Interplay Between Structure, Stoichiometry, and Electron Transfer Dynamics in SILAR-based Quantum Dot-Sensitized Oxides

We quantify the rate and efficiency of picosecond electron transfer (ET) from PbS nanocrystals, grown by successive ionic layer adsorption and reaction (SILAR), into a mesoporous SnO2 support. Successive SILAR deposition steps allow for stoichiometry- and size-variation of the QDs, characterized using transmission electron microscopy. Whereas for sulfur-rich (p-type) QD surfaces substantial electron trapping at the QD surface occurs, for lead-rich (n-type) QD surfaces, the QD trapping channel is suppressed and the ET efficiency is boosted. The ET efficiency increase achieved by lead-rich QD surfaces is found to be QD-size dependent, increasing linearly with QD surface area. On the other hand, ET rates are found to be independent of both QD size and surface stoichiometry, suggesting that the donor–acceptor energetics (constituting the driving force for ET) are fixed due to Fermi level pinning at the QD/oxide interface. Implications of our results for QD-sensitized solar cell design are discussed.

Quantum Dot-Sensitized Solar Cells Based on Directly Adsorbed Zinc Copper Indium Sulfide Colloids

Heavy metal-based quantum dots (QDs) have demonstrated to behave as efficient sensitizers in QD-sensitized solar cells (QDSSCs), as attested by the countless works and encouraging efficiencies reported so far. However, their intrinsic toxicity has arisen as a major issue for the prospects of commercialization. Here, we examine the potential of environmentally friendly zinc copper indium sulfide (ZCIS) QDs for the fabrication of liquid-junction QDSSCs by means of photoelectrochemical measurements. A straightforward approach to directly adsorb ZCIS QDs on TiO2 from a colloidal dispersion is presented. Incident photon-to-current efficiency (IPCE) spectra of sensitized photoanodes show a marked dependence on the adsorption time, with longer times leading to poorer performances. Cyclic voltammograms point to a blockage of the channels of the mesoporous TiO2 film by the agglomeration of QDs as the main reason for the decrease in efficiency. Photoanodes were also submitted to the ZnS treatment. Its effects on electron recombination with the electrolyte are analyzed through electrochemical impedance spectroscopy and photopotential measurements. The corresponding results bring out the role of the ZnS coating as a barrier layer preventing electron leakage toward the electrolyte, as argued in other QD-sensitized systems. The beneficial effect of the ZnS coating is ultimately reflected on the power conversion efficiency of complete devices, reaching values of 2 %. In a more general vein, through these findings, we aim to call the attention to the potentiality of this quaternary alloy, virtually unexplored as a light harvester for sensitized devices.

Inelastic electron tunneling spectroscopy of a single nuclear spin

Detection of a single nuclear spin constitutes an outstanding problem in different fields of physics such as quantum computing or magnetic imaging. Here we show that the energy levels of a single nuclear spin can be measured by means of inelastic electron tunneling spectroscopy (IETS). We consider two different systems, a magnetic adatom probed with scanning tunneling microscopy and a single Bi dopant in a silicon nanotransistor. We find that the hyperfine coupling opens new transport channels which can be resolved at experimentally accessible temperatures. Our simulations evince that IETS yields information about the occupations of the nuclear spin states, paving the way towards transport-detected single nuclear spin resonance.

Spectral BRDF-based determination of proper measurement geometries to characterize color shift of special effect coatings

A reduced set of measurement geometries allows the spectral reflectance of special effect coatings to be predicted for any other geometry. A physical model based on flake-related parameters has been used to determine nonredundant measurement geometries for the complete description of the spectral bidirectional reflectance distribution function (BRDF). The analysis of experimental spectral BRDF was carried out by means of principal component analysis. From this analysis, a set of nine measurement geometries was proposed to characterize special effect coatings. It was shown that, for two different special effect coatings, these geometries provide a good prediction of their complete color shift.

A study of a soft computing based method for 3D scenario reconstruction

Several recent works deal with 3D data in mobile robotic problems, e.g., mapping. Data comes from any kind of sensor (time of flight, Kinect or 3D lasers) that provide a huge amount of unorganized 3D data. In this paper we detail an efficient approach to build complete 3D models using a soft computing method, the Growing Neural Gas (GNG). As neural models deal easily with noise, imprecision, uncertainty or partial data, GNG provides better results than other approaches. The GNG obtained is then applied to a sequence. We present a comprehensive study on GNG parameters to ensure the best result at the lowest time cost. From this GNG structure, we propose to calculate planar patches and thus obtaining a fast method to compute the movement performed by a mobile robot by means of a 3D models registration algorithm. Final results of 3D mapping are also shown.

Flexible Framework for Real-Time Embedded Systems Based on Mobile Cloud Computing Paradigm

The development of applications as well as the services for mobile systems faces a varied range of devices with very heterogeneous capabilities whose response times are difficult to predict. The research described in this work aims to respond to this issue by developing a computational model that formalizes the problem and that defines adjusting computing methods. The described proposal combines imprecise computing strategies with cloud computing paradigms in order to provide flexible implementation frameworks for embedded or mobile devices. As a result, the imprecise computation scheduling method on the workload of the embedded system is the solution to move computing to the cloud according to the priority and response time of the tasks to be executed and hereby be able to meet productivity and quality of desired services. A technique to estimate network delays and to schedule more accurately tasks is illustrated in this paper. An application example in which this technique is experimented in running contexts with heterogeneous work loading for checking the validity of the proposed model is described.