CHARACTERIZATION OF SURFACE-PLASMONS ON METAL-OXIDE-SEMICONDUCTOR STRUCTURES

Using the Otto (prism-air gap-sample) configuration p-polarized light of wavelength 632.8 nm has been coupled with greater than 80% efficiency to surface plasmons on the aluminium electrode of silicon-silicon dioxide-aluminium structures. The results show that if the average power per unit area dissipated on the metal film exceeds approximately 1 mW mm-2, then the coupling gap and thus the characteristics of the surface plasmon resonance are noticeably altered. In modelling the optical response of such systems the inclusion of both a non-uniform air coupling gap and a thin cermet layer at the aluminium surface may be necessary.

CHARACTERIZATION OF THE AU SURFACE-STRUCTURE OF AL-L-AU LIGHT-EMITTING TUNNEL-JUNCTIONS

Visible light is emitted from the Au-air interface of Al-I-Au thin-film tunnel junctions (deposited over a thin layer of CaF2 on glass) as a result of the decay of surface plasmon polaritons (SPPs). We show the surface topography of such a Au film and relate its large-scale features to the outcoupling of fast SPP's to photons. The absence of short-scale roughness features is explained by thier disappearance through surface diffusion. To confirm this a controlled sequence of 5-nm, 20-ms scanning tunneling microscope (STM) W tip crashes has been used to produce indentations 3 nm deep with a lateral dimension of 5-7 nm on a Au crystal in air at room temperature. Four sequences of indentations were drawn in the form of a square box. Right from the start, feature decay is observed and over a period of 2 h a succession of images shows that the structure disappears into the background as a result of surface diffusion. The surface diffusion constant is estimated to be 10(-18) cm2 s-1. The lack of light output via slow mode SPPs is an inevitable consequence of surface annealing.

Gaussian pulse mixing by stacked semiconductor layers

The nonlinear scattering of two Gaussian pulses with different central frequencies incident at slant angles on the periodic stack of binary semiconductor layers has been modelled in the self-consistent problem formulation taking into account the dynamics of charges. The effects of the pump pulse length and central frequencies, and the stack physical and geometrical parameters on the properties of the emitted combinatorial frequency waveforms are analysed and discussed.

Insight Extraction for Semiconductor Manufacturing Processes

In the semiconductor manufacturing environment it is very important to understand which factors have the most impact on process outcomes and to control them accordingly. This is usually achieved through design of experiments at process start-up and long term observation of production. As such it relies heavily on the expertise of the process engineer. In this work, we present an automatic approach to extracting useful insights about production processes and equipment based on state-of-the-art Machine Learning techniques. The main goal of this activity is to provide tools to process engineers to accelerate the learning-by-observation phase of process analysis. Using a Metal Deposition process as an example, we highlight various ways in which the extracted information can be employed.

On Regression Methods for Virtual Metrology in Semiconductor Manufacturing

Virtual metrology (VM) aims to predict metrology values using sensor data from production equipment and physical metrology values of preceding samples. VM is a promising technology for the semiconductor manufacturing industry as it can reduce the frequency of in-line metrology operations and provide supportive information for other operations such as fault detection, predictive maintenance and run-to-run control. The prediction models for VM can be from a large variety of linear and nonlinear regression methods and the selection of a proper regression method for a specific VM problem is not straightforward, especially when the candidate predictor set is of high dimension, correlated and noisy. Using process data from a benchmark semiconductor manufacturing process, this paper evaluates the performance of four typical regression methods for VM: multiple linear regression (MLR), least absolute shrinkage and selection operator (LASSO), neural networks (NN) and Gaussian process regression (GPR). It is observed that GPR performs the best among the four methods and that, remarkably, the performance of linear regression approaches that of GPR as the subset of selected input variables is increased. The observed competitiveness of high-dimensional linear regression models, which does not hold true in general, is explained in the context of extreme learning machines and functional link neural networks.

Inhibition of Rho-kinase protects cerebral barrier from ischaemia-evoked injury through modulations of endothelial cell oxidative stress and tight junctions

Ischaemic strokes evoke blood-brain barrier (BBB) disruption and oedema formation through a series of mechanisms involving Rho-kinase activation. Using an animal model of human focal cerebral ischaemia, this study assessed and confirmed the therapeutic potential of Rho-kinase inhibition during the acute phase of stroke by displaying significantly improved functional outcome and reduced cerebral lesion and oedema volumes in fasudil- versus vehicle-treated animals. Analyses of ipsilateral and contralateral brain samples obtained from mice treated with vehicle or fasudil at the onset of reperfusion plus 4 h post-ischaemia or 4 h post-ischaemia alone revealed these benefits to be independent of changes in the activity and expressions of oxidative stress- and tight junction-related parameters. However, closer scrutiny of the same parameters in brain microvascular endothelial cells subjected to oxygen-glucose deprivation ± reperfusion revealed marked increases in prooxidant NADPH oxidase enzyme activity, superoxide anion release and in expressions of antioxidant enzyme catalase and tight junction protein claudin-5. Cotreatment of cells with Y-27632 prevented all of these changes and protected in vitro barrier integrity and function. These findings suggest that inhibition of Rho-kinase after acute ischaemic attacks improves cerebral integrity and function through regulation of endothelial cell oxidative stress and reorganization of intercellular junctions. Inhibition of Rho-kinase (ROCK) activity in a mouse model of human ischaemic stroke significantly improved functional outcome while reducing cerebral lesion and oedema volumes compared to vehicle-treated counterparts. Studies conducted with brain microvascular endothelial cells exposed to OGD ± R in the presence of Y-27632 revealed restoration of intercellular junctions and suppression of prooxidant NADPH oxidase activity as important factors in ROCK inhibition-mediated BBB protection.

Pulse mixing by Fibonacci and Thue-Morse ordered semiconductor layers

The properties of combinatorial frequency generation by two-tone Gaussian pulses incident at oblique angles on quasiperiodic (Fibonacci and Thue-Morse) stacks of binary semiconductor layers are discussed. The analysis has been performed using the self-consistent model taking into account the nonlinear dynamics of mobile charges in the layers. The effects of the stack arrangements and constituent layer parameters on the combinatorial frequency waveforms are presented for the specific structures of both types

The Application of Semiconductor Photocatalysis for the Removal of Cyanotoxins from Water and Design Concepts for Solar Photocatalytic Reactors for Large Scale Water Treatment

There has been a significant increase in the occurrence of cyanobacterial blooms in freshwaters over the past few decades due to escalating nutrient levels. These cyanobacteria release a range of toxins, for example microcystins which are chemically very stable. Many cyanotoxins are consequently very difficult to remove from water using existing treatment technologies. Semiconductor photocatalysis, however, has proven to be a very effective process for the removal of these compounds from water. In this chapter we consider the application of this highly versatile and exciting technology for the decomposition of cyanotoxins. Furthermore design concepts for solar photocatalytic reactors that could be utilized for the removal of these toxins are also considered

Removal of microorganisms and their chemical metabolites from water using semiconductor photocatalysis

Semiconductor photocatalysis has been applied to the remediation of an extensive range of chemical pollutants in water over the past 30 years. The application of this versatile technology for removal of micro-organisms and cyanotoxins has recently become an area that has also been the subject of extensive research particularly over the past decade. This paper considers recent research in the application of semiconductor photocatalysis for the treatment of water contaminated with pathogenic micro-organisms and cyanotoxins. The basic processes involved in photocatalysis are described and examples of recent research into the use of photocatalysis for the removal of a range of microorganisms are detailed. The paper concludes with a review of the key research on the application of this process for the removal of chemical metabolites generated from cyanobacteria.

Factors affecting the photoelectrochemical fixation of carbon dioxide with semiconductor colloids

Carbon dioxide was reduced photocatalytically using aqueous CdS or ZnS colloids containing tetramethylammonium chloride to give the dimeric and tetrameric products namely, oxalate, glyoxylate, glycolate and tartrate. A model is presented to explain the role of the tetramethylammonium ions. Studies were also performed using ZnO, SiC, BaTiO₃ and Sr TiO₃, which in the absence of tetramethylammonium ions produced formate and formaldehyde. The relative quantum efficiencies of the six semiconductors were related to their band gaps and conduction band potentials. The role and effectiveness of several 'hole acceptor' (electron donor) compounds in this process is shown to be related to their redox potentials.

Destruction of cyanobacterial toxins by semiconductor photocatalysis

The rapid destruction of microcystin, a cyanobacterial toxin, using a titanium dioxide photocatalyst is observed; the process is extremely efficient with high concentrations of toxin completely undetectable within 10-40 min, depending on the initial concentration.