A closely integrated digital image capture device for embedded applications

A modular image capture system with close integration to CCD cameras has been developed. The aim is to produce a system capable of integrating CCD sensor, image capture and image processing into a single compact unit. This close integration provides a direct mapping between CCD pixels and digital image pixels. The system has been interfaced to a digital signal processor board for the development and control of image processing tasks. These have included characterization and enhancement of noisy images from an intensified camera and measurement to subpixel resolutions. A highly compact form of the image capture system is in an advanced stage of development. This consists of a single FPGA device and a single VRAM providing a two chip image capturing system capable of being integrated into a CCD camera. A miniature compact PC has been developed using a novel modular interconnection technique, providing a processing unit in a three dimensional format highly suited to integration into a CCD camera unit. Work is under way to interface the compact capture system to the PC using this interconnection technique, combining CCD sensor, image capture and image processing into a single compact unit. ©2005 Copyright SPIE - The International Society for Optical Engineering.

Embedded Model Predictive Control (MPC) using a FPGA

Model Predictive Control (MPC) is increasingly being proposed for application to miniaturized devices, fast and/or embedded systems. A major obstacle to this is its computation time requirement. Continuing our previous studies of implementing constrained MPC on Field Programmable Gate Arrays (FPGA), this paper begins to exploit the possibilities of parallel computation, with the aim of speeding up the MPC implementation. Simulation studies on a realistic example show that it is possible to implement constrained MPC on an FPGA chip with a 25MHz clock and achieve MPC implementation rates comparable to those achievable on a Pentium 3.0 GHz PC. Copyright © 2007 International Federation of Automatic Control All Rights Reserved.

The role of the surfaces in the photon absorption in Ge nanoclusters embedded in silica.

The usage of semiconductor nanostructures is highly promising for boosting the energy conversion efficiency in photovoltaics technology, but still some of the underlying mechanisms are not well understood at the nanoscale length. Ge quantum dots (QDs) should have a larger absorption and a more efficient quantum confinement effect than Si ones, thus they are good candidate for third-generation solar cells. In this work, Ge QDs embedded in silica matrix have been synthesized through magnetron sputtering deposition and annealing up to 800°C. The thermal evolution of the QD size (2 to 10 nm) has been followed by transmission electron microscopy and X-ray diffraction techniques, evidencing an Ostwald ripening mechanism with a concomitant amorphous-crystalline transition. The optical absorption of Ge nanoclusters has been measured by spectrophotometry analyses, evidencing an optical bandgap of 1.6 eV, unexpectedly independent of the QDs size or of the solid phase (amorphous or crystalline). A simple modeling, based on the Tauc law, shows that the photon absorption has a much larger extent in smaller Ge QDs, being related to the surface extent rather than to the volume. These data are presented and discussed also considering the outcomes for application of Ge nanostructures in photovoltaics.PACS: 81.07.Ta; 78.67.Hc; 68.65.-k.

Light absorption in silicon quantum dots embedded in silica

The photon absorption in Si quantum dots (QDs) embedded in SiO2 has been systematically investigated by varying several parameters of the QD synthesis. Plasma-enhanced chemical vapor deposition (PECVD) or magnetron cosputtering (MS) have been used to deposit, upon quartz substrates, single layer, or multilayer structures of Si-rich- SiO2 (SRO) with different Si content (43-46 at. %). SRO samples have been annealed for 1 h in the 450-1250 °C range and characterized by optical absorption measurements, photoluminescence analysis, Rutherford backscattering spectrometry and x-ray Photoelectron Spectroscopy. After annealing up to 900 °C SRO films grown by MS show a higher absorption coefficient and a lower optical bandgap (∼2.0 eV) in comparison with that of PECVD samples, due to the lower density of Si-Si bonds and to the presence of nitrogen in PECVD materials. By increasing the Si content a reduction in the optical bandgap has been recorded, pointing out the role of Si-Si bonds density in the absorption process in small amorphous Si QDs. Both the photon absorption probability and energy threshold in amorphous Si QDs are higher than in bulk amorphous Si, evidencing a quantum confinement effect. For temperatures higher than 900 °C both the materials show an increase in the optical bandgap due to the amorphous-crystalline transition of the Si QDs. Fixed the SRO stoichiometry, no difference in the optical bandgap trend of multilayer or single layer structures is evidenced. These data can be profitably used to better implement Si QDs for future PV technologies. © 2009 American Institute of Physics.

First-principles energetics of water clusters and ice: a many-body analysis.

Standard forms of density-functional theory (DFT) have good predictive power for many materials, but are not yet fully satisfactory for cluster, solid, and liquid forms of water. Recent work has stressed the importance of DFT errors in describing dispersion, but we note that errors in other parts of the energy may also contribute. We obtain information about the nature of DFT errors by using a many-body separation of the total energy into its 1-body, 2-body, and beyond-2-body components to analyze the deficiencies of the popular PBE and BLYP approximations for the energetics of water clusters and ice structures. The errors of these approximations are computed by using accurate benchmark energies from the coupled-cluster technique of molecular quantum chemistry and from quantum Monte Carlo calculations. The systems studied are isomers of the water hexamer cluster, the crystal structures Ih, II, XV, and VIII of ice, and two clusters extracted from ice VIII. For the binding energies of these systems, we use the machine-learning technique of Gaussian Approximation Potentials to correct successively for 1-body and 2-body errors of the DFT approximations. We find that even after correction for these errors, substantial beyond-2-body errors remain. The characteristics of the 2-body and beyond-2-body errors of PBE are completely different from those of BLYP, but the errors of both approximations disfavor the close approach of non-hydrogen-bonded monomers. We note the possible relevance of our findings to the understanding of liquid water.