Dendrite

The exceptional properties of localised surface plasmons (LSPs), such as local field enhancement and confinement effects, resonant behavior, make them ideal candidates to control the emission of luminescent nanoparticles. In the present work, we investigated the LSP effect on the steady-state and time-resolved emission properties of quantum dots (QDs) by organizing the dots into self-assembled dendrite structures deposited on plasmonic nanostructures. Self-assembled structures consisting of water-soluble CdTe mono-size QDs, were developed on the surface of co-sputtered TiO2 thin films doped with Au nanoparticles (NPs) annealed at different temperatures. Their steady-state fluorescence properties were probed by scanning the spatially resolved emission spectra and the energy transfer processes were investigated by the fluorescence lifetime imaging (FLIM) microscopy. Our results indicate that a resonant coupling between excitons confined in QDs and LSPs in Au NPs located beneath the self-assembled structure indeed takes place and results in (i) a shift of the ground state luminescence towards higher energies and onset of emission from excited states in QDs, and (ii) a decrease of the ground state exciton lifetime (fluorescence quenching).

A two-dimensional lattice Boltzmann-cellular automaton model is coupled with the CALPHAD (Calculation of Phase Diagrams) method for simulating dendritic growth during ternary alloy solidification with convection. In the model, the kinetics of dendritic growth is determined by the difference between the equilibrium liquidus temperature and the actual temperature at the solid/liquid interface, incorporating the effects of the interface curvature and the preferred dendritic growth orientation. The lattice Boltzmann method is used for evaluating the local liquid compositions of the two solutes impacted by diffusion and convection. Based on the local liquid compositions, the equilibrium liquidus temperature and the solid concentrations of the two solutes are obtained by the CALPHAD method. The model is applied to simulate dendritic growth of an Al–4 wt-%Cu–1 wt-%Mg ternary alloy with melt convection. The results demonstrate the high numerical convergence and stability, as well as computational efficiency, of the proposed model. Melt convection is found to influence the dendritic morphologies and microsegregation patterns in the solidification of ternary alloys.

For many decades, neurons were considered to be the elementary computational units of the brain and were assumed to summate incoming signals and elicit action potentials only in response to suprathreshold stimuli. Although modelling studies predicted that single neurons constitute a much more powerful computational entity, able to perform an array of nonlinear calculations, this possibility was not explored experimentally until the discovery of active mechanisms in the dendrites of most neuron types. Here, we review several modelling studies that have addressed information processing in single neurons, starting with those characterizing the arithmetic of different dendritic components, to those tackling neuronal integration at the cell body and, finally, those analysing the computational abilities of the axon. We present modelling predictions along with supporting experimental data in an effort to highlight the significant contribution of modelling work to enhancing our understanding of single-neuron arithmetic.

During development, Gamma-aminobutyric acidergic (GABAergic) neurons mature at early stages, long before excitatory neurons. Conversely, GABA reuptake transporters become operative later than glutamate transporters. GABA is therefore not removed efficiently from the extracellular domain and it can exert significant paracrine effects. Hence, GABA-mediated activity is a prominent source of overall neural activity in developing CNS networks, while neurons extend dendrites and axons, and establish synaptic connections. One of the unique features of GABAergic functional plasticity is that in early development, activation of GABAA receptors results in depolarizing (mainly excitatory) responses and Ca2+ influx. Although there is strong evidence from several areas of the CNS that GABA plays a significant role in neurite growth not only during development but also during adult neurogenesis, surprisingly little effort has been made into putting all these observations into a common framework in an attempt to understand the general rules that regulate these basic and evolutionary well-conserved processes. In this review, we discuss the current knowledge in this important field. In order to decipher common, universal features and highlight differences between systems throughout development, we compare findings about dendritic proliferation and remodeling in different areas of the nervous system and species, and we also review recent evidence for a role in axonal elongation. In addition to early developmental aspects, we also consider the GABAergic role in dendritic growth during adult neurogenesis, extending our discussion to the roles played by GABA during dendritic proliferation in early developing networks versus adult, well established networks.

Providing benchmark data of the thermal and metallographic parameters during the columnar-to-equiaxed transition (CET) in a wide range of alloy concentrations is of fundamental importance for understanding this phenomenon as well as for metallurgical and modeling purposes. The aim of this study was to investigate the columnar-to-equiaxed transition (CET) in aluminum-copper alloys of different compositions covering a wide range from 2 to 33.2 wt%Cu (eutectic composition), which were directionally solidified from a chill face. The thermal parameters studied included recalescence, cooling rates, temperature gradients and interphase velocities. We found that the temperature gradient and velocity of the liquidus interphase reached critical values at the CET; these critical values were between -0.44 and 0.09 K/mm and between 0.67 and 2.16 mm/s, respectively. The metallographic parameters analyzed were grain size, primary and secondary dendritic arm spacing and also eutectic spacing. The results obtained were compared with previous experimental studies, published predictions and models of the CET for similar alloys.

This work investigates the origin of creep dislocations in a Ni-base, single crystal superalloy subject to creep at an intermediate stress and temperature. Employing high angular resolution electron backscatter diffraction (HR-EBSD), electron channeling contrast imaging under controlled diffraction conditions (cECCI) and discrete dislocation dynamics (DDD) modelling, it is shown that low-angle boundariesd-which correspond to dendrite boundaries or their residues after annealingdare not the major sources of creep dislocations. At the onset of creep deformation, they are the only active sources. Creep dislocations are emitted from them and percolate into the dislocation-depleted crystal. However, the percolation is very slow. As creep deformation proceeds, before the boundary-originated dislocations move further than a few micrometers away from their source boundary, individual dislocations that are spread throughout the undeformed microstructure become active and emit avalanches of creep dislocations in boundary-free regions, i.e. regions farther than a few micrometer away from boundaries. Upon their activation, the density of creep dislocations in boundary-free regions soars by two orders of magnitude; and the entire microstructure becomes deluged with creep dislocations. The total area of boundary-free regions is several times the total area of regions covered by boundary-originated creep dislocations. Therefore, the main sources of creep dislocations are not low-angle boundaries but individual, isolated dislocations in boundary-free regions.

A nonlinear phase-field model, accounting for the Butler–Volmer electrochemical reaction kinetics, is developed to investigate the dendritic patterns during an electrodeposition process. Using lithium electrodeposition as an example, the proposed model is first verified by comparison with the Nernst equation in a 1D equilibrium system. The nonlinear electrochemical kinetics is also confirmed at non-equilibrium condition. The dendritic patterns are examined as a function of applied voltage and initial electrode surface morphology. A design map is proposed to tailor the electrode surface morphology and the applied voltage to avoid undesired dendritic patterns.

Past physiological and psychophysical experiments have shown that attention can modulate the effects of contextual information appearing outside the classical receptive field of a cortical neuron. Specifically, it has been suggested that attention, operating via cortical feedback connections, gates the effects of long-range horizontal connections underlying collinear facilitation in cortical area V1. This article proposes a novel mechanism, based on the computations performed within the dendrites of cortical pyramidal cells, that can account for these observations. Furthermore, it is shown that the top-down gating signal into V1 can result from a process of biased competition occurring in extrastriate cortex. A model based on these two assumptions is used to replicate the results of physiological and psychophysical experiments on collinear facilitation and attentional modulation.