Nanoscale control of energy and matter in plasma–surface interactions : toward energy- and matter-efficient nanotech

The approach to control the elementary processes of plasma–surface interactions to direct the fluxes of energy and matter at nano- and subnanometer scales is introduced. This ability is related to the solution of the grand challenge of directing energy and matter at nanoscales and is critical for the renewable energy and energy-efficient technologies for a sustainable future development. The examples of deterministic synthesis of self-organized arrays of metastable nanostructures in the size range beyond the reach of the present-day nanofabrication are considered to illustrate this possibility. By using precisely controlled and kinetically fast nanoscale transfer of energy and matter under nonequilibrium conditions and harnessing numerous plasma-specific controls of species creation, delivery to the surface,nucleation, and large-scale self-organization of nuclei and nanostructures, the arrays of metastable nanostructures can be created, arranged, stabilized, and further processed to meet the specific requirements of the envisaged applications.

Nanoscale transfer of energy and matter in plasma–surface interactions

The main issues related to control of energy and matter in hierarchical low-temperature plasma-solid systems used in nanoscale synthesis and processing are critically examined. A conceptual approach to identify the most effective carriers and transport mechanisms of energy and matter at the nano- and subnanometer scales in plasma-aided nanofabrication is proposed. This approach is highly relevant to the envisaged energy- and matter-efficient plasma-based production of the next-generation advanced nanomaterials for applications in the energy, environment, food, water, health, and security technologies critically needed for a sustainable future.

Magnetic control of breakdown : toward energy-efficient hollow-cathode magnetron discharges

Characteristics of electrical breakdown of a planar magnetron enhanced with an electromagnet and a hollow-cathode structure, are studied experimentally and numerically. At lower pressures the breakdown voltage shows a dependence on the applied magnetic field, and the voltage necessary to achieve the self-sustained discharge regime can be significantly reduced. At higher pressures, the dependence is less sensitive to the magnetic field magnitude and shows a tendency of increased breakdown voltage at the stronger magnetic fields. A model of the magnetron discharge breakdown is developed with the background gas pressure and the magnetic field used as parameters. The model describes the motion of electrons, which gain energy by passing the electric field across the magnetic field and undergo collisions with neutrals, thus generating new bulk electrons. The electrons are in turn accelerated in the electric field and effectively ionize a sufficient amount of neutrals to enable the discharge self-sustainment regime. The model is based on the assumption about the combined classical and near-wall mechanisms of electron conductivity across the magnetic field, and is consistent with the experimental results. The obtained results represent a significant advance toward energy-efficient multipurpose magnetron discharges.

Disentangling fluxes of energy and matter in plasma-surface interactions : effect of process parameters

The possibility to discriminate between the relative importance of the fluxes of energy and matter in plasma-surface interaction is demonstrated by the energy flux measurements in low-temperature plasmas ignited by the radio frequency discharge (power and pressure ranges 50-250 W and 8-11.5 Pa) in Ar, Ar+ H2, and Ar+ H2 + CH4 gas mixtures typically used in nanoscale synthesis and processing of silicon- and carbon-based nanostructures. It is shown that by varying the gas composition and pressure, the discharge power, and the surface bias one can effectively control the surface temperature and the matter supply rates. The experimental findings are explained in terms of the plasma-specific reactions in the plasma bulk and on the surface.

Customizing electron confinement in plasma-assembled Si/AlN nanodots for solar cell applications

Size-uniform Si nanodots (NDs) are synthesized on an AlN buffer layer at low Si(111) substrate temperatures using inductively coupled plasma-assisted magnetron sputtering deposition. High-resolution electron microscopy reveals that the sizes of the Si NDs range from 9 to 30 nm. Room-temperature photoluminescence (PL) spectra indicate that the energy peak shifts from 738 to 778 nm with increasing the ND size. In this system, the quantum confinement effect is fairly strong even for relatively large (up to 25 nm in diameter) NDs, which is promising for the development of the next-generation all-Si tandem solar cells capable of effectively capturing sunlight photons with the energies between 1.7 (infrared: large NDs) and 3.4 eV (ultraviolet: small NDs). The strength of the resulting electron confinement in the Si/AlN ND system is evaluated and justified by analyzing the measured PL spectra using the ionization energy theory approximation.

Diffusivity of adatoms on plasma-exposed surfaces determined from the ionization energy approximation and ionic polarizability

Microscopic surface diffusivity theory based on atomic ionization energy concept is developed to explain the variations of the atomic and displacement polarizations with respect to the surface diffusion activation energy of adatoms in the process of self-assembly of quantum dots on plasma-exposed surfaces. These polarizations are derived classically, while the atomic polarization is quantized to obtain the microscopic atomic polarizability. The surface diffusivity equation is derived as a function of the ionization energy. The results of this work can be used to fine-tune the delivery rates of different adatoms onto nanostructure growth surfaces and optimize the low-temperature plasma based nanoscale synthesis processes.

Electron/ion energy loss to discharge walls revised : a case study in low-temperature, thermally nonequilibrium plasmas

Reliable calculations of the electron/ion energy losses in low-pressure thermally nonequilibrium low-temperature plasmas are indispensable for predictive modeling related to numerous applications of such discharges. The commonly used simplified approaches to calculation of electron/ion energy losses to the chamber walls use a number of simplifying assumptions that often do not account for the details of the prevailing electron energy distribution function (EEDF) and overestimate the contributions of the electron losses to the walls. By direct measurements of the EEDF and careful calculation of contributions of the plasma electrons in low-pressure inductively coupled plasmas, it is shown that the actual losses of kinetic energy of the electrons and ions strongly depend on the EEDF. It is revealed that the overestimates of the total electron/ion energy losses to the walls caused by improper assumptions about the prevailing EEDF and about the ability of the electrons to pass through the repulsive potential of the wall may lead to significant overestimates that are typically in the range between 9 and 32%. These results are particularly important for the development of power-saving strategies for operation of low-temperature, low-pressure gas discharges in diverse applications that require reasonably low power densities. © 2008 American Institute of Physics.

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.

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.

Determination of battery storage capacity in energy buffer for wind farm

Design of a battery energy storage system (BESS) in a buffer scheme is examined for the purpose of attenuating the effects of unsteady input power from wind farms. The design problem is formulated as maximization of an objective function that measures the economic benefit obtainable from the dispatched power from the wind farm against the cost of the BESS. Solution to the problem results in the determination of the capacity of the BESS to ensure constant dispatched power to the connected grid, while the voltage level across the dc-link of the buffer is kept within preset limits. A computational procedure to determine the BESS capacity and the evaluation of the dc voltage is shown. Illustrative examples using the proposed design method are included.

Buffer scheme with battery energy storage capability for enhancement of network transient stability and load ride-through

This paper examines a buffer scheme to mitigate the negative impacts of power-conditioned loads on network voltage and transient stabilities. The scheme is based on the use of battery energy-storage systems in the buffers. The storage systems ensure that protected loads downstream of the buffers can ride through upstream voltage sags and swells. Also, by controlling the buffers to operate in either constant impedance or constant power modes, power is absorbed or injected by the storage systems. The scheme thereby regulates the rotor-angle deviations of generators and enhances network transient stability. A computational method is described in which the capacity of the storage systems is determined to achieve simultaneously the above dual objectives of load ride-through and stability enhancement. The efficacy of the resulting scheme is demonstrated through numerical examples.

Visualization of long-duration acoustic recordings of the environment

Acoustic recordings of the environment are an important aid to ecologists monitoring biodiversity and environmental health. However, rapid advances in recording technology, storage and computing make it possible to accumulate thousands of hours of recordings, of which, ecologists can only listen to a small fraction. The big-data challenge addressed in this paper is to visualize the content of long-duration audio recordings on multiple scales, from hours, days, months to years. The visualization should facilitate navigation and yield ecologically meaningful information. Our approach is to extract (at one minute resolution) acoustic indices which reflect content of ecological interest. An acoustic index is a statistic that summarizes some aspect of the distribution of acoustic energy in a recording. We combine indices to produce false-color images that reveal acoustic content and facilitate navigation through recordings that are months or even years in duration.

Long-term exploration and tours for energy constrained robots with online proprioceptive traversability estimation

This paper is concerned with how a localised and energy-constrained robot can maximise its time in the field by taking paths and tours that minimise its energy expenditure. A significant component of a robot's energy is expended on mobility and is a function of terrain traversability. We estimate traversability online from data sensed by the robot as it moves, and use this to generate maps, explore and ultimately converge on minimum energy tours of the environment. We provide results of detailed simulations and parameter studies that show the efficacy of this approach for a robot moving over terrain with unknown traversability as well as a number of a priori unknown hard obstacles.

Systems modelling of mine water and energy tradeoffs

In the coming decades, the mining industry faces the dual challenge of lowering both its water and energy use. This presents a difficulty since technological advances that decrease the use of one can increase the use of the other. Historically, energy and water use have been modelled independently, making it difficult to evaluate the true costs and benefits from water and energy improvements. This paper presents a hierarchical systems model that is able to represent interconnected water and energy use at a whole of site scale. In order to explore the links between water and energy four technologies advancements have been modelled: use of dust suppression additives, the adoption of thickened tailings, the transition to dry processing and the incorporation of a treatment plant. The results show a synergy between decreased water and energy use for dust suppression additives, but a trade-off for the others.

Defect healing and enhanced nucleation of carbon nanotubes by low-energy ion bombardment

Structural defects inevitably appear during the nucleation event that determines the structure and properties of single-walled carbon nanotubes. By combining ion bombardment experiments with atomistic simulations we reveal that ion bombardment in a suitable energy range allows these defects to be healed resulting in an enhanced nucleation of the carbon nanotube cap. The enhanced growth of the nanotube cap is explained by a nonthermal ion-induced graphene network restructuring mechanism.