Functionalised zinc oxide nanowire gas sensors : enhanced NO2 gas sensor response by chemical modification of nanowire surfaces

Surface coating with an organic self-assembled monolayer (SAM) can enhance surface reactions or the absorption of specific gases and hence improve the response of a metal oxide (MOx) sensor toward particular target gases in the environment. In this study the effect of an adsorbed organic layer on the dynamic response of zinc oxide nanowire gas sensors was investigated. The effect of ZnO surface functionalisation by two different organic molecules, tris(hydroxymethyl)aminomethane (THMA) and dodecanethiol (DT), was studied. The response towards ammonia, nitrous oxide and nitrogen dioxide was investigated for three sensor configurations, namely pure ZnO nanowires, organic-coated ZnO nanowires and ZnO nanowires covered with a sparse layer of organic-coated ZnO nanoparticles. Exposure of the nanowire sensors to the oxidising gas NO2 produced a significant and reproducible response. ZnO and THMA-coated ZnO nanowire sensors both readily detected NO2 down to a concentration in the very low ppm range. Notably, the THMA-coated nanowires consistently displayed a small, enhanced response to NO2 compared to uncoated ZnO nanowire sensors. At the lower concentration levels tested, ZnO nanowire sensors that were coated with THMA-capped ZnO nanoparticles were found to exhibit the greatest enhanced response. ΔR/R was two times greater than that for the as-prepared ZnO nanowire sensors. It is proposed that the ΔR/R enhancement in this case originates from the changes induced in the depletion-layer width of the ZnO nanoparticles that bridge ZnO nanowires resulting from THMA ligand binding to the surface of the particle coating. The heightened response and selectivity to the NO2 target are positive results arising from the coating of these ZnO nanowire sensors with organic-SAM-functionalised ZnO nanoparticles.

Gas sensing characteristics of Fe-doped tungsten oxide thin films

This study reports on the gas sensing characteristics of Fe-doped (10 at.%) tungsten oxide thin films of various thicknesses (100–500 nm) prepared by electron beam evaporation. The performance of these films in sensing four gases (H2, NH3, NO2 and N2O) in the concentration range 2–10,000 ppm at operating temperatures of 150–280 °C has been investigated. The results are compared with the sensing performance of a pure WO3 film of thickness 300 nm produced by the same method. Doping of the tungsten oxide film with 10 at.% Fe significantly increases the base conductance of the pure film but decreases the gas sensing response. The maximum response measured in this experiment, represented by the relative change in resistance when exposed to a gas, was ΔR/R = 375. This was the response amplitude measured in the presence of 5 ppm NO2 at an operating temperature of 250 °C using a 400 nm thick WO3:Fe film. This value is slightly lower than the corresponding result obtained using the pure WO3 film (ΔR/R = 450). However it was noted that the WO3:Fe sensor is highly selective to NO2, exhibiting a much higher response to NO2 compared to the other gases. The high performance of the sensors to NO2 was attributed to the small grain size and high porosity of the films, which was obtained through e-beam evaporation and post-deposition heat treatment of the films at 300 °C for 1 h in air.

A comparative study of the number and mass of fine particles emitted with diesel fuel and marine gas oil (MGO)

The current investigation reports on diesel particulate matter emissions, with special interest in fine particles from the combustion of two base fuels. The base fuels selected were diesel fuel and marine gas oil (MGO). The experiments were conducted with a four-stroke, six-cylinder, direct injection diesel engine. The results showed that the fine particle number emissions measured by both SMPS and ELPI were higher with MGO compared to diesel fuel. It was observed that the fine particle number emissions with the two base fuels were quantitatively different but qualitatively similar. The gravimetric (mass basis) measurement also showed higher total particulate matter (TPM) emissions with the MGO. The smoke emissions, which were part of TPM, were also higher for the MGO. No significant changes in the mass flow rate of fuel and the brake-specific fuel consumption (BSFC) were observed between the two base fuels.

Computationally efficient methods for solving time-variable-order time-space fractional reaction-diffusion equation

Fractional differential equations are becoming more widely accepted as a powerful tool in modelling anomalous diffusion, which is exhibited by various materials and processes. Recently, researchers have suggested that rather than using constant order fractional operators, some processes are more accurately modelled using fractional orders that vary with time and/or space. In this paper we develop computationally efficient techniques for solving time-variable-order time-space fractional reaction-diffusion equations (tsfrde) using the finite difference scheme. We adopt the Coimbra variable order time fractional operator and variable order fractional Laplacian operator in space where both orders are functions of time. Because the fractional operator is nonlocal, it is challenging to efficiently deal with its long range dependence when using classical numerical techniques to solve such equations. The novelty of our method is that the numerical solution of the time-variable-order tsfrde is written in terms of a matrix function vector product at each time step. This product is approximated efficiently by the Lanczos method, which is a powerful iterative technique for approximating the action of a matrix function by projecting onto a Krylov subspace. Furthermore an adaptive preconditioner is constructed that dramatically reduces the size of the required Krylov subspaces and hence the overall computational cost. Numerical examples, including the variable-order fractional Fisher equation, are presented to demonstrate the accuracy and efficiency of the approach.

Efficient preconditioning of the method of lines for solving nonlinear two-sided space-fractional diffusion equations

A standard method for the numerical solution of partial differential equations (PDEs) is the method of lines. In this approach the PDE is discretised in space using �finite di�fferences or similar techniques, and the resulting semidiscrete problem in time is integrated using an initial value problem solver. A significant challenge when applying the method of lines to fractional PDEs is that the non-local nature of the fractional derivatives results in a discretised system where each equation involves contributions from many (possibly every) spatial node(s). This has important consequences for the effi�ciency of the numerical solver. First, since the cost of evaluating the discrete equations is high, it is essential to minimise the number of evaluations required to advance the solution in time. Second, since the Jacobian matrix of the system is dense (partially or fully), methods that avoid the need to form and factorise this matrix are preferred. In this paper, we consider a nonlinear two-sided space-fractional di�ffusion equation in one spatial dimension. A key contribution of this paper is to demonstrate how an eff�ective preconditioner is crucial for improving the effi�ciency of the method of lines for solving this equation. In particular, we show how to construct suitable banded approximations to the system Jacobian for preconditioning purposes that permit high orders and large stepsizes to be used in the temporal integration, without requiring dense matrices to be formed. The results of numerical experiments are presented that demonstrate the effectiveness of this approach.

Microcosm study of ion mobilization and greenhouse gas evolution in soils of a plantation-forested subtropical coastal catchment

This study examined the potential for Fe mobilization and greenhouse gas (GHG, e.g. CO2, and CH4) evolution in SEQ soils associated with a range of plantation forestry practices and water-logged conditions. Intact, 30-cm-deep soil cores collected from representative sites were saturated and incubated for 35 days in the laboratory, with leachate and headspace gas samples periodically collected. Minimal Fe dissolution was observed in well-drained sand soils associated with mature, first-rotation Pinus and organic Fe complexation, whereas progressive Fe dissolution occurred over 14 days in clear-felled and replanted Pinus soils with low organic matter and non-crystalline Fe fractions. Both CO2 and CH4 effluxes were relatively lower in clear-felled and replanted soils compared with mature, first-rotation Pinus soils, despite the lack of statistically significant variations in total GHG effluxes associated with different forestry practices. Fe dissolution and GHG evolution in low-lying, water-logged soils adjacent to riparian and estuarine, native-vegetation buffer zones were impacted by mineral and physical soil properties. Highest levels of dissolved Fe and GHG effluxes resulted from saturation of riparian loam soils with high Fe and clay content, as well as abundant organic material and Fe-metabolizing bacteria. Results indicate Pinus forestry practices such as clear-felling and replanting may elevate Fe mobilization while decreasing CO2 and CH4 emissions from well-drained, SEQ plantation soils upon heavy flooding. Prolonged water-logging accelerates bacterially mediated Fe cycling in low-lying, clay-rich soils, leading to substantial Fe dissolution, organic matter mineralization, and CH4 production in riparian native-vegetation buffer zones.

Offsetting greenhouse gas emissions through biological carbon sequestration in North Eastern Australia

The Kyoto Protocol recognises trees as a sink of carbon and a valid means to offset greenhouse gas emissions and meet internationally agreed emissions targets. This study details biological carbon sequestration rates for common plantation species Araucaria cunninghamii (hoop pine), Eucalyptus cloeziana, Eucalyptus argophloia, Pinus elliottii and Pinus caribaea var hondurensis and individual land areas required in north-eastern Australia to offset greenhouse gas emissions of 1000tCO 2e. The 3PG simulation model was used to predict above and below-ground estimates of biomass carbon for a range of soil productivity conditions for six representative locations in agricultural regions of north-eastern Australia. The total area required to offset 1000tCO 2e ranges from 1ha of E. cloeziana under high productivity conditions in coastal North Queensland to 45ha of hoop pine in low productivity conditions of inland Central Queensland. These areas must remain planted for a minimum of 30years to meet the offset of 1000tCO 2e.

Numerical methods for solving the multi-term time-fractional wave-diffusion equations

In this paper, the multi-term time-fractional wave diffusion equations are considered. The multiterm time fractional derivatives are defined in the Caputo sense, whose orders belong to the intervals [0,1], [1,2), [0,2), [0,3), [2,3) and [2,4), respectively. Some computationally effective numerical methods are proposed for simulating the multi-term time-fractional wave-diffusion equations. The numerical results demonstrate the effectiveness of theoretical analysis. These methods and techniques can also be extended to other kinds of the multi-term fractional time-space models with fractional Laplacian.

Development of a gas nanosensor node powered by solar cells

This work focuses on the development of a stand-alone gas nanosensor node, powered by solar energy to track concentration of polluted gases such as NO2, N2O, and NH3. Gas sensor networks have been widely developed over recent years, but the rise of nanotechnology is allowing the creation of a new range of gas sensors [1] with higher performance, smaller size and an inexpensive manufacturing process. This work has created a gas nanosensor node prototype to evaluate future field performance of this new generation of sensors. The sensor node has four main parts: (i) solar cells; (ii) control electronics; (iii) gas sensor and sensor board interface [2-4]; and (iv) data transmission. The station is remotely monitored through wired (ethernet cable) or wireless connection (radio transmitter) [5, 6] in order to evaluate, in real time, the performance of the solar cells and sensor node under different weather conditions. The energy source of the node is a module of polycrystalline silicon solar cells with 410cm2 of active surface. The prototype is equipped with a Resistance-To-Period circuit [2-4] to measure the wide range of resistances (KΩ to GΩ) from the sensor in a simple and accurate way. The system shows high performance on (i) managing the energy from the solar panel, (ii) powering the system load and (iii) recharging the battery. The results show that the prototype is suitable to work with any kind of resistive gas nanosensor and provide useful data for future nanosensor networks.

Analytical solutions for the multi-term time-space Caputo-Riesz fractional advection-diffusion equations on a finite domain

Generalized fractional partial differential equations have now found wide application for describing important physical phenomena, such as subdiffusive and superdiffusive processes. However, studies of generalized multi-term time and space fractional partial differential equations are still under development. In this paper, the multi-term time-space Caputo-Riesz fractional advection diffusion equations (MT-TSCR-FADE) with Dirichlet nonhomogeneous boundary conditions are considered. The multi-term time-fractional derivatives are defined in the Caputo sense, whose orders belong to the intervals [0, 1], [1, 2] and [0, 2], respectively. These are called respectively the multi-term time-fractional diffusion terms, the multi-term time-fractional wave terms and the multi-term time-fractional mixed diffusion-wave terms. The space fractional derivatives are defined as Riesz fractional derivatives. Analytical solutions of three types of the MT-TSCR-FADE are derived with Dirichlet boundary conditions. By using Luchko's Theorem (Acta Math. Vietnam., 1999), we proposed some new techniques, such as a spectral representation of the fractional Laplacian operator and the equivalent relationship between fractional Laplacian operator and Riesz fractional derivative, that enabled the derivation of the analytical solutions for the multi-term time-space Caputo-Riesz fractional advection-diffusion equations. © 2012.

Numerical techniques for the variable order time fractional diffusion equation

In this paper we consider the variable order time fractional diffusion equation. We adopt the Coimbra variable order (VO) time fractional operator, which defines a consistent method for VO differentiation of physical variables. The Coimbra variable order fractional operator also can be viewed as a Caputo-type definition. Although this definition is the most appropriate definition having fundamental characteristics that are desirable for physical modeling, numerical methods for fractional partial differential equations using this definition have not yet appeared in the literature. Here an approximate scheme is first proposed. The stability, convergence and solvability of this numerical scheme are discussed via the technique of Fourier analysis. Numerical examples are provided to show that the numerical method is computationally efficient. Crown Copyright © 2012 Published by Elsevier Inc. All rights reserved.

Analytical solutions for the multi-term time-fractional diffusion-wave/diffusion equations in a finite domain

Multi-term time-fractional differential equations have been used for describing important physical phenomena. However, studies of the multi-term time-fractional partial differential equations with three kinds of nonhomogeneous boundary conditions are still limited. In this paper, a method of separating variables is used to solve the multi-term time-fractional diffusion-wave equation and the multi-term time-fractional diffusion equation in a finite domain. In the two equations, the time-fractional derivative is defined in the Caputo sense. We discuss and derive the analytical solutions of the two equations with three kinds of nonhomogeneous boundary conditions, namely, Dirichlet, Neumann and Robin conditions, respectively.

Towards the development of a gas sensor system for monitoring pollutant gases in the low troposphere using small unmanned aerial vehicles

The world is facing problems due to the effects of increased atmospheric pollution, climate change and global warming. Innovative technologies to identify, quantify and assess fluxes exchange of the pollutant gases between the Earth’s surface and atmosphere are required. This paper proposes the development of a gas sensor system for a small UAV to monitor pollutant gases, collect data and geo-locate where the sample was taken. The prototype has two principal systems: a light portable gas sensor and an optional electric–solar powered UAV. The prototype will be suitable to: operate in the lower troposphere (100-500m); collect samples; stamp time and geo-locate each sample. One of the limitations of a small UAV is the limited power available therefore a small and low power consumption payload is designed and built for this research. The specific gases targeted in this research are NO2, mostly produce by traffic, and NH3 from farming, with concentrations above 0.05 ppm and 35 ppm respectively which are harmful to human health. The developed prototype will be a useful tool for scientists to analyse the behaviour and tendencies of pollutant gases producing more realistic models of them.

Thermally evaporated tungsten oxide (WO3) thin films for gas sensing applications

In this thesis, the author proposed and developed gas sensors made of nanostructured WO3 thin film by a thermal evaporation technique. This technique gives control over film thickness, grain size and purity. The device fabrication, nanostructured material synthesis, characterization and gas sensing performance have been undertaken. Three different types of nanostructured thin films, namely, pure WO3 thin films, iron-doped WO3 thin films by co-evaporation and Fe-implanted WO3 thin films have been synthesized. All the thin films have a film thickness of 300 nm. The physical, chemical and electronic properties of these films have been optimized by annealing heat treatment at 300ºC and 400ºC for 2 hours in air. Various analytical techniques were employed to characterize these films. Atomic Force Microscopy and Transmission Electron Microscopy revealed a very small grain size of the order 5-10 nm in as-deposited WO3 films, and annealing at 300ºC or 400ºC did not result in any significant change in grain size. X-ray diffraction (XRD) analysis revealed a highly amorphous structure of as-deposited films. Annealing at 300ºC for 2 hours in air did not improve crystallinity in these films. However, annealing at 400ºC for 2 hours in air significantly improved the crystallinity in pure and iron-doped WO3 thin films, whereas it only slightly improved the crystallinity of iron-implanted WO3 thin film as a result of implantation. Rutherford backscattered spectroscopy revealed an iron content of 0.5 at.% and 5.5 at.% in iron-doped and iron-implanted WO3 thin films, respectively. The RBS results have been confirmed using energy dispersive x-ray spectroscopy (EDX) during analysis of the films using transmission electron microscopy (TEM). X-ray photoelectron spectroscopy (XPS) revealed significant lowering of W 4f7/2 binding energy in all films annealed at 400ºC as compared with the as-deposited and 300ºC annealed films. Lowering of W 4f7/2 is due to increase in number of oxygen vacancies in the films and is considered highly beneficial for gas sensing. Raman analysis revealed that 400ºC annealed films except the iron-implanted film are highly crystalline with significant number of O-W-O bonds, which was consistent with the XRD results. Additionally, XRD, XPS and Raman analyses showed no evidence of secondary peaks corresponding to compounds of iron due to iron doping or implantation. This provided an understanding that iron was incorporated in the host WO3 matrix rather than as a separate dispersed compound or as catalyst on the surface. WO3 thin film based gas sensors are known to operate efficiently in the temperature range 200ºC-500 ºC. In the present study, by optimizing the physical, chemical and electronic properties through heat treatment and doping, an optimum response to H2, ethanol and CO has been achieved at a low operating temperature of 150ºC. Pure WO3 thin film annealed at 400ºC showed the highest sensitivity towards H2 at 150ºC due to its very small grain size and porosity, coupled with high number of oxygen vacancies, whereas Fe-doped WO3 film annealed at 400ºC showed the highest sensitivity to ethanol at an operating temperature of 150ºC due to its crystallinity, increased number of oxygen vacancies and higher degree of crystal distortions attributed to Fe addition. Pure WO3 films are known to be insensitive to CO, but iron-doped WO3 thin film annealed at 300ºC and 400ºC showed an optimum response to CO at an operating temperature of 150ºC. This result is attributed to lattice distortions produced in WO3 host matrix as a result of iron incorporation as substitutional impurity. However, iron-implanted WO3 thin films did not show any promising response towards the tested gases as the film structure has been damaged due to implantation, and annealing at 300ºC or 400ºC was not sufficient to induce crystallinity in these films. This study has demonstrated enhanced sensing properties of WO3 thin film sensors towards CO at lower operating temperature, which was achieved by optimizing the physical, chemical and electronic properties of the WO3 film through Fe doping and annealing. This study can be further extended to systematically investigate the effects of different Fe concentrations (0.5 at.% to 10 at.%) on the sensing performance of WO3 thin film gas sensors towards CO.