled directly on the SiO2 MC surface, which was followed by grafting another sensing group functionalized molecule layer on top of the siloxane layer.
Organic/inorganic responsive phase
When gaseous analytes diffuse into the organic responsive phases, which begin to swell, jointly with the mass increase, a change of interfacial stress between the coating and the MC occurs, resulting in MC motions (Battiston et al. 2001). Dong et al. (2010b) recently investigated the effect of the polymer coating location on the sensor’s sensitivity and presented a formula to calculate the polymer-analyte partition coefficient without knowing the polymer coating features. It was concluded that the effective mass of the polymer-coated MC (meff) is in inverse proportion to the square of the amplitude at the coating location (w) based on the equation below:
where ρ, L, b, and h are the mean density, length, width, and thickness of the MC respectively; madd is a small mass loading; and the MC was treated as a line structure where the position of each mass point could be represented by a one-dimensional variable, x (x=0 is set at the fixed end of the MC). The partition coefficient (K) of the polymer layers to different analytes through calibration of the MC gas sensors was estimated with the model deduced as
where ω0 and ωMC are the resonant frequencies of the polymer-coated MC without mass loading and of the bare MC, respectively; Δω≈-0.5ω0 madd /meff; and cgas is the concentration of the gaseous analyte loaded to the polymer layer coated on MC.
MC sensors modified with organic responsive phases have commonly been applied to gas phase sensing (Battiston et al. 2001, Pinnaduwage et al. 2004, Amirola et al. 2005, Vancura et al. 2005, Voiculescu et al. 2005, Then et al. 2006). The phases were usually deposited onto MC surfaces through spray coating (Vancura et al. 2005, Then et al. 2006, Dong et al. 2010a), spin coating (Sanghun et al. 2005), spotting (Loui et al. 2008), dropping (Dong et al. 2010a), inkjet printing (Lang et al. 2007, Yoshikawa et al. 2009), or vapor deposition (Dutta et al. 2004, Senesac et al. 2006, Chapman et al. 2007b, Long et al. 2009). Before deposition, the MCs were usually modified with other inorganic materials, especially piezoresistive or piezoelectric materials, while deposition of organic phases onto plain Si MC surfaces for gas phase sensing was rarely reported during recent years.
Sometimes, traditional organic polymers are dense, impeding analyte uptake and slowing sensor response. Allendorf et al. (2008) integrated a thin film of metal-organic frameworks (MOFs) composed of Cu(II) ions linked by benzenetricarboxylate ligands [Cu3BTC2(H2O)3]n. The results showed that the energy of molecular adsorption caused slight distortions in the MOF crystal structure, which could be converted to mechanical energy to create a responsive, reversible, and selective MC sensor. This sensor responded to water, methanol, and ethanol vapors, but yielded no response to either N2 or O2. Lee et al. (2010) demonstrated the potential of MOFs to provide selectivity and sensitivity to a broad range of analytes, including explosives, nerve agents, toxic industrial chemicals, and VOCs. The nanoporosity and ultrahigh surface areas compared with dense traditional organic phases enhanced analyte transport into and out of the MOF layer, improving response time and selectivity. Venkatasubramanian et al. (2012) recently analyzed the effect of the structural flexibility of MOFs on the MC sensor response. The authors examined the effects of important MOF mechanical properties such as the Young’s modulus, Poisson’s ratio, and density on the sensor response. It was determined that increasing the Young’s modulus and Poisson’s ratio improved the response, while the density of the MOF had a negligible effect on the cantilever response. The authors also examined the influence on cantilever response of the intermediate layer used to bind the MOF, and observed that SiO2 provided the best sensor response for a given MOF layer.
Pd-coated MCs started being applied to H2 sensing years ago (Okuyama et al. 2000, Baselt et al. 2003, Fabre et al. 2003). Recently, in order to overcome the interface sliding between the coated film and the MC surface due to overlying structural expansion of the coating, Yen et al. (2008) employed a sputtering deposition technique to coat Pd film and surface design through trench modification, which benefited superior sensing characteristics for H2 with high sensitivity. Afterward, Patton et al. (2010) reported an MC-based H2 microsensor modified with a nanostructured Pd thin film with short response and recovery time measured for this sensor. A galvanic displacement reaction between the silver film coated on MC surface and PdCl2 solution resulted in the formation of a granular Pd film.
Other responsive phases were reported in recent years as well. Yang et al. (2011) demonstrated that cubic Cu2O crystals with preferred orientation could be grown on MC surface through an electrochemical redox process, which was used for DMMP sensing. The sensing mechanism lies in the complexation of phosphonyl group with Cu(I) that generates surface stress on the MC surface. Urbiztondo et al. (2009) developed a zeolite-coated cantilever used for gas phase sensing. Different cantilever designs (rectangular or paddle shaped) and different methods of zeolite deposition were investigated. Especially for nitrotoluene detection, “co-exchanged BEA” zeolites were deposited on cantilevers by a microdropping method. The exchange with Co increased the affinity of the sensor toward nitrotoluene.
MC differential array
For most MCAs, each MC in the array was fabricated and modified in the same manner before the functionalization procedure in which different analyte receptors or responsive phases were coated onto different MCs (one per MC), with only a couple of exceptions (Lee et al. 2011, Kimura et al. 2012). Several approaches were employed during recent years to accomplish MCA functionalization. Dutta et al. (2004) thermally coated different organic phases correspondingly on different cantilevers (one coating per MC) by using the physical vapor deposition approach. The deposition procedures were carried out in a vacuum chamber with a resistively heated source at a pressure of approximately 10-6 Torr. A slit was used to selectively expose single MCs to accomplish depositing different molecular recognition phases on each single MC. This procedure was used for other MC gas phase sensing purposes years later (Senesac et al. 2006, Chapman et al. 2007b, Long et al. 2009). Long et al. (2010) functionalized the MCA modified with alumina nanoparticles by immersing all MCs in the array in parallel configured capillaries filled with different reagents for immobilizing chemical receptors onto the MC surfaces. An MCA prepared for chemical sensing was exposed to different VOCs. The characteristic response signatures for each VOC analyte showed substantial diversity. Lee et al. (2011) used MCA to investigate the kinetics of CO2 adsorption and desorption over amine-functionalized mesoporous silica. Each MC was coated with specific silica sorbent by using a microcapillary tube, which was filled with suspensions of the sorbents in ethanol. Kimura et al. (2012) also used a microcapillary to prepare an MCA by coating TiO2 porous films covered with different polythiophene layers onto different MCs in the array. Loui et al. (2008) recently experimented with two methods for preparing a polymer-coated MCA. One method used a manually positioned, drop-on-demand jetting device, with three or more drops of polymer solution required, producing visibly non-uniform coatings caused by clogging. The other method used a microarray spotting pin and the polymer coatings were deposited directly onto the cantilever, producing highly uniform films within seconds of solvent evaporation.
Recently, a cell holding more than one MC chip was prepared as a different type of array for MC gas phase sensing. Filenko et al. (2008) prepared an eight-MC-chip cell by bonding eight MCs on double-sided printed circuit boards. Mounted MCs were individually functionalized for particular applications by coating them with specifically selective molecular layers. The eight boards were then placed into the Teflon cantilever cell, as shown in Figure 9. Kelling et al. (2009) developed a sample cell that held four cantilever array chips (each chip with two MCs), allowing for fast and reproducible sensor chip replacement and individual or common addressing of all chips in the sample cell. Of the eight MCs, two were functionalized with alkane thiol, two were coated with a phenolic thiol, and four were coated with a thiol presenting a dichlorobenzene head group. The phenol and dichlorobenzene head groups were prepared by Cu-catalyzed “click” reactions.
Teflon measurement cell holding eight MC chips applicable for either gas single injection or gas flow mode. Reproduced with permission from Filenko et al. (2008).
Selectivity and sensitivity
There have been two common approaches to overcoming the selectivity challenge for MC-based gas phase sensing. The first approach was functionalizing the MCA by covering each MC with a different sensing layer from the other MCs. To maximize this diversity (and possible concomitant discrimination) for MCA sensors, the sensing sites must be carefully selected on the basis of their chemical and physical interactions with the analytes of interest. The selected sites were usually for the purpose of covering a wide range of physical properties or chemical behavior. Generally, it is challenging to elucidate all individual components when they are introduced to MC sensor systems as mixtures, and pattern recognition techniques are helpful in identifying single component, binary mixture, or composite responses of distinct mixtures. The second approach employed a separation technique before MC-based detection. This approach was developed for the purpose of analyzing relatively complex mixtures. The MC sensing device was employed as a substitute for the traditional GC detector.
To achieve the classification and identification of the target analyte, a fingerprint with a diverse response pattern is essential. The diverse pattern can only be obtained from an MCA sensor system, with each MC in the array being able to generate a unique response pattern compared with the other MCs functionalized in different manners, upon the exposure of the MCA to the same analyte. A pattern recognition algorithm employing MCs for gas phase analyte identification has been accomplished by the PCA design or by ANN multivariate data analysis. Using the PCA method, the individual compounds can be distinguished as clusters of points in the PCA plot, each point representing a measurement, and MCA sensors could rapidly recognize previously measured analytes (Then et al. 2006, Lang et al. 2007). For instance, Yoshikawa et al. (2009) evaluated the performance of MCA sensors by using vapors of various alkanes with different chain lengths from 5 (n-pentane) to 14 (n-tetradecane). It was demonstrated that MCA sensors had the selectivity of discriminating individual alkanes in a homologous series as well as common VOCs according to PCA. Loui et al. (2008) rendered the response in a three-dimensional PCA plot (Figure 10), which represented the library of 13 analyte signatures, with each species at a particular vapor concentration corresponding to a spatially distinct cluster in the PCA subspace. Nevertheless, it was also revealed from the PCA data that the mixture responses did not obey linear superposition over the entire concentration range examined. In 2006, Senesac et al. (2006) performed analyte species and concentration identification using an MCA coupled with a back-propagation ANN pattern recognition algorithm for identification as well as quantitation of tested individual analytes and their binary mixtures (Figure 11). Since then, this developed pattern recognition algorithm was applied more than once to the identification and quantification of the components of a ternary vapor mixture while using an MCA-based electronic nose (Pinnaduwage et al. 2007, Zhao et al. 2008, Leis et al. 2010).
Three-dimensional PCA plot of MC sensor array response to 13 gaseous analytes. Reproduced with permission from Loui et al. (2008).
The sequence of five bar plots above displays the output of the ANN in response to the dioxane signature at five stages during training. Each bar plot shows the values of the 11 probabilities corresponding to the 11 analytes being tested. The y-axis is the probability of 11 analytes ranging from 0 to 1 and the x-axis represents the 11 analytes. The fourth bar from the left of each plot represents the analyte dioxane. Reproduced with permission from Senesac et al. (2006).
Chapman et al. (2007b) demonstrated that only three components of a four-component VOC mixture could be identified without mixture separation. To generate a more selective signal, an MC differential array was used to supply a diverse response and analyte-identifying capabilities rather than a single signal peak given by traditional GC detectors. They demonstrated the coupling of a standard packed-column GC with a differential MCA functionalized with responsive organic phases for enhanced selectivity in the analysis of VOCs. VOC mixtures were first separated using a standard GC and then introduced to the MCA for analysis. Studies of operational parameters, including column temperature, column flow rate, and array cell temperature, were conducted.
Recently, Loui et al. (2010b) investigated a new method for detecting and discriminating pure gases and binary mixtures. The approach was based on two distinct physical mechanisms that could be simultaneously employed within a single MC: heat dissipation and resonant damping in the viscous regime. An experimental study of the heat dissipation mechanism indicated that the sensor response was directly correlated to the thermal conductivity of the gaseous analyte. A theoretical data set of resonant damping was generated corresponding to the gas mixtures examined in the thermal response experiments. The combination of the thermal and resonant response data yielded more distinct analyte signatures. Yu and Li (2009) proposed mass loading detection of multiple kinds of analytes with a single resonant MC with experimental validation. By exciting the cantilever in different resonance modes and adsorbing different analytes at different locations of the cantilever, the specific mass of either kind of analyte could be independently detected. Used as simulant adsorbates, Au and Cr thin films were selectively implemented on the cantilever to verify the bianalyte detecting function. The testing results were consistent with the theoretical analysis, with the detection error being an order of magnitude lower than the analyzed mass. This resonant MC sensor might be promising in on-the-spot detecting applications in both gas and liquid phases.
On the basis of the discussion in previous sections, it can be easily concluded that the fabrication, modification, and functionalization of MC chips in appropriate manners are essential for obtaining high sensitivity in MC sensors. Moreover, remolding the sensor system other than focusing on the MC chip might be another option for sensitivity enhancement. Recently, Mihara et al. (2009) combined an affiliated carbon fiber-filled adsorption tube and a temperature-controlled preconcentrator (Mihara et al. 2011) with the MC gas sensors for sensitivity enhancement. The estimated LOD of the sensor system was <1 ppb for toluene and p-xylene. Improvements in the sensitivity were also achieved by the reduction of the volume in the sensor chamber and the enlargement of the resonance frequency of the cantilever using high-speed analog-oscillation circuits and a low-noise package, with the sensitivity enhanced by about 100 times.
Application
Although the current applications of MC gas sensors lie in the analysis of laboratory samples, most of them highly illustrated realistic human concerns such as environmental, health-care, security, energy, etc. This section briefly discusses some representative applications of MC gas sensors followed by a widespread summarization in Table 1.
Summary of recent applications of MC gas sensors.
| Target analyte | Chemicals with sensing sites | Modification materials | Carrier gas | Operation mode | Detection scheme | LOD | References |
|---|---|---|---|---|---|---|---|
| TNT | HFIP | Carbon nanotube | N2 | Dynamic | Electrical | N.R. | (Xu et al. 2010) |
| TNT | p-ABA | SiO2 | N2 | Static | Electrical | N.R. | (Chen et al. 2010) |
| TNT | 4-MBA | SU-8-CB | N2 | Static | Electrical | 6 ppb | (Seena et al. 2011a) |
| Toluene | Polythiophene | TiO2 | N2 | Static | Electrical | Sub-ppb | (Kimura et al. 2012) |
| Toluenea, octaneb | PDMS, PECH | Si | Air | Static | Electrical | <50 ppma, <10 ppmb | (Amirola et al. 2005) |
| Nitrotoluene | Zeolite | Si | N2 | Dynamic | Electrical | 0.5 ppm V | (Urbiztondo et al. 2009) |
| Dinitrotoluene | 4-(2,4-Dinitrophenyl)butan-1-amine | Au | N2 | Dynamic | Electrical | 431 ppt | (Hwang et al. 2011) |
| Trinitrobenzene | TTF-C4P | Polyimide | N.R. | Static | Electrical | 10 ppb | (Zhu et al. 2011) |
| Alkanes | PVA, PEI, PAAM, PVP | Si | N2, Ar | Static | Electrical | Sub-ppm | (Yoshikawa et al. 2009) |
| DMMP | Cu2O | 11-MUA | N2 | Static | Electrical | N.R. | (Yang et al. 2011) |
| DMMPa, NH3b | 11-MUA/Cu2+ bilayer | Au | N2 | Static | Electrical | 10 ppba, 0.1 ppmb | (Li and Li 2006) |
| H2 | Pd | Ag | O2 | Static | Optical | 100 ppm | (Patton et al. 2010) |
| H2 | Pd | Si | N2 | Static | Optical | 30 ppm | (Yen et al. 2008) |
| H2O | Al2O3 | Si | N2 | Static and dynamic | Optical | 1 ppm | (Kapa et al. 2008) |
| H2O | Al2O3 | Al2O3 | N2 | Static and dynamic | Optical | N.R. | (Lee et al. 2009) |
| Cl2 | PDMS-NaI composite | N.R. | Under vacuum | Static | Electrical | 20 ppm | (Porter et al. 2009) |
| CO | Fe(III)porphyrin | SU-8-CB | N2 | Static | Electrical | 2 ppm | (Reddy et al. 2012) |
| HCN | Keratin | Au | Under vacuum | Static | Electrical | N.R. | (Porter et al. 2007) |
| TMA | 11-MUA | Au | N.R. | Static | Electrical | 1.65 μg/l | (Yang et al. 2010) |
| HCHO | 3-Mercaptophenol | Au | Air | Static | Electrical | 0.01 ppm | (Seo et al. 2007) |
| Ethanol | Polymer | Silicon nitride | Synthetic air | Static | Electrical | 250 ppm | (Zimmermann et al. 2008) |
| Ethanol isotope | P4VP | Si | N2 | Static | Optical | N.R. | (Shemesh et al. 2011) |
| Siloxane | AcβCD, Cal-4, Cal-6, PDPP, PEI, Squ, TBATS | Au | CH4, N2, CO2 | Static | Optical | Sub-ppm | (Long et al. 2009) |
AcβCD, heptakis(6-O-tert-butyldimethylsilyl-2,3-di-O-acetyl)-β-cyclodextrin; Cal-4, 4-tert-butylcalix[4]arene; Cal-6, 4-tert-butylcalix[6]arene; HFIP, hexafluoroisopropanol; PAAM, poly-acryl amide; pABA, p-aminobenzoic acid; PDMS, poly(dimethylsiloxane); PDPP, poly(diphenoxyphosphazene); PECH, polyepichlorohydrin; PEI, poly-ethylene imine; PVA, poly-vinyl alcohol; PVP, poly-vinyl pyrrolidone; P4VP, poly-4-vinylpyridine; TBATS, tetrabutylammonium p-toluenesulfonate; Squ, squalane; N.R., not reported in the literature.
Gas flow sensor
Jeung Sang et al. (2006) presented an approach to measure the fluid velocity by using the flow-induced vibration of an MC. The sensor was fabricated and mounted on a printed circuit board, with a Wheatstone bridge circuit prepared for signal processing. The vibrating frequency was constant, independently of the inlet velocity, which was different from the conventional flow-induced vibration. Ma et al. (2009) fabricated and characterized a micro gas flow sensor comprising four silicon nitride/Si wafer cantilever beams arranged in a cross-form configuration, with induced residual stresses in the beams during fabrication, causing each beam tip to curve slightly in the upward direction. As air traveled over the surface of the sensor, the upstream cantilevers were deflected in the downward direction, while the downstream cantilevers were deflected in the upward direction. Both the velocity and the direction of the air flow could be determined by measuring the corresponding change in resistance of the piezoresistors patterned on the upper surface of all four cantilever beams. Lee et al. (2009c) designed and characterized an MC-based flow rate microsensor consisting of a Pt resistor deposited on a silicon nitride-coated Si cantilever beam. As air traveled across the upper surface of the sensor, it interfered with the curved tip and displaced the beam in either the upward or the downward direction, which resulted in a signal change. A microsensor was constructed by arranging eight such cantilever structures on an octagonal platform, with each cantilever separated from its neighbors by a tapered baffle plate connected to a central octagonal pillar designed to attenuate the aerodynamic force acting on the cantilever beams. The sensor was capable of measuring both the flow rate and the flow direction of the air passing over the sensor. Zhang et al. (2010a) presented a curved-up piezoresistive MC flow sensor, which consisted of two layers of SiO2 and an Si piezoresistor in between. The difference in the residual stresses between Si and SiO2 layers curved the MC upward and the free end bends out of plane. The curved-up MC transfers fluidic momentum that acted on it to a drag force, which bent the curved-up MC and changed the resistance of the piezoresistor. This configuration allowed the MC to be integrated in microchannels to measure steady flow. Seo and Kim (2010) developed a self-resonant flow MC sensor based on a resonant frequency shift due to flow-induced vibrations. The vibration of an MC beam, induced by a turbulent flow, was modulated with its own natural frequency, and the resonant frequency was shifted by a surface stress on the beam due to fluid drag force. Liu et al. (2012) developed an MC as an air flow sensor and a wind-driven energy harvester for a self-sustained flow-sensing microsystem. A self-sustained flow-sensing microsystem with an array of similar MCs was able to measure the flow rate of ambient wind by one MC, while the rest were used to scavenge wind energy. The experimental results elucidated the function of using piezoelectric MCs as flow sensors and wind-driven energy harvesters simultaneously.
Keskar et al. (2008) reported the non-linear dynamics of MCs under varying pressure and different gases. The authors exploited non-linearities in the cantilever-counter electrode system to allow electrostatic actuation and detection of the responses of the MC to the pressure and gas composition. The MC demonstrated a quality factor of 10,000 at 10-3 Torr, and a usable response in the range from 10-3 to 103 Torr. The experimental results were in reasonable agreement with theoretical calculations, despite the non-linearities involved. Lee et al. (2007) developed MC-based metrology tools to characterize liquid and gaseous jets generated from microfabricated nozzles. MC sensors fabricated with either piezoresistive elements or integrated heating elements were applied to measure thrusts, velocities, and heat transfer characteristics of micro-/nanojets. Jet velocities estimated from cantilever measurements agreed well with shadowgraphy results.
Laboratory samples
Most analyzed laboratory samples contain target analytes that reflected practical concern about environmental monitoring, health care, safety, etc. Hydrogen-based transportation fuel economy has become attractive, while perceived hazard from H2 gas leaks is always a safety concern. MC gas sensors have been developed for detecting trace-level H2 for the purpose of providing valid alerts for leaks (Baselt et al. 2003, Fabre et al. 2003, Tang et al. 2004). During recent years, Yen et al. (2008) used a Pd-coated MC with trench modification and obtained superior sensing characteristics. Patton et al. (2010) created a nanostructured Pd film on MC surfaces through a galvanic displacement reaction between Pd and Ag. The film could absorb and desorb H2 gas in a fast manner, with short response and recovery time obtained. Zhang et al. (2010b) developed an MC-based sensor with fiber Bragg grating for H2 detection. MC deflection due to H2 detection was measured by the wavelength shift of fiber Bragg grating, with the content of H2 inferred afterward. It was also shown that the sensitivity of the sensor can be improved by changing the thickness ratio of Pd and Si MC. Palm et al. (Pham et al. 2011a,b) demonstrated a proof of concept of a compact integrated mechano-optical sensor for H2 detection based on an MC suspended above an Si3N4 grated waveguide. Besides H2, landfill biogases recently have attracted more interest as a new source of fuel energy, while the usually contained volatile siloxane compounds could increase abrasion of combustion engines. Long et al. (2009) introduced a low-cost and compact method employing MCA for nanomechanical-based sensing of siloxanes. The cantilevers on the MCA were differentially functionalized and exhibited selective signatures of response to aid in siloxane recognition. LODs were down to the sub-ppm range and comparable with GC-MS. Studies were performed in a simulated realistic matrix.
As one of the warfare agents of greatest concern, TNT has always attracted attention in the field of MC-based sensors. Muralidharan et al. (2003) reported the adsorption-desorption characteristics of TNT from an Si MC. It was observed that TNT readily stuck to the exposed Si surface with the adsorption kinetics showing an initial exponential behavior followed by roughly linear kinetics. It was also observed that for cantilever temperatures close to room temperature, TNT desorbed spontaneously from the surface with decaying exponential kinetics. Recently, Xu et al. (2010) applied MWCNT-modified MC sensors for detecting TNT vapors. The MWCNTs were further functionalized by grafting TNT-sensitive groups onto the sidewalls, with the TNT vapor at ppb level detected in a rapid manner, and a long-term reproducibility of sensitivity was observed. Chen et al. (2010), for the first time, modified a siloxane sensing bilayer on the piezoresistor-integrated MCs. A siloxane-head bottom layer was self-assembled on the SiO2 cantilever surface, followed by grafting another layer of explosive sensing group on top. The sensor exhibited a response to 0.1 ppb TNT vapor with no attenuation in sensing signals observed after 140 days. A piezoresistive SU-8 MC was reported for the detection of TNT vapors by Seena et al. (2011b), with a better dispersion of CB in the SU-8/CB nanocomposite piezoresistor obtained. The ability of the sensor in detecting TNT vapor concentration down to <6 ppb, with a sensitivity of 1 mV/ppb, was reported. Another explosive vapor, nitrotoluene, was detected with a zeolite-coated cantilever developed by Urbiztondo et al. (2009). Co-exchanged BEA zeolites were prepared and deposited on cantilevers and the exchange with Co increased the affinity of the sensor toward nitrotoluene. The Co-BEA-coated cantilevers were able to detect nitrotoluene gas phase concentrations <1 ppm. Reliable detection of peroxide explosives and their liquid precursors is needed for aviation security to eliminate the threat of these homemade explosives. Peroxide sensors are also anticipated in industrial applications and leak detection. Lock et al. (2009) reported an MC sensor for the trace detection of peroxide vapors. The sensor featured an SAM that underwent chain polymerization in the presence of peroxide radicals. An SAM of reactive monomers were attached to the MC surface, and the adsorption of peroxide radicals onto the SAM initiated chain polymerization reactions among neighboring monomers, which induced a surface stress on the MC and caused a measurable deflection. The sensor was successfully demonstrated with a selective, self-amplified response, with air and water tested as interferents.
Detection of corrosive or toxic inorganic gaseous analytes with MC sensors was reported during recent years. Primarily based on the reaction between HF and Si or SiO2, MCs made of these materials were selected as a sensor platform for HF sensing (Mertens et al. 2004, Tang et al. 2004). Recently, it was demonstrated that embedded piezoresistive MC (EPM) sensors could provide a simple and robust platform for the detection of various types of gaseous analytes. Porter et al. (2008) used EPM sensors for the detection of HF gas, and these sensors contained a keratin-based compound as the primary sensing material, and exposures to HF within a wide concentration range resulted in nearly immediate response. Later, Porter et al. (2009, 2010) reported the designed EPM sensors functionalized for the detection of Cl2. The EPM sensors were constructed using composite materials consisting of a polymer or hydrogel matrix loaded with agents specific for the detection, such as NaI. These materials were tested in both controlled laboratory conditions and in outdoor releases, with LODs in an outdoor exposure setting of approximately 20 ppm. EPM sensors were also used by Kooser et al. (2004) for detecting the presence of CO gas earlier, with the sensing material of PEO swelling slightly upon CO exposure. For small exposures the sensor was fully recoverable, whereas for very large exposures irreversible chemical changes in the sensing material occurred. In terms of CO detection, Reddy et al. (2012) recently used a piezoresistive SU-8 MC coated with 5,10,15,20-tetra (4,5-dimethoxyphenyl)-21H,23H-porphyrin iron(III) chloride as a CO sensor. Detection of CO down to 2 ppm was achieved, with a fast and fully recoverable response observed after repeated exposures. Moreover, the sensor did not respond to other gaseous analytes, including N2, CO2, O2, N2O, ethanolamine, and moisture. Adams et al. (2005) used a self-sensing, self-actuating, piezoelectric MC to detect adsorption-induced bending caused by Hg adsorption onto Au, with a 50 ppb Hg detected. Kadam et al. (2006) used thermally induced higher-order modes of MC as a detection technique by studying Au-Hg interactions. However, there have been no recent reports of Hg vapor detection using MC sensors during the past few years. As a nerve agent simulant, DMMP is one of the most focused VOCs that have been explored in MC gas sensing (Voiculescu et al. 2005, Li and Li 2006, Voiculescu et al. 2006, Zuo et al. 2006). Recently, Leis et al. (2010) demonstrated that DMMP at ppb levels could be resolved present in a mixture containing water and ethanol at ppb levels. The authors investigated both linear and non-linear approaches, with the linear approach using a separate least-squares model for each component and non-linear approach estimating the component concentrations in parallel. Yang et al. (2011) coated cubic Cu2O crystals with preferred orientation through an electrochemical redox process, for DMMP sensing, with tens of ppb DMMP vapor reproducibly detected. Detection of other harmful VOCs, such as alkanes (Yoshikawa et al. 2009), toluene, and p-xylene (Mihara et al. 2011), by using MC sensors was also reported recently.
TMA has attracted considerable research attention in recent years as an indicator of food freshness, which is produced in the process of microbial decomposition of animal organs and proteins. The volume fraction of TMA increases as freshness decreases. Yang et al. (2010) detected TMA using a piezoresistive MC sensor consisting of two SiO2 layers and a single crystalline Si piezoresistor in between, allowing MCs to achieve high sensitivity because of the low stiffness of SiO2 and the high piezoresistive coefficients of single crystalline Si. The surface of the MC was chemically functionalized with an 11-MUA SAM, and a minimum LOD of 1.65 μg/l for TMA was achieved.
Recent MC moisture sensors were fabricated or modified with alumina. Shi et al. (2008) demonstrated that the alumina-modified MCs could be used to detect low-level moisture with an LOD of 10 ppm and a response time of <3 min obtained. The bending amplitudes were proportional to the moisture level and temperature, and the detection of moisture was not affected by alcohols in the environment. Kapa et al. (2008) tested two types of alumina-modified MCs for-low level moisture detection, with the MC modified through anodization giving better sensitivity. Both static and dynamic modes were tested, with less response time obtained from the latter. Lee et al. (2009a) fabricated alumina MCs by a two-step anodization process for moisture sensing, which had the structure of hexagonally ordered nanowells. The resulting MCs had a large surface area and low modulus.
Separation of gas analytes in mixtures before the detection of MC sensor was reported (Chapman et al. 2007b); however, MC-based analysis of gaseous mixtures was more often accomplished by employing differentially functionalized MCA (Senesac et al. 2006). Zhao et al. (2008) reported the experimental details on the successful application of the electronic nose approach to identify and quantify components in ternary vapor mixtures, using an MCA with seven individual sensors for vapor detection and ANN for pattern recognition. Two vapor systems – one included DMMP at the ppb level and water and ethanol at ppm levels, and the other included acetone, water, and ethanol, all of which were at ppm levels – were studied. Shemesh et al. (2011) presented a novel porous-silicon-over-silicon MC sensor for the isotope discrimination of gas phase substances. A strong isotope effect was observed in the guest-induced MC bending curves of novel poly-4-vinylpyridine-coated MC, and a clear difference in the time-dependent bending response patterns for the isotopologues of ethanol and water was exhibited. The sorption of protiated isotopologues exhibited Langmuir-type sorption curves, while deuterated isotopologues exhibited anomalous bending overshoot curves.
Real-world applications
Lang et al. (2007) used MCA sensors for an artificial nose setup, with each cantilever coated with a polymer layer. A characteristic fingerprint of a specific analyte was obtained and evaluated using PCA. The authors showed examples of analysis of solvents, perfume essences, and beverage flavors as an indication of the presence of diseases in patients’ breath samples. Kelling et al. (2011) developed an MC sensor array readout method based on PSIM and built an exhaled breath analysis research instrument for the Point of Care Diagnostics Development Unit at the University of Leicester, UK. They described a PSIM readout system and the breath analysis instrument that would be used to test sensor surface coatings and develop sensor sets with response patterns suitable for clear correlation to patients’ health condition.
Conclusions and perspectives
MC sensors have become a more attractive technique for gas phase sensing during recent years. Other than common flexure modes, lateral and torsional motions are more often applied to MC gas sensors recently, and it turns out that these operation modes could achieve high mass sensitivity. Analyte adsorption inducing MC mechanical response and the damping effects of gaseous ambiance have been studied deeply, with various models and theoretical approaches presented in recent years. On the basis of those research efforts and correlated research concerns, MC gas sensors with better operation and higher sensitivity could be highly expected in the future.
MC gas sensors employing electrical detection schemes have been thoroughly developed during the past years, in terms of piezoelectrical/piezoresistive materials, sensor fabrication and integration, design of Wheatstone bridge circuit, drift, output signal, and so on. It could be expected that piezoelectric or piezoresistive detection would become the most widely used detection approach for MC gas phase sensing, along with more MC-incorporated prototypes further developed in the future. Moreover, the piezoelectrical/piezoresistive MC sensor has turned out to be a promising candidate for a self-sustained flow and pressure sensing. However, optical detection has more often been applied to MC sensor arrays recently, especially with PSIM becoming a favorite.
MC fabricated with Si-based materials has always been a widespread choice, while other materials with specific and physical properties have attracted more attention for MC fabrication. Varieties of newly developed coatings, responsive phases, or sensing layers have been created on MC surfaces according to the expanding interest scope of gaseous analytes reflecting realistic analytical concerns of humans. Some of those developed MC sensors hold great promise in the future development of MC-based artificial olfactory systems or electronic nose.
The sensitivity of MC gas sensors will probably be further enhanced by remolding the sensing system in the future, such as assembling a “preconcentrator” before MC detection. For selectivity enhancement, various types of MC sensor arrays have been developed since the last decade. Pattern recognition algorithms such as PCA and ANN have been widely employed for the analysis of binary or tertiary mixtures by using MCA, while hyphenating a separation technique before MCA detection can be another option. Although the separation-MCA coupling technique still needs further development, in the future it might be a promising approach for the analysis of more complex real samples, which, however, is still out of the current research scope of MC gas sensors.
About the authors
Dr. Zhou Long received a BS in Chemistry from Sichuan University of China under the supervision of Dr. Xiandeng Hou, and a PhD in Analytical Chemistry from The University of Tennessee, USA (advisor: Dr. Michael J. Sepaniak) in 2010 when he started working as a postdoctoral research fellow with Dr. Sepaniak and was also affiliated with Oak Ridge National Laboratory. Currently, he is an Assistant Professor of Analytical Chemistry at Sichuan University of China, and his research interests include miniature bio/chemical sensors, analytical atomic spectrometry, and bio/chemical separation.
Dr. Michael J. Sepaniak received a PhD in Analytical Chemistry from Iowa State University in 1980. He joined the faculty of the University of Tennessee in 1981 and has also been affiliated with Oak Ridge National Laboratory since that time. His research interest in Analytical Chemistry broadly spans chemical separations, laser spectroscopy, sensor development, and nanoscience and technology. He has directed the research of approximately 20 post docs, 70 graduate students, and has over 190 peer-reviewed publications.
Dr. Xiandeng Hou received his PhD in Chemistry from University of Connecticut under the supervision of Dr. Robert G. Michel in 1999. After two periods of postdoctoral research experience with Dr. Bradley T. Jones at Wake Forest University, he joined the Faculty of Chemistry of Sichuan University, Chengdu, China. He is now a Professor of Analytical Chemistry, and the Director of the Analytical and Testing Center of Sichuan University. His main research interest lies in spectral analysis. He has authored and coauthored over 130 publications, and is on editorial boards of several international journals of analytical spectrometry.
The authors gratefully acknowledge the financial support from the National Natural Science Foundation of China through grant no. 21205083, Sichuan University of China (no. 2011SCU11070), and the US National Science Foundation.
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