Temperature-dependent growth mechanisms of low-dimensional ZnO nanostructures

One-dimensional ZnO nanostructures were successfully synthesized on single-crystal silicon substrates via a simple thermal evaporation and vapour-phase transport method under different process temperatures from 500 to 1000 °C. The detailed and in-depth analysis of the experimental results shows that the growth of ZnO nanostructures at process temperatures of 500, 800, and 1000 °C is governed by different growth mechanisms. At a low process temperature of 500 °C, the ZnO nanostructures feature flat and smooth tips, and their growth is primarily governed by the vapour-solid mechanism. At an intermediate process temperature of 800 °C, the ZnO nanostructures feature cone-shape tips, and their growth is primarily governed by the self-catalyzed and saturated vapour–liquid–solid mechanism. At a high process temperature of 1000 °C, the alloy tip appears on the front side of the ZnO nanostructures, and their growth is primarily governed by the common catalyst-assisted vapour–liquid–solid mechanism. It is also shown that the morphological, structural, optical, and compositional properties of the synthesized ZnO nanostructures are closely related to the process temperature. These results are highly relevant to the development of light-emitting diodes, chemical sensors, energy conversion devices, and other advanced applications.

Diagnostics and two-dimensional simulation of low-frequency inductively coupled plasmas with neutral gas heating and electron heat fluxes

This article presents the results on the diagnostics and numerical modeling of low-frequency (∼460 KHz) inductively coupled plasmas generated in a cylindrical metal chamber by an external flat spiral coil. Experimental data on the electron number densities and temperatures, electron energy distribution functions, and optical emission intensities of the abundant plasma species in low/intermediate pressure argon discharges are included. The spatial profiles of the plasma density, electron temperature, and excited argon species are computed, for different rf powers and working gas pressures, using the two-dimensional fluid approach. The model allows one to achieve a reasonable agreement between the computed and experimental data. The effect of the neutral gas temperature on the plasma parameters is also investigated. It is shown that neutral gas heating (at rf powers≥0.55kW) is one of the key factors that control the electron number density and temperature. The dependence of the average rf power loss, per electron-ion pair created, on the working gas pressure shows that the electron heat flux to the walls appears to be a critical factor in the total power loss in the discharge.

Self-assembled low-dimensional nanomaterials via low-temperature plasma processing

Examples of successful fabrication of low-dimensional semiconducting nanomaterials in the Integrated Plasma-Aided Nanofabrication Facility are shown. Self-assembled size-uniform ZnO nanoparticles, ultra-high-aspect ratio Si nanowires, vertically aligned cadmium sulfide nanostructures, and quarternary semiconducting SiCAlN nanomaterial have been synthesized using inductively coupled plasma-assisted RF magnetron sputtering deposition. The observed increase in crystallinity and growth rates of the nanostructures are explained by using a model of plasma-enhanced adatom surface diffusion under conditions of local energy exchange between the ion flux and the growth surface. Issues related to plasma-based growth of low-dimensional semiconducting nanomaterials are discussed as well. © 2007 Elsevier B.V. All rights reserved.

Nanopowder management and plasma parameters in nanofabrication of low-dimensional quantum structures in reactive silane-based plasmas

Management of nanopowder and reactive plasma parameters in a low-pressure RF glow discharge in silane is studied. It is shown that the discharge control parameters and reactor volume can be adjusted to ensure lower abundance of nanopowders, which is one of the requirements of the plasma-assisted fabrication of low-dimensional quantum nanostructures. The results are relevant to micro- and nanomanufacturing technologies employing low-pressure glow discharge plasmas of silane-based gas mixtures.

Reactive species in Ar+H2 plasma-aided nanofabrication : two-dimensional discharge modelling

Understanding the generation of reactive species in a plasma is an important step towards creating reliable and robust plasma-aided nanofabrication processes. A two-dimensional fluid simulation of the number densities of surface preparation species in a low-temperature, low-pressure, non-equilibrium Ar+H2 plasma is conducted. The operating pressure and H2 partial pressure have been varied between 70-200 mTorr and 0.1-50%, respectively. An emphasis is placed on the application of these results to nanofabrication. A reasonable balance between operating pressures and H 2 partial pressures that would optimize the number densities of the two working units largely responsible for activation and passivation of surface dangling bonds (Ar+ and H respectively) in order to achieve acceptable rates of surface activation and passivation is obtained. It is found that higher operating pressures (150-200 mTorr) and lower H2 partial pressures (∼5%) are required in order to ensure high number densities of Ar+ and H species. This paper contributes to the improvement of the controllability and predictability of plasma-based nanoassembly processes.

Two-dimensional simulation of nanoassembly precursor species in Ar+H2+C2H2 reactive plasmas

The results of two-dimensional fluid simulation of number densities and fluxes of the main building blocks and surface preparation species involved in nanoassembly of carbon-based nanopatterns in Ar+H2+C2H2 reactive plasmas are reported. It is shown that the process parameters and non-uniformity of surface fluxes of each particular species may affect the targeted nanopattern quality. The results can be used to improve predictability of plasma-aided nanofabrication processes and optimize the parameters of plasma nanotools.KGaA, Weinheim.

Two-dimensional simulation of nanoparticle deposition from high-density plasmas on microstructured surfaces

Selective and controlled deposition of plasma-grown nanoparticles is one of the pressing problems of plasma-aided nanofabrication. The results of advanced numerical simulations of motion of charge-variable nanoparticles in the plasma presheath and sheath areas and in localized microscopic electric fields created by surface microstructures are reported. Conditions for site-selective deposition of such nanoparticles onto individual microstructures and open surface areas within a periodic micropattern are formulated. The effects of plasma parameters, surface potential, and micropattern features on nanoparticle deposition are investigated and explained using particle charging and plasma force arguments. The results are generic and applicable to a broad range of nanoparticle-generating plasmas and practical problems ranging from management of nanoparticle contamination in microelectronics to site-selective nanoparticle deposition into specified device locations, and synthesis of advanced microporous materials and nanoparticle superlattices. © 2007 American Institute of Physics.

Improving the accuracy of mine site water balances through improved estimation of runoff volumes

A mine site water balance is important for communicating information to interested stakeholders, for reporting on water performance, and for anticipating and mitigating water-related risks through water use/demand forecasting. Gaining accuracy over the water balance is therefore crucial for sites to achieve best practice water management and to maintain their social license to operate. For sites that are located in high rainfall environments the water received to storage dams through runoff can represent a large proportion of the overall inputs to site; inaccuracies in these flows can therefore lead to inaccuracies in the overall site water balance. Hydrological models that estimate runoff flows are often incorporated into simulation models used for water use/demand forecasting. The Australian Water Balance Model (AWBM) is one example that has been widely applied in the Australian context. However, the calibration of AWBM in a mining context can be challenging. Through a detailed case study, we outline an approach that was used to calibrate and validate AWBM at a mine site. Commencing with a dataset of monitored dam levels, a mass balance approach was used to generate an observed runoff sequence. By incorporating a portion of this observed dataset into the calibration routine, we achieved a closer fit between the observed vs. simulated dataset compared with the base case. We conclude by highlighting opportunities for future research to improve the calibration fit through improving the quality of the input dataset. This will ultimately lead to better models for runoff prediction and thereby improve the accuracy of mine site water balances.

A coupled SPH-DEM model for micro-scale structural deformations of plant cells during drying

A single plant cell was modeled with smoothed particle hydrodynamics (SPH) and a discrete element method (DEM) to study the basic micromechanics that govern the cellular structural deformations during drying. This two-dimensional particle-based model consists of two components: a cell fluid model and a cell wall model. The cell fluid was approximated to a highly viscous Newtonian fluid and modeled with SPH. The cell wall was treated as a stiff semi-permeable solid membrane with visco-elastic properties and modeled as a neo-Hookean solid material using a DEM. Compared to existing meshfree particle-based plant cell models, we have specifically introduced cell wall–fluid attraction forces and cell wall bending stiffness effects to address the critical shrinkage characteristics of the plant cells during drying. Also, a moisture domain-based novel approach was used to simulate drying mechanisms within the particle scheme. The model performance was found to be mainly influenced by the particle resolution, initial gap between the outermost fluid particles and wall particles and number of particles in the SPH influence domain. A higher order smoothing kernel was used with adaptive smoothing length to improve the stability and accuracy of the model. Cell deformations at different states of cell dryness were qualitatively and quantitatively compared with microscopic experimental findings on apple cells and a fairly good agreement was observed with some exceptions. The wall–fluid attraction forces and cell wall bending stiffness were found to be significantly improving the model predictions. A detailed sensitivity analysis was also done to further investigate the influence of wall–fluid attraction forces, cell wall bending stiffness, cell wall stiffness and the particle resolution. This novel meshfree based modeling approach is highly applicable for cellular level deformation studies of plant food materials during drying, which characterize large deformations.

Three-dimensional analysis of budding sites and released virus suggests a revised model for HIV-1 morphogenesis

Current models of HIV-1 morphogenesis hold that newly synthesized viral Gag polyproteins traffic to and assemble at the cell membrane into spherical protein shells. The resulting late-budding structure is thought to be released by the cellular ESCRT machinery severing the membrane tether connecting it to the producer cell. Using electron tomography and scanning transmission electron microscopy, we find that virions have a morphology and composition distinct from late-budding sites. Gag is arranged as a continuous but incomplete sphere in the released virion. In contrast, late-budding sites lacking functional ESCRT exhibited a nearly closed Gag sphere. The results lead us to propose that budding is initiated by Gag assembly, but is completed in an ESCRT-dependent manner before the Gag sphere is complete. This suggests that ESCRT functions early in HIV-1 release-akin to its role in vesicle formation-and is not restricted to severing the thin membrane tether.

Three dimensional digitisation of plant leaves

Realistic plant models are important for leaf area and plant volume estimation, reconstruction of growth canopies, structure generation of the plant, reconstruction of leaf surfaces and agrichemical spray droplet modelling. This article investigates several different scanning devices for obtaining a three dimensional digitisation of plant leaves with a point cloud resolution of 200-500μm. The devices tested were a Roland mdx-20, Microsoft Kinect, Roland lpx-250, Picoscan and Artec S. The applicability of each of these devices for scanning plant leaves is discussed. The most suitable tested digitisation device for scanning plant leaves is the Artec S scanner.

Blood transfer devices for malaria rapid diagnostic tests : evaluation of accuracy, safety and ease of use

Background: Malaria rapid diagnostic tests (RDTs) are increasingly used by remote health personnel with minimal training in laboratory techniques. RDTs must, therefore, be as simple, safe and reliable as possible. Transfer of blood from the patient to the RDT is critical to safety and accuracy, and poses a significant challenge to many users. Blood transfer devices were evaluated for accuracy and precision of volume transferred, safety and ease of use, to identify the most appropriate devices for use with RDTs in routine clinical care. Methods: Five devices, a loop, straw-pipette, calibrated pipette, glass capillary tube, and a new inverted cup device, were evaluated in Nigeria, the Philippines and Uganda. The 227 participating health workers used each device to transfer blood from a simulated finger-prick site to filter paper. For each transfer, the number of attempts required to collect and deposit blood and any spilling of blood during transfer were recorded. Perceptions of ease of use and safety of each device were recorded for each participant. Blood volume transferred was calculated from the area of blood spots deposited on filter paper. Results: The overall mean volumes transferred by devices differed significantly from the target volume of 5 microliters (p < 0.001). The inverted cup (4.6 microliters) most closely approximated the target volume. The glass capillary was excluded from volume analysis as the estimation method used is not compatible with this device. The calibrated pipette accounted for the largest proportion of blood exposures (23/225, 10%); exposures ranged from 2% to 6% for the other four devices. The inverted cup was considered easiest to use in blood collection (206/ 226, 91%); the straw-pipette and calibrated pipette were rated lowest (143/225 [64%] and 135/225 [60%] respectively). Overall, the inverted cup was the most preferred device (72%, 163/227), followed by the loop (61%, 138/227). Conclusions: The performance of blood transfer devices varied in this evaluation of accuracy, blood safety, ease of use, and user preference. The inverted cup design achieved the highest overall performance, while the loop also performed well. These findings have relevance for any point-of-care diagnostics that require blood sampling.

Mining business process deviance : a quest for accuracy

This paper evaluates the suitability of sequence classification techniques for analyzing deviant business process executions based on event logs. Deviant process executions are those that deviate in a negative or positive way with respect to normative or desirable outcomes, such as non-compliant executions or executions that undershoot or exceed performance targets. We evaluate a range of feature types and classification methods in terms of their ability to accurately discriminate between normal and deviant executions both when deviances are infrequent (unbalanced) and when deviances are as frequent as normal executions (balanced). We also analyze the ability of the discovered rules to explain potential causes and contributing factors of observed deviances. The evaluation results show that feature types extracted using pattern mining techniques only slightly outperform those based on individual activity frequency. The results also suggest that more complex feature types ought to be explored to achieve higher levels of accuracy.

Surface reconstruction of wheat leaf morphology from three-dimensional scanned data

Realistic virtual models of leaf surfaces are important for a number of applications in the plant sciences, such as modelling agrichemical spray droplet movement and spreading on the surface. In this context, the virtual surfaces are required to be sufficiently smooth to facilitate the use of the mathematical equations that govern the motion of the droplet. While an effective approach is to apply discrete smoothing D2-spline algorithms to reconstruct the leaf surfaces from three-dimensional scanned data, difficulties arise when dealing with wheat leaves that tend to twist and bend. To overcome this topological difficulty, we develop a parameterisation technique that rotates and translates the original data, allowing the surface to be fitted using the discrete smoothing D2-spline methods in the new parameter space. Our algorithm uses finite element methods to represent the surface as a linear combination of compactly supported shape functions. Numerical results confirm that the parameterisation, along with the use of discrete smoothing D2-spline techniques, produces realistic virtual representations of wheat leaves.