High-efficiency exfoliation of large-area mono-layer graphene oxide with controlled dimension

In this work, we introduce a novel and facile method of exfoliating large-area, single-layer graphene oxide using a shearing stress. The shearing stress reactor consists of two concentric cylinders, where the inner cylinder rotates at controlled speed while the outer cylinder is kept stationary. We found that the formation of Taylor vortex flow with shearing stress can effectively exfoliate the graphite oxide, resulting in large-area single- or few-layer graphene oxide (GO) platelets with high yields (>90%) within 60 min of reaction time. Moreover, the lateral size of exfoliated GO sheets was readily tunable by simply controlling the rotational speed of the reactor and reaction time. Our approach for high-efficiency exfoliation of GO with controlled dimension may find its utility in numerous industrial applications including energy storage, conducting composite, electronic device, and supporting frameworks of catalyst

A Novel Role of Three Dimensional Graphene Foam to Prevent Heater Failure during Boiling

We report a novel boiling heat transfer (NBHT) in reduced graphene oxide (RGO) suspended in water (RGO colloid) near critical heat flux (CHF), which is traditionally the dangerous limitation of nucleate boiling heat transfer because of heater failure. When the heat flux reaches the maximum value (CHF) in RGO colloid pool boiling, the wall temperature increases gradually and slowly with an almost constant heat flux, contrary to the rapid wall temperature increase found during water pool boiling. The gained time by NBHT would provide the safer margin of the heat transfer and the amazing impact on the thermal system as the first report of graphene application. In addition, the CHF and boiling heat transfer performance also increase. This novel boiling phenomenon can effectively prevent heater failure because of the role played by the self-assembled three-dimensional foam-like graphene network (SFG).open2

Self-assembled foam-like graphene networks formed through nucleate boiling

Self-assembled foam-like graphene (SFG) structures were formed using a simple nucleate boiling method, which is governed by the dynamics of bubble generation and departure in the graphene colloid solution. The conductivity and sheet resistance of the calcined (400 degrees C) SFG film were 11.8 S.cm(-1) and 91.2 Omega square(-1), respectively, and were comparable to those of graphene obtained by chemical vapor deposition (CVD) (similar to 10 S.cm(-1))(.) The SFG structures can be directly formed on any substrate, including transparent conductive oxide (TCO) glasses, metals, bare glasses, and flexible polymers. As a potential application, SFG formed on fluorine-doped tin oxide (FTO) exhibited a slightly better overall efficiency (3.6%) than a conventional gold electrode (3.4%) as a cathode of quantum dot sensitized solar cells (QDSSCs)open232

Dynamic excitatory and inhibitory gain modulation can produce flexible, robust and optimal decision-making

<div><p>Behavioural and neurophysiological studies in primates have increasingly shown the involvement of urgency signals during the temporal integration of sensory evidence in perceptual decision-making. Neuronal correlates of such signals have been found in the parietal cortex, and in separate studies, demonstrated attention-induced gain modulation of both excitatory and inhibitory neurons. Although previous computational models of decision-making have incorporated gain modulation, their abstract forms do not permit an understanding of the contribution of inhibitory gain modulation. Thus, the effects of co-modulating both excitatory and inhibitory neuronal gains on decision-making dynamics and behavioural performance remain unclear. In this work, we incorporate time-dependent co-modulation of the gains of both excitatory and inhibitory neurons into our previous biologically based decision circuit model. We base our computational study in the context of two classic motion-discrimination tasks performed in animals. Our model shows that by simultaneously increasing the gains of both excitatory and inhibitory neurons, a variety of the observed dynamic neuronal firing activities can be replicated. In particular, the model can exhibit winner-take-all decision-making behaviour with higher firing rates and within a significantly more robust model parameter range. It also exhibits short-tailed reaction time distributions even when operating near a dynamical bifurcation point. The model further shows that neuronal gain modulation can compensate for weaker recurrent excitation in a decision neural circuit, and support decision formation and storage. Higher neuronal gain is also suggested in the more cognitively demanding reaction time than in the fixed delay version of the task. Using the exact temporal delays from the animal experiments, fast recruitment of gain co-modulation is shown to maximize reward rate, with a timescale that is surprisingly near the experimentally fitted value. Our work provides insights into the simultaneous and rapid modulation of excitatory and inhibitory neuronal gains, which enables flexible, robust, and optimal decision-making.</p></div

Of monkeys and men:Impatience in perceptual decision-making

For decades sequential sampling models have successfully accounted for human and monkey decision-making, relying on the standard assumption that decision makers maintain a pre-set decision standard throughout the decision process. Based on the theoretical argument of reward rate maximization, some authors have recently suggested that decision makers become increasingly impatient as time passes and therefore lower their decision standard. Indeed, a number of studies show that computational models with an impatience component provide a good fit to human and monkey decision behavior. However, many of these studies lack quantitative model comparisons and systematic manipulations of rewards. Moreover, the often-cited evidence from single-cell recordings is not unequivocal and complimentary data from human subjects is largely missing. We conclude that, despite some enthusiastic calls for the abandonment of the standard model, the idea of an impatience component has yet to be fully established; we suggest a number of recently developed tools that will help bring the debate to a conclusive settlement