Self-organized colloidal quantum dots and metal nanoparticles for plasmon-enhanced intermediate-band solar cells

A colloidal deposition technique is presented to construct long-range ordered hybrid arrays of self-assembled quantum dots and metal nanoparticles. Quantum dots are promising for novel opto-electronic devices but, in most cases, their optical transitions of interest lack sufficient light absorption to provide a significant impact in their implementation. A potential solution is to couple the dots with localized plasmons in metal nanoparticles. The extreme confinement of light in the near-field produced by the nanoparticles can potentially boost the absorption in the quantum dots by up to two orders of magnitude. In this work, light extinction measurements are employed to probe the plasmon resonance of spherical gold nanoparticles in lead sulfide colloidal quantum dots and amorphous silicon thin-films. Mie theory computations are used to analyze the experimental results and determine the absorption enhancement that can be generated by the highly intense near-field produced in the vicinity of the gold nanoparticles at their surface plasmon resonance. The results presented here are of interest for the development of plasmon-enhanced colloidal nanostructured photovoltaic materials, such as colloidal quantum dot intermediate-band solar cells.

Self-organized defensive behavior in honeybees

We investigated the defensive behavior of honeybees under controlled experimental conditions. During an attack on two identical targets, the spatial distribution of stings varied as a function of the total number of stings, evincing the classic “pitchfork bifurcation” phenomenon of nonlinear dynamics. The experimental results support a model of defensive behavior based on a self-organizing mechanism. The model helps to explain several of the characteristic features of the honeybee defensive response: (i) the ability of the colony to localize and focus its attack, (ii) the strong variability between different hives in the intensity of attack, as well as (iii) the variability observed within the same hive, and (iv) the ability of the colony to amplify small differences between the targets.

Self-organized phase transitions in neural networks as a neural mechanism of information processing.

Transitions between dynamically stable activity patterns imposed on an associative neural network are shown to be induced by self-organized infinitesimal changes in synaptic connection strength and to be a kind of phase transition. A key event for the neural process of information processing in a population coding scheme is transition between the activity patterns encoding usual entities. We propose that the infinitesimal and short-term synaptic changes based on the Hebbian learning rule are the driving force for the transition. The phase transition between the following two dynamical stable states is studied in detail, the state where the firing pattern is changed temporally so as to itinerate among several patterns and the state where the firing pattern is fixed to one of several patterns. The phase transition from the pattern itinerant state to a pattern fixed state may be induced by the Hebbian learning process under a weak input relevant to the fixed pattern. The reverse transition may be induced by the Hebbian unlearning process without input. The former transition is considered as recognition of the input stimulus, while the latter is considered as clearing of the used input data to get ready for new input. To ensure that information processing based on the phase transition can be made by the infinitesimal and short-term synaptic changes, it is absolutely necessary that the network always stays near the critical state corresponding to the phase transition point.

Self-organized criticality: sandpiles, singularities, and scaling.

We present an overview of the statistical mechanics of self-organized criticality. We focus on the successes and failures of hydrodynamic description of transport, which consists of singular diffusion equations. When this description applies, it can predict the scaling features associated with these systems. We also identify a hard driving regime where singular diffusion hydrodynamics fails due to fluctuations and give an explicit criterion for when this failure occurs.

Evolution as a self-organized critical phenomenon.

We present a simple mathematical model of biological macroevolution. The model describes an ecology of adapting, interacting species. The environment of any given species is affected by other evolving species; hence, it is not constant in time. The ecology as a whole evolves to a "self-organized critical" state where periods of stasis alternate with avalanches of causally connected evolutionary changes. This characteristic behavior of natural history, known as "punctuated equilibrium," thus finds a theoretical explanation as a self-organized critical phenomenon. The evolutionary behavior of single species is intermittent. Also, large bursts of apparently simultaneous evolutionary activity require no external cause. Extinctions of all sizes, including mass extinctions, may be a simple consequence of ecosystem dynamics. Our results are compared with data from the fossil record.

Parents of the handicapped; self-organized parents' and relatives' groups for treatment of ill and handicapped children.

Mode of access: Internet.

Nanostructures, Semicrytalline Morphology, and Nanoscale Confinement Effect on the Crystallization Kinetics in Self-Organized Block Copolymer/Thermoset Blends

This work reports the first instance of self-organized thermoset blends containing diblock copolymers with a crystallizable thermoset-immiscible block. Nanostructured thermoset blends of bisphenol A-type epoxy resin (ER) and a low-molecular-weight (M-n = 1400) amphiphilic polyethylene-block-poly(ethylene oxide) (EEO) symmetric diblock copolymer were prepared using 4,4'-methylenedianiline (MDA) as curing agent and were characterized by transmission electron microscopy (TEM), atomic force microscopy (AFM), small-angle X-ray scattering (SAXS), and differential scanning calorimetry (DSC). All the MDA-cured ER/EEO blends do not show macroscopic phase separation but exhibit microstructures. The ER selectively mixes with the epoxy-miscible PEO block in the EEO diblock copolymer whereas the crystallizable PE blocks that are immiscible with ER form separate microdomains at nanoscales in the blends. The PE crystals with size on nanoscales are formed and restricted within the individual spherical micelles in the nanostructured ER/EEO blends with EEO content up to 30 wt %. The spherical micelles are highly aggregated in the blends containing 40 and 50 wt % EEO. The PE dentritic crystallites exist in the blend containing 50 wt % EEO whereas the blends with even higher EEO content are completely volume-filled with PE spherulites. The semicrystalline microphase-separated lamellae in the symmetric EEO diblock copolymer are swollen in the blend with decreasing EEO content, followed by a structural transition to aggregated spherical micellar phase morphology and, eventually, spherical micellar phase morphology at the lowest EEO contents. Three morphological regimes are identified, corresponding precisely to the three regimes of crystallization kinetics of the PE blocks. The nanoscale confinement effect on the crystallization kinetics in nanostructured thermoset blends is revealed for the first time. This new phenomenon is explained on the basis of homogeneous nucleation controlled crystallization within nanoscale confined environments in the block copolymer/thermoset blends.

Use of Start Pages for Building a Mashup Personal Learning Environment to Support Self-Organized Learners

The paper explores the functionalities of eight start pages and considers their usefulness when used as a mashable platform for deployment of personal learning environments (PLE) for self-organized learners. The Web 2.0 effects and eLearning 2.0 strategies are examined from the point of view of how they influence the methods of gathering and capturing data, information and knowledge, and the learning process. Mashup technology is studied in order to see what kind of components can be used in PLE realization. A model of a PLE for self-organized learners is developed and it is used to prototype a personal learning and research environment in the start pages Netvibes, Pageflakes and iGoogle.

Living bacteria rheology: Population growth, aggregation patterns, and collective behaviour under diferente shear flows

The activity of growing living bacteria was investigated using real-time and in situ rheology-in stationary and oscillatory shear. Two different strains of the human pathogen Staphylococcus aureus-strain COL and its isogenic cell wall autolysis mutant, RUSAL9-were considered in this work. For low bacteria density, strain COL forms small clusters, while the mutant, presenting deficient cell separation, forms irregular larger aggregates. In the early stages of growth, when subjected to a stationary shear, the viscosity of the cultures of both strains increases with the population of cells. As the bacteria reach the exponential phase of growth, the viscosity of the cultures of the two strains follows different and rich behaviors, with no counterpart in the optical density or in the population's colony-forming units measurements. While the viscosity of strain COL culture keeps increasing during the exponential phase and returns close to its initial value for the late phase of growth, where the population stabilizes, the viscosity of the mutant strain culture decreases steeply, still in the exponential phase, remains constant for some time, and increases again, reaching a constant plateau at a maximum value for the late phase of growth. These complex viscoelastic behaviors, which were observed to be shear-stress-dependent, are a consequence of two coupled effects: the cell density continuous increase and its changing interacting properties. The viscous and elastic moduli of strain COL culture, obtained with oscillatory shear, exhibit power-law behaviors whose exponents are dependent on the bacteria growth stage. The viscous and elastic moduli of the mutant culture have complex behaviors, emerging from the different relaxation times that are associated with the large molecules of the medium and the self-organized structures of bacteria. Nevertheless, these behaviors reflect the bacteria growth stage.

Controlled growth of anodic aluminium oxide films with hexagonal array of nanometer-sized pores filled with textured copper nanowires

Anodic aluminium oxide (AAO) films exhibiting a homogeneous morphology of parallel pores perpendicular to the surface were prepared in a two-step anodization process and filled with copper by electrochemical deposition. The optimum growth conditions for the formation of freestanding AAO films with hexagonal compact array of cylindrical pores were studied by field emission scanning electron microscopy and small angle X-ray scattering. The results show well-defined periodic structures with uniform pores size distribution for films with pore diameters between 40 and 70 nm prepared using different voltages and temperatures during the second anodization step. X-ray photoelectron spectroscopy and X-ray diffraction analysis of AAO films filled with copper show the formation of nanowires with high structural order, exhibiting a preferential crystalline orientation along the (2 2 0) axis and only small fraction of copper oxides. The best results for textured Cu nanowires were obtained at a reduction potential of -300 mV. (C) 2009 Elsevier Ltd. All rights reserved.

State detection in a financial portfolio: a self-organizing maps approach for financial time series

This study analyses financial data using the result characterization of a self-organized neural network model. The goal was prototyping a tool that may help an economist or a market analyst to analyse stock market series. To reach this goal, the tool shows economic dependencies and statistics measures over stock market series. The neural network SOM (self-organizing maps) model was used to ex-tract behavioural patterns of the data analysed. Based on this model, it was de-veloped an application to analyse financial data. This application uses a portfo-lio of correlated markets or inverse-correlated markets as input. After the anal-ysis with SOM, the result is represented by micro clusters that are organized by its behaviour tendency. During the study appeared the need of a better analysis for SOM algo-rithm results. This problem was solved with a cluster solution technique, which groups the micro clusters from SOM U-Matrix analyses. The study showed that the correlation and inverse-correlation markets projects multiple clusters of data. These clusters represent multiple trend states that may be useful for technical professionals.

Solovian and New Growth Theory from the Perspective of Allyn Young on Macroeconomic Increasing Returns

This paper evaluates, from an Allyn Youngian perspective, the neoclassical Solow model of growth and the associated empirical estimates of the sources of growth based on it. It attempts to clarify Young’s particular concept of generalised or macroeconomic “increasing returns” to show the limitations of a model of growth based on an assumption that the aggregate production function is characterised by constant returns to scale but “augmented” by exogenous technical progress. Young’s concept of endogenous, self-sustaining growth is also shown to differ in important respects (including in its policy implications) from modern endogenous growth theory.

Self-Development of Competences for Social Inclusion Using the TENCompetence Infrastructure

This paper describes a pilot study centred on the technology-enhanced self-development of competences in lifelong learning education carried out in the challenging context of the Association of Participants Àgora. The pilot study shows that the use of the TENCompetence infrastructure, i.e. in this case the Personal Development Planner tool, provides various kinds of benefits for adult participants with low educational profiles and who are traditionally excluded from the use of innovative learning technologies and the knowledge society. The selforganized training supported by the PDP tool aims at allowing the learners to create and control their own learning plans based on their interests and educational background including informal and non-formal experiences. In this sense, the pilot participants had the opportunity to develop and improve their competences in English language (basic and advanced levels) and ICT competence profiles which are mostly related to functional and communicative skills. Besides, the use of the PDP functionalities, such as the self-assessment, the planning and the self-regulating elements allowed the participants to develop reflective skills. Pilot results also provide indications for future developments in the field of technology support for self-organized learners. The paper introduces the context and the pilot scenario, indicates the evaluation methodology applied and discusses the most significant findings derived from the pilot study.

Nucleation and growth of GaN nanorods on Si (111) surfaces by plasma-assisted molecular beam epitaxy - The influence of Si- and Mg-doping

The self-assembled growth of GaN nanorods on Si (111) substrates by plasma-assisted molecular beam epitaxy under nitrogen-rich conditions is investigated. An amorphous silicon nitride layer is formed in the initial stage of growth that prevents the formation of a GaN wetting layer. The nucleation time was found to be strongly influenced by the substrate temperature and was more than 30 min for the applied growth conditions. The observed tapering and reduced length of silicon-doped nanorods is explained by enhanced nucleation on nonpolar facets and proves Ga-adatom diffusion on nanorod sidewalls as one contribution to the axial growth. The presence of Mg leads to an increased radial growth rate with a simultaneous decrease of the nanorod length and reduces the nucleation time for high Mg concentrations.