Vacancy and interstitial depth profiles in ion-implanted silicon

An experimental method of studying shifts between concentration-versus-depth profiles of vacancy- and interstitial-type defects in ion-implanted silicon is demonstrated. The concept is based on deep level transient spectroscopy measurements utilizing the filling pulse variation technique. The vacancy profile, represented by the vacancy¿oxygen center, and the interstitial profile, represented by the interstitial carbon¿substitutional carbon pair, are obtained at the same sample temperature by varying the duration of the filling pulse. The effect of the capture in the Debye tail has been extensively studied and taken into account. Thus, the two profiles can be recorded with a high relative depth resolution. Using low doses, point defects have been introduced in lightly doped float zone n-type silicon by implantation with 6.8 MeV boron ions and 680 keV and 1.3 MeV protons at room temperature. The effect of the angle of ion incidence has also been investigated. For all implantation conditions the peak of the interstitial profile is displaced towards larger depths compared to that of the vacancy profile. The amplitude of this displacement increases as the width of the initial point defect distribution increases. This behavior is explained by a simple model where the preferential forward momentum of recoiling silicon atoms and the highly efficient direct recombination of primary point defects are taken into account.

Identification of amino acid residues in the alpha, beta, and gamma subunits of the epithelial sodium channel (ENaC) involved in amiloride block and ion permeation.

The amiloride-sensitive epithelial Na channel (ENaC) is a heteromultimeric channel made of three alpha beta gamma subunits. The structures involved in the ion permeation pathway have only been partially identified, and the respective contributions of each subunit in the formation of the conduction pore has not yet been established. Using a site-directed mutagenesis approach, we have identified in a short segment preceding the second membrane-spanning domain (the pre-M2 segment) amino acid residues involved in ion permeation and critical for channel block by amiloride. Cys substitutions of Gly residues in beta and gamma subunits at position beta G525 and gamma G537 increased the apparent inhibitory constant (Ki) for amiloride by > 1,000-fold and decreased channel unitary current without affecting ion selectivity. The corresponding mutation S583 to C in the alpha subunit increased amiloride Ki by 20-fold, without changing channel conducting properties. Coexpression of these mutated alpha beta gamma subunits resulted in a non-conducting channel expressed at the cell surface. Finally, these Cys substitutions increased channel affinity for block by external Zn2+ ions, in particular the alpha S583C mutant showing a Ki for Zn2+ of 29 microM. Mutations of residues alpha W582L, or beta G522D also increased amiloride Ki, the later mutation generating a Ca2+ blocking site located 15% within the membrane electric field. These experiments provide strong evidence that alpha beta gamma ENaCs are pore-forming subunits involved in ion permeation through the channel. The pre-M2 segment of alpha beta gamma subunits may form a pore loop structure at the extracellular face of the channel, where amiloride binds within the channel lumen. We propose that amiloride interacts with Na+ ions at an external Na+ binding site preventing ion permeation through the channel pore.

White luminescence from Si+ and C+ ion-implanted SiO2 films

The microstructural and optical analysis of SiO2 layers emitting white luminescence is reported. These structures have been synthesized by sequential Si+ and C+ ion implantation and high-temperature annealing. Their white emission results from the presence of up to three bands in the photoluminescence (PL) spectra, covering the whole visible spectral range. The microstructural characterization reveals the presence of a complex multilayer structure: Si nanocrystals are only observed outside the main C-implanted peak region, with a lower density closer to the surface, being also smaller in size. This lack of uniformity in their density has been related to the inhibiting role of C in their growth dynamics. These nanocrystals are responsible for the band appearing in the red region of the PL spectrum. The analysis of the thermal evolution of the red PL band and its behavior after hydrogenation shows that carbon implantation also prevents the formation of well passivated Si/SiO2 interfaces. On the other hand, the PL bands appearing at higher energies show the existence of two different characteristics as a function of the implanted dose. For excess atomic concentrations below or equal to 10%, the spectra show a PL band in the blue region. At higher doses, two bands dominate the green¿blue spectral region. The evolution of these bands with the implanted dose and annealing time suggests that they are related to the formation of carbon-rich precipitates in the implanted region. Moreover, PL versus depth measurements provide a direct correlation of the green band with the carbon-implanted profile. These PL bands have been assigned to two distinct amorphous phases, with a composition close to elemental graphitic carbon or stoichiometric SiC.

Modifications in the Si valence band after ion-beam-induced oxidation

The changes undergone by the Si surface after oxygen bombardment have special interest for acquiring a good understanding of the Si+-ion emission during secondary ion mass spectrometry (SIMS) analysis. For this reason a detailed investigation on the stoichiometry of the builtup surface oxides has been carried out using in situ x-ray photoemission spectroscopy (XPS). The XPS analysis of the Si 2p core level indicates a strong presence of suboxide chemical states when bombarding at angles of incidence larger than 30°. In this work a special emphasis on the analysis and interpretation of the valence band region was made. Since the surface stoichiometry or degree of oxidation varies with the angle of incidence, the respective valence band structures also differ. A comparison with experimentally measured and theoretically derived Si valence band and SiO2 valence band suggests that the new valence bands are formed by a combination of these two. This arises from the fact that Si¿Si bonds are present on the Si¿suboxide molecules, and therefore the corresponding 3p-3p Si-like subband, which extends towards the Si Fermi level, forms the top of the respective new valence bands. Small variations in intensity and energy position for this subband have drastic implications on the intensity of the Si+-ion emission during sputtering in SIMS measurements. A model combining chemically enhanced emission and resonant tunneling effects is suggested for the variations observed in ion emission during O+2 bombardment for Si targets.

Structural and gas-sensing properties of WO3 nanocrystalline powders obtained by a sol-gel method from tungstic acid

WO3 nanocrystalline powders were obtained from tungstic acid following a sol-gel process. Evolution of structural properties with annealing temperature was studied by X-ray diffraction and Raman spectroscopy. These structural properties were compared with those of WO3 nanopowders obtained by the most common process of pyrolysis of ammonium paratungstate, usually used in gas sensors applications. Sol-gel WO3 showed a high sensor response to NO2 and low response to CO and CH4. The response of these sensor devices was compared with that of WO3 obtained from pyrolysis, showing the latter a worse sensor response to NO2. Influence of operating temperature, humidity, and film thickness on NO2 detection was studied in order to improve the sensing conditions to this gas.

Gas-sensing properties of sprayed films of (CdO)x(ZnO)1-x mixed oxide

A novel NO2 sensor based on (CdO)x(ZnO)1-x mixed-oxide thin films deposited by the spray pyrolysis technique is developed. The sensor response to 3-ppm NO2 is studied in the range 50°C-350°C for three different film compositions. The device is also tested for other harmful gases, such as CO (300 ppm) and CH4 (3000 ppm). The sensor response to these reducing gases is different at different temperatures varying from the response typical for the p-type semiconductor to that typical for the n-type semiconductor. Satisfactory response to NO2 and dynamic behavior at 230°C, as well as low resistivity, are observed for the mixed-oxide film with 30% Cd. The response to interfering gas is poor at working temperature (230°C). On the basis of this study, a possible sensing mechanism is proposed.

Gas sensing properties of catalytically modified WO3 with copper and vanadium for NH3 detection

Ammonia gas detection by pure and catalytically modified WO3 based gas sensor was analysed. The sensor response of pure WO3 to NH3 was not only rather low but also presented an abnormal behaviour, probably due to the unselective oxidation of ammonia to NOx. Copper and vanadium were introduced in different concentrations and the resulting material was annealed at different temperatures in order to improve the sensing properties for NH3 detection. The introduction of copper and vanadium as catalytic additives improved the response to NH3 and also eliminated the abnormal behaviour. Possible mechanisms of NH3 reaction over these materials are discussed. Sensor responses to other gases like NO2 or CO and the interference of humidity on ammonia detection were also analysed so as to choose the best sensing element.

Configurational statistical model for the damaged structure of silicon oxide after ion implantation

A configurational model for silicon oxide damaged after a high-dose ion implantation of a nonreactive species is presented. Based on statistics of silicon-centered tetrahedra, the model takes into account not only the closest environment of a given silicon atom, but also the second neighborhood, so it is specified whether the oxygen attached to one given silicon is bridging two tetrahedra or not. The frequencies and intensities of infrared vibrational bands have been calculated by averaging over the distributions and these results are in agreement with the ones obtained from infrared experimental spectra. Likewise, the chemical shifts obtained from x-ray photoelectron spectroscopy (XPS) analysis are similar to the reported values for the charge-transfer model of SiOx compounds.

Effect of a temperature increase in the non-noxious range on proton-evoked ASIC and TRPV1 activity.

Acid-sensing ion channels (ASICs) are neuronal H(+)-gated cation channels, and the transient receptor potential vanilloid 1 channel (TRPV1) is a multimodal cation channel activated by low pH, noxious heat, capsaicin, and voltage. ASICs and TRPV1 are present in sensory neurons. It has been shown that raising the temperature increases TRPV1 and decreases ASIC H(+)-gated current amplitudes. To understand the underlying mechanisms, we have analyzed ASIC and TRPV1 function in a recombinant expression system and in dorsal root ganglion (DRG) neurons at room and physiological temperature. We show that temperature in the range studied does not affect the pH dependence of ASIC and TRPV1 activation. A temperature increase induces, however, a small alkaline shift of the pH dependence of steady-state inactivation of ASIC1a, ASIC1b, and ASIC2a. The decrease in ASIC peak current amplitudes at higher temperatures is likely in part due to the observed accelerated open channel inactivation kinetics and for some ASIC types to the changed pH dependence of steady-state inactivation. The increase in H(+)-activated TRPV1 current at the higher temperature is at least in part due to a hyperpolarizing shift in its voltage dependence. The contribution of TRPV1 relative to ASICs to H(+)-gated currents in DRG neurons increases with higher temperature and acidity. Still, ASICs remain the principal pH sensors of DRG neurons at 35°C in the pH range ≥6.

Domain Adaptation in remote sensing: increasing the portability of land-cover classifiers

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

Nonlinear inverse dynamic models of gas sensing systems based on chemical sensor arrays for quantitative measurements

Gas sensing systems based on low-cost chemical sensor arrays are gaining interest for the analysis of multicomponent gas mixtures. These sensors show different problems, e.g., nonlinearities and slow time-response, which can be partially solved by digital signal processing. Our approach is based on building a nonlinear inverse dynamic system. Results for different identification techniques, including artificial neural networks and Wiener series, are compared in terms of measurement accuracy.

Raman microstructural analysis of silicon-on-insulator formed by high dose oxygen ion implantation: As-implanted structures

A microstructural analysis of silicon-on-insulator samples obtained by high dose oxygen ion implantation was performed by Raman scattering. The samples analyzed were obtained under different conditions thus leading to different concentrations of defects in the top Si layer. The samples were implanted with the surface covered with SiO2 capping layers of different thicknesses. The spectra measured from the as-implanted samples were fitted to a correlation length model taking into account the possible presence of stress effects in the spectra. This allowed quantification of both disorder effects, which are determined by structural defects, and residual stress in the top Si layer before annealing. These data were correlated to the density of dislocations remaining in the layer after annealing. The analysis performed corroborates the existence of two mechanisms that generate defects in the top Si layer that are related to surface conditions during implantation and the proximity of the top Si/buried oxide layer interface to the surface before annealing.