Control of ion density distribution by magnetic traps for plasma electrons

The effect of a magnetic field of two magnetic coils on the ion current density distribution in the setup for low-temperature plasma deposition is investigated. The substrate of 400 mm diameter is placed at a distance of 325 mm from the plasma duct exit, with the two magnetic coils mounted symmetrically under the substrate at a distance of 140 mm relative to the substrate centre. A planar probe is used to measure the ion current density distribution along the plasma flux cross-sections at distances of 150, 230, and 325 mm from the plasma duct exit. It is shown that the magnetic field strongly affects the ion current density distribution. Transparent plastic films are used to investigate qualitatively the ion density distribution profiles and the effect of the magnetic field. A theoretical model is developed to describe the interaction of the ion fluxes with the negative space charge regions associated with the magnetic trapping of the plasmaelectrons. Theoretical results are compared with the experimental measurements, and a reasonable agreement is demonstrated.

Thin single-walled carbon nanotubes with narrow chirality distribution : constructive interplay of plasma and Gibbs–Thomson effects

Multiscale, multiphase numerical modeling is used to explain the mechanisms of effective control of chirality distributions of single-walled carbon nanotubes in direct plasma growth and suggest effective approaches to further improvement. The model includes an unprecedented combination of the plasma sheath, ion/radical transport, species creation/loss, plasma–surface interaction, heat transfer, surface/bulk diffusion, graphene layer nucleation, and bending/lift-off modules. It is shown that the constructive interplay between the plasma and the Gibbs–Thomson effect can lead to the effective nucleation and lift-off of small graphene layers on small metal catalyst nanoparticles. As a result, much thinner nanotubes with narrower chirality distributions can nucleate at much lower process temperatures and pressures compared to thermal CVD. This approach is validated by a host of experimental results, substantially reduces the amounts of energy and atomic matter required for the nanotube growth, and can be extended to other nanoscale structures and materials systems, thereby nearing the ultimate goal of energy- and matter-efficient nanotechnology.

Plasma-controlled adatom delivery and (re)distribution: Enabling uninterrupted, low-temperature growth of ultralong vertically aligned single walled carbon nanotubes

Large-scale (∼109 atoms) numerical simulations reveal that plasma-controlled dynamic delivery and redistribution of carbon atoms between the substrate and nanotube surfaces enable the growth of ultralong single walled carbon nanotubes (SWCNTs) and explain the common experimental observation of slower growth at advanced stages. It is shown that the plasma-based processes feature up to two orders of magnitude higher growth rates than equivalent neutral-gas systems and are better suited for the SWCNT synthesis at low nanodevice friendly temperatures. © 2008 American Institute of Physics.

Distribution of ion-current density on substrate between carbon nanotubes grown from low-temperature plasma

Using Monte Carlo simulation technique, we have calculated the distribution of ion current extracted from low-temperature plasmas and deposited onto the substrate covered with a nanotube array. We have shown that a free-standing carbon nanotube is enclosed in a circular bead of the ion current, whereas in square and hexagonal nanotube patterns, the ion current is mainly concentrated along the lines connecting the nearest nanotubes. In a very dense array (with the distance between nanotubes/nanotube-height ratio less than 0.05), the ions do not penetrate to the substrate surface and deposit on side surfaces of the nanotubes.

Spatially averaged model of complex-plasma discharge with self-consistent electron energy distribution

A global, or averaged, model for complex low-pressure argon discharge plasmas containing dust grains is presented. The model consists of particle and power balance equations taking into account power loss on the dust grains and the discharge wall. The electron energy distribution is determined by a Boltzmann equation. The effects of the dust and the external conditions, such as the input power and neutral gas pressure, on the electron energy distribution, the electron temperature, the electron and ion number densities, and the dust charge are investigated. It is found that the dust subsystem can strongly affect the stationary state of the discharge by dynamically modifying the electron energy distribution, the electron temperature, the creation and loss of the plasma particles, as well as the power deposition. In particular, the power loss to the dust grains can take up a significant portion of the input power, often even exceeding the loss to the wall.

Angular distribution of carbon ion flux in a nanotube array during the plasma process by the Monte Carlo technique

Angular distribution of microscopic ion fluxes around nanotubes arranged into a dense ordered pattern on the surface of the substrate is studied by means of multiscale numerical simulation. The Monte Carlo technique was used to show that the ion current density is distributed nonuniformly around the carbon nanotubes arranged into a dense rectangular array. The nonuniformity factor of the ion current flux reaches 7 in dense (5× 1018 m-3) plasmas for a nanotube radius of 25 nm, and tends to 1 at plasma densities below 1× 1017 m-3. The results obtained suggest that the local density of carbon adatoms on the nanotube side surface, at areas facing the adjacent nanotubes of the pattern, can be high enough to lead to the additional wall formation and thus cause the single- to multiwall structural transition, and other as yet unexplained nanoscience phenomena.

Simulation of ion flux distribution in conductive and nonconductive nanotip patterns

The distribution of flux of carbon-bearing cations over nanopatterned surfaces with conductive nanotips and nonconductive nanoislands is simulated using the Monte-Carlo technique. It is shown that the ion current is focused to nanotip surfaces when the negative substrate bias is low and only slightly perturbed at higher substrate biases. In the low-bias case, the mean horizontal ion displacement caused by the nanotip electric field exceeds 10 nm. However, at higher substrate biases, this value reduces down to 2 nm. In the nonconductive nanopattern case, the ion current distribution is highly nonuniform, with distinctive zones of depleted current density around the nanoislands. The simulation results suggest the efficient means to control ion fluxes in plasma-aided nanofabrication of ordered nanopatterns, such as nanotip microemitter structures and quantum dot or nanoparticle arrays. © World Scientific Publishing Company.

Effect of pupil dilation and constriction on the distribution of bit errors within the iris

Texture information in the iris image is not uniform in discriminatory information content for biometric identity verification. The bits in an iris code obtained from the image differ in their consistency from one sample to another for the same identity. In this work, errors in bit strings are systematically analysed in order to investigate the effect of light-induced and drug-induced pupil dilation and constriction on the consistency of iris texture information. The statistics of bit errors are computed for client and impostor distributions as functions of radius and angle. Under normal conditions, a V-shaped radial trend of decreasing bit errors towards the central region of the iris is obtained for client matching, and it is observed that the distribution of errors as a function of angle is uniform. When iris images are affected by pupil dilation or constriction the radial distribution of bit errors is altered. A decreasing trend from the pupil outwards is observed for constriction, whereas a more uniform trend is observed for dilation. The main increase in bit errors occurs closer to the pupil in both cases.

Electron energy distribution function in low-pressure complex plasmas

The effect of density and size of dust grains on the electron energy distribution function (EEDF) in low-temperature complex plasmas is studied. It is found that the EEDF depends strongly on the dust density and size. The behavior of the electron temperature can differ significantly from that of a pristine plasma. For low-pressure argon glow discharge, the Druyvesteyn-like EEDF often found in pristine plasmas can become nearly Maxwellian if the dust density and/or sizes are large. One can thus control the plasma parameters by the dust grains.

The geographical co-distribution and socio-ecological drivers of childhood pneumonia and diarrhoea in Queensland, Australia

This study aimed to explore the spatiotemporal patterns, geographic co-distribution, and socio-ecological drivers of childhood pneumonia and diarrhea in Queensland. A Bayesian conditional autoregressive model was used to quantify the impacts of socio-ecological factors on both childhood pneumonia and diarrhea at a postal area level. A distinct seasonality of childhood pneumonia and diarrhea was found. Childhood pneumonia and diarrhea mainly distributed in northwest of Queensland. Mount Isa was the high-risk cluster where childhood pneumonia and diarrhea co-distributed. Emergency department visits (EDVs) for pneumonia increased by 3% per 10-mm increase in monthly average rainfall, in wet seasons. In comparison, a 10-mm increase in monthly average rainfall may increase 4% of EDVs for diarrhea. Monthly average temperature was negatively associated with EDVs for childhood diarrhea, in wet seasons. Low socioeconomic index for areas (SEIFA) was associated with high EDVs for childhood pneumonia. Future pneumonia and diarrhea prevention and control measures in Queensland should focus more on Mount Isa.

Robust multiple-sensing-modality data fusion using Gaussian Process Implicit Surfaces

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.

Enhanced stochastic mobility prediction with multi-output Gaussian processes

Outdoor robots such as planetary rovers must be able to navigate safely and reliably in order to successfully perform missions in remote or hostile environments. Mobility prediction is critical to achieving this goal due to the inherent control uncertainty faced by robots traversing natural terrain. We propose a novel algorithm for stochastic mobility prediction based on multi-output Gaussian process regression. Our algorithm considers the correlation between heading and distance uncertainty and provides a predictive model that can easily be exploited by motion planning algorithms. We evaluate our method experimentally and report results from over 30 trials in a Mars-analogue environment that demonstrate the effectiveness of our method and illustrate the importance of mobility prediction in navigating challenging terrain.

Geographical distribution of human Schistosoma japonicum infection in the Philippines : tools to support disease control and further elimination

S. japonicum infection is believed to be endemic in 28 of the 80 provinces of the Philippines and the most recent data on schistosomiasis prevalence have shown considerable variability between provinces. In order to increase the efficient allocation of parasitic disease control resources in the country, we aimed to describe the small scale spatial variation in S. japonicum prevalence across the Philippines, quantify the role of the physical environment in driving the spatial variation of S. japonicum, and develop a predictive risk map of S. japonicum infection. Data on S. japonicum infection from 35,754 individuals across the country were geo-located at the barangay level and included in the analysis. The analysis was then stratified geographically for Luzon, the Visayas and Mindanao. Zero-inflated binomial Bayesian geostatistical models of S. japonicum prevalence were developed and diagnostic uncertainty was incorporated. Results of the analysis show that in the three regions, males and individuals aged ≥ 20 years had significantly higher prevalence of S. japonicum compared with females and children <5 years. The role of the environmental variables differed between regions of the Philippines. S. japonicum infection was widespread in the Visayas whereas it was much more focal in Luzon and Mindanao. This analysis revealed significant spatial variation in prevalence of S. japonicum infection in the Philippines. This suggests that a spatially targeted approach to schistosomiasis interventions, including mass drug administration, is warranted. When financially possible, additional schistosomiasis surveys should be prioritized to areas identified to be at high risk, but which were underrepresented in our dataset.

Design of a wind turbine - battery energy storage scheme to achieve power dispatchability

Battery energy storage system (BESS) is to be incorporated in a wind farm to achieve constant power dispatch. The design of the BESS is based on the forecasted wind speed, and the technique assumes the distribution of the error between the forecasted and actual wind speeds is Gaussian. It is then shown that although the error between the predicted and actual wind powers can be evaluated, it is non-Gaussian. With the known distribution in the error of the predicted wind power, the capacity of the BESS can be determined in terms of the confident level in meeting specified constant power dispatch commitment. Furthermore, a short-term power dispatch strategy is also developed which takes into account the state of charge (SOC) of the BESS. The proposed approach is useful in the planning of the wind farm-BESS scheme and in the operational planning of the wind power generating station.

Improving voltage profile of residential distribution systems using rooftop PVs and Battery Energy Storage systems

Large number of rooftop Photovoltaics (PVs) have turned traditional passive networks into active networks with intermittent and bidirectional power flow. A community based distribution network grid reinforcement process is proposed to address technical challenges associated with large integration of rooftop PVs. Probabilistic estimation of intermittent PV generation is considered. Depending on the network parameters such as the R/X ratio of distribution feeder, either reactive control from PVs or coordinated control of PVs and Battery Energy Storage (BES) has been proposed. Determination of BES capacity is one of the significant outcomes from the proposed method and several factors such as variation in PV installed capacity as well as participation from community members are analyzed. The proposed approach is convenient for the community members providing them flexibility of managing their integrated PV and BES systems