The nature of non-equilibrium solidification of undercooled Agsingle bondCu alloys in contact with primary copper dendrites

Liquids of silver-copper alloys with near eutectic compositions embedded in a copper matrix were undercooled. The structural and microstructural investigations of these alloys solidified from undercooled temperature indicated the absence of both the eutectic reaction and diffusionless transformation below the equal free energy curve (T0). Instead the liquid maintained local equilibrium with the copper dendrites continuously until it intersected the extended solidus of the silver rich solid solution.

Modeling of growth and motion of equiaxed dendrites in a convecting melt

A numerical micro-scale model is developed to study the behavior of dendrite growth in presence of melt convection. In this method, an explicit, coupled enthalpy model is used to simulate the growth of an equiaxed dendrite, while a Volume of Fluid (VOF) method is used to track the movement of the dendrite in the convecting melt in a two-dimensional Eulerian framework. Numerical results demonstrate the effectiveness of the enthalpy model in simulating the dendritic growth involving complex shape, and the accuracy of VOF method in conserving mass and preserving the complex dendritic shape during motion. Simulations are performed in presence of uniform melt flow for both fixed and moving dendrites, and the difference in dendrite morphology is shown.

A coupled VOF-IBM-enthalpy approach for modeling motion and growth of equiaxed dendrites in a solidifying melt

A coupled methodology for simulating the simultaneous growth and motion of equiaxed dendrites in solidifying melts is presented. The model uses the volume-averaging principles and combines the features of the enthalpy method for modeling growth, immersed boundary method for handling the rigid solid-liquid interfaces, and the volume of fluid method for tracking the advection of the dendrite. The algorithm also performs explicit-implicit coupling between the techniques used. A two-dimensional framework with incompressible and Newtonian fluid is considered. Validation with available literature is performed and dendrite growth in the presence of rotational and buoyancy driven flow fields is studied. It is seen that the flow fields significantly alter the position and morphology of the dendrites. (C) 2012 Elsevier Inc. All rights reserved.

Influence fields: a quantitative framework for representation and analysis of active dendrites

Rathour RK, Narayanan R. Influence fields: a quantitative framework for representation and analysis of active dendrites. J Neurophysiol 107: 2313-2334, 2012. First published January 18, 2012; doi:10.1152/jn.00846.2011.-Neuronal dendrites express numerous voltage-gated ion channels (VGICs), typically with spatial gradients in their densities and properties. Dendritic VGICs, their gradients, and their plasticity endow neurons with information processing capabilities that are higher than those of neurons with passive dendrites. Despite this, frameworks that incorporate dendritic VGICs and their plasticity into neurophysiological and learning theory models have been far and few. Here, we develop a generalized quantitative framework to analyze the extent of influence of a spatially localized VGIC conductance on different physiological properties along the entire stretch of a neuron. Employing this framework, we show that the extent of influence of a VGIC conductance is largely independent of the conductance magnitude but is heavily dependent on the specific physiological property and background conductances. Morphologically, our analyses demonstrate that the influences of different VGIC conductances located on an oblique dendrite are confined within that oblique dendrite, thus providing further credence to the postulate that dendritic branches act as independent computational units. Furthermore, distinguishing between active and passive propagation of signals within a neuron, we demonstrate that the influence of a VGIC conductance is spatially confined only when propagation is active. Finally, we reconstruct functional gradients from VGIC conductance gradients using influence fields and demonstrate that the cumulative contribution of VGIC conductances in adjacent compartments plays a critical role in determining physiological properties at a given location. We suggest that our framework provides a quantitative basis for unraveling the roles of dendritic VGICs and their plasticity in neural coding, learning, and homeostasis.

On the microstructure-tensile property correlations in bulk metallic glass matrix composites with crystalline dendrites

Bulk metallic glass (BMG) matrix composites with crystalline dendrites as reinforcements exhibit a wide variance in their microstructures (and thus mechanical properties), which in turn can be attributed to the processing route employed, which affects the size and distribution of the dendrites. A critical investigation on the microstructure and tensile properties of Zr/Ti-based BMG composites of the same composition, but produced by different routes, was conducted so as to identify ``structure-property'' connections in these materials. This was accomplished by employing four different processing methods-arc melting, suction casting, semi-solid forging and induction melting on a water-cooled copper boat-on composites with two different dendrite volume fractions, V-d. The change in processing parameters only affects microstructural length scales such as the interdendritic spacing, lambda, and dendrite size, delta, whereas compositions of the matrix and dendrite are unaffected. Broadly, the composite's properties are insensitive to the microstructural length scales when V-d is high (similar to 75%), whereas they become process dependent for relatively lower V-d (similar to 55%). Larger delta in arc-melted and forged specimens result in higher ductility (7-9%) and lower hardening rates, whereas smaller dendrites increase the hardening rate. A bimodal distribution of dendrites offers excellent ductility at a marginal cost of yield strength. Finer lambda result in marked improvements in both ductility and yield strength, due to the confinement of shear band nucleation sites in smaller volumes of the glassy phase. Forging in the semi-solid state imparts such a microstructure. (c) 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Non-Enzymatic Electroanalysis of Glucose on Electrodeposited Au-PEDOT Dendrites

Electrodeposition of Au on poly (3,4-ethylenedioxythiophene) (PEDOT) coated carbon paper electrode results in the formation of a stable 3-D urchin-like morphology. Au-PEDOT/C electrode exhibits higher surface area, greater catalytic activity, higher sensitivity and lower detection limit for glucose analysis in an alkaline medium than Au/C electrode. Au-PEDOT/C electrode exhibits a linear current response in glucose concentration ranging up to 10 mu M with sensitivity of 515 mu A cm(-2) mu M-1 (on the basis of geometric area) and a low detection limit of 0.03 mu M with signal to noise ratio of 3. Thus, the PEDOT under-layer improves the property of Au for glucose analysis. (c) 2013 The Electrochemical Society.

Active Dendrites Regulate Spectral Selectivity in Location-Dependent Spike Initiation Dynamics of Hippocampal Model Neurons

How does the presence of plastic active dendrites in a pyramidal neuron alter its spike initiation dynamics? To answer this question, we measured the spike-triggered average (STA) from experimentally constrained, conductance-based hippocampal neuronal models of various morphological complexities. We transformed the STA computed from these models to the spectral and the spectrotemporal domains and found that the spike initiation dynamics exhibited temporally localized selectivity to a characteristic frequency. In the presence of the hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, the STA characteristic frequency strongly correlated with the subthreshold resonance frequency in the theta frequency range. Increases in HCN channel density or in input variance increased the STA characteristic frequency and its selectivity strength. In the absence of HCN channels, the STA exhibited weak delta frequency selectivity and the characteristic frequency was related to the repolarization dynamics of the action potentials and the recovery kinetics of sodium channels from inactivation. Comparison of STA obtained with inputs at various dendritic locations revealed that nonspiking and spiking dendrites increased and reduced the spectrotemporal integration window of the STA with increasing distance from the soma as direct consequences of passive filtering and dendritic spike initiation, respectively. Finally, the presence of HCN channels set the STA characteristic frequency in the theta range across the somatodendritic arbor and specific STA measurements were strongly related to equivalent transfer-impedance-related measurements. Our results identify explicit roles for plastic active dendrites in neural coding and strongly recommend a dynamically reconfigurable multi-STA model to characterize location-dependent input feature selectivity in pyramidal neurons.

Homeostasis of functional maps in active dendrites emerges in the absence of individual channelostasis

The maintenance of ion channel homeostasis, or channelostasis, is a complex puzzle in neurons with extensive dendritic arborization, encompassing a combinatorial diversity of proteins that encode these channels and their auxiliary subunits, their localization profiles, and associated signaling machinery. Despite this, neurons exhibit amazingly stereotypic, topographically continuous maps of several functional properties along their active dendritic arbor. Here, we asked whether the membrane composition of neurons, at the level of individual ion channels, is constrained by this structural requirement of sustaining several functional maps along the same topograph. We performed global sensitivity analysis on morphologically realistic conductance-based models of hippocampal pyramidal neurons that coexpressed six well-characterized functional maps along their trunk. We generated randomized models by varying 32 underlying parameters and constrained these models with quantitative experimental measurements from the soma and dendrites of hippocampal pyramidal neurons. Analyzing valid models that satisfied experimental constraints on all six functional maps, we found topographically analogous functional maps to emerge from disparate model parameters with weak pairwise correlations between parameters. Finally, we derived a methodology to assess the contribution of individual channel conductances to the various functional measurements, using virtual knockout simulations on the valid model population. We found that the virtual knockout of individual channels resulted in variable, measurement and location-specific impacts across the population. Our results suggest collective channelostasis as a mechanism behind the robust emergence of analogous functional maps and have significant ramifications for the localization and targeting of ion channels and enzymes that regulate neural coding and homeostasis.

Uninterrupted galvanic reaction for scalable and rapid synthesis of metallic and bimetallic sponges/dendrites as efficient catalysts for 4-nitrophenol reduction

Here, we demonstrate an uninterrupted galvanic replacement reaction (GRR) for the synthesis of metallic (Ag, Cu and Sn) and bimetallic (Cu M, M=Ag, Au, Pt and Pd) sponges/dendrites by sacrificing the low reduction potential metals (Mg in our case) in acidic medium. The acidic medium prevents the oxide formation on Mg surface and facilitates the uninterrupted reaction. The morphology of dendritic/spongy structures is controlled by the volume of acid used for this reaction. The growth mechanism of the spongy/dendritic microstructures is explained by diffusion-limited aggregate model (DLA), which is also largely affected by the volume of acid. The significance of this method is that the yield can be easily predicted, which is a major challenge for the commercialization of the products. Furthermore, the synthesis is complete in 1-2 minutes at room temperature. We show that the sponges/dendrites efficiently act as catalysts to reduce 4-nitrophenol (4-NP) to 4-aminophenol (4-AP) using NaBH4-a widely studied conversion process.

Multifunctional magnetic reduced graphene oxide dendrites: Synthesis, characterization and their applications

In this paper, for the first time, we have reported the novel synthesis of reduced graphene oxide (r-GO) dendrite kind of nanomaterial. The proposed r-GO dendrite possesses multifunctional properties in various fields of sensing and separation. The dendrite was synthesized by chemical reaction in different steps. Initially, the r-GO sheet was conjugated with silane group modified magnetic nanoparticle, resulting in nanoparticle decorated r-GO. The above r-GO sheet was further reacted with a new r-GO sheet, resulting in the formation of r-GO dendrite type of structure. Multifunctional behavior of this r-GO dendrite structure was studied by different methods. First, magnetic properties were studied by vibrating sample magnetometer (VSM) and it was found that dendrite structure shows good magnetic susceptibility (180.2 emu/g). The proposed r-GO dendrite also shows a very good antibacterial behavior for Escherichia coli and excellent electrochemical behavior towards ferrocyanide probe molecule. Along with these, it also acts as a substrate for the synthesis of molecularly imprinted polymer for europium metal ion, a lanthanide. The proposed imprinted sensor shows a very high selectivity and sensitivity for europium metal ion (limit of detection= 0.019 mu g L-1) in aqueous as well as real samples. (C) 2015 Elsevier B.V. All rights reserved.

Active dendrites mediate stratified gamma-range coincidence detection in hippocampal model neurons

Hippocampal pyramidal neurons exhibit gamma-phase preference in their spikes, selectively route inputs through gamma frequency multiplexing and are considered part of gamma-bound cell assemblies. How do these neurons exhibit gamma-frequency coincidence detection capabilities, a feature that is essential for the expression of these physiological observations, despite their slow membrane time constant? In this conductance-based modelling study, we developed quantitative metrics for the temporal window of integration/coincidence detection based on the spike-triggered average (STA) of the neuronal compartment. We employed these metrics in conjunction with quantitative measures for spike initiation dynamics to assess the emergence and dependence of coincidence detection and STA spectral selectivity on various ion channel combinations. We found that the presence of resonating conductances (hyperpolarization-activated cyclic nucleotide-gated or T-type calcium), either independently or synergistically when expressed together, led to the emergence of spectral selectivity in the spike initiation dynamics and a significant reduction in the coincidence detection window (CDW). The presence of A-type potassium channels, along with resonating conductances, reduced the STA characteristic frequency and broadened the CDW, but persistent sodium channels sharpened the CDW by strengthening the spectral selectivity in the STA. Finally, in a morphologically precise model endowed with experimentally constrained channel gradients, we found that somatodendritic compartments expressed functional maps of strong theta-frequency selectivity in spike initiation dynamics and gamma-range CDW. Our results reveal the heavy expression of resonating and spike-generating conductances as the mechanism underlying the robust emergence of stratified gamma-range coincidence detection in the dendrites of hippocampal and cortical pyramidal neurons.

Dendrites Inhibition in Rechargeable Lithium Metal Batteries

The specific high energy and power capacities of rechargeable lithium metal (Li⁰) batteries are ideally suited to portable devices and are valuable as storage units for intermittent renewable energy sources. Lithium, the lightest and most electropositive metal, would be the optimal anode material for rechargeable batteries if it were not for the fact that such devices fail unexpectedly by short-circuiting via the dendrites that grow across electrodes upon recharging. This phenomenon poses a major safety issue because it triggers a series of adverse events that start with overheating, potentially followed by the thermal decomposition and ultimately the ignition of the organic solvents used in such devices.

In this thesis, we developed experimental platform for monitoring and quantifying the dendrite populations grown in a Li battery prototype upon charging under various conditions. We explored the effects of pulse charging in the kHz range and temperature on dendrite growth, and also on loss capacity into detached “dead” lithium particles.

Simultaneously, we developed a computational framework for understanding the dynamics of dendrite propagation. The coarse-grained Monte Carlo model assisted us in the interpretation of pulsing experiments, whereas MD calculations provided insights into the mechanism of dendrites thermal relaxation. We also developed a computational framework for measuring the dead lithium crystals from the experimental images.

Active dendrites: Adaptation to spike-based communication

Computational analyses of dendritic computations often assume stationary inputs to neurons, ignoring the pulsatile nature of spike-based communication between neurons and the moment-to-moment fluctuations caused by such spiking inputs. Conversely, circuit computations with spiking neurons are usually formalized without regard to the rich nonlinear nature of dendritic processing. Here we address the computational challenge faced by neurons that compute and represent analogue quantities but communicate with digital spikes, and show that reliable computation of even purely linear functions of inputs can require the interplay of strongly nonlinear subunits within the postsynaptic dendritic tree.Our theory predicts a matching of dendritic nonlinearities and synaptic weight distributions to the joint statistics of presynaptic inputs. This approach suggests normative roles for some puzzling forms of nonlinear dendritic dynamics and plasticity.

Simple Electrochemical Route to Nanofiber Junctions and Dendrites of Conducting Polymer

We first report a simple and rapid electrochemical approach to synthesize novel nanofiber junctions and dendrites of conducting poly(o-phenylenediamine) without any surfactant or template. Through controlling some parameters such as the time and potential of electrodeposition and concentration of the reactant, nanofiber junctions and dendrites of conducting polymer can be easily obtained on the solid surface.