Optical Fibre, New Developments Part 3 ppt

OpticalFibre,NewDevelopments64 In the experiment, the fiber has been laid across a section of wave flume, which is essentially a long water channel equipped with a wave generator at one end and a wave absorbing device at the other end; hence the fiber serves as a point sensor acting as a wave gauge. The fiber sensor is capable of detecting water wave frequencies accurately for all types of wave generated by the flume. With the optimum sag of fiber, the output response of the optical fiber sensor is linear within 0.7 m ± 0.2 m wave level. Fig. 14 is the wave measurement by the wave gauge and fiber sensor. The sensor monitors the polarization state change induced intensity variation of the light when the sensing fiber is affected by the presence of the water wave. As a result, the sensing fiber should be fully submerged in the water and be able to be moved physically by the water wave for the frequency range of 1-10 Hz, although the vibration sensor can have a KHz response signal. The sensor is capable of providing accurate frequency distributions for both regular waves and irregular waves, confirmed by a conventional wave gauge. 8. Spectral analysis of POTDR for intrusion sensing Up to now, distributed optical fiber sensors have been mainly studied for static measurements, i.e. no time-varying or slowly time-varying signals, such as, static strain or temperature. Dynamic measurements using the above techniques are difficult to achieve because of the large number of waveforms required to average out the polarization effect induced signal fluctuation or because of the large range of frequency scans that are needed in order to obtain a reasonable signal to noise ratio (SNR) and spatial resolution over a kilometer fiber length. A frequency modulated source to realize distributed Brillouin sensor based on correlation of pump and probe in fiber is demonstrated for vibration measurement (Hotate & Ong, 2003]. However, each time only one sensing point is chosen by the correlation peak of pump and probe light, it is particularly suitable for material processing over a short fiber distance while it is not essentially a fully distributed sensor which should provide information for every point along the fiber under test simultaneously. A truly distributed vibration sensor has been demonstrated recently based on the spectrum density of POTDR system (Zhang & Bao, 2008b). This new sensor can detect a vibration frequency of 5 KHz over 1 km sensing length with 10 m spatial resolution. POTDR was developed as the first fully distributed optical fiber measurement for static physical parameters in the earlier 80’s (Rogers, 1981) and then adopted as a diagnostic tool in optical communication systems to identify high polarization mode dispersion (PMD) fiber sections (Gisin et al., 1999). In conventional POTDR, the SOP is measured with 4 polarization controllers so that the rotation angle of SOP can be measured in every location to recover the PMD or strain, this process takes minutes, as a result, it can only be used for static measurement. To realize dynamic measurement with ms time scale, only one polarizer is sufficient to identify dynamic events, through which the birefringence change along the fiber could be detected; the setup is shown in Fig. 15. Moreover, with a novel fast Fourier transform (FFT) spectrum analysis, multiple simultaneous events with different vibration frequencies or even with the same frequencies are able to be accurately located. The spectral density function of location change is equivalent to many variable narrowband filters with bandwidth of < 1Hz to improve the SNR of multiple events detection, which allows the disturbance to be detected simultaneously at any location along the sensing fiber. Fig. 15. Experimental setup of POTDR system Data processing for the POTDR is done using four steps: in step (1) a large number of POTDR curves are acquired, step (2) at a particular position the time domain plot can be acquired from multiple POTDR curves, step (3) the FFT can be performed at that position using the time domain information and step (4) by performing steps (2) and (3) at all points along the fiber the magnitude of a certain frequency can be plotted as a function of distance. The post-signal processing is shown in Fig. 16. Step (1) to (3), is employed here by taking an average every 100 POTDR curves in step (2). Considering a 10 kHz repetition rate of the pulsed light, the effective sampling rate becomes 100 Hz, which has set the limitation for impact wave detection. Fig. 17(a) plots the FFT spectrum of 1.5 seconds time domain data at 550 m with a peak at 22 Hz when the PZT is driven by 5 Vpp, 22 Hz square wave. Benefited to its high sensitivity, this POTDR system makes it possible to measure higher frequency disturbance without any averaging in step (2). Hence, the maximum detectable frequency is 5 kHz using a 10 kHz sampling rate. In Fig. 17(b) when the driven frequency of the piezo is set to 4234 Hz, this peak frequency is clearly shown in the FFT spectrum at 550 m. Fig. 16. The data processing of the spectrum density of POTDR FiberSensorApplicationsinDynamicMonitoringofStructures, BoundaryIntrusion,SubmarineandOpticalGroundWireFibers 65 In the experiment, the fiber has been laid across a section of wave flume, which is essentially a long water channel equipped with a wave generator at one end and a wave absorbing device at the other end; hence the fiber serves as a point sensor acting as a wave gauge. The fiber sensor is capable of detecting water wave frequencies accurately for all types of wave generated by the flume. With the optimum sag of fiber, the output response of the optical fiber sensor is linear within 0.7 m ± 0.2 m wave level. Fig. 14 is the wave measurement by the wave gauge and fiber sensor. The sensor monitors the polarization state change induced intensity variation of the light when the sensing fiber is affected by the presence of the water wave. As a result, the sensing fiber should be fully submerged in the water and be able to be moved physically by the water wave for the frequency range of 1-10 Hz, although the vibration sensor can have a KHz response signal. The sensor is capable of providing accurate frequency distributions for both regular waves and irregular waves, confirmed by a conventional wave gauge. 8. Spectral analysis of POTDR for intrusion sensing Up to now, distributed optical fiber sensors have been mainly studied for static measurements, i.e. no time-varying or slowly time-varying signals, such as, static strain or temperature. Dynamic measurements using the above techniques are difficult to achieve because of the large number of waveforms required to average out the polarization effect induced signal fluctuation or because of the large range of frequency scans that are needed in order to obtain a reasonable signal to noise ratio (SNR) and spatial resolution over a kilometer fiber length. A frequency modulated source to realize distributed Brillouin sensor based on correlation of pump and probe in fiber is demonstrated for vibration measurement (Hotate & Ong, 2003]. However, each time only one sensing point is chosen by the correlation peak of pump and probe light, it is particularly suitable for material processing over a short fiber distance while it is not essentially a fully distributed sensor which should provide information for every point along the fiber under test simultaneously. A truly distributed vibration sensor has been demonstrated recently based on the spectrum density of POTDR system (Zhang & Bao, 2008b). This new sensor can detect a vibration frequency of 5 KHz over 1 km sensing length with 10 m spatial resolution. POTDR was developed as the first fully distributed optical fiber measurement for static physical parameters in the earlier 80’s (Rogers, 1981) and then adopted as a diagnostic tool in optical communication systems to identify high polarization mode dispersion (PMD) fiber sections (Gisin et al., 1999). In conventional POTDR, the SOP is measured with 4 polarization controllers so that the rotation angle of SOP can be measured in every location to recover the PMD or strain, this process takes minutes, as a result, it can only be used for static measurement. To realize dynamic measurement with ms time scale, only one polarizer is sufficient to identify dynamic events, through which the birefringence change along the fiber could be detected; the setup is shown in Fig. 15. Moreover, with a novel fast Fourier transform (FFT) spectrum analysis, multiple simultaneous events with different vibration frequencies or even with the same frequencies are able to be accurately located. The spectral density function of location change is equivalent to many variable narrowband filters with bandwidth of < 1Hz to improve the SNR of multiple events detection, which allows the disturbance to be detected simultaneously at any location along the sensing fiber. Fig. 15. Experimental setup of POTDR system Data processing for the POTDR is done using four steps: in step (1) a large number of POTDR curves are acquired, step (2) at a particular position the time domain plot can be acquired from multiple POTDR curves, step (3) the FFT can be performed at that position using the time domain information and step (4) by performing steps (2) and (3) at all points along the fiber the magnitude of a certain frequency can be plotted as a function of distance. The post-signal processing is shown in Fig. 16. Step (1) to (3), is employed here by taking an average every 100 POTDR curves in step (2). Considering a 10 kHz repetition rate of the pulsed light, the effective sampling rate becomes 100 Hz, which has set the limitation for impact wave detection. Fig. 17(a) plots the FFT spectrum of 1.5 seconds time domain data at 550 m with a peak at 22 Hz when the PZT is driven by 5 Vpp, 22 Hz square wave. Benefited to its high sensitivity, this POTDR system makes it possible to measure higher frequency disturbance without any averaging in step (2). Hence, the maximum detectable frequency is 5 kHz using a 10 kHz sampling rate. In Fig. 17(b) when the driven frequency of the piezo is set to 4234 Hz, this peak frequency is clearly shown in the FFT spectrum at 550 m. Fig. 16. The data processing of the spectrum density of POTDR OpticalFibre,NewDevelopments66 Fig. 17. Piezo fiber stretcher driven by 5 Vpp square wave, FFT spectrum of time trace signal at 550 m of (a) 22 Hz driven signal; (b) 4234 Hz driven signal The present sensing uses post-signal processing, with the introduction of a micro-processor there would be a significant reduction of the signal processing time without going through computer for digitization and programming timing, which makes the current system response in the ms time frame, as the FFT signal processing and averaging can be conducted by electronic circuits directly. This new technology could in a cost-effective manner provide intrusion sensing for perimeter security at various places or structure health monitoring for large structures, such as bridges, highway pavements, pipeline leakage, etc. with low fault rate due to the multiple frequency components discrimination at < 1 Hz narrow band. 9. Conclusion Monitoring of health is not a new idea and it is literally practiced by physicians using a knowledge base, tools, methods, and systems for diagnosis and then prognosis of one’s state of health. Some of these tools were specifically developed for the practice of medicine and in a similar fashion this occurred in the current chapters. The ability to accurately and efficiently monitor the long-term performance of engineering structures is an extremely valuable one. The potential benefits of structural monitoring includes reducing lifetime maintenance costs, improved safety and the ability to confidently use more efficient designs and advanced materials. Today, a new and interdisciplinary area of structural health monitoring is likewise needed in order to address the structural, economic, and safety needs of the 21st century society and beyond. As with other industries, civil engineering must also undergo such a catharsis for a similar industry development. In this Chapter we focused on fiber sensors using birefringence properties which have the fastest response to dynamic changes, using this idea combined with nonlinear effects we have demonstrated point and distributed sensors for dynamic monitoring in structures, communication fibers and security applications. 10. References Allen, C.; Kondamuri, P.; Richards, D. & Hague, D. (2003). Measured temporal and spectral PMD characteristics and their implications for network-level mitigation approaches. J. Lightwave Technol., Vol. 21, No. 1, (January 2003) 79–86, doi:10.1109/JLT.2003.808634 Bao, X.; W. Li, W.; Zhang, C.; Eisa, M.; El-Gamal S. & Benmokrane, B. (2008). Monitoring the distributed impact wave on concrete slab due to the traffics based on polarization dependence on the stimulated Brillouin scattering. Smart Mater. Structures, Vol. 17, No. 1, (November 2008) 1-5, doi:10.1016/j.engstruct.2004.05.018 Barnoski, J. K. & Jensen, S. M. (1976). Fiber waveguides: A novel technique for investigation attenuation characteristics. Appl. Opt., Vol. 15, No. 9, (Sept. 1976) 2112-2115 Boyd, R. W. (2003). Nonlinear Optics, Second Edition, Academic Press, ISBN: 0-12-121682-9, San Diego Brosseau, C. (1998). Fundamentals of Polarized Light: A Statistical Optical Approach, Wiley Inter- Science, ISBN: 978-0-471-14302-4, New York Cameron, J.; Chen, L.; Bao, X. & Stears, J. (1998). Time evolution of polarization mode dispersion in optical fibers. Photon. Technol. Lett., Vol. 10, No. 9, (September 1998) 1265–1267, ISSN: 1041-1135 Chen, L.; Zhang, Z. & Bao, X. (2007). Combined PMD-PDL effects on BERs in simplified optical systems: an analytical approach. Opt. Express, Vol. 15, No. 5, (March 2007) 2106-2119, doi:10.1364/OE.15.002106 Gisin, N.; Gisin, B.; der Weid, J. P. V. & Passy, R. (1996). How accurately can one measure a Statistical Quantity like Polarization-Mode Dispersion?. Photon. Technol. Lett., Vol. 8, No. 12, (December 1996) 1671–1673, ISSN: 1041-1135 Gordon, J. P. & Kogelnik, H. (2000). PMD fundamentals: polarization mode dispersion in optical fibers. Proc. Nat. Acad. Sci., Vol. 97, No. 9, (April 2000) 4541-4550, PMID: 10781059 Hotate, K. & Ong, S. L. (2003). Distributed dynamic strain measurement using a correlation- based Brillouin sensing system. IEEE Photon. Technol. Lett., Vol. 15, No. 2, (February 2003) 272–274, ISSN: 1041-1135 Hunttner, B.; Gisin, B. & Gisin, N. (1999). Distributed PMD measurement with a polarization-OTDR in optical fibers . J. Lightwave Technol. Vol. 17, No. 10, (October 1999) 1843-1848, ISSN: 0733-8724 Huttner, B.; Geiser, C. & Gisin, N. (2000). Polarization-induced distortion in optical fiber networks with polarization-mode dispersion and polarization-dependent losses. IEEE J. Select. Topics Quantum Electron., Vol. 6, No. 2, (March/April 2000) 317-329, ISSN: 1077-260X Karlsson, M.; Brentel, J. & Andrekson, P. (2000). Long-term measurement of PMD and polarization drift in installed fibers. J. Lightw. Technol., Vol. 18, No. 7, (July 2000) 941–951, ISSN: 0733-8724 Krispin, H.; Fuchs, S. & Hagedorn, P. (2007). Optimization of the efficiency of aeolian vibration dampers, Proceeding of Power Engineering Society Conference and Exposition in Africa , South Africa, pp 1-3, ISBN: 978-1-4244-1477-2, July 2007, IEEE PowerAfrica '07, Johanesburg FiberSensorApplicationsinDynamicMonitoringofStructures, BoundaryIntrusion,SubmarineandOpticalGroundWireFibers 67 Fig. 17. Piezo fiber stretcher driven by 5 Vpp square wave, FFT spectrum of time trace signal at 550 m of (a) 22 Hz driven signal; (b) 4234 Hz driven signal The present sensing uses post-signal processing, with the introduction of a micro-processor there would be a significant reduction of the signal processing time without going through computer for digitization and programming timing, which makes the current system response in the ms time frame, as the FFT signal processing and averaging can be conducted by electronic circuits directly. This new technology could in a cost-effective manner provide intrusion sensing for perimeter security at various places or structure health monitoring for large structures, such as bridges, highway pavements, pipeline leakage, etc. with low fault rate due to the multiple frequency components discrimination at < 1 Hz narrow band. 9. Conclusion Monitoring of health is not a new idea and it is literally practiced by physicians using a knowledge base, tools, methods, and systems for diagnosis and then prognosis of one’s state of health. Some of these tools were specifically developed for the practice of medicine and in a similar fashion this occurred in the current chapters. The ability to accurately and efficiently monitor the long-term performance of engineering structures is an extremely valuable one. The potential benefits of structural monitoring includes reducing lifetime maintenance costs, improved safety and the ability to confidently use more efficient designs and advanced materials. Today, a new and interdisciplinary area of structural health monitoring is likewise needed in order to address the structural, economic, and safety needs of the 21st century society and beyond. As with other industries, civil engineering must also undergo such a catharsis for a similar industry development. In this Chapter we focused on fiber sensors using birefringence properties which have the fastest response to dynamic changes, using this idea combined with nonlinear effects we have demonstrated point and distributed sensors for dynamic monitoring in structures, communication fibers and security applications. 10. References Allen, C.; Kondamuri, P.; Richards, D. & Hague, D. (2003). Measured temporal and spectral PMD characteristics and their implications for network-level mitigation approaches. J. Lightwave Technol., Vol. 21, No. 1, (January 2003) 79–86, doi:10.1109/JLT.2003.808634 Bao, X.; W. Li, W.; Zhang, C.; Eisa, M.; El-Gamal S. & Benmokrane, B. (2008). Monitoring the distributed impact wave on concrete slab due to the traffics based on polarization dependence on the stimulated Brillouin scattering. Smart Mater. Structures, Vol. 17, No. 1, (November 2008) 1-5, doi:10.1016/j.engstruct.2004.05.018 Barnoski, J. K. & Jensen, S. M. (1976). Fiber waveguides: A novel technique for investigation attenuation characteristics. Appl. Opt., Vol. 15, No. 9, (Sept. 1976) 2112-2115 Boyd, R. W. (2003). Nonlinear Optics, Second Edition, Academic Press, ISBN: 0-12-121682-9, San Diego Brosseau, C. (1998). Fundamentals of Polarized Light: A Statistical Optical Approach, Wiley Inter- Science, ISBN: 978-0-471-14302-4, New York Cameron, J.; Chen, L.; Bao, X. & Stears, J. (1998). Time evolution of polarization mode dispersion in optical fibers. Photon. Technol. Lett., Vol. 10, No. 9, (September 1998) 1265–1267, ISSN: 1041-1135 Chen, L.; Zhang, Z. & Bao, X. (2007). Combined PMD-PDL effects on BERs in simplified optical systems: an analytical approach. Opt. Express, Vol. 15, No. 5, (March 2007) 2106-2119, doi:10.1364/OE.15.002106 Gisin, N.; Gisin, B.; der Weid, J. P. V. & Passy, R. (1996). How accurately can one measure a Statistical Quantity like Polarization-Mode Dispersion?. Photon. Technol. Lett., Vol. 8, No. 12, (December 1996) 1671–1673, ISSN: 1041-1135 Gordon, J. P. & Kogelnik, H. (2000). PMD fundamentals: polarization mode dispersion in optical fibers. Proc. Nat. Acad. Sci., Vol. 97, No. 9, (April 2000) 4541-4550, PMID: 10781059 Hotate, K. & Ong, S. L. (2003). Distributed dynamic strain measurement using a correlation- based Brillouin sensing system. IEEE Photon. Technol. Lett., Vol. 15, No. 2, (February 2003) 272–274, ISSN: 1041-1135 Hunttner, B.; Gisin, B. & Gisin, N. (1999). Distributed PMD measurement with a polarization-OTDR in optical fibers . J. Lightwave Technol. Vol. 17, No. 10, (October 1999) 1843-1848, ISSN: 0733-8724 Huttner, B.; Geiser, C. & Gisin, N. (2000). Polarization-induced distortion in optical fiber networks with polarization-mode dispersion and polarization-dependent losses. IEEE J. Select. Topics Quantum Electron., Vol. 6, No. 2, (March/April 2000) 317-329, ISSN: 1077-260X Karlsson, M.; Brentel, J. & Andrekson, P. (2000). Long-term measurement of PMD and polarization drift in installed fibers. J. Lightw. Technol., Vol. 18, No. 7, (July 2000) 941–951, ISSN: 0733-8724 Krispin, H.; Fuchs, S. & Hagedorn, P. (2007). Optimization of the efficiency of aeolian vibration dampers, Proceeding of Power Engineering Society Conference and Exposition in Africa , South Africa, pp 1-3, ISBN: 978-1-4244-1477-2, July 2007, IEEE PowerAfrica '07, Johanesburg OpticalFibre,NewDevelopments68 Landau, L. & Lifchitz, E. M. (1981). Electrodynamics of Continuous Media (J. B. Sykes & J. S. Bell, Trans.), Pergamon Press, ISBN: 0080091059, Oxford (Original work published 1969) Leeson, J; Bao X.; Côté, A. (2009). Polarization Dynamics in Optical Ground Wire (OPGW) Network. Appl. Opt., Vol. 48, No. 14, (May 2009) 2214-2219, doi:10.1364/AO.48.002214 Measures, R. M. (2001). Structural Monitoring with Fibre Optics Technology, Academic Press, ISBN: 0-12-487430-4, London Rogers, A. J. (1981). Polarization-optical time domain reflectometry: A technique for the measurement of field distributions. Appl. Opt., Vol. 20, No. 6, (March 1981) 1060- 1074, ISSN: 0003-6935 Snoody, J. (2008). Study on Brillouin Scattering in Optical Fibers with Emphasis on Sensing. Unpublished master's thesis, University of Ottawa, Ottawa, Canada Waddy, D.; Lu, P.; Chen, L. & Bao, X. (2001). Fast state of polarization changes in aerial fiber under different climatic conditions. Photon. Technol. Lett., Vol. 13, No. 9, (September 2001) 1035–1037, ISSN: 1041-1135 Waddy, D. S.; Chen, L. & Bao, X. (2005). Polarization effects in aerial fibers . Opt. Fiber Technol., Vol. 11, No. 1, (October 2005) 1-19, doi:10.1016/j.yofte.2004.07.002 Wuttke, J.; Krummrich, P. & Rosch, J. (2003). Polarization oscillations in aerial fiber caused by wind and power-line current. Photon. Technol. Lett., Vol. 15, No. 6, (June 2003) 882–884, ISSN: 1041-1135 Zhang, Z.; Bao, X.; Yu, Q. & Chen, L. (2006). Fast states of polarization and PMD drift in submarine fibres. Photon. Technol. Lett., Vol. 18, No. 9, (May 2006) 1034-1036, ISSN: 1041-1135 Zhang, Z.; Bao, X.; Yu, Q. & Chen, L. (2007). Time evolution of PMD due to the tides and sun radiation on submarine fibers. Opt. Fiber Technol., Vol. 13, No. 1, (January 2007) 62- 66, doi:10.1016/j.yofte.2006.07.003 Zhang, Z & Bao, X. (2008a). Continuous and damped vibration detection based on fiber diversity detection sensor by rayleigh backscattering. J. Lightwave Technol., Vol. 26, No. 7, (April 2008) 852-838, ISSN: 0733-8724 Zhang, Z. & Bao, X. (2008b). Distributed optical fiber vibration sensor based on spectrum analysis of polarization-OTDR system. Opt. Express, Vol. 16, No. 14, (July 2008) 10240-10247, doi:10.1364/OE.16.010240 Zhang, Z.; LeBlanc, S.; Bao X. (2008a). Concrete pavement vibration monitoring due to the car passing using optical fiber sensor, Proceedings of the 19th International Conference on Optical Fibre Sensors (OFS-19) , pp.1-5, ISBN: 9780819472045, Australia, June 2008, SPIE, Perth Zhang Z.; Bao X.; Rennie C. D.; Nistor I. & Cornett A. (2008b). Water wave frequency detection by optical fiber sensor. Opt. Communication, Vol. 281, No. 24, (December 2008) 6011–6015, ISSN: 0030-4018 Near-FieldOpto-ChemicalSensors 69 Near-FieldOpto-ChemicalSensors AntoniettaBuosciolo,MarcoConsales,MarcoPisco,MicheleGiordanoandAndreaCusano X Near-Field Opto-Chemical Sensors Antonietta Buosciolo 1 , Marco Consales 2 , Marco Pisco 2 , Michele Giordano 1 and Andrea Cusano 2 1 National Research Council, Institute for Composite and Biomedical Materials Napoli, Italy 2 University of Sannio, Optoelectronic Division, Engineering Department, Benevento, Italy 1. Introduction Nanotechnology and nanoscale materials are a new and exciting field of research. The inherently small size and unusual optical, magnetic, catalytic, and mechanical properties of nanoparticles not found in bulk materials permit the development of novel devices and applications previously unavailable. One of the earliest applications of nanotechnology that has been realized is the development of improved chemical and biological sensors. Remarkable progress has been made in the last years in the development of optical nanosensors and their utilization in life science applications. This new technology demonstrates the breadth of analytical science and the impact that will be made in the coming years by implementing novel sensing principles as well as new measurement techniques where currently none are available. What is exciting in sensor research and development today? This is a tough question. There are many significant innovations and inventions being made daily. Micro and nanotechnology, novel materials and smaller, smarter and more effective systems will play an important role in the future of sensors. With the increasing interest in and practical use of nanotechnology, the application of nanosensors to different types of molecular measurements is expanding rapidly. Further development of delivery techniques and new sensing strategies to enable quantification of an increased number of analytes are required to facilitate the desired uptake of nanosensor technology by researchers in the biological and life sciences. To fulfil the promise of ubiquitous sensor systems providing situational awareness at low cost, there must be a demonstrated benefit that is only gained through further miniaturization. For example, new nanowire-based materials that have unique sensing properties can provide higher sensitivity, greater selectivity and possibly improved stability at a lower cost and such improvements are necessary to the sensor future. Nano-sensors can improve the world through diagnostics in medical applications; they can lead to improved health, safety and security for people; and improved environmental monitoring. The seed technologies are now being developed for a long-term vision that 5 OpticalFibre,NewDevelopments70 includes intelligent systems that are self-monitoring, self-correcting and repairing, and self- modifying or morphing not unlike sentient beings. On this line of argument, in last years, our interdisciplinary group has been involved in research activities focused on the development of novel opto-chemical nano-sensors employing near-field effects to enhance the overall performance of the final device. In this chapter, thus, we report recent findings on new class of opto-chemical sensors whose excellent sensing performance are related to an enhancement effect of the optical near-field induced by semiconductive structures of tin dioxide (SnO 2 ) when their spatial dimensions are comparable to the employed radiation wavelength (). The main objective is to investigate the possibility to concentrate the electro-magnetic field in precise localized spots, by means of metal oxide micro and nano-sized structures, to increase light matter interaction and provide innovative and valuable sensing mechanisms for next generation of fiber optic chemical and biological nano-sized sensors (Pisco et al., 2006; Buosciolo et al., 2006). Due to the strong interdisciplinary nature of the problem, research activities have been carried out following an integrated approach where all the aspects (material selection, integration techniques and transducer development), have been simultaneously addressed and optimized. Taking this line, interest was focused on issues like investigation of the surface morphology and of the near-field optical properties in relation to suitable processing and post-processing conditions; correlation of the surface layer morphology and the emerging near-field intensity distribution with the sensing performance [Consales et al., 2006b; Cusano et al., 2006). We found that sensitive layers with very rough morphologies inducing a significant perturbation of the optical near-field, exhibited surprisingly sensing performance for both water chemicals monitoring and against chemical pollutants in air environment, at room temperature (Cusano et al., 2006; Buosciolo et al., 2008b). Similar effects of light manipulation have been observed, in recent years, only in noble metal nanostructures explained in terms of localized surface plasmons and in subwavelength hole arrays in both metal films and non metallic systems; in a recent convincing theoretical model (Lezec & Thio, 2004) relative to the last case, the transmission of light is modulated not by coupling to surface plasmons, but by interference of diffracted evanescent waves generated by subwavelength periodic features at the surface, leading to transmission enhancement as well as suppression. In light of this argument, it is clear that the manipulation of light through semicondutive micro and nano sized structures opens new frontiers not only in sensing applications but have also vast potential to be applied in many fields ranging from high performance nanometer-scale photonic devices up to in-fiber micro systems. Here, we review the technological steps carried out by our group for the demonstration of a novel sensing mechanism arising from near-field effects in confined domains constituted by particle layers of tin dioxide with size approaching the optical wavelength. To this aim, we have structured the present chapter as follows: sections 2 and 3 are focused on the properties and characteristics of tin dioxide as sensing layer for chemical transducers with particular emphasis on the state of the art on chemical sensors based on this type of semiconductor. Section 4 deals with the principle of operation of the proposed reflectometric opto-chemical sensors and with the electrostatic-spray pyrolysis method as valuable tool to deposit particle layers of tin dioxide on optical fiber substrates at wavelength scale. Section 5 reports the morphological and optical characterization of the so produced superstrates carried out by atomic force and scanning near-field optical microscopy, very useful to clearly outline the effects of processing parameters on particles size and distribution as wells on the optical near-field emerging from the overlays. Finally, in section 6 we present the sensing performances of fiber optic chemo-sensors incorporating tin dioxide particle layers in both air and liquid environments discussing the dependence of the sensing properties on film morphology and optical near-field. 2. Tin dioxide as sensing material Metal oxides are widely used as sensitive materials for electrical gas sensors in environmental, security and industrial applications. The idea of using semiconductors as gas sensitive devices leads back to 1952 when Brattain and Bardeen first reported gas sensitive effects on germanium (Brattain & Bardeen, 1952). Later, Seiyama et al. found gas sensing effect on metal oxides (Seiyama et al., 1962). The principle of operation of such class of sensors relies upon a change of electrical conductivity of the semiconductor material as a consequence of the gas adsorption. Even if many chemo-physical coupled phenomena, such as surface and bulk chemical reactions and mass and energy diffusion, are involved in the operation of the semiconductor solid state conductivity sensors (Lundstrom, 1996), in general, the sensing principle is dominated by the variation of the electronic properties of wide-band-gap semiconductors such as SnO 2 and ZnO due to the gases adsorption that modifies the intrinsic electronic defect formation (Szklarski, 1989). The gas sensitivity of semiconductor materials is underlain by reversible effects resulting from chemisorption of molecules, formation of space charge areas, and variation of the concentration of the charge carriers in the subsurface layer. Although the general principle of the detection mechanism is appreciated, the size of the change of electric conductivity (sensor signal) is largely determined by the structural type of the semiconductor, the nature and concentration of surface reactive centers, and the real structure of the material: the size, structure, and degree of agglomeration of crystallites, specific surface area, and pore geometry (Rumyantsevaa et al., 2008). In principle, any semiconducting oxide can be exploited as a sensor by monitoring changes of its resistance during interaction with the detected gas molecules at an operating temperature typically above 200 °C. Because tin oxide (SnO 2 ) offers high sensitivity at conveniently low operating temperatures, attention has been concentrated on this material although lately many studies extended also to other oxides. In fact, several commercial devices based on SnO 2 for detecting low concentration of both flammable, i.e. CH 4 and H 2 , and toxic; i.e. CO, H 2 S and NO x , gases, are available. SnO 2 sensors can be referred to as the best-understood prototype of oxide based gas sensors. Nevertheless, highly specific and sensitive SnO 2 sensors are not yet available. It is well known that sensor selectivity can be fine-tuned over a wide range by varying the SnO 2 crystal structure and morphology, dopants, contact geometries, operation temperature or mode of operation, etc. The electric conductivity of oxide semiconductors is extremely sensitive to the composition of the surface, which reversibly varies as a consequence of surface reactions involving chemisorbed oxygen (O 2 – , O 2– , O – ) and the gas mixture components, proceeding at 100–500°C. (Rumyantsevaa et al., 2008; Barsan, et al., 1999). Near-FieldOpto-ChemicalSensors 71 includes intelligent systems that are self-monitoring, self-correcting and repairing, and self- modifying or morphing not unlike sentient beings. On this line of argument, in last years, our interdisciplinary group has been involved in research activities focused on the development of novel opto-chemical nano-sensors employing near-field effects to enhance the overall performance of the final device. In this chapter, thus, we report recent findings on new class of opto-chemical sensors whose excellent sensing performance are related to an enhancement effect of the optical near-field induced by semiconductive structures of tin dioxide (SnO 2 ) when their spatial dimensions are comparable to the employed radiation wavelength (). The main objective is to investigate the possibility to concentrate the electro-magnetic field in precise localized spots, by means of metal oxide micro and nano-sized structures, to increase light matter interaction and provide innovative and valuable sensing mechanisms for next generation of fiber optic chemical and biological nano-sized sensors (Pisco et al., 2006; Buosciolo et al., 2006). Due to the strong interdisciplinary nature of the problem, research activities have been carried out following an integrated approach where all the aspects (material selection, integration techniques and transducer development), have been simultaneously addressed and optimized. Taking this line, interest was focused on issues like investigation of the surface morphology and of the near-field optical properties in relation to suitable processing and post-processing conditions; correlation of the surface layer morphology and the emerging near-field intensity distribution with the sensing performance [Consales et al., 2006b; Cusano et al., 2006). We found that sensitive layers with very rough morphologies inducing a significant perturbation of the optical near-field, exhibited surprisingly sensing performance for both water chemicals monitoring and against chemical pollutants in air environment, at room temperature (Cusano et al., 2006; Buosciolo et al., 2008b). Similar effects of light manipulation have been observed, in recent years, only in noble metal nanostructures explained in terms of localized surface plasmons and in subwavelength hole arrays in both metal films and non metallic systems; in a recent convincing theoretical model (Lezec & Thio, 2004) relative to the last case, the transmission of light is modulated not by coupling to surface plasmons, but by interference of diffracted evanescent waves generated by subwavelength periodic features at the surface, leading to transmission enhancement as well as suppression. In light of this argument, it is clear that the manipulation of light through semicondutive micro and nano sized structures opens new frontiers not only in sensing applications but have also vast potential to be applied in many fields ranging from high performance nanometer-scale photonic devices up to in-fiber micro systems. Here, we review the technological steps carried out by our group for the demonstration of a novel sensing mechanism arising from near-field effects in confined domains constituted by particle layers of tin dioxide with size approaching the optical wavelength. To this aim, we have structured the present chapter as follows: sections 2 and 3 are focused on the properties and characteristics of tin dioxide as sensing layer for chemical transducers with particular emphasis on the state of the art on chemical sensors based on this type of semiconductor. Section 4 deals with the principle of operation of the proposed reflectometric opto-chemical sensors and with the electrostatic-spray pyrolysis method as valuable tool to deposit particle layers of tin dioxide on optical fiber substrates at wavelength scale. Section 5 reports the morphological and optical characterization of the so produced superstrates carried out by atomic force and scanning near-field optical microscopy, very useful to clearly outline the effects of processing parameters on particles size and distribution as wells on the optical near-field emerging from the overlays. Finally, in section 6 we present the sensing performances of fiber optic chemo-sensors incorporating tin dioxide particle layers in both air and liquid environments discussing the dependence of the sensing properties on film morphology and optical near-field. 2. Tin dioxide as sensing material Metal oxides are widely used as sensitive materials for electrical gas sensors in environmental, security and industrial applications. The idea of using semiconductors as gas sensitive devices leads back to 1952 when Brattain and Bardeen first reported gas sensitive effects on germanium (Brattain & Bardeen, 1952). Later, Seiyama et al. found gas sensing effect on metal oxides (Seiyama et al., 1962). The principle of operation of such class of sensors relies upon a change of electrical conductivity of the semiconductor material as a consequence of the gas adsorption. Even if many chemo-physical coupled phenomena, such as surface and bulk chemical reactions and mass and energy diffusion, are involved in the operation of the semiconductor solid state conductivity sensors (Lundstrom, 1996), in general, the sensing principle is dominated by the variation of the electronic properties of wide-band-gap semiconductors such as SnO 2 and ZnO due to the gases adsorption that modifies the intrinsic electronic defect formation (Szklarski, 1989). The gas sensitivity of semiconductor materials is underlain by reversible effects resulting from chemisorption of molecules, formation of space charge areas, and variation of the concentration of the charge carriers in the subsurface layer. Although the general principle of the detection mechanism is appreciated, the size of the change of electric conductivity (sensor signal) is largely determined by the structural type of the semiconductor, the nature and concentration of surface reactive centers, and the real structure of the material: the size, structure, and degree of agglomeration of crystallites, specific surface area, and pore geometry (Rumyantsevaa et al., 2008). In principle, any semiconducting oxide can be exploited as a sensor by monitoring changes of its resistance during interaction with the detected gas molecules at an operating temperature typically above 200 °C. Because tin oxide (SnO 2 ) offers high sensitivity at conveniently low operating temperatures, attention has been concentrated on this material although lately many studies extended also to other oxides. In fact, several commercial devices based on SnO 2 for detecting low concentration of both flammable, i.e. CH 4 and H 2 , and toxic; i.e. CO, H 2 S and NO x , gases, are available. SnO 2 sensors can be referred to as the best-understood prototype of oxide based gas sensors. Nevertheless, highly specific and sensitive SnO 2 sensors are not yet available. It is well known that sensor selectivity can be fine-tuned over a wide range by varying the SnO 2 crystal structure and morphology, dopants, contact geometries, operation temperature or mode of operation, etc. The electric conductivity of oxide semiconductors is extremely sensitive to the composition of the surface, which reversibly varies as a consequence of surface reactions involving chemisorbed oxygen (O 2 – , O 2– , O – ) and the gas mixture components, proceeding at 100–500°C. (Rumyantsevaa et al., 2008; Barsan, et al., 1999). OpticalFibre,NewDevelopments72 Moreover, tin oxide is sensitive to both oxidizing gases, such as ozone, O 3 , and NO 2 , and reducing species, such as CO and CH 4 (Becker, 2001). In particular, in the case of oxidizing gases the raising in conductivity upon gas-solid interaction is due to the injection into the conductivity band of electrons produced by the surface reaction between the gas and the chemically active species, O ads - of tin oxide, as an example CO+ O ads -  CO 2 +e - ; while, in the case of reducing gases, the reactions consume the conduction electrons increasing the tin oxide resistivity, as an example NO 2 + e - NO+ O ads - . In conclusions, the advantages offered by wide-band-gap semiconductor oxides as sensing materials include their stability in air, relative inexpensiveness, and easy preparation in the ultradispersed state (Rumyantsevaa et al., 2008). Three main drawbacks characterize such class of sensors materials: the relatively high operative temperature, the poor selectivity due to unspecificity of the contribution made by the gas phase molecules to the total electric response and the long term drift (Sberveglieri, 1995). 3. State of the art on SnO 2 based sensors The first great production and utilization of tin dioxide based gas sensors started in Japan from a patent (Taguchi, 1962) deposited by Naoyoshi Taguchi in the far 1962. His work was completed in the years 1968-69 when he established mass production and started selling the Taguchi Gas Sensor (TGS) and founded the “Figaro Engineering Inc.” currently a world leader company in gas sensors production. The first TGS was a ceramic thick film sensor using tin-dioxide powder as sensitive element. The rapid success and the grown in the production of the TGSs in the years following the first TGS realization is attributed not only to the exhibited performances but also to the large diffusion in that years in Japan of bottled gas and the consequent numerous accidental gas explosions (Ihokura & Watson, 1994), leading to the need of security gas sensors. After almost fifty years since the first TGS realization, many and many technological advancements in the sensing field strongly widened the classes of available sensors both commercially and in the scientific community. Many of them are still based on tin dioxide as sensitive material. The first generation of sensors based on tin dioxide as sensitive material was manufactured by ceramic thick film technology. In ceramic thick film sensors, the tin dioxide is most commonly sintered onto a substrate, usually of alumina (Ihokura, 1981). In operation, this substrate is heated by an electrically energized filament and the resistance of the active material, which is very high in fresh air, falls as the concentration of (combustible) contaminant gas rises (Watson, 1984). Since thick film sensors’ performance depend on percolation path of electrons through inter- granular regions, by varying small details in the preparation process, each sensor differed slightly in its initial characteristics. Therefore the materials fabrication processes have been improved towards thin film technology, that offers higher reproducibility and long term stability. In order to enhance the performances and the selectivity of these sensors, several approaches have been pursued. An approach consists in the careful choice of the working temperature of the sensor that is able to enhance the sensitivity to certain gases by comparison with others (Fort et al., 2002). Since the optimum oxidation temperatures are different from gas to gas, operating the transducer at two different temperatures leads to the enhancement of the sensor selectivity (Heilig et al., 1999). A large number of additives in SnO 2 , such as In, Cd, Bi 2 O 3 and noble metals (i.e. palladium or platinum) either in thick or in thin films based sensors have been investigated to improve the selectivity and to enhance the response of the tin-dioxide gas sensors (Yamazoe, 1983). These dopants are added to improve sensor sensitivity to a particular gas, to minimize cross sensitivity to other gases and to reduce temperature of operation. Palladium inclusions, for example, leads to a lowering of the sensor resistance, a speeding up of transient behavior and modifies the selectivity characteristics of the sensor by changing the rates of the redox reactions (Watsont et al., 1993; Cirera et al., 2001). The doping of SnO 2 with Pt reduces in particular the optimum operating temperature for sensing CO gas. On the other hand, the doping of SnO 2 with trivalent additive favors the detection of oxidant gases. By suitably selecting the dopant the temperature of device operation can be tailored for a specific application (Erann et al., 2004; Ivanov et al., 2004). Other additives such as gold, rhodium, ruthenium and indium have more significant effects on selectivity, as do several metal oxides including those of lanthanum and copper. A widely employed approach to enhance the sensor selectivity concerns exploiting different measurement techniques and/or data processing algorithms. Of course, these approaches are not limited to tin-oxide based sensors. Nonetheless, interesting results have been achieved also with tin oxide by measuring the transducer conductivity variations during chemical transients obtained with abrupt changes in target molecules concentration. In fact in this case the reaction kinetics can be exploited to differentiate among different compounds (Schweizer-Berberich et al., 2000; Llobet et al., 1997; Ngo et al., 2006). More generally, the realization of an array of sensors with different features and the employment of pattern recognition techniques demonstrated to be a suitable strategy to discriminate among different target molecules (Gardner et al., 1992; Hong et al., 2000; Lee et al., 2001; Delpha et al., 2004). The effect of grain size on the sensitivities of SnO 2 films has been also investigated since 1991, when Yamazoe (Yamazoe, 1991) showed that reduction of crystallite size caused a huge improvement in conductometric sensor performance. In fact, in a low grain size metal oxide almost all the carriers are trapped in surface states and only a few thermal activated carriers are available for conduction. In this configuration the transition from activated to strongly not activated carrier density, produced by target gases species, has a great effect on sensor conductance. The challenge thus became to prepare stable materials with small crystallite size. This process has been assisted by the recent progress in nanotechnology, thank to which fine control over the crystallinity, morphology, composition and doping level of these sensing materials could be obtained. An important step forward has been achieved by the successful preparation of stable single crystal quasi-one-dimensional semiconducting oxides nanostructures (the so-called nanobelts, nanowires or nanoribbons) (Pan et al., 2001; Comini et al., 2002). This was followed by the publication of some fundamental demonstrations (Cui et al., 2001; Law et al., 2002; Arnold et al., 2003; Li et al., 2003) of detecting a variety of chemicals and bio-agents using semiconducting 1-D oxides. Since then, this area has been experiencing significant growth in the past six years and it is not yet clear whether it will reach saturation soon (Comini, 2008; Chen et al., 2008). [...]... concentration of 0.01 mol/l, are reported 9 8 7 6 5 4 3 2 1 0 85 2 .38 3 µm Y[µm] Y[µm] Near-Field Opto-Chemical Sensors 0.000 µm 0 1 2 3 4 5 6 7 8 9 (a) 1.5 53 µm 0.000 µm 0 1 2 3 4 5 6 7 8 9 10 X[µ ] m 12 (c) 12.5 V 0.0 V 0 1 2 3 4 5 6 7 8 9 X[µ ] m Y[µm] Y[µm] X[µ ] m 12 11 10 9 8 7 6 5 4 3 2 1 0 9 8 7 6 5 4 3 2 1 0 12 11 10 9 8 7 6 5 4 3 2 1 0 (b) 11.8 V 0.0 V 0 1 2 3 4 5 6 7 8 9 10 X[µ ] m 12 (d) Fig 8 AFM topographic... significantly influence the optical near-field Optical Fibre, New Developments 10 9 8 7 6 5 4 3 2 1 0 528.4 nm Y[µm] Y[µm] 86 0.0 nm 0 1 2 3 4 5 6 7 8 9 10 11 9 8 7 6 5 4 3 2 1 0 (a) 8.419 µm 0.000 µm 0 1 2 3 4 5 6 7 8 9 X[µ ] m (c) 1.8 V 0.0 V 0 1 2 3 4 5 6 7 8 9 10 11 X[µ ] m Y[µm] Y[µm] X[µ ] m 10 9 8 7 6 5 4 3 2 1 0 9 8 7 6 5 4 3 2 1 0 (b) 10.2 V 0.0 V 0 1 2 3 4 5 6 7 8 9 X[µ ] m (d) Fig 9 AFM topographic... ppm 44 ppm 25 ppm 100 200 30 0 400 500 600 60 120 180 240 30 0 36 0 420 480 540 600 660 Time (min) (a) Output signal variation I (A.U.) TOLUENE VAPORS 0,00 -0,05 -0,10 40 ppm -0,15 -0,20 -0,25 -0 ,30 -0 ,35 -0,40 -0,45 64 ppm 0,0020 0,0015 0,0010 0,0005 0,0000 -0,0005 -0,0010 -0,0015 83 ppm 100 120 200 180 30 0 400 240 SAMPLE E SAMPLE G 500 30 0 36 0 420 480 540 Time (min) (b) Fig 13 Output signal variations... inset in Fig 13 (b)) In particular, with regards sample G, excellent sensitivities (calculated as output signal variation upon concentration unit) of 6.610 -3 ppm-1 92 Optical Fibre, New Developments and 3. 010 -3 ppm-1 for xylene and toluene vapors, respectively, that lead to sub-ppm limits of detection, good and fast reversibility features as well as response times of approximately 25 and 35 minutes,... occurred inside the test chamber, since it is not perfectly thermostated 94 Optical Fibre, New Developments 3, 0 5 5 ppm 5 ppm 1 ppm 1 ppm 2 -5 1 -10 5 ppm 5 ppm 1 ppm 1 ppm 2,0 0 R/R0 (10-2) 3 2,5 T(°C) R/R0 (10-2) 4 1,5 1,0 0,5 0,0 0 0 100 200 Time (min) 30 0 400 (a) -15 -0,5 0 100 200 30 0 Time (min) 400 500 (b) Fig 16 Optical response obtained with the probe Sensor B in correspondence of four injections... Cusano, A (2006) Near Field Behaviour of SnO2 Particle-layers Deposited on Optical Fibers: New Perspectives for Sensing Applications Technical Digest of 18th International Optical Fiber Sensors Conference, Paper TuE77,Cancun, Mexico, October 2006 96 Optical Fibre, New Developments Chen, X H and Moskovits, M (2007) Observing catalysis through the agency of the participating electrons: Surface-chemistry-induced... nichrome wire connected with a 30 0W voltage source The heater was supplied with a chromium-nickel thermocouple connected with a multimeter for the temperature monitoring The distance between the needle and the optical fiber-end was about 30 mm 78 Optical Fibre, New Developments Syringe Sprayed Solution High Voltage Source Fiber Tip Needle Heater Thermocouple Metal Substrate Optical Fiber Mutimeter GND... 2001; Law et al., 2002; Arnold et al., 20 03; Li et al., 20 03) of detecting a variety of chemicals and bio-agents using semiconducting 1-D oxides Since then, this area has been experiencing significant growth in the past six years and it is not yet clear whether it will reach saturation soon (Comini, 2008; Chen et al., 2008) 74 Optical Fibre, New Developments In particular, SnO2 nanowires and nanobelts... of about 700 nm and a mean width of about 550 nm 82 Optical Fibre, New Developments 1.901 µm 15.5 V 10 8 8 Y[µm] 12 10 Y[µm] 12 6 4 0.000 µm 2 0 0 2 4 6 8 X[µ ] m 10 12 (a) 6 4 0.0 V 2 0 0 2 4 6 8 X[µ ] m 10 12 (b) Fig 5 Topographic image of the sample B (a) and optical near-field simultaneously collected by the SNOM probe in the same region (13x 13) μm2 (b) It was demonstrated that this effect can... modify the collected near-field intensity, as it possible to see in Fig 10 (b) 0.0 nm 0 1 2 3 4 5 6 7 8 9 10 11 9 8 7 6 5 4 3 2 1 0 0 1 2 3 4 5 6 7 8 9 10 11 X[µ ] m 15.971 µm 0.000 µm 0 1 2 3 4 5 6 7 8 9 X[µ ] m 0.0 V (a) Y[µm] Y[µm] X[µ ] m 4.7 V 10 9 8 7 6 5 4 3 2 1 0 (c) 9 8 7 6 5 4 3 2 1 0 (b) 11.7 V 0.0 V 0 1 2 3 4 5 6 7 8 9 X[µ ] m (d) Fig 10 AFM topographic images (a), ( c) and near-field intensity . coupling the cantilevered 98765 432 10 9 8 7 6 5 4 3 2 1 0 X[µm] Y[µm] 98765 432 10 9 8 7 6 5 4 3 2 1 0 X[µm] Y[µm] 0.000 µm 2. 036 µm 0.0 V 14 .3 V (a) (b) optical probe to the superluminescent. about 30 mm. Optical Fibre, New Developments7 8 Fig. 2. Schematic view of the experimental set-up used for the deposition of the sensitive layer onto the optical. film surface. Optical Fibre, New Developments8 0 Fig. 3. Scanning probe system: simultaneous atomic force (AFM) and scanning near-field optical microscopy