RESUMEN
Ion beam analysis (IBA) is a cluster of techniques including Rutherford and non-Rutherford backscattering spectrometry and particle-induced X-ray emission (PIXE). Recently, the ability to treat multiple IBA techniques (including PIXE) self-consistently has been demonstrated. The utility of IBA for accurately depth profiling thin films is critically reviewed. As an important example of IBA, three laboratories have independently measured a silicon sample implanted with a fluence of nominally 5 × 10(15) As/cm(2) at an unprecedented absolute accuracy. Using 1.5 MeV (4)He(+) Rutherford backscattering spectrometry (RBS), each lab has demonstrated a combined standard uncertainty around 1% (coverage factor k = 1) traceable to an Sb-implanted certified reference material through the silicon electronic stopping power. The uncertainty budget shows that this accuracy is dominated by the knowledge of the electronic stopping, but that special care must also be taken to accurately determine the electronic gain of the detection system and other parameters. This RBS method is quite general and can be used routinely to accurately validate ion implanter charge collection systems, to certify SIMS standards, and for other applications. The generality of application of such methods in IBA is emphasized: if RBS and PIXE data are analysed self-consistently then the resulting depth profile inherits the accuracy and depth resolution of RBS and the sensitivity and elemental discrimination of PIXE.
RESUMEN
We report on the structural and electrical properties of Mn-doped ZnO/Al(2)O(3) nanostructures produced by the pulsed laser deposition technique. Grazing incidence small angle x-ray scattering (GISAXS) and Rutherford backscattering spectrometry revealed the multilayered structure in as-deposited samples. Annealing of the nanostructures was shown to promote the formation of nanocrystals embedded in the Al(2)O(3) matrix, as was evidenced by GISAXS and high resolution transmission microscopy. Particle-induced x-ray emission analysis showed a doping of 8 at.% Mn in ZnO. Grazing incidence x-ray diffraction and Raman spectroscopy demonstrated that the nanocrystals have the pure wurtzite ZnMnO crystalline phase. Resonant Raman scattering displayed an increase of intensity of the 1LO mode as well as broadening of the 2LO mode related to the size effect. Capacitance-voltage measurements showed carrier retention with a voltage shift higher than those reported for similar systems.
RESUMEN
A study on the structure, electrical and optical properties of ZnO thin films produced by r.f. magnetron sputtering and implanted either with phosphorous (P) or antimony (Sb) is reported in this work. Raman spectroscopy, X-ray diffraction, optical transmittance and Hall effect measurements have been employed to characterize the samples. X-ray diffraction and Raman scattering patterns confirm that, after a 500 degrees C annealing, the doped films keep a polycrystalline nature with (002) preferred orientation. These films are very transparent and Hall effect results show that all have p-type conduction, despite doping ion and dose. The electric resistivity reaches values of 0.012 (omega cm) and 0.042 (omega cm) for the P and Sb-doped samples, respectively.
RESUMEN
Active polymer substrates have found their way in the semiconductor industry as a base layer for flexible electronics, as well as in sensor and actuator applications. The optimum performance of these systems may be affected by dirt adsorbed on its surface, which can also originate mechanisms for the degradation of the polymer. Titanium dioxide (titania) semiconductor photocatalytic thin films have been deposited by unbalanced reactive magnetron sputtering on one of the most applied and investigated electroactive polymer: poly(vinilidene fluoride), PVDF. In order to increase the photocatalytic efficiency of the titania coatings, a reduction of the semiconductor band-gap has been attempted by using a nitrogen doping. Rutherford Backscattering Spectroscopy was used in order to assess the composition of the titania thin films, whereas Heavy Ion Elastic Recoil Detection Analysis provided the evaluation of the doping level of nitrogen. X-ray Photoelectron Spectroscopy provided valuable information about the cation-anion binding within the semiconductor lattice. The photocatalytic performance of the titania films have been characterized by decomposing an organic dye illuminated with combined UV/visible light.
RESUMEN
ZnO films were deposited on c-plane sapphire substrates in Ar atmosphere by rf magnetron sputtering and were post-annealed at 400 degrees C in green gas (95% N2 + 5% H2). The properties of the as-grown and annealed films have been characterized by X-ray diffraction (XRD), Rutherford backscattering (RBS), elastic recoil detection analysis (ERDA), Hall measurement and photoluminescence spectra. XRD studies confirmed the variation in strain and an improvement in crystallinity. From RBS and ERDA analysis, the presence of H atoms on the surface of the as-grown ZnO films was evidenced. Annealing in green gas increased the amount of H in the film. Compared with the as-grown films, the ultra exciting intensity obviously decreases in the annealed films and new optical active centres in the blue/violet (approximately 3.0 eV) and red (approximately 1.9) regions are emerged in the PL spectrum. The positive sign of Hall coefficient confirmed the low p-type conductivity in the as grown films, which was improved after annealing. However, the p-type conductivity was not stable, especially for the annealed sample it changes from p type to n type after 9 days.
RESUMEN
We present an algorithm based on artificial neural networks able to determine optimized experimental conditions for Rutherford backscattering measurements of Ge-implanted Si. The algorithm can be implemented for any other element implanted into a lighter substrate. It is foreseeable that the method developed in this work can be applied to still many other systems. The algorithm presented is a push-button black box, and does not require any human intervention. It is thus suited for automated control of an experimental setup, given an interface to the relevant hardware. Once the experimental conditions are optimized, the algorithm analyzes the final data obtained, and determines the desired parameters. The method is thus also suited for automated analysis of the data. The algorithm presented can be easily extended to other ion beam analysis techniques. Finally, it is suggested how the artificial neural networks required for automated control and analysis of experiments could be automatically generated. This would be suited for automated generation of the required computer code. Thus could RBS be done without experimentalists, data analysts, or programmers, with only technicians to keep the machines running.
RESUMEN
AlO(x)N(y) ultrathin films are used as insulating layers in advanced microelectronic devices. Structural characterization of these films is often done by the Rutherford backscattering (RBS) analysis. The RBS analysis of these oxinitrides is a difficult task since the relevant signals of the spectrum are washed out by the large substrate background and a considerable time is required for an analyst to characterize the sample. In this work we developed specialized artificial neural networks that are able to perform a fast and efficient analysis of the data. The results are in good agreement with traditional methods.
RESUMEN
In this work, the influence of air pressure during the annealing of Ge quantum dot (QD) lattices embedded in an amorphous Al(2)O(3) matrix on the structural, morphological and compositional properties of the film is studied. The formation of a regularly ordered void lattice after performing a thermal annealing process is explored. Our results show that both the Ge desorption from the film and the regular ordering of the QDs are very sensitive to the annealing parameters. The conditions for the formation of a void lattice, a crystalline Ge QD lattice and a disordered QD lattice are presented. The observed effects are explained in terms of oxygen interaction with the Ge present in the film.
RESUMEN
Variable angle spectroscopic ellipsometry is a nondestructive technique for accurately determining the thicknesses and refractive indices of thin films. Experimentally, the ellipsometry parameters psi and Delta are measured, and the sample structure is then determined by one of a variety of approaches, depending on the number of unknown variables. The ellipsometry parameters have been inverted analytically for only a small number of sample types. More general cases require either a model-based numerical technique or a series of approximations combined with a sound knowledge of the test sample structure. In this paper, the combinatorial optimization technique of simulated annealing is used to perform least-squares fits of ellipsometry data (both simulated and experimental) from both a single layer and a bilayer on a semi-infinite substrate using what is effectively a model-free system, in which the thickness and refractive indices of each layer are unknown. The ambiguity inherent in the best-fit solutions is then assessed using Bayesian inference. This is the only way to consistently treat experimental uncertainties along with prior knowledge. The Markov chain Monte Carlo algorithm is used. Mean values of unknown parameters and standard deviations are determined for each and every solution. Rutherford backscattering spectrometry is used to assess the accuracy of the solutions determined by these techniques. With our computer analysis of ellipsometry data, we find all possible models that adequately describe that data. We show that a bilayer consisting of a thin film of poly(styrene) on a thin film of silicon dioxide on a silicon substrate results in data that are ambiguous; there is more than one acceptable description of the sample that will result in the same experimental data.