A polymer-Metglas sensor used to detect volatile organic compounds

A polymer-Metglas sensor used to detect volatile organic compounds

Sensors and Actuators A 158 (2010) 249–253 Contents lists available at ScienceDirect Sensors and Actuators A: Physical journal homepage: www.elsevie...

618KB Sizes 0 Downloads 108 Views

Sensors and Actuators A 158 (2010) 249–253

Contents lists available at ScienceDirect

Sensors and Actuators A: Physical journal homepage: www.elsevier.com/locate/sna

A polymer-Metglas sensor used to detect volatile organic compounds Theodoros Baimpos a,b , Panagiotis Boutikos b , Vladimiros Nikolakis a , Dimitris Kouzoudis c,∗ a

Foundation for Research and Technology Hellas, Institute of Chemical Engineering and High-Temperature Chemical Process, P.O. Box 1414, GR 265 04 Patras, Greece Department of Chemical Engineering, University of Patras, GR 265 04 Patras, Greece c Department of Engineering Sciences, University of Patras, GR 265 04 Patras, Greece b

a r t i c l e

i n f o

Article history: Received 13 October 2009 Received in revised form 8 December 2009 Accepted 4 January 2010 Available online 15 January 2010 Keywords: Magnetoelastic VOC Volatile organic compounds BAYHYDROL o-Xylene p-Xylene

a b s t r a c t In this work, the commercial polymer BAYHYDROL-110 has been employed as the analyte-responsive recognition layer on a magnetoelastic sensor used to detect several volatile organic compounds. The sensor exhibits enhanced selectivity to o-xylene and p-xylene compared to six other tested volatile organic compounds as well as to humidity. The sensitivities to o-xylene and p-xylene were −0.27 and −0.19 kHz/ppm of vapor concentration in air, respectively. The sensor exhibits excellent repeatability and stability over a period of at least 75 days, and relatively quick response times (on the order of a minute), but rather low recovery times (in the range of several minutes). The sensor’s sensitivity increases linearly with the mass of the polymer, but it is only slightly dependent on the sensor’s length. © 2010 Elsevier B.V. All rights reserved.

1. Introduction Volatile organic compounds (VOCs) are organic liquids with high vapor pressure. They are frequently found in air as a result of both human activities (i.e. exhausts, industrial processes) and natural sources (i.e. deciduous trees). Unfortunately, many VOCs are hazardous and are known to cause long-term health and environmental problems even down to the ppm concentration ranges, making their detection a necessity [1–3]. Of special interest are low-cost, low-power and portable detection techniques. Numerous VOC detection techniques have been proposed in the literature, based on different principles such as quartz-crystal-microbalances (QCM) [4–7], surface-acoustic-wave (SAW) [8,9] sensors, microcantilevers [10,11], resistive [12,13] and optical sensors [14,15]. One common feature of these techniques is an appropriate coating which is used as a sensitizing layer. Its role is to selectively adsorb VOCs, which result in a corresponding shift in the sensor detection property such as resonance frequency, resistance, refractive index, etc. Commonly used materials for sensitizing layers are semiconducting metal-oxides [16,17] and conductive polymers [18,19]. However, these materials frequently have limited selectivity, require high operational temperatures (200–500 ◦ C), or have issues related to long-term stability. In the current work, a commercially available polymer, BAYHYDROL-110 (an anionic

∗ Corresponding author. Fax: +30 2610996846. E-mail address: [email protected] (D. Kouzoudis). 0924-4247/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.sna.2010.01.020

dispersion of an aliphatic polyester urethane resin in water/nmethyl-2-pyrrolidone), is used as the adsorbing layer together with a magnetoelastic sensor. This particular polymer has been used by other groups [20] as a protective layer on magnetoelastic sensors, but we discovered that it is also an excellent adsorbing layer for various VOCs. Throughout the past decade there has been considerable interest in magnetoelastic sensors due to their low cost and remote query ability [21–25]. Magnetoelastic materials are usually amorphous metallic alloys, commonly known as Metglas, or composites of rare-earth elements, such as Terfenol. Our magnetoelastic sensor consists of a strip of Metglas 2826MBA with an average composition of Fe40 Ni38 Mo4 B18 , which can be set to resonate under an external alternating magnetic field. The vibrations result in the generation of both acoustic and magnetic flux, which can be detected by an appropriate microphone or a pickup coil. The measured flux passes through a maximum when the strip is vibrating at its resonance frequency f0 , given by [26] f0 =

1 2L

E s (1 − 2 )


where E, s , and  are correspondingly the Young’s modulus of elasticity, the density, and the Poisson’s ratio of the Metglas material, and L is the length of the strip. The Poisson ratio is defined as the ratio of the lateral strain (normal to the applied load) to the axial strain [27]. Usually the (1 − 2 )–1/2 term is ignored for simplicity because it only amounts to approximately a 3% correction to f0 for typical values of  = 0.25. Starting with Eq. (1) it can be easily shown


T. Baimpos et al. / Sensors and Actuators A 158 (2010) 249–253

that when a sensor of mass m0 and resonance frequency f0 is uniformly loaded by some small mass m, the resulting shift of the resonance frequency f is given approximately by: f ≈ −f0

m 2m0


Based on this principle, different physical and chemical parameters can be measured by coating the sensor with an appropriate mass change, analyte-responsive recognition layer which is capable of selectively adsorbing certain molecules. In this way various parameters have been previously detected such as CO2 concentration [28], humidity [29], bio-salts like calcium oxalate and brushite [30], pH [31], glucose [20], and microorganisms [32,33]. The advantages of using magnetoelastic sensors are (a) the remote sensing by means of pick-up coils, (b) the sensor’s low price which can be used on a disposable basis, and (c) the low power and cost of the equipment. Further information concerning the principles of operation, as well as the design and applications of magnetoelastic sensors [34–37], can be found in the review of Grimes at al. [21] and in the references mentioned therein. In the current work, we present the ability of the BAYHYDROL110-Metglas sensor to detect various VOCs at different concentrations in synthetic air at room temperature. Eight different VOCs were examined for that purpose, with compositions varied between 0.05% and 11% depending on the examined VOC. Experiments with humidity were also carried out since it is a basic ingredient of the atmosphere and tends to interfere with the sensor’s signal. This new sensor can selectively detect o-xylene and p-xylene compared to other VOC’s (n-hexane, c-hexane) and humidity.

2. Materials and methods The commercially available polymer BAYHYDROL-110 was used throughout this work. This polymer has been used by other authors in the literature [33–38] as a protective layer of the magnetoelastic ribbons due to its excellent binding properties to the metallic glass surfaces and its long-term stability in aqueous environments where most of the polymers fail. We discovered that BAYHYDROL110 shows a very positive response to several VOCs, with various sensitivities. The polymer was spread on the outer surface of 2 mm × 6 mm × 28 ␮m Metglas 2826 MBA magnetoelastic strips using a glass spatula. The response of the sensor was tested for the following eight different VOC’s: c-hexane and n-hexane, benzene, o-xylene and p- xylene, ethyl-acetate, methyl-ethyl-ketone (MEK) and dichloromethane. The experimental setup used for the detection of the VOCs is shown in Fig. 1. The concentration of each VOC was controlled using the following procedure: a stream of synthetic air was fed to a saturator (bubbler) with the VOC of interest. The concentration of the VOC was adjusted by diluting it with a second stream of synthetic air. The VOC vapor concentration was calculated assuming that the air stream leaving the bubbler was saturated with organic vapors and by taking into account the vapor pressure of each particular VOC at room temperature. Fig. 2 shows typical sensor resonance peaks as a function of polymer mass under the flow of synthetic air. As the inset shows, the dependence of the resonance frequency f0 on the polymer mass m is quite linear for polymer masses up to 30 mg, in accordance to Eq. (2). For the rest of the current work, all polymer masses were chosen to lie within this linear region. The adsorbed mass is typically only a small fraction of the polymer mass and thus it does not cause deviation from the linear region. The slope of the straight line is equal to 0.834 kHz/mg and it can be used as a calibration factor to convert resonance frequency shifts to mass loads.

Fig. 1. Experimental setup designed to detect VOCs using a polymer-Metglas sensors.

3. Results and discussion 3.1. VOC detection Fig. 3 shows the responses of a sensor when it is exposed to alternating environments of air and VOC at various concentrations. Measurements of humidity are also shown for comparison. All graphs are depicted on the same vertical scale. It is clear from these graphs that the sensor shows a small response to humidity, no remarkable response to either of the hexane compounds, and a remarkable response to the other VOCs with various sensitivities. Even though it is not apparent at a first glance, the sensitivity of the sensor to the xylene compounds is at least a factor of 10 higher than the other VOCs. This becomes more evident in Fig. 4a where the average stabilized resonance frequency values of Fig. 3 are depicted as a function of the VOC concentrations. The three ellipses have been drawn by the authors to stretch the fact that there are three different sensitivity ranges; a small one (range I) which includes the n- and c-hexane, a large one (range III) with the xylene isomers, and a middle one (range II) with the rest of the compounds. Humidity data, which is shown for comparison, lies in the middle range. The sensor’s sensitivity, which is defined as the signal change per concentration change, equals the slope of the data curves of Fig. 4a, assuming a linear dependence. The results for each individual VOC are shown in Fig. 4 as a selectivity plot, which clearly indicates the preference of the sensor to the xylene isomers. Table 1 also presents these sensitivities as numerical data for the three afore-

Fig. 2. Shifts of the resonance peaks as a function of polymer mass deposited on the Metglas ribbon.

T. Baimpos et al. / Sensors and Actuators A 158 (2010) 249–253


Fig. 3. Sensor response to alternating environments of air and VOC of various concentrations. Results shown for dichloromethane, ethyl-acetate, methyl-ethyl-ketone (MEK), benzene, n-hexane, c-hexane, p-xylene and o-xylene, and humidity. Res. freq in the y-axes corresponds to the resonance frequency of the sensor.

mentioned regions of Fig. 4a. It should be noted that the sensitivity to the o-xylene is 32% larger than the corresponding sensitivity to its para isomer, which means that the molecular weight does not play the dominant role in the adsorption process. Table 1 also shows the values of “figure-of-merit” which is a quantity similar to the sensitivity but with the detection signal given in dimensionless numbers. These numbers allow for an easier cross-platform comparison where sensor signals are different in general. For a magnetoelastic sensor, where the signal is the resonance frequency, the figure-of-merit is obtained by dividing the sensitivity numbers by the sensor’s initial frequency f0 in air, which, according to Fig. 4 is ∼105 kHz. It can be seen from Fig. 3 that the sensor’s response time is on the order of a few minutes, but the sensor’s recovery time is much longer (on the order of 20 min). This was expected because vapors tend to adsorb on material surfaces faster than they tend to desorb. As a result, higher temperatures are sometimes needed in order to desorb all the remaining molecules from the material. It can also be seen in Fig. 3 that the sensor’s repeatability (the difference in senTable 1 Sensor sensitivities and figures-of-merit calculated from the plots of Fig. 4. Humidity data is also shown for comparison. Sensitivity (Hz/ppm)

Figure-of-merit (ppm−1 , ×10-6 )



Range II

Humidity Average VOC

−0.017 −0.024

−0.16 −0.23

Range III

p-Xylene o-Xylene

−0.187 −0.272

−1.78 −2.59

Range I (average)

sor signal in air beforeafter cycling in VOC vapors) is good, which implies that the VOC’s are almost completely removed from the polymer in every cycle, even though the removal process happens rather slowly. Thus in our case, higher temperatures are not necessarily needed for VOC removal, but they can be used to accelerate the desorption process. Concerning the sensor’s stability, the sensors were tested for a total period of 3 months with no apparent signs of polymer degradation or signal reduction. 3.2. Sensor optimization A series of experiments were conducted in order to optimize the sensor’s sensitivity with respect to the polymer’s deposited mass and the sensor’s length, as shown in Fig. 5. Comparative measurements were performed for only one VOC, namely the MEK compound, at three different concentrations, 2.1%, 6.8% and 8.7% in air. The plot of Fig. 5 is similar to the inset of Fig. 2, but with the following differences: (a) the vertical axis represents relative resonance frequency changes |(f − fAIR )|/fAIR where fAIR = 105 kHz is the resonance frequency in air, (b) the deposited polymer masses are in the linear region 0–30 mg, and (c) there are sets of data for two different sensor lengths, the open symbols representing 1.5 cm, and the closed ones 2.0 cm. It is obvious that the sensor’s sensitivity (the slope) increases with polymer mass. The amount of VOC sorbed in the polymer is proportional to the polymer mass. As a result, a sensor with higher polymer mass is expected to adsorb higher amounts of VOCs and exhibit the highest response. Thus, the optimum polymer mass is 26 mg, which is the largest one in the linear region. On the other hand, the measurements show that the 1.5 cm sensor has a slightly better sensitivity than the 2.0 cm one. Based on Eq. (1) this can be attributed to the smaller mass of the shorter sensor.


T. Baimpos et al. / Sensors and Actuators A 158 (2010) 249–253 Table 2 Sensor sensitivities for various VOCs reported in the literature. Reference


VOCs tested




Benzene Toluene p-Xylene

0.0720 0.0831 0.1494



Ethanol Acetone Formalin Ammonia formic acid

0.12 0.05 0.02 0.07 0.79




Toluene Ethanol Acetone 2-propanol

0.273 0.091 0.298 0.039




Toluene Methanol

1.16 0.10





Fig. 4. Overall sensor response to all tested VOCs: (a) resonance frequency as a function of VOC concentration (the three ellipses I, II, III, indicate different sensitivity ranges). (b) Bar chart selectivity plot that compares the figures-of-merit of the different compounds.

The sensitivities of various sensor techniques reported in the literature for a number of different VOCs are shown in Table 2. Due to the large number of tested compounds, a direct comparison with all the references in Table 2 is difficult. The paper of Ju et al. [4] reports sensitivities of about 0.15 and 0.07 Hz/ppm for p-xylene and benzene, correspondingly; two VOC’s that were also examined in the current work. As it can be seen in Table 1, our corresponding numbers of ∼0.19 and 0.02 Hz/ppm (absolute values) are similar to the ones of the aforementioned reference.






MEMS cantilever

Toluene Octane

3.2 × 10−6 18.2 × 10−6




Ethanol Methanol Propanol

0.52 0.49 0.43




Methanol Acetone Ethylacetate

100 × 10−6 3 × 10−6 16 × 10−6


The minimum detection limit for o-xylene and p-xylene has been estimated to be ∼180 and ∼260 ppm respectively. These values have been calculated by dividing the detection limit of our measuring technique (∼50 Hz) with the sensitivity of the sensor (0.27 Hz/ppm for o-xylene and 0.19 Hz/ppm for p-xylene). It must be mentioned that the sensitivity values shown in Table 1 and the minimum detection limits reported above have been measured using sensors with 4.6 mg of BAYHYDROL-110. As shown in Fig. 5, these values can be increased for up to an order of magnitude if higher masses of polymer are deposited on the Metglas ribbons. Furthermore, the electronics of our equipment are susceptible to low frequency E/M noise, setting the detection limits of our technique to ∼50 Hz. We hope that a better design, together with proper shielding, will enable us to increase sensitivity and decrease the minimum detection limits. 4. Conclusions A magnetoelastic sensor which consists of BAYHYDROL-110 polymer coated on a Metglas 2826MBA strip is shown to respond to different VOC vapors in air. In particular, the sensor shows high selectivity to p- and o-xylenes with corresponding sensitivities of −1.87 and −2.72 kHz per % concentration in air. The figure-of-merit numbers are −1.25 × 10-6 and −1.81 × 10-6 ppm−1 correspondingly. The sensitivity for each xylene is an order of magnitude higher than the sensitivities of the other tested VOCs or humidity. Thus it can be concluded that the sensor of the current work is a selective xylene sensor. The sensitivity increases linearly with increasing polymer mass, up to the maximum mass load of 52.7 mg that could be added to the 2 mm × 6 mm Metglas strip before the signal become undetectable. The optimum polymer mass for this strip was found to be ∼26 mg. The sensor’s length plays no crucial role in the sensitivity.

Fig. 5. Relative resonance frequency change as a function of polymer mass, MEK concentration and sensor’s length (The % numbers indicate MEK concentration in air. The open and closed symbols indicate two different sensor lengths of 1.5 and 2.0 cm correspondingly, while the straight lines correspond to 2.1%, the dotted lines to 6.77% while the dashed lines to 8.7% of MEK concentration in air.).

Acknowledgements We acknowledge the financial support from the Operational Programme “Competitiveness” of the European Union (75 %) and

T. Baimpos et al. / Sensors and Actuators A 158 (2010) 249–253

from The General Secretariat for Research and Technology of Hellenic Ministry of Development (25 %) through the Project No. 05-NON-EU-152. References [1] M.A.J. Bevan, C.J. Proctor, J. Baker-Rogers, N.D. Warren, Exposure to carbon monoxide, respirable suspended particulates, and volatile organic compounds while commuting by bicycle, Environ. Sci. Technol. 25 (1991) 788–791. [2] L.M. Hagerman, V.P. Aneja, W.A. Lonneman, Characterization of non-methane hydrocarbons in the rural southern united states, Atmos. Environ. 31 (1997) 4017–4038. [3] M.L. Boeglin, D. Wessels, D. Henshel, An investigation of the relationship between air emissions of volatile organic compounds and the incidence of cancer in Indiana counties, Environ. Res. 100 (2006) 242–254. [4] J.F. Ju, M.J. Syu, H.S. Teng, S.K. Chou, Y.S. Chang, Preparation and identification of ␤-cyclodextrin polymer thin film for quartz crystal microbalance sensing of benzene, toluene, and p-xylene, Sensors Actuators B 132 (2008) 319–326. [5] M. Matsuguchi, T. Uno, T. Aoki, M. Yoshida, Chemically modified copolymer coatings for mass-sensitive toluene vapor sensors, Sensors Actuators B 131 (2008) 652–659. [6] V.L. Strashilov, G.E. Alexieva, V.N. Velichkov, R.P. Mateva, I.D. Avramov, Polymer coated quartz crystal microbalance sensors for volatile organic compound gases, Sensor Lett. 7 (2009) 203–211. [7] C. C¸oban, E. Demirbas¸, Detection of volatile organic compounds in aqueous solutions by phthalocyanine coated quartz crystal microbalance, Sensor Lett. 4 (2006) 446–451. [8] N. Levit, D. Pestov, G. Tepper, High surface area polymer coatings for SAW-based chemical sensor applications, Sensors Actuators B 82 (2002) 241–249. [9] D. Dermody, R. Crooks, T. Kim, Interactions between organized, surfaceconfined monolayers and vapor-phase probe molecules. 11. Synthesis, characterization, and chemical sensitivity of self-assembled polydiacetylene/calix[n]arene bilayers, J. Am. Chem. Soc. 118 (1996) 11912–11917. [10] J. Ricart, J. Pons, M. Dominguez, A. Rodrigues, E. Figueras, M.C. Horrillo, J. Gutierrez, I. Sayago, Application of pulsed digital oscillators to volatile organic compounds sensing, Sensors Actuators B 134 (2008) 773–779. [11] D. Lange, C. Hagleitner, A. Hierlemann, O. Brand, H. Baltes, Complementary metal oxide semiconductor cantilever arrays on a single chip: mass-sensitive detection of volatile organic compounds, Anal. Chem. 74 (2002) 3084–3095. [12] M. Kozlowski, R. Diduszko, K. Olszewska, H. Wronka, E. Czerwosz, Nanostructural palladium films for sensor applications, Vacuum 82 (2008) 956–961. [13] A. Taurino, S. Capone, A. Boschetti, T. Toccoli, R. Verucchi, A. Pallaoro, P. Siciliano, S. Iannotta, Titanium dioxide thin films prepared by seeded supersonic beams for gas sensing applications, Sensors Actuators B 100 (2004) 177–184. [14] C. Bariain, I.R. Matıas, C. Valdivielso, F.J. Arregui, M.L. Rodrıguez-Mendez, J.A. de Saja, Optical fiber sensor based on lutetium bisphthalocyanine for the detection of gases using standard telecommunication wavelengths, Sensors Actuators B 93 (2003) 153–158. [15] M. Penza, G. Cassano, P. Aversa, A. Cusano, A. Cutolo, M. Giordano, L. Nicolais, Carbon nanotube acoustic and optical sensors for volatile organic compounds detection, Nanotechnology 16 (2005) 2536–2547. [16] A.K. Srivastava, Detection of volatile organic compounds (VOCs) using SnO2 gas-sensor array and artificial neural network, Sensors Actuators B 96 (2003) 24–37. [17] A.A. Tomchenko, G.P. Harmer, B.T. Marquis, J.W. Allen, Semiconducting metal oxide sensor array for the selective detection of combustion gases, Sensors Actuators B 93 (2003) 126–134. [18] S. Hamilton, M.J. Hepher, J. Sommerville, Polypyrrole materials for detection and discrimination of volatile organic compounds, Sensors Actuators B 107 (2005) 424–432. [19] Y. Sakurai, H.S. Jung, T. Shimanouchi, T. Inoguchi, S. Morita, R. Kuboi, K. Natsukawa, Novel array-type gas sensors using conducting polymers, and their performance for gas identification, Sensors Actuators B 83 (2002) 270–275. [20] Q. Cai, K. Zeng, C. Ruan, T.A. Desai, C.A. Grimes, A. Wireless, Remote query glucose biosensor based on a pH-sensitive polymer, Anal. Chem. 76 (2004) 4038–4043. [21] C.A. Grimes, C.S. Mungle, Z.F. Zeng, M.K. Jain, W.R. Dreschel, M. Paulose, K.G. Ong, Wireless magnetoelastic resonance sensors: a critical review, Sensors 2 (2002) 294–313.


[22] J.M. Barandiaran, J. Gutierrez, Magnetoelastic sensors based on soft amorphous magnetic alloys, Sensors Actuators A 59 (1997) 38–42. [23] C. Petridis, P. Dimitropoulos, E. Hristoforou, A new magnetoelastic device for sensing applications, Sensors Actuators A 129 (2006) 131–137. [24] E. Hristoforou, New magnetostrictive delay line arrangements for sensor applications, Sensors Actuators A 81 (2000) 142–146. [25] R.S. Lakshmanan, R. Guntupalli, J. Hu, V.A. Petrenko, J.M. Barbaree, B.A. Chin, Detection of Salmonella typhimurium in fat free milk using a phage immobilized magnetoelastic sensor, Sensors Actuators B 126 (2007) 544–550. [26] P.G. Stoyanov, C.A. Grimes, A remote query magnetostrictive viscosity sensor, Sensors Actuators A 80 (2000) 8–14. [27] J.W.D. Callister, Materials Science and Engineering: An Introduction, 3rd ed., Wiley & Sons, New York, 1994. [28] I.G. Giannakopoulos, D. Kouzoudis, C.A. Grimes, V. Nikolakis, Synthesis and characterization of a composite zeolite-Metglas carbon dioxide sensor, Adv. Funct. Mater. 15 (2005) 1165–1170. [29] C.A. Grimes, D. Kouzoudis, Remote query measurement of pressure, fluid-flow velocity, and humidity using magnetoelastic thick-film sensors, Sensors Actuators 84 (2000) 205–212. [30] N. Bouropoulos, D. Kouzoudis, C.A. Grimes, The real-time, in situ monitoring of calcium oxalate and brushite precipitation using magnetoelastic sensors, Sensors Actuators B 109 (2005) 227–232. [31] Q.Y. Cai, C.A. Grimes, A remote query magnetoelastic pH sensor, Sensors Actuators B 71 (2000) 112–117. [32] K.G. Ong, J. Wang, R.S. Singh, L.G. Bachas, C.A. Grimes, Monitoring of bacteria growth using a wireless, remote query resonant-circuit sensor: application to environmental sensing, Biosens. Bioelectron. 16 (4-5) (2001) 305– 312. [33] P. Pang, Q. Cai, S. Yao, C.A. Grimes, The detection of Mycobacterium tuberculosis in sputum sample based on a wireless magnetoelastic-sensing device, Talanta 76 (2008) 360–364. [34] P. Pang, X. Xiao, Q. Cai, S. Yao, C.A. Grimes, A wireless magnetoelastic-sensing device for in situ evaluation of Pseudomonas aeruginosa biofilm formation, Sensors Actuators B 133 (2008) 473–477. [35] P. Pang, Y. Zhang, S. Ge, Q. Cai, S. Yao, C.A. Grimes, Determination of glucose using bienzyme layered assembly magnetoelastic sensing device, Sensors Actuators B 136 (2009) 310–314. [36] X. Xiao, M. Guo, Q. Li, Q. Cai, S. Yao, C.A. Grimes, In situ monitoring of breast cancer cell (MCF-7) growth and quantification of the cytotoxicity of anticancer drugs fluorouracil and cisplatin, Biosens. Bioelectron. 24 (2008) 247– 252. [37] S. Huang, S. Ge, L. He, Q. Cai, C.A. Grimes, A remote-query sensor for predictive indication of milk spoilage, Biosens. Bioelectron. 23 (2008) 1745–1748. [38] M. Zourob, K.G. Ong, K. Zeng, F. Mouffoukd, C.A. Grimes, A wireless magnetoelastic biosensor for the direct detection of organophosphorus pesticides, Analyst 132 (2007) 338–343.

Biographies Theodoros Baimpos received his chemical engineer diploma from University of Patras, Greece in 2007. He is currently a PhD candidate investigating the performance of zeolite–Metglas composites to detect VOCs. Panagiotis Boutikos is a chemical engineer. He received his diploma from university of Patras, and he is currently a PhD candidate. Vladimiros Nikolakis received his PhD in chemical engineering from University of Massachusetts Amherst, USA. He is currently a principal researcher at the Institute of Chemical Engineering & High Temperature Chemical Processes, Greece. He is research interests include the synthesis and characterization of zeolite films for gas separation and sensing applications, zeolite crystallization and encapsulation of optically or electrically active compounds in microporous materials. Dimitris Kouzoudis received his BSc in physics from The University of Ioannina, Greece and his MSc and PhD in physics from Iowa State University. Currently he is an assistant professor in Engineering Science Department University of Patras, Greece. His research interests include applications of sensors in biology and chemistry and magnetic properties of magnetoelastic materials.