942 resultados para SEMICONDUCTOR COLLOIDS
Resumo:
Unlabelled single- and double-stranded DNA (ssDNA and dsDNA, respectively) has been detected at concentrations =10-9?M by surface-enhanced Raman spectroscopy. Under appropriate conditions the sequences spontaneously adsorbed to the surface of both Ag and Au colloids through their nucleobases; this allowed highly reproducible spectra with good signal-to-noise ratios to be recorded on completely unmodified samples. This eliminated the need to promote absorption by introducing external linkers, such as thiols. The spectra of model ssDNA sequences contained bands of all the bases present and showed systematic changes when the overall base composition was altered. Initial tests also showed that small but reproducible changes could be detected between oligonucleotides with the same bases arranged in a different order. The spectra of five ssDNA sequences that correspond to different strains of the Escherichia coli bacterium were found to be sufficiently composition-dependent so that they could be differentiated without the need for any advanced multivariate data analysis techniques.
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The optical properties of plasmonic semiconductor devices fabricated by focused ion beam (FIB) milling deteriorate because of the amorphisation of the semiconductor substrate. This study explores the effects of combining traditional 30 kV FIB milling with 5 kV FIB patterning to minimise the semiconductor damage and at the same time maintain high spatial resolution. The use of reduced acceleration voltages is shown to reduce the damage from higher energy ions on the example of fabrication of plasmonic crystals on semiconductor substrates leading to 7-fold increase in transmission. This effect is important for focused-ion beam fabrication of plasmonic structures integrated with photodetectors, light-emitting diodes and semiconductor lasers.
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The nonlinear scattering of pulses by periodic stacks of semiconductor layers with magnetic bias has been studied in the self-consistent problem formulation, taking into account mobility of carriers. The three-wave mixing technique has been applied to the analysis of the waveform evolution in the stacks illuminated by two Gaussian pulses with different central frequencies and lengths. The effects of external magnetic bias, and stack physical and geometrical parameters on the properties of the scattered waveforms are discussed. © 2013 IEEE.
Resumo:
The pulsed second harmonic generation (SHG) by periodic stacks of nonlinear semiconductor layers with external magnetic bias has been studied in the self-consistent problem formulation, taking into account mobility of carriers. The products of nonlinear scattering in the three-wave mixing process are examined. It is demonstrated that the waveform evolution in magnetoactive weakly nonlinear semiconductor periodic structure illuminated by Gaussian pulse is strongly affected by the magnetic bias and collision frequency of the carriers. The effect of nonreciprocity on the SHG efficiency is discussed and illustrated by the examples. © 2013 European Microwave Association.
Resumo:
The properties of the combinatorial frequency generation and wave scattering by periodic stacks of nonlinear passive semiconductor layers are explored. It is demonstrated that the nonlinearity in passive weakly nonlinear semiconductor medium has the resistive nature associated with the dynamics of carriers. The features of the combinatorial frequency generation and the effects of the pump wave scattering and parameters of the constituent semiconductor layers on the efficiency of the frequency mixing are discussed and illustrated by the examples. © 2013 IEICE.
Resumo:
Smart management of maintenances has become fundamental in manufacturing environments in order to decrease downtime and costs associated with failures. Predictive Maintenance (PdM) systems based on Machine Learning (ML) techniques have the possibility with low added costs of drastically decrease failures-related expenses; given the increase of availability of data and capabilities of ML tools, PdM systems are becoming really popular, especially in semiconductor manufacturing. A PdM module based on Classification methods is presented here for the prediction of integral type faults that are related to machine usage and stress of equipment parts. The module has been applied to an important class of semiconductor processes, ion-implantation, for the prediction of ion-source tungsten filament breaks. The PdM has been tested on a real production dataset. © 2013 IEEE.
Resumo:
The combinatorial frequency generation by the periodic stacks of magnetically biased semiconductor layers has been modelled in a self-consistent problem formulation, taking into account the nonlinear dynamics of carriers. It is shown that magnetic bias not only renders nonreciprocity of the three-wave mixing process but also significantly enhances the nonlinear interactions in the stacks, especially at the frequencies close to the intrinsic magneto-plasma resonances of the constituent layers. The main mechanisms and properties of the combinatorial frequency generation and emission from the stacks are illustrated by the simulation results, and the effects of the individual layer parameters and the structure arrangement on the stack nonlinear and nonreciprocal response are discussed. © 2014 Elsevier B.V. All rights reserved.
Resumo:
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.
Resumo:
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.
Resumo:
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.