Optical immersion of mid-infrared LEDs and photodiodes for gas-sensing applications

The high gains in performance predicted for optical immersion are difficult to achieve in practice due to total internal reflection at the lens/detector interface. By reducing the air gap at this interface optical tunneling becomes possible and the predicted gains can be realized in practical devices. Using this technique we have demonstrated large performance gains by optically immersing mid-infrared heterostructure InA1Sb LEDs and photodiodes using hypershperical germanium lenses. The development of an effective method of optical immersion that gives excellent optical coupling has produced a photodiode with a peak room temperature detectivity (D*) of 5.3 x 109 cmHz½W-1 at λpeak=5.4μm and a 40° field of view. A hyperspherically immersed LED showed a f-fold improvement in the external efficiency, and a 3-fold improvement in the directionality compared with a conventional planar LED for f/2 optical systems. The incorporation of these uncooled devices in a White cell produced a NO2 gas sensing system with 2 part-per-million sensitivity, with an LED drive current of <5mA. These results represent a significant advance in the use of solid state devices for portable gas sensing systems.

Structural and gas-sensing properties of WO3 nanocrystalline powders obtained by a sol-gel method from tungstic acid

WO3 nanocrystalline powders were obtained from tungstic acid following a sol-gel process. Evolution of structural properties with annealing temperature was studied by X-ray diffraction and Raman spectroscopy. These structural properties were compared with those of WO3 nanopowders obtained by the most common process of pyrolysis of ammonium paratungstate, usually used in gas sensors applications. Sol-gel WO3 showed a high sensor response to NO2 and low response to CO and CH4. The response of these sensor devices was compared with that of WO3 obtained from pyrolysis, showing the latter a worse sensor response to NO2. Influence of operating temperature, humidity, and film thickness on NO2 detection was studied in order to improve the sensing conditions to this gas.

Gas-sensing properties of sprayed films of (CdO)x(ZnO)1-x mixed oxide

A novel NO2 sensor based on (CdO)x(ZnO)1-x mixed-oxide thin films deposited by the spray pyrolysis technique is developed. The sensor response to 3-ppm NO2 is studied in the range 50°C-350°C for three different film compositions. The device is also tested for other harmful gases, such as CO (300 ppm) and CH4 (3000 ppm). The sensor response to these reducing gases is different at different temperatures varying from the response typical for the p-type semiconductor to that typical for the n-type semiconductor. Satisfactory response to NO2 and dynamic behavior at 230°C, as well as low resistivity, are observed for the mixed-oxide film with 30% Cd. The response to interfering gas is poor at working temperature (230°C). On the basis of this study, a possible sensing mechanism is proposed.

Gas sensing properties of catalytically modified WO3 with copper and vanadium for NH3 detection

Ammonia gas detection by pure and catalytically modified WO3 based gas sensor was analysed. The sensor response of pure WO3 to NH3 was not only rather low but also presented an abnormal behaviour, probably due to the unselective oxidation of ammonia to NOx. Copper and vanadium were introduced in different concentrations and the resulting material was annealed at different temperatures in order to improve the sensing properties for NH3 detection. The introduction of copper and vanadium as catalytic additives improved the response to NH3 and also eliminated the abnormal behaviour. Possible mechanisms of NH3 reaction over these materials are discussed. Sensor responses to other gases like NO2 or CO and the interference of humidity on ammonia detection were also analysed so as to choose the best sensing element.

Nonlinear inverse dynamic models of gas sensing systems based on chemical sensor arrays for quantitative measurements

Gas sensing systems based on low-cost chemical sensor arrays are gaining interest for the analysis of multicomponent gas mixtures. These sensors show different problems, e.g., nonlinearities and slow time-response, which can be partially solved by digital signal processing. Our approach is based on building a nonlinear inverse dynamic system. Results for different identification techniques, including artificial neural networks and Wiener series, are compared in terms of measurement accuracy.

Porous silicon optical filters in gas sensing applications

In this thesis, the gas sensing properties of porous silicon-based thin-film optical filters are explored. The effects of surface chemistry on the adsorption and desorption of various gases are studied in detail. Special emphasis is placed on investigating thermal carbonization as a stabilization method for optical sensing applications. Moreover, the possibility of utilizing the increased electrical conductivity of thermally carbonized porous silicon for implementing a multiparametric gas sensor, which would enable simultaneous monitoring of electrical and optical parameters, is investigated. In addition, different porous silicon-based optical filter-structures are prepared, and their properties in sensing applications are evaluated and compared. First and foremost, thermal carbonization is established as a viable method to stabilize porous silicon optical filters for chemical sensing applications. Furthermore, a multiparametric sensor, which can be used for increasing selectivity in gas sensing, is also demonstrated. Methods to improve spectral quality in multistopband mesoporous silicon rugate filters are studied, and structural effects to gas sorption kinetics are evaluated. Finally, the stability of thermally carbonized optical filters in basic environments is found to be superior in comparison to other surface chemistries currently available for porous silicon. The results presented in this thesis are of particular interest for developing novel reliable sensing systems based on porous silicon, e.g., label-free optical biosensors.

Development and characterization of thin printed films for gas sensing applications

The monitoring and control of hydrogen sulfide (H2S) level is of great interest for a wide range of application areas including food quality control, defense and antiterrorist applications and air quality monitoring e.g. in mines. H2S is a very poisonous and flammable gas. Exposure to low concentrations of H2S can result in eye irritation, a sore throat and cough, shortness of breath, and fluid retention in the lungs. These symptoms usually disappear in a few weeks. Long-term, low-level exposure may result in fatigue, loss of appetite, headache, irritability, poor memory, and dizziness. Higher concentrations of 700 - 800 ppm tend to be fatal. H2S has a characteristic smell of rotten egg. However, because of temporary paralysis of olfactory nerves, the smelling capability at concentrations higher than 100 ppm is severely compromised. In addition, volatile H2S is one of the main products during the spoilage of poultry meat in anaerobic conditions. Currently, no commercial H2S sensor is available which can operate under anaerobic conditions and can be easily integrated in the food packaging. This thesis presents a step-wise progress in the development of printed H2S gas sensors. Efforts were made in the formulation, characterization and optimization of functional printable inks and coating pastes based on composites of a polymer and a metal salt as well as a composite of a metal salt and an organic acid. Different processing techniques including inkjet printing, flexographic printing, screen printing and spray coating were utilized in the fabrication of H2S sensors. The dispersions were characterized by measuring turbidity, surface tension, viscosity and particle size. The sensing films were characterized using X-ray photoelectron spectroscopy, X-ray diffraction, atomic force microscopy and an electrical multimeter. Thin and thick printed or coated films were developed for gas sensing applications with the aim of monitoring the H2S concentrations in real life applications. Initially, a H2S gas sensor based on a composite of polyaniline and metal salt was developed. Both aqueous and solvent-based dispersions were developed and characterized. These dispersions were then utilized in the fabrication of roll-to-roll printed H2S gas sensors. However, the humidity background, long term instability and comparatively lower detection limit made these sensors less favourable for real practical applications. To overcome these problems, copper acetate based sensors were developed for H2S gas sensing. Stable inks with excellent printability were developed by tuning the surface tension, viscosity and particle size. This enabled the formation of inkjet-printed high quality copper acetate films with excellent sensitivity towards H2S. Furthermore, these sensors showed negligible humidity effects and improved selectivity, response time, lower limit of detection and coefficient of variation. The lower limit of detection of copper acetate based sensors was further improved to sub-ppm level by incorporation of catalytic gold nano-particles and subsequent plasma treatment of the sensing film. These sensors were further integrated in an inexpensive wirelessly readable RLC-circuit (where R is resistor, L is inductor and C is capacitor). The performance of these sensors towards biogenic H2S produced during the spoilage of poultry meat in the modified atmosphere package was also demonstrated in this thesis. This serves as a proof of concept that these sensors can be utilized in real life applications.

Sol-gel synthesis of mesoporous CaCu3Ti4O12 thin films and their gas sensing response

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

P-type semiconducting gas sensing behavior of nanoporous rf sputtered CaCu3Ti4O12 thin films

The fabrication of nanoporous sputtered CaCu3Ti4O12 thin films with high gas sensitivity is reported in this work. The porous microstructure and the nanocrystalline nature of the material promoted the diffusion of the atmosphere into the film, shortening the response time of the samples. Behaving as p-type semiconductor, the material presents enhanced sensitivity even at low working temperatures. Impedance spectroscopy measurements were performed in order to investigate the mechanisms responsible for the performance of the devices. (C) 2008 American Institute of Physics.

The role of hierarchical morphologies in the superior gas sensing performance of CuO-based chemiresistors

The development of gas sensors with innovative designs and advanced functional materials has attracted considerable scientific interest given their potential for addressing important technological challenges. This work presents new insight towards the development of high-performance p-type semiconductor gas sensors. Gas sensor test devices, based on copper (II) oxide (CuO) with innovative and unique designs (urchin-like, fiber-like, and nanorods), are prepared by a microwave-assisted synthesis method. The crystalline composition, surface area, porosity, and morphological characteristics are studied by X-ray powder diffraction, nitrogen adsorption isotherms, field-emission scanning electron microscopy and high-resolution transmission electron microscopy. Gas sensor measurements, performed simultaneously on multiple samples, show that morphology can have a substantial influence on gas sensor performance. An assembly of urchin-like structures is found to be most effective for hydrogen detection in the range of parts-per-million at 200 °C with 300-fold larger response than the previously best reported values for semiconducting CuO hydrogen gas sensors. These results show that morphology plays an important role in the gas sensing performance of CuO and can be effectively applied in the further development of gas sensors based on p-type semiconductors. High-performance gas sensors based on CuO hierarchical morphologies with in situ gas sensor comparison are reported. Urchin-like morphologies with high hydrogen sensitivity and selectivity that show chemical and thermal stability and low temperature operation are analyzed. The role of morphological influences in p-type gas sensor materials is discussed. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An investigation into the influence of zinc precursor on the microstructural, photoluminescence, and gas-sensing properties of ZnO nanoparticles

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Low refractive index gas sensing using a Surface Plasmon Resonance fibre device

A series of surface plasmonic fibre devices were fabricated using multiple coatings deposited on a lapped section of a single mode fibre. Coupling from the guided mode to surface plasmons was promoted following UV laser irradiation of the coated region through a phase mask, which generated a surface relief grating structure. The devices showed high spectral sensitivities and strong coupling for low refractive indices as compared to other grating-type fibre devices. The plasmonic devices were used to detect the variation in the refractive indices of alkane gases with measured wavelength and coupling sensitivity to index of 3400 nm RIU-1 and 8300 dB RIU-1, respectively. As a demonstration of the performance of these gas sensors, a minimum concentration of 2% by volume of butane in ethane was achieved.

Superior gas-sensing performance of amorphous CdO nanoflake arrays prepared at room temperature

Highly sensitive and selective detection of volatile organic compounds (VOCs) with fast response time is imperative based on safety requirements, yet often remains a challenge. Herein, we propose an effective solution, preparing a novel gas sensor comprised of amorphous nanoflake arrays (a-NFAs) with specific surface groups. The sensor was produced via an extremely simple process in which a-NFAs of CdO were deposited directly onto an interdigital electrode immersed in a chemical bath under ambient conditions. Upon exposure to a widely used VOC, diethyl ether (DEE), the sensor exhibits excellent performance, more specifically, the quickest response, lowest detection limit and highest selectivity ever reported for DEE as a target gas. The superior gas-sensing properties of the prepared a-NFAs are found to arise from their open trumpet-shaped morphology, defect-rich amorphous nature, and surface CO groups.

A Generalized Fuzzy Linguistic Model for Predicting Component Concentrations in an Optical Gas Sensing System

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

A generalized fuzzy linguistic model for predicting component concentrations in an optical gas sensing system

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NO_x, SO₂ etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.