Article pubs.acs.org/ac
Chemical Sensor Based Upon Stress-Induced Changes in the Permeability of a Magnetoelastic Wire Nahla A. Hatab,† Nichole A. Crane,†,§ David K. Mee,‡ L. Neville Howell, Jr.,‡,# Larry R. Mooney,‡ Russell L. Hallman, Jr.,‡ Michael J. Sepaniak,† and Vincent E. Lamberti*,‡ †
Department of Chemistry, University of Tennessee, Knoxville, Tennessee 37996-1600, United States Consolidated Nuclear Security, LLC, Y-12 National Security Complex, P.O Box 2009, Oak Ridge, Tennessee 37831, United States
‡
ABSTRACT: We introduce a chemical sensing technology, named ChIMES (Chemical Identification through MagnetoElastic Sensing), that can detect a broad range of targets and that has the capability of untethered communication through a metallic or nonmetallic barrier. These features enable many applications in which penetrations into the sampled environment are unwanted or infeasible because of health, safety, or environmental concerns, such as following the decomposition of a dangerous material in a sealed container. The sensing element is passive and consists of a target response material hard-coupled to a magnetoelastic wire. When the response material encounters a target, it expands, imposing mechanical stress on the wire and altering its magnetic permeability. Using a remote excitation-detection coil set, the changes in permeability are observed by switching the magnetic domains in the wire and measuring the modifications in the Faraday voltage as the stress is varied. Sensors with different response materials can be arrayed and interrogated individually. We describe the sensor and its associated instrumentation, compare the performance of several types of wire, and evaluate analytical metrics of single and arrayed ChIMES sensors against a suite of volatile organic compounds.
R
absence and presence of a target, and a photograph of several sensors mounted on a stiff fiber. Amorphous magnetoelastic wires are available commercially and contain one or more ferromagnetic elements, one or more glass-forming elements, and sometimes small amounts of other elements like Cr, Mn, Al, Cu, or Nb for enhancement of mechanical, magnetic, or anticorrosive properties.7 The wires are manufactured by rapid solidification techniques, resulting in large radially directed residual stresses and stress-induced anisotropies. These structural features couple with magnetostriction in the wire to produce a variety of properties that are attractive for sensor applications. Fe−Si−B and Co−Si−B wires with large positive and negative magnetostriction, respectively, exhibit magnetic bistability; while Co-rich Co−Fe−Si−B wires with vanishing magnetostriction, like those used in this work, are very soft and display giant magnetoimpedance.8 The wires generally are considered to have a domain structure consisting of a single axially oriented core domain surrounded by many shell domains; the magnetization in the shells is radial in positive-magnetostriction wires and circumferential in zeromagnetostriction wires. Jiles,9 Vázquez and Hernando,10 and Squire11 et al. have described the domain structures of magnetic microwires, and these and other authors12−14 have discussed applications.
ecent advances in materials science, photonics, and microelectromechanical systems have led to the development of many innovative chemical sensors, with principles of detection based on quartz-crystal microbalances,1 surface acoustic waves,2 microcantilevers,3,4 flexural plates,5 and various optical absorbance and fluorescence techniques.6 Nearly all of these sensors, like their predecessors, require a mechanical or an electrical connection between the sensing element and the control and reporting components of the device, making them unsuitable for applications in which penetrations into the sampled environment are unwanted or infeasible because of health, safety, or environmental concerns. In this article, we introduce a gas sensor that can be applied to many kinds of targets and can be queried through both metallic and nonmetallic barriers. The technology, named ChIMES (Chemical Identification by Magneto-Elastic Sensing), relies on detection of stress-induced changes in the magnetic permeability of an amorphous magnetoelastic wire. The stress is imposed by a “target response material” (TRM) that is hardcoupled to the wire and significantly expands upon reaction with certain kinds of molecules. Using a remote excitationdetection coil set, the changes in permeability are observed by switching the magnetic domains in the wire and measuring the modifications in the Faraday voltage as the stress is varied. Measurable changes in permeability occur when the wire has been extended by a few percent in the axial direction. Figure 1 displays a schematic of the sensor, depictions of a TRM in the © XXXX American Chemical Society
Received: January 10, 2017 Accepted: June 8, 2017
A
DOI: 10.1021/acs.analchem.7b00120 Anal. Chem. XXXX, XXX, XXX−XXX
Article
Analytical Chemistry
Baimpos28 et al. reported that a Metglas ribbon coated with Bayhydrol-110 exhibits enhanced selectivity toward o-xylene and p-xylene among a group of eight volatile organic compounds (VOCs). In a somewhat different approach, Stoyanov29 et al. described a device consisting of an array of ferromagnetic thin-film structures attached to a polymer that swells or shrinks in response to a target. The deforming polymer expands or diminishes the distance between the magnetic films, changing their magnetostatic coupling and switching behavior. Atalay30 et al. demonstrated that the resonance frequency of a freestanding bare Fe77.5Si7.5B15 wire decreases with increasing viscosity of a surrounding liquid; and 31 ́ Zhukov, Vázquez, and Garcia-Beneytez built a “magnetoelastic pen” that can be used to represent a signature as a characteristic series of stresses. Dimogianopoulos32 recently reviewed patents related to the magnetoelastic property, with emphasis on sensors and energy harvesters. Compared with devices that rely upon changes in the resonant frequency of a magnetoelastic foil, the sensors described here should exhibit better communication through solid barriers, since they operate at a much lower frequency (see below in the Instrumentation section). Also, they have greater potential for miniaturization, since the wire is smaller than the foil and does not need to be mounted in a manner that will permit free vibration. On the other hand, the resonancebased detection mechanism may offer more reproducibility than the permeability-based method, and the amount of response material needed to coat a foil is substantially less than that required to fabricate a ChIMES sensor body. Because ChIMES sensor bodies contain just two components (and epoxy), they are much simpler than radio frequency identification (RFID) tags,33,34 which incorporate memory, radio chips, and antennas. ChIMES sensors can be interrogated through both solid metallic and nonmetallic barriers, while RFID devices can communicate only through dielectric materials. However, an RFID tag can be read over much longer distances, with much less angular dependence, and it can store kilobytes of data as well as a unique identifier. In addition, RFID tags can be manufactured with size profiles substantially smaller than a ChIMES sensor body; for example, the Murata HF MAGICSTRAP has dimensions of 3.2 mm × 3.2 mm × 0.7 mm. In the remaining parts of this paper, the new sensor technology is described in detail and several aspects of its performance are presented. In the next section, the main features of the commercial wires and TRMs that have been used to build devices are summarized; the sensor fabrication process is outlined; and the electronics and instrumentation packages are described. Then, the results of experiments characterizing the stress sensitivities of the wires and the responses of a sensor array toward eight common VOCs are discussed.
Figure 1. (A) Schematic of the ChIMES sensor. (B) Exposure to analyte causes the TRM to swell, imposing axial stress on the magnetoelastic wire. (C) Photograph of four sensors mounted on a stiff fiber.
Conceptually, a sensor can be built for any target for which a suitable TRM can be found. TRMs can come from many classes of chemical and biochemical compounds. TRMs with strong affinities for specific targets, like aptamers15 and antibodies,16 can be used individually, while TRMs with distributed selectivity, such as chemically diverse polymers and polymer composites, can be formed into multisensor arrays. The TRMs are chosen to exploit a broad range of structural, physical, and chemical interactions, including the Keesom, Debye, and London forces; donor and acceptor Hbonds; and orientation, steric, coordination, and ion exchange effects. These interactions have been discussed in detail by Karger, Snyder, and Horvath17 and by Miller.18 The extent of swelling in a TRM can be understood by considering the added molecular volume of the target as well as the conformational changes induced in the TRM by the target.4 For an array of sensors, the collection of responses provides a unique signature, and a machine-learning tool can be taught the pattern corresponding to a specific target. While ChIMES signatures are not based on fundamental molecular properties like the oscillator strengths measured through FT-IR, they are targetdistinctive when coupled with appropriate data analysis techniques. If the TRMs are modular and interchangeable, one device will be adaptable to many applications. Magnetoelastic materials have been used in many other sensor technologies, but, to our knowledge, the detection mechanism described here has not previously been reported. Grimes19−21 et al. described many variations of a magnetoelastic chemical sensor in which the principle of detection is based on changes in the resonant frequency of an amorphous ferromagnetic foil. The devices operate in the kilohertz or megahertz range. The modifications in resonant frequency are caused by uptake of chemical or biological analytes by a response material coated on the foil. The targets of these devices include humidity,22 ammonia,23 carbon dioxide,24 Salmonella typhimurium,25 glucose,26 and Bacillus anthracis.27
■
EXPERIMENTAL SECTION Magnetoelastic Wire. Most of the experiments reported here were performed with Co−Fe−Si−B “SENCY DC2T” wires of two diameters (30 and 100 μm) fabricated by Unitika, Ltd., of Japan. (Unitika does not publicize the full compositions of its products.) According to the manufacturer, these wires have high permeability (∼10 000 at 10 kHz), very low coercivity (0.06 Oe), and nearly zero magnetostriction. SENCY wire is produced by directing a jet of molten alloy into a layer of cold water in a rotating drum.35,36 A few early B
DOI: 10.1021/acs.analchem.7b00120 Anal. Chem. XXXX, XXX, XXX−XXX
Article
Analytical Chemistry experiments were performed with Co80.9Fe4.4Nb4.5Si8.7B1.5 wires obtained from Melt Extraction Technology (MXT) of Montreal, Canada. These wires have diameters in the range 30−40 μm, and they are manufactured using a technique in which an alloy rod with a tapered end is inductively heated and a sharpened wheel is used to extract the melt from the tip.37 In addition, a few sensors were constructed with high-strength 50μm-diameter Co−Fe−Cr−Si−B “BOLFUR DE10” wire, also provided by Unitika, but these devices exhibited poor performance and rapidly were abandoned. Sensor Fabrication. As the sensor was being developed, several ways to couple the wire to the TRM were investigated. Of these, the method that gave the best results comprised threading the wire through a channel drilled through the long axis of a TRM cylinder, prestressing it to a small amount, and then attaching it at both ends of the cylinder with epoxy. The step-by-step procedure follows: (1) Fabricate a 1 cm-diameter TRM disk using a 12-ton Carver benchtop laboratory press. In some cases, the TRMs are moldable in their pure forms; in others, various mechanical composites are needed to minimize friability. (2) Using a Dremel tool, cut a TRM mini-rod from the disk measuring slightly larger than 13 mm in length. (3) Drill a central 0.5 mm channel axially through the mini-rod. (4) With the bit in the channel, grind off excess material with the Dremel tool to reduce the diameter and length of the mini-rod to 4 and 13 mm, respectively. (5) Laterally drill multiple 0.5 mm-diameter holes into the mini-rod to enhance permeation of analyte. (6) Thread a magnetoelastic wire through the channel and attach one end with epoxy. (7) After the epoxy dries, load the other end of the wire with 1 g-force for 30-μm wire and 5 gforce for 100-μm wire. (8) Epoxy the second end of the wire in place and cut off excess wire. (9) Mill a groove along the long side of the mini-rod. (10) Epoxy a stiff fiber into the groove using a minimum amount of adhesive. The size of the sensor body produced by this scheme represents trade-offs in both length and diameter: The size of the switching signal increases with the length of the wire, but the sensors in an array must be short enough to be magnetically isolated within the confines of the coil set. Also, the rate of response increases with decreasing sensor diameter, but the TRM must be thick enough to have sufficient compressive strength to impose stress on the wire. Instrumentation. In the current benchtop system, the sensors are interrogated by a LabVIEW-controlled electronics package. The control system is shown schematically in Figure 2 along with the gas sampling and delivery system, which includes an optional cryogenic concentrator. Exposures to the target are done in a 6.35 mm-o.d. Pyrex flow tube tightly mounted within a concentric excitation-detection coil set. The flow cell is thoroughly purged with dried air before measurements are begun. The dried air is obtained by forcing compressed room air through an inline desiccator containing Drierite. (For a fielded sensor, several standard drying methods can be used, but selective removal of water from a sample may be difficult.) During an experiment, a drive coil imposes an alternating magnetic field on the wire to switch its ferromagnetic domains, and an adjacent detection coil picks up the Faraday voltage created by the variations in magnetic flux. The drive coil has 2556 turns of 24-gauge copper wire, a length of 245 mm, and a magnetic induction per unit current of 13.1 mT A−1; the current in the coil typically is 1.4 App at 25 Hz. A “cancellation coil,” reverse-wired in series with the detection coil, nullifies the strong drive field within the detection coil. In addition, if
Figure 2. ChIMES instrumentation and gas sampling systems.
multiple wire-TRM assemblies are present in the flow tube, a direct-current bias coil compensates for the tendency of all wires to switch at the same time and appear as a single sensor. The bias coil consists of 640 turns of 18-gauge copper wire, and it is wrapped so that the spacing linearly increases toward the center of the solenoid and the winding direction reverses at the midpoint. This configuration provides an additional magnetic field, with strength linearly varying along the length of the flow tube, which causes the switching time of each sensor to depend upon its location in the array. There are no physical or electrical connections to any of the units in the array. Figure 3A shows the magnetic switching signals obtained from a linear array of four sensors. The data are given in units of current in the detection coil, since by using a current (lowimpedance) rather than a voltage (high-impedance) amplifier, it is possible to ignore the capacitance in the cable connecting the coil set to the instrumentation package. If a voltage-based measurement were performed, the cable capacitance would adversely affect the frequency response. There is one positive and one negative pulse for each wire, corresponding to the oscillations of the magnetic domains as they follow the excitation field. The frequency of the switching signal is of the order of 10 kHz. During data processing, the absolute values of the heights of the positive and negative switching signals are averaged, and the response of a sensor is reported as the difference between the averages obtained in the absence and presence of imposed stress. One thousand cycles are averaged for each reported current value. The present configuration includes only the thin Pyrex wall between the coil set and the sensor array, but it is possible to interrogate the sensors through more substantial metallic and nonmetallic barriers. Early experiments with a larger coil set and longer wire (75 mm) were performed through aluminum barriers as thick as 12.7 mm. The electromagnetic fields generated during a measurement decay exponentially in the barrier, and the magnitude of each field drops to (1/e) of its incident value within one penetration depth (δ).38 If the barrier is a poor conductor, δ ≈ (2/σ)(ε/μ)1/2, in which σ, ε, and μ are the electrical conductivity, absolute permittivity, and absolute permeability of the barrier, respectively. For materials like Pyrex, the penetration depth is much larger than a meter, so the C
DOI: 10.1021/acs.analchem.7b00120 Anal. Chem. XXXX, XXX, XXX−XXX
Article
Analytical Chemistry
similar figures illustrating the effect of tensile stress on the hysteresis loop of Fe77.5B15Si7.5 amorphous wire. Exposures and Calibrations. In the next section, responses toward eight VOCs are presented. The VOCs include HPLC-grade methanol (MeOH), ethanol (EtOH), tetrahydrofuran (THF), acetone (ACON), toluene, hexane, trichloroethylene (TCE), and acetonitrile (ACN). The sensors used in these experiments were constructed from 100-μm SENCY wire and TRMs fabricated from the following materials, either neat or as mechanical composites: poly(ethylene oxide) (PEO), methyl cellulose (MC), heptakis(6-Otert-butyldimethylsilyl-2,3-di-O-acetyl)-β-cyclodextrin (CD), 4tert-butylcalix[6]arene (Cal[6]), and poly(methacrylic acid) (MAA). These TRMs have a variety of recognition properties, and many of them have been used as coatings in microcantilever-based sensors.3,4 PEO is a basic polymeric ether that can act as an H-bond acceptor, and MC is a polymeric sugar that can both accept and donate H-bonds; both have modest polarity. CD is a macrocyclic sugar that has hydroxyl groups substituted with nonpolar alkanes; it has a teacup shape and forms size-selective inclusion complexes with targets. Cal[6] is a macrocyclic phenolic compound, with moderate polarity, that has aromatic rings and hydroxyl groups available for interaction with targets. Like CD, Cal[6] provides size selectivity but has a more flexible basket shape. Finally, MAA is acidic, with high polarity, and it can both accept and donate H-bonds. It was found that PEO and MC could be pressed into sturdy sensor bodies in their neat forms, but the others needed to be composited. Because all TRMs showed sensitivity toward moisture, they were stored in a desiccator (10% RH) when not in use. All TRM materials were obtained from Sigma-Aldrich, with purities ≥99.5%. Exposures were made at two or more concentrations for most of the VOCs; in addition, TCE calibration curves were obtained for sensors fabricated from MAA-PEO and CD-PEO. For each VOC, the headspace concentration was established by transferring 20 mL of the liquid to a 500 mL HPLC bottle, purging the capped bottle with dried air for 15 min, and then allowing equilibrium to develop for 15 min. To create a 50% dilution, 300 mL of the headspace gas along with an equal volume of dried air were injected into an SKC gas-sampling bag. A volume of 300 mL of this mixture then was used to prepare a 25% dilution in a new bag in the same manner, and so on. Separate syringes were used to transfer analyte and dried air. For the calibration experiments, the gas sampling system of the test bed was reconfigured to accommodate two programmable single-syringe pumps (New Era Pump Systems, Inc.; model NE-1000), one for analyte and the other for dried air. The standard disposable syringes for these pumps are manufactured from laboratory-grade polypropylene and polyethylene. These syringes were suitable for all VOCs except trichloroethylene; for TCE, it was necessary to use glass syringes to avoid reaction. The pump controllers were set to equal flow rates of 300 mL h−1. For each set of exposures, dried air was streamed through the flow cell for 15 min to establish a baseline, and then the analyte and dried air were alternated at recurring intervals. In most cases, the TRMs required an initial “conditioning” exposure before they would provide reproducible responses. After the experiments at each concentration were concluded, the analyte syringe was rinsed with dried air and the next dilution of analyte.
Figure 3. (A) Magnetic domain switching signals from a 4-sensor array. (B) B−H curve for a 100-μm-diameter SENCY wire, showing the effect of axial loading on permeability.
feasibility of a measurement mostly depends upon the strengths of the excitation and response fields. If the barrier is a good conductor, then δ ≈ (πνσμ)−1/2, where ν is the frequency of the field. For aluminum 6062 and typical cold-rolled steel at 20 °C, the penetration depths are about 16 and 38 mm, respectively, for measurements made at 25 Hz, indicating that attenuation in the barrier also is a concern. (Metal storage drums are often manufactured from cold-rolled steel.) The penetration depth can be increased by working at a lower frequency, at the cost of a longer measurement time. Note that the expression for δ for a poor conductor does not depend upon frequency. The present instrument set also provides the capability of estimating the magnetic hysteresis curve of the wire at different levels of imposed stress. In this calculation, the magnetic field (H) is taken as the excitation signal and the magnetic induction (B) is obtained from the area under the current spike. Figure 3B illustrates the displacement of the B−H curves of a 16 mm length of 100-μm-diameter SENCY wire when the axial load is increased from 5 to 150 g-force. The changes in the slopes of the curves reflect the change in the permeability of the wire. The initial stress value corresponds to the preloading imposed upon the wire when it is mounted inside a TRM. The wire was tested as received, except for having lengths of monofilament glued to both ends. During testing, one of the monofilament strands was fixed to locate the wire at the proper measurement position inside the (horizontal) flow tube, and the other was attached to a roller and calibrated-mass system that applied the force along the axis of the wire. Zhukova39 et al. have published D
DOI: 10.1021/acs.analchem.7b00120 Anal. Chem. XXXX, XXX, XXX−XXX
Article
Analytical Chemistry
sensitivity to small amounts of stress is relatively low. In contrast, the 50-μm BOLFUR wire exhibits the largest responses to small loads, but its response curve rapidly levels at loads above the 10 g-force. The 30-μm MXT wire displays a linear response curve for small loads (≤20 g-force) and relatively low noise; in addition, its responses have the opposite direction from those of the 100-μm SENCY and 50-μm BOLFUR wires. The 30-μm SENCY wire is the least usable of the group, since its response curve inverts at axial forces above 20 g-force. (Repeated tests with the same wire indicated that the inversion is reversible.) The causes of the different behaviors are not known at this point. Figure 4B displays the mildly nonlinear relationship of detection-coil current and axial load in a 16 mm-long section of 100-μm-diameter SENCY wire. Figure 5 presents the responses of ChIMES sensors toward trichloroethylene and acetone. Figure 5A compares the responses of two sensors with different TRMs toward mixtures of TCE and dried air containing from 100 to 0.39% of TCE’s room-temperature headspace (HS) concentration. The TRMs were fabricated from 40% MAA−60% PEO and 40% CD−60% PEO composites; both sensors had 100-μm SENCY wire. The exposures were performed for 10 min, with intervening periods of 20 min, and the concentration of analyte was halved from one exposure to the next. The offset in the baselines of the two sets of peaks reflects different levels of initial stress in the sensors. The response of the MAA-PEO sensor toward the HS concentration is beginning to clip near the end of the exposure period, which probably is due to off-axis expansion of the TRM, elastic deformation of the TRM or epoxy, or nonlinear partitioning of the analyte into the TRM. The data shown in Figure 4B indicates that the clipping did not result from extension of the wire beyond its elastic limit, and irreversible changes to the sensor were not observed. Exposures to analytefree carrier gas produced no response. Figure 5B displays TCE calibration curves for the MAA-PEO and CD-PEO sensors. The points in the two plots represent the responses over the initial 5 min intervals of the 10 min exposure periods. The different slopes of the plots demonstrate different sensitivities of the sensors to TCE, with the MAA-PEO sensor exhibiting the greater sensitivity. Overall, the curves display very good linearityif the zero point is included, the correlation coefficients (r2) for first-order least-squares fits to the data are 0.9948 and 0.9964 for MAA-PEO and CD-PEO, respectively. The limit of detection (LOD) for each TRM was estimated by extrapolating the response at the lowest tested concentration to the equivalent of two times the standard deviation of the baseline noise; for MAA-PEO and CD-PEO, the values are about 350 and 1500 ppm, respectively. The LOD reflects the minimum amount of analyte necessary to expand the TRM enough to result in a measurable change in the permeability of the wire. The sensitivity could be improved with TRMs that exhibit larger volume increases per unit of absorbed analyte or enhanced expansion in the axial direction. Sensors like those used in the experiments reported here typically give reproducible results for at least 6 months. The schematic of the gas delivery system includes an inline cold trap (Figure 2). Use of the trap is optional (the results presented so far were obtained without it), but it can significantly improve the sensitivity. Figure 5C presents the results of three attempts to detect low concentrations of acetone vapor in dried air with MAA-PEO and CD-PEO sensors. The first two sets of plots in the figure demonstrate that the sensors can detect 0.2% of the headspace concentration
Figure 4. (A) Responses of four types of magnetoelastic wire to various axial forces (in units of gram-force). (B) Detail of the detection-coil currents induced in a 100-μm-diameter, 16 mm-long SENCY wire. Error bars are smaller than the points.
Using a type-T thermocouple mounted within the flow cell, the temperature dependence of a sensor fabricated from 40% CD−60% PEO was determined to be about 0.3 μA K−1. The temperature was controlled here with a standard heat gun. This result suggests a means for accounting for temperature variations during a measurement: if a temperature-calibrated sensor in an array were coated with a material that prevented reaction with analyte, it would function as an in situ thermometer.
■
RESULTS AND DISCUSSION Four aspects of the performance of the sensor are discussed in this section. Beginning with the characteristics of the amorphous magnetoelastic wire, Figure 4A presents the results of experiments in which the responses of four types of bare wire were measured under axial forces of 5, 10, 20, 30, 40, 50, and 100 g-force. For 30-μm-diameter wire, these forces correspond to tensile stresses of 69.4, 139, 277, 416, 555, 694, and 1390 MPa, respectively; for 50-μm-diameter wire, the stresses are 25.0, 49.9, 100, 150, 200, 250, and 499 MPa; and for 100-μmdiameter wire, they are 6.24, 12.5, 25.0, 37.5, 49.9, 62.4, and 125 MPa. The forces were applied in the same manner as described above for estimating the B−H curve of a wire under different loads. Recall that the response of a wire refers to the difference between the average switching signal heights in the absence and presence of imposed stress. Of the four varieties of wire, the 100-μm SENCY brand displays the least noise and the greatest linearity between response and stress, although its E
DOI: 10.1021/acs.analchem.7b00120 Anal. Chem. XXXX, XXX, XXX−XXX
Article
Analytical Chemistry
Figure 6. Responses of a four-sensor array to a suite of eight VOCs. The TRM compositions are given at the top.
the solubility limit of the analyte in the TRM. Clipping is apparent in the responses of the MAA-PEO sensor toward several of the neat VOCs. For a specific VOC, the amount of noise in the response is strongly dependent on the choice of TRM. Normalizing to the response ranges of the TRMs, the typical noise level is less than 1% for MAA-PEO, a few percent for Cal[6]-MC and CD-PEO, and as much as 8% for PEO. To help visualize the discrimination of the headspace concentrations of the VOCs by the present set of TRMs, principal components (PCs) were constructed in the sevendimensional space defined by the initial rising and descending slopes of the response curves.40 (The falling slopes from the MAA-PEO sensor were not included because of the clipping of the waveforms.) Using TableCurve 2D v5.01, the slopes were calculated from the derivatives of low-order polynomials fitted to the data. The PC computations were done with Matlab R2016b. Before the PCs were determined, the data were meancentered and subjected to various scaling procedures [auto, range, Pareto, variable-stability (VAST), and level].41 The PCs were obtained as the eigenvectors of the covariance matrix. Overall, the best separation of the VOCs is provided by Pareto scaling; that is, scaling by the square root of the standard deviation.41 This preprocessing technique tends to reduce the relative importance of large values. After Pareto scaling, the first four PCs contain 93.4, 3.2, 2.1, and 0.9% of the variance, respectively, totaling 99.6%. Given the noise levels discussed above, at most two PCs should be retained. Figure 7A displays a score plot for PC 2 vs PC 1. The eight VOCs are separated to varying extents along PC 1. At slightly below 0.1 on this axis, the points representing hexane, toluene, and ethanol form a tight cluster. Hexane and toluene are the only pure hydrocarbons in the test set, the former being aliphatic and the latter aromatic, and ethanol has the longer hydrocarbon chain of the two alcohols. Closer to the origin, TCE, the only halocarbon, and methanol, the smaller of the two alcohols, are near neighbors. The remaining three solvents are well separated from the two groupings and from each other. These include the only ether (THF), the only nitrile (ACN), and the only ketone
Figure 5. (A) Responses of two sensors to various concentrations of TCE vapor, given as percentages of the headspace concentration. Both sensors were built with 100-μm SENCY wire. (B) Calibration curves calculated from the data in panel A. (C) Use of the cold trap can significantly improve the LOD for acetone (HS = head space, B = blank, T = trap, P = purge).
of acetone without trapping, but not 0.02%. However, both sensors respond when the more dilute mixture is trapped for 20 min at −80.0 °C and then purged at 40 °C. The response toward the purged sample from the MAA-PEO sensor is more than 2.5 times as strong as the response from the CD-PEO sensor. Figure 6 displays the responses of four sensors toward all eight VOCs. The exposures lasted 20 min. For methanol, ethanol, THF, and acetone, data were obtained at multiple concentrations. The numbers across the top signify magnifications of the plots. The rising and falling parts of the curves distinguish the different TRMs and VOCs as well as different concentrations of the same VOC. This is expected, since the rate of diffusion of an analyte into a TRM is influenced by the concentration, size, shape, and chemical functionality of the analyte; the morphology and surface energy of the TRM; and F
DOI: 10.1021/acs.analchem.7b00120 Anal. Chem. XXXX, XXX, XXX−XXX
Article
Analytical Chemistry
configurations are possible. Another resettable version can be built if the wire is prestressed and mounted in a TRM that reversibly contracts when exposed to the target. Alternatively, devices that provide persistent readings can be constructed if the TRM permanently expands or collapses in the presence of analyte.
■
AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. ORCID
Vincent E. Lamberti: 0000-0002-6702-8863 Present Address
§ N.A.C.: Vaporsens, 36 S. Wasatch Drive, Mail Stop SMBB 5527, Salt Lake City, UT 84112.
Author Contributions
All authors approved the final manuscript. Notes
The authors declare no competing financial interest. # L.N.H., Jr.: Retired
■
ACKNOWLEDGMENTS This manuscript has been authored by Consolidated Nuclear Security LLC, under Contract No. DE-NA0001942 with the United States Department of Energy (DOE). The content is solely the responsibility of the authors and does not necessarily represent the official views of the DOE or CNS. The authors are grateful to Unitika, Ltd. for providing several types of amorphous magnetoelastic wire.
■
REFERENCES
(1) Li, X.; Chen, X.; Yao, Y.; Li, N.; Chen, X. Sens. Actuators, B 2014, 196, 183−188. (2) Sayago, I.; Fernandez, M.; Fontecha, J.; Horrillo, M.; Vera, C.; Obieta, I.; Bustero, I. Sens. Actuators, B 2012, 175, 67−72. (3) Chapman, P.; Vogt, F.; Dutta, P.; Datskos, P.; DeVault, G.; Sepaniak, M. Anal. Chem. 2007, 79, 364−370. (4) Lavrik, N. V.; Sepaniak, M. J.; Datskos, P. G. Rev. Sci. Instrum. 2004, 75, 2229−2253. (5) Cunningham, B.; Weinberg, M.; Pepper, J.; Clapp, C.; Bousquet, R.; Hugh, B.; Kant, R.; Daly, C.; Hauser, E. Sens. Actuators, B 2001, 73, 112−123. (6) Poole, Z.; Ohodnicki, P.; Chen, R.; Lin, Y.; Chen, K. Opt. Express 2014, 22, 2665−2673. (7) Makhnovskiy, D. P.; Panina, L. V. In Progress in Ferromagnetism Research; Murray, V. N., Ed.; Nova Science Publishers: New York, 2006; pp 255−292. (8) Vázquez, M. In Handbook of Magnetism and Advanced Magnetic Materials, Vol. 4: Novel Materials; Kronmüller, H., Parkin, S., Eds.; John Wiley & Sons: Hoboken, NJ, 2007; pp 1−34. (9) Jiles, D. C. Acta Mater. 2003, 51, 5907−5939. (10) Vázquez, M.; Hernando, A. J. Phys. D: Appl. Phys. 1996, 29, 939−949. (11) Squire, P. T.; Atkinson, D.; Gibbs, M. R. J.; Atalay, S. J. Magn. Magn. Mater. 1994, 132, 10−21. (12) Mohri, K.; Humphrey, F. B.; Panina, L. V.; Honkura, Y.; Yamasaki, J.; Uchiyama, T.; Hirami, M. Phys. Status Solidi A 2009, 206, 601−607. (13) Calkins, F. T.; Flatau, A. B.; Dapino, M. J. J. Intell. Mater. Syst. Struct. 2007, 18, 1057−1066. (14) Donald, I. W. J. Mater. Sci. 1987, 22, 2661−2679. (15) Cho, E. J.; Lee, J.-W.; Ellington, A. D. Annu. Rev. Anal. Chem. 2009, 2, 241−264. (16) Byrne, B.; Stack, E.; Gilmartin, N.; O’Kennedy, R. Sensors 2009, 9, 4407−4445.
Figure 7. (A) Score plot for PC 2 vs PC 1 in the seven-dimensional space defined by the initial rising and descending slopes of the response curves. The clipped responses from the MAA-PEO sensor are excluded. (B) Variable contributions to PCs 1 and 2 (R = rising, D = descending).
(acetone). There is less separation along PC 2 (the points representing TCE and toluene overlap), but the VOC relationships here are less significant because the axis contains very little of the total variance. Figure 7B shows the variable contributions to the two PCs. The contributions were obtained from the squared loadings of the variables.42 PC 1 is strongly dominated by the rising slope of the MAA-PEO sensor, but also has significant (10% or higher) contributions from the rising slope of the CD-PEO sensor and the descending slopes of the CD-PEO and PEO sensors. In contrast, PC 2 is strongly dominated by the descending slope of the CD-PEO sensor, and it contains contributions approaching 10% for all other variables except the rising slope of the Cal[6]-MC sensor and the descending slope of the PEO sensor. These observations suggest that a ChIMES array could be considerably selective even with a small number of TRMs. Finally, while all results have been presented for a TRM that expands in the presence of analyte and for a sensor that resets after the analyte is removed, it should be noted that other G
DOI: 10.1021/acs.analchem.7b00120 Anal. Chem. XXXX, XXX, XXX−XXX
Article
Analytical Chemistry (17) Karger, B. L.; Snyder, L. R.; Horvath, C. An Introduction to Separation Science; John Wiley & Sons: New York, 1973; Chapter 2. (18) Miller, J. M. Chromatography: Concepts and Contrasts, 2nd ed.; John Wiley & Sons: Hoboken, NJ, 2009; Chapter 4. (19) Grimes, C. A.; Roy, S. C.; Sanju, R.; Cai, Q. Sensors 2011, 11, 2809−2844. (20) Zeng, K.; Grimes, C. A. IEEE Trans. Magn. 2007, 43, 2358− 2363. (21) Grimes, C. A.; Mungle, C. S.; Zeng, K.; Jain, M. K.; Dreschel, W. R.; Paulose, M.; Ong, K. G. Sensors 2002, 2, 294−313. (22) Grimes, C. A.; Kouzoudis, D.; Dickey, E. C.; Qian, D.; Anderson, M. A.; Shahidain, R.; Lindsey, M.; Green, L. J. Appl. Phys. 2000, 87, 5341−5343. (23) Cai, Q. Y.; Jain, M. K.; Grimes, C. A. Sens. Actuators, B 2001, 77, 614−619. (24) Cai, Q. Y.; Cammers-Goodwin, A.; Grimes, C. A. J. Environ. Monit. 2000, 2, 556−560. (25) Lakshmanan, R. S.; Guntupalli, R.; Hu, J.; Petrenko, V. A.; Barbaree, J. M.; Chin, B. A. Sens. Actuators, B 2007, 126, 544−550. (26) Pang, P.; Yang, W.; Huang, S.; Cai, Q.; Yao, S. Anal. Lett. 2007, 40, 897−906. (27) Shen, W.; Lakshmanan, R. S.; Mathison, L. C.; Petrenko, V. A.; Chin, B. A. Sens. Actuators, B 2009, 137, 501−506. (28) Baimpos, T.; Boutikos, P.; Nikolakis, V.; Kouzoudis, D. Sens. Actuators, A 2010, 158, 249−253. (29) Stoyanov, P. G.; Doherty, S. A.; Grimes, C. A.; Seitz, W. R. IEEE Trans. Magn. 1998, 34, 1315−1317. (30) Atalay, S.; Kolat, V. S.; Bayri, N.; Izgi, T. J. Supercond. Novel Magn. 2016, 29, 1551. (31) Zhukov, A.; Vázquez, M.; García-Beneytez, J. M. J. Phys. IV 1998, 8, Pr2-763−Pr2-766. (32) Dimogianopoulos, D. G. Recent Pat. Electr. Electron. Eng. 2012, 5, 103−119. (33) Kaur, M.; Sandhu, M.; Mohan, N.; Sandhu, P. S. Int. J. Comput. Electr. Eng. 2011, 3, 151−157. (34) Khan, M. Z. A.; Saleem, H.; Afzal, S. IOSR J. Comput. Eng. 2012, 8, 1−6. (35) Abe, Y.; Miyazawa, K.; Nakamura, M.; Ohashi, T. Trans. Iron Steel Inst. Jpn. 1987, 27, 929−935. (36) Masumoto, T.; Ohnaka, I.; Inoue, A.; Hagiwara, M. Scr. Metall. 1981, 15, 293−296. (37) Ström-Olsen, J. Mater. Sci. Eng., A 1994, 178, 239−243. (38) Kaiser, K. L. Electromagnetic Shielding; CRC Press: Boca Raton, FL, 2006; pp 1-23−1-27. (39) Zhukova, V.; Zhukov, A.; Blanco, J. M.; Gonzalez, J.; GómezPolo, C.; Vázquez, M. J. Appl. Phys. 2003, 93, 7208−7210. (40) Joliffe, I. T. Principal Component Analysis, 2nd ed.; Springer: New York, 2002. (41) van den Berg, R. A.; Hoefsloot, H. C. J.; Westerhuis, J. A.; Smilde, A. K.; van der Werf, M. J. BMC Genomics 2006, 7, 142−156. (42) Abdi, H.; Williams, L. J. WIREs Comp. Stat. 2010, 2, 433−459.
H
DOI: 10.1021/acs.analchem.7b00120 Anal. Chem. XXXX, XXX, XXX−XXX
