807 resultados para OPTICAL SENSING


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Al-doped zinc oxide (AZO) thin films are deposited onto glass substrates using radio-frequency reactive magnetron sputtering and the improvements in their physical properties by post-synthesis thermal treatment are reported. X-ray diffraction spectra show that the structure of films can be controlled by adjusting the annealing temperatures, with the best crystallinity obtained at 400°C under a nitrogen atmosphere. These films exhibit improved quality and better optical transmittance as indicated by the UV-Vis spectra. Furthermore, the sheet resistivity is found to decrease from 1.87 × 10-3 to 5.63 × 10-4Ω⋅cm and the carrier mobility increases from 6.47 to 13.43 cm2 ⋅ V-1 ⋅ s-1 at the optimal annealing temperature. Our results demonstrate a simple yet effective way in controlling the structural, optical and electrical properties of AZO thin films, which is important for solar cell applications.

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Structural stability, electronic, and optical properties of InN under high pressure are studied using the first-principles calculations. The lattice constants and electronic band structure are found consistent with the available experimental and theoretical values. The pressure of the wurtzite-to-rocksalt structural transition is 13.4 GPa, which is in an excellent agreement with the most recent experimental values. The optical characteristics reproduce the experimental data thus justifying the feasibility of our theoretical predictions of the optical properties of InN at high pressures.

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This paper reports on ab initio numerical simulations of the effect of Co and Cu dopings on the electronic structure and optical properties of ZnO, pursued to develop diluted magnetic semiconductors vitally needed for spintronic applications. The simulations are based upon the Perdew-Burke-Enzerh generalized gradient approximation on the density functional theory. It is revealed that the electrons with energies close to the Fermi level effectively transfer only between Cu and Co ions which substitute Zn atoms, and are located in the neighbor sites connected by an O ion. The simulation results are consistent with the experimental observations that addition of Cu helps achieve stable ferromagnetism of Co-doped ZnO. It is shown that simultaneous insertion of Co and Cu atoms leads to smaller energy band gap, redshift of the optical absorption edge, as well as significant changes in the reflectivity, dielectric function, refractive index, and electron energy loss function of ZnO as compared to the doping with either Co or Cu atoms. These highly unusual optical properties are explained in terms of the computed electronic structure and are promising for the development of the next-generation room-temperature ferromagnetic semiconductors for future spintronic devices on the existing semiconductor micromanufacturing platform.

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This paper investigates compressed sensing using hidden Markov models (HMMs) and hence provides an extension of recent single frame, bounded error sparse decoding problems into a class of sparse estimation problems containing both temporal evolution and stochastic aspects. This paper presents two optimal estimators for compressed HMMs. The impact of measurement compression on HMM filtering performance is experimentally examined in the context of an important image based aircraft target tracking application. Surprisingly, tracking of dim small-sized targets (as small as 5-10 pixels, with local detectability/SNR as low as − 1.05 dB) was only mildly impacted by compressed sensing down to 15% of original image size.

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Recent research in the rapidly emerging field of plasmonics has shown the potential to significantly enhance light trapping inside thin-film solar cells by using metallic nanoparticles. In this article it is demonstrated the plasmon enhancement of optical absorption in amorphous silicon solar cells by using silver nanoparticles. Based on the analysis of the higher-order surface plasmon modes, it is shown how spectral positions of the surface plasmons affect the plasmonic enhancement of thin-film solar cells. By using the predictive 3D modeling, we investigate the effect of the higher-order modes on that enhancement. Finally, we suggest how to maximize the light trapping and optical absorption in the thin-film cell by optimizing the nanoparticle array parameters, which in turn can be used to fine tune the corresponding surface plasmon modes.

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Strong electromagnetic field enhancement that occurs under conditions of the surface plasmon excitation in metallic nanoparticles deposited on a semiconductor surface is a very efficient and promising tool for increasing the optical absorption within semiconductor solar cells and, hence, their photocurrent response. The enhancement of the optical absorption in thin-film silicon solar cells via the excitation of localized surface plasmons in spherical silver nanoparticles is investigated. Using the effective medium model, the effect of the nanoparticle size and the surface coverage on that enhancement is analyzed. The optimum configuration and the nanoparticle parameters leading to the maximum enhancement in the optical absorption and the photocurrent response in a single p-n junction silicon cell are obtained. The effect of coupling between the silicon layer and the surface plasmon fields on the efficiency of the above enhancement is quantified as well.

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Experimentally observed optical and photoelectrical spectra of nitrogen-contaminated (unintentionally doped) nano-crystalline CVD diamond films are simulated using semi-empirical adiabatic General Skettrup Model (GSM), which presumes dominant contributions of defect states from sp 3-coordinated intra-granular carbon atoms to intra-band single electron spectrum N(E) of the material. This picture disagrees with a common viewpoint that the N(E) spectrum of the gap states in diamond powders and polycrystalline CVD films mainly originates from π and π* bonds of sp2-coordinated carbon atoms, which are distributed nearly uniformly over outer surfaces and/or interfaces of the diamond grains. The GSM predicts as well strong effect of granular morphology on the density of intra-band defect states in polycrystalline diamonds.

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An attempt was made to investigate the optical emission spectra of atomic, molecular, and ionic species in low-frequency, high-density ICP discharges in pure nitrogen, ar con gases, and gas mixtures Ar+H2, N2+Ar, and N2+H2. The excited species were identified by in situ optical emission intensity (OEI) measurements in the discharge chamber. In general, significant results were obtained.

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The effect of temperature on childhood pneumonia in subtropical regions is largely unknown so far. This study examined the impact of temperature on childhood pneumonia in Brisbane, Australia. A quasi-Poisson generalized linear model combined with a distributed lag non linear model was used to quantify the main effect of temperature on emergency department visits (EDVs) for childhood pneumonia in Brisbane from 2001 to 2010. The model residuals were checked to identify added effects due to heat waves or cold spells. Both high and low temperatures were associated with an increase in EDVs for childhood pneumonia. Children aged 2–5 years, and female children were particularly vulnerable to the impacts of heat and cold, and Indigenous children were sensitive to heat. Heat waves and cold spells had significant added effects on childhood pneumonia, and the magnitude of these effects increased with intensity and duration. There were changes over time in both the main and added effects of temperature on childhood pneumonia. Children, especially those female and Indigenous, should be particularly protected from extreme temperatures. Future development of early warning systems should take the change over time in the impact of temperature on children’s health into account.

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The ability to build high-fidelity 3D representations of the environment from sensor data is critical for autonomous robots. Multi-sensor data fusion allows for more complete and accurate representations. Furthermore, using distinct sensing modalities (i.e. sensors using a different physical process and/or operating at different electromagnetic frequencies) usually leads to more reliable perception, especially in challenging environments, as modalities may complement each other. However, they may react differently to certain materials or environmental conditions, leading to catastrophic fusion. In this paper, we propose a new method to reliably fuse data from multiple sensing modalities, including in situations where they detect different targets. We first compute distinct continuous surface representations for each sensing modality, with uncertainty, using Gaussian Process Implicit Surfaces (GPIS). Second, we perform a local consistency test between these representations, to separate consistent data (i.e. data corresponding to the detection of the same target by the sensors) from inconsistent data. The consistent data can then be fused together, using another GPIS process, and the rest of the data can be combined as appropriate. The approach is first validated using synthetic data. We then demonstrate its benefit using a mobile robot, equipped with a laser scanner and a radar, which operates in an outdoor environment in the presence of large clouds of airborne dust and smoke.

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Monitoring gases for environmental, industrial and agricultural fields is a demanding task that requires long periods of observation, large quantity of sensors, data management, high temporal and spatial resolution, long term stability, recalibration procedures, computational resources, and energy availability. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) are currently representing the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialised gas sensing systems, and offer the possibility of geo-located and time stamp samples. However, these technologies are not fully functional for scientific and commercial applications as their development and availability is limited by a number of factors: the cost of sensors required to cover large areas, their stability over long periods, their power consumption, and the weight of the system to be used on small UAVs. Energy availability is a serious challenge when WSN are deployed in remote areas with difficult access to the grid, while small UAVs are limited by the energy in their reservoir tank or batteries. Another important challenge is the management of data produced by the sensor nodes, requiring large amount of resources to be stored, analysed and displayed after long periods of operation. In response to these challenges, this research proposes the following solutions aiming to improve the availability and development of these technologies for gas sensing monitoring: first, the integration of WSNs and UAVs for environmental gas sensing in order to monitor large volumes at ground and aerial levels with a minimum of sensor nodes for an effective 3D monitoring; second, the use of solar energy as a main power source to allow continuous monitoring; and lastly, the creation of a data management platform to store, analyse and share the information with operators and external users. The principal outcomes of this research are the creation of a gas sensing system suitable for monitoring any kind of gas, which has been installed and tested on CH4 and CO2 in a sensor network (WSN) and on a UAV. The use of the same gas sensing system in a WSN and a UAV reduces significantly the complexity and cost of the application as it allows: a) the standardisation of the signal acquisition and data processing, thereby reducing the required computational resources; b) the standardisation of calibration and operational procedures, reducing systematic errors and complexity; c) the reduction of the weight and energy consumption, leading to an improved power management and weight balance in the case of UAVs; d) the simplification of the sensor node architecture, which is easily replicated in all the nodes. I evaluated two different sensor modules by laboratory, bench, and field tests: a non-dispersive infrared module (NDIR) and a metal-oxide resistive nano-sensor module (MOX nano-sensor). The tests revealed advantages and disadvantages of the two modules when used for static nodes at the ground level and mobile nodes on-board a UAV. Commercial NDIR modules for CO2 have been successfully tested and evaluated in the WSN and on board of the UAV. Their advantage is the precision and stability, but their application is limited to a few gases. The advantages of the MOX nano-sensors are the small size, low weight, low power consumption and their sensitivity to a broad range of gases. However, selectivity is still a concern that needs to be addressed with further studies. An electronic board to interface sensors in a large range of resistivity was successfully designed, created and adapted to operate on ground nodes and on-board UAV. The WSN and UAV created were powered with solar energy in order to facilitate outdoor deployment, data collection and continuous monitoring over large and remote volumes. The gas sensing, solar power, transmission and data management systems of the WSN and UAV were fully evaluated by laboratory, bench and field testing. The methodology created to design, developed, integrate and test these systems was extensively described and experimentally validated. The sampling and transmission capabilities of the WSN and UAV were successfully tested in an emulated mission involving the detection and measurement of CO2 concentrations in a field coming from a contaminant source; the data collected during the mission was transmitted in real time to a central node for data analysis and 3D mapping of the target gas. The major outcome of this research is the accomplishment of the first flight mission, never reported before in the literature, of a solar powered UAV equipped with a CO2 sensing system in conjunction with a network of ground sensor nodes for an effective 3D monitoring of the target gas. A data management platform was created using an external internet server, which manages, stores, and shares the data collected in two web pages, showing statistics and static graph images for internal and external users as requested. The system was bench tested with real data produced by the sensor nodes and the architecture of the platform was widely described and illustrated in order to provide guidance and support on how to replicate the system. In conclusion, the overall results of the project provide guidance on how to create a gas sensing system integrating WSNs and UAVs, how to power the system with solar energy and manage the data produced by the sensor nodes. This system can be used in a wide range of outdoor applications, especially in agriculture, bushfires, mining studies, zoology, and botanical studies opening the way to an ubiquitous low cost environmental monitoring, which may help to decrease our carbon footprint and to improve the health of the planet.

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In this paper we demonstrate that existing cooperative spectrum sensing formulated for static primary users cannot accurately detect dynamic primary users regardless of the information fusion method. Performance error occurs as the sensing parameters calculated by the conventional detector result in sensing performance that violates the sensing requirements. Furthermore, the error is accumulated and compounded by the number of cooperating nodes. To address this limitation, we design and implement the duty cycle detection model for the context of cooperative spectrum sensing to accurately calculate the sensing parameters that satisfy the sensing requirements. We show that longer sensing duration is required to compensate for dynamic primary user traffic.

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Effective control of morphology and electrical connectivity of networks of single-walled carbon nanotubes (SWCNTs) by using rough, nanoporous silica supports of Fe catalyst nanoparticles in catalytic chemical vapor deposition is demonstrated experimentally. The very high quality of the nanotubes is evidenced by the G-to-D Raman peak ratios (>50) within the range of the highest known ratios. Transitions from separated nanotubes on smooth SiO2 surface to densely interconnected networks on the nanoporous SiO2 are accompanied by an almost two-order of magnitude increase of the nanotube density. These transitions herald the hardly detectable onset of the nanoscale connectivity and are confirmed by the microanalysis and electrical measurements. The achieved effective nanotube interconnection leads to the dramatic, almost three-orders of magnitude decrease of the SWCNT network resistivity compared to networks of similar density produced by wet chemistry-based assembly of preformed nanotubes. The growth model, supported by multiscale, multiphase modeling of SWCNT nucleation reveals multiple constructive roles of the porous catalyst support in facilitating the catalyst saturation and SWCNT nucleation, consistent with the observed higher density of longer nanotubes. The associated mechanisms are related to the unique surface conditions (roughness, wettability, and reduced catalyst coalescence) on the porous SiO2 and the increased carbon supply through the supporting porous structure. This approach is promising for the direct integration of SWCNT networks into Si-based nanodevice platforms and multiple applications ranging from nanoelectronics and energy conversion to bio- and environmental sensing.

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We report fabrication and optical properties of electrochemically deposited silver nanowires into nanoporous alumina template. A finite element method is used to study plasmonic coupling of dipole emitters with the silver nanowires.

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We investigate the photoexcited state dynamics in a donor-acceptor copolymer, poly{3,6-dithiophene-2-yl-2,5-di(2-octyldodecyl)-pyrrolo[3,4-c]- pyrrole-1,4-dione-alt-naphthalene} (pDPP-TNT), by picosecond fluorescence and femtosecond transient absorption spectroscopies. Timeresolved fluorescence lifetime measurements of pDPP-TNT thin films reveal that the lifetime of the singlet excited state is 185 ± 5 ps and that singlet-singlet annihilation occurs at excitation photon densities above 6 × 1017 photons/cm3. From the results of singlet-singlet annihilation analysis, we estimate that the single-singlet annihilation rate constant is (6.0 ± 0.2) × 109cm3 s-1 and the singlet diffusion length is -7 nm. From the comparison of femtosecond transient absorption measurements and picosecond fluorescence measurements, it is found that the time profile of the photobleaching signal in the charge-transfer (CT) absorption band coincides with that of the fluorescence intensity and there is no indication of long-lived species, which clearly suggests that charged species, such as polaron pairs and triplet excitons, are not effectively photogenerated in the neat pDPP-TNT polymer.