365 resultados para temperature sensing
Resumo:
The response of complex ionized gas systems to the presence of nonuniform distribution of charged grains is investigated using a kinetic model. Contrary to an existing view that the electron temperature inevitably increases in the grain-occupied region because of enhanced ionization to compensate for the electrons lost to the grains, it is shown that this happens only when the ionizing electric field increases in the electron depleted region. The results for two typical plasma systems suggest that when the ionizing electric field depends on the spatially averaged electron density, the electron temperature in the grain containing region can actually decrease.
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In this work, we report a plasma-based synthesis of nanodevice-grade nc-3C-SiC films, with very high growth rates (7-9 nm min-1) at low and ULSI technology-compatible process temperatures (400-550 °C), featuring: (i) high nanocrystalline fraction (67% at 550 °C); (ii) good chemical purity; (iii) excellent stoichiometry throughout the entire film; (iv) wide optical band gap (3.22-3.71 eV); (v) refractive index close to that of single-crystalline 3C-SiC, and; (vi) clear, uniform, and defect-free Si-SiC interface. The counter-intuitive low SiC hydrogenation in a H2-rich plasma process is explained by hydrogen atom desorption-mediated crystallization.
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The results of a hybrid numerical simulation of the growth kinetics of carbon nanowall-like nanostructures in the plasma and neutral gas synthesis processes are presented. The low-temperature plasma-based process was found to have a significant advantage over the purely neutral flux deposition in providing the uniform size distribution of the nanostructures. It is shown that the nanowall width uniformity is the best (square deviations not exceeding 1.05) in high-density plasmas of 3.0× 1018 m-3, worsens in lower-density plasmas (up to 1.5 in 1.0× 1017 m-3 plasmas), and is the worst (up to 1.9) in the neutral gas-based process. This effect has been attributed to the focusing of ion fluxes by irregular electric field in the vicinity of plasma-grown nanostructures on substrate biased with -20 V potential, and differences in the two-dimensional adatom diffusion fluxes in the plasma and neutral gas-based processes. The results of our numerical simulations are consistent with the available experimental reports on the effect of the plasma process parameters on the sizes and shapes of relevant nanostructures.
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The means of reducing nanoparticle contamination in the synthesis of carbon nanostructures in reactive Ar + H2 + CH4 plasmas are studied. It is shown that by combining the electrostatic filtering and thermophoretic manipulation of nanoparticles, one can significantly improve the quality of carbon nanopatterns. By increasing the substrate heating power, one can increase the size of deposited nanoparticles and eventually achieve nanoparticle-free nanoassemblies. This approach is generic and is applicable to other reactive plasma-aided nanofabrication processes.
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High-density inductively coupled plasma (ICP)-assisted self-assembly of the ordered arrays of various carbon nanostructures (NS) for the electron field emission applications is reported. Carbon-based nano-particles, nanotips, and pyramid-like structures, with the controllable shape, ordering, and areal density are grown under remarkably low process temperatures (260-350 °C) and pressures (below 0.1 Torr), on the same Ni-based catalyst layers, in a DC bias-controlled floating temperature regime. A high degree of positional and directional ordering, elevated sp2 content, and a well-structured graphitic morphology are achieved without the use of pre-patterned or externally heated substrates.
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Manipulation of a single nanoparticle in the near-substrate areas of high-density plasmas of low-temperature glow discharges is studied. It is shown that the nanoparticles can be efficiently manipulated by the thermophoretic force controlled by external heating of the substrate stage. Particle deposition onto or repulsion from nanostructured carbon surfaces critically depends on the values of the neutral gas temperature gradient in the near-substrate areas, which is directly measured in situ in different heating regimes by originally developed temperature gradient probe. The measured values of the near-surface temperature gradient are used in the numerical model of nanoparticle dynamics in a variable-length presheath. Specific conditions enabling the nanoparticle to overcome the repulsive potential and deposit on the substrate during the discharge operation are investigated. The results are relevant to fabrication of various nanostructured films employing structural incorporation of the plasma-grown nanoparticles, in particular, to nanoparticle deposition in the plasma-enhanced chemical-vapor deposition of carbon nanostructures in hydrocarbon-based plasmas.
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Large area, highly uniform vertically aligned carbon nanotips (VACNTP) and other nanostructures have been grown on silicon (100) substrates with Ni catalyst in the low-temperature, low-frequency, high-density inductively coupled plasmas (ICP) of methane-hydrogen-argon gas mixtures. The control strategies for the morphology, crystalline structure and chemical states of the resulting nanostructures by varying the growth conditions are proposed. XRD and Roman analyses confirm that the nanotips are well graphitized, which is favorable for the field emission applications.
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Carbon-doped hydrogenated silicon oxide (SiOCH) low-k films have been prepared using 13.56 MHz discharge in trimethylsilane (3MS) - oxygen gas mixtures at 3, 4, and 5 Torr sustained with RF power densities 1.3 - 2.6 W/cm2. The atomic structure of the SiOCH films appears to be a mixture the amorphous SiO2-like and the partially polycrystalline SiC-like phases. Results of the infra-red spectroscopy reflect the increment in the volume fraction of the SiC-like phase from 0.22 - 0.28 to 0.36 - 0.39 as the RF power increment. Steady-state near-UV laser-excited (364 nm wavelength, 40±2 mW) photoluminescence (PL) has been studied at room temperatures in the visible (1.8 eV - 3.1 eV) subrange of photon spectrum. Two main bands of the PL signal (at the photon energies of 2.5 - 2.6 eV and 2.8 - 2.9 eV) are observed. Intensities of the both bands are changed monotonically with RF power, whereas the bandwidth of ∼0.1 eV remains almost invariable. It is likely that the above lines are dumped by the non-radiative recombination involving E1-like centres in the amorphous-nanocrystalline SiC-like phases. Such explanation of the PL intensity dependences on the RF power density is supported by results of experimental studies of defect states spectrum in bandgap of the SiOCH films.
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Self-organization and dynamic processes of nano/micron-sized solid particles grown in low-temperature chemically active plasmas as well as the associated physico-chemical processes are reviewed. Three specific reactive plasma chemistries, namely, of silane (SiH4), acetylene (C 2H2), and octafluorocyclobutane (c-C4F 8) RF plasma discharges for plasma enhanced chemical vapor deposition of amorphous hydrogenated silicon, hydrogenated and fluorinated carbon films, are considered. It is shown that the particle growth mechanisms and specific self-organization processes in the complex reactive plasma systems are related to the chemical organization and size of the nanoparticles. Correlation between the nanoparticle origin and self-organization in the ionized gas phase and improved thin film properties is reported. Self-organization and dynamic phenomena in relevant reactive plasma environments are studied for equivalent model systems comprising inert buffer gas and mono-dispersed organic particulate powders. Growth kinetics and dynamic properties of the plasma-assembled nanoparticles can be critical for the process quality in microelectronics as well as a number of other industrial applications including production of fine metal or ceramic powders, nanoparticle-unit thin film deposition, nanostructuring of substrates, nucleating agents in polymer and plastics synthesis, drug delivery systems, inorganic additives for sunscreens and UV-absorbers, and several others. Several unique properties of the chemically active plasma-nanoparticle systems are discussed as well.
Resumo:
Background Few data on the relationship between temperature variability and childhood pneumonia are available. This study attempted to fill this knowledge gap. Methods A quasi-Poisson generalized linear regression model combined with a distributed lag nonlinear model was used to quantify the impacts of diurnal temperature range (DTR) and temperature change between two neighbouring days (TCN) on emergency department visits (EDVs) for childhood pneumonia in Brisbane, from 2001 to 2010, after controlling for possible confounders. Results An adverse impact of TCN on EDVs for childhood pneumonia was observed, and the magnitude of this impact increased from the first five years (2001–2005) to the second five years (2006–2010). Children aged 5–14 years, female children and Indigenous children were particularly vulnerable to TCN impact. However, there was no significant association between DTR and EDVs for childhood pneumonia. Conclusions As climate change progresses, the days with unstable weather pattern are likely to increase. Parents and caregivers of children should be aware of the high risk of pneumonia posed by big TCN and take precautionary measures to protect children, especially those with a history of respiratory diseases, from climate impacts.
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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 diarrhea in Brisbane from 2001 to 2010. Residual of the model was checked to examine whether there was an added effect due to heat waves. The change over time in temperature-diarrhea relation was also assessed. Both low and high temperatures had significant impact on childhood diarrhea. Heat waves had an added effect on childhood diarrhea, and this effect increased with intensity and duration of heat waves. There was a decreasing trend in the main effect of heat on childhood diarrhea in Brisbane across the study period. Brisbane children appeared to have gradually adapted to mild heat, but they are still very sensitive to persistent extreme heat. Development of future heat alert systems should take the change in temperature-diarrhea relation over time 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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The emission of particles in the ultrafine range (<100 nm) from laser printers has not been reported until recently (Uhde et al., 2006; He et al., 2007; Morawska et al., 2009). The research reported to date has provided a body of information about printer emissions and shed light on particle formation mechanisms. However, until now, the effect of fuser roller temperature on particle emissions had not been comprehensively investigated...
Resumo:
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.
Resumo:
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.